I     I Zone 1 (Red) 1,000 uCi/m2
I     | Zone 2 (Orange) 2 feat PAG 240 MCI/m2
  ~] Zone 3 (Yellowi 50 Yeat PAG 112 iiCwr

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United States
Environmental Protection
Agency
         RDD Waste Estimation Support Tool Report


                               Version 1.2
                      National Homeland Security Research Center


                          Office of Research and Development


                         U.S. Environmental Protection Agency


                          Research Triangle Park, NC 27711
        Office of Research and Development
        National Homeland Security Research Center

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                                Acknowledgments




The authors would like to acknowledge the support of Dan Schultheisz and Tom Peake of




EPA/ORIA, who provided partial funding for this effort. In addition, there are several




individuals whose input was particularly valuable in the development of the Waste Estimation




Support Tool, including Bill Steuteville of EPA/Region 3, Jim Michael and Mario lerardi of




EPA/ORCR, Cayce Parrish of EPA/OHS, Emily Snyder of EPA/ORD, and Paul Kudarauskas of




EPA/OEM.
                                                                              Page i

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                                     Disclaimer




The U.S. Environmental Protection Agency (EPA), through its Office of Research and




Development, funded and managed the research described here under EPA Contract Number EP-




C-07-015, Work Assignment Number 4-14, with Eastern Research Group and Interagency




Agreement DW89922983 with the Oak Ridge Institute for Science and Education. This




document has been subjected to the Agency's review and has been approved for publication.




Note that approval does not signify that the contents necessarily reflect the views of the Agency.




Mention of trade names or commercial products in this document or in the methods referenced in




this document does not constitute endorsement or recommendation for use. EPA does not




endorse the purchase or sale of any commercial products or services.
                                                                               Page ii

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                                   Table of Contents




Acknowledgments	i





Table of Contents	iii





List of Figures	v





List of Tables	viii





Acronyms, Abbreviations, and Glossary	ix





Executive Summary	1





1.0 Introduction	3





1.1 Background	5





   1.2 Purpose	6





    1.1.1. Liberty RadEx	8





2.0 Description	10





  2.1 Approach	11





  2.2 GIS Data Analysis Tools	12





  2.3 Image Analysis Tool	14





    2.3.1 Artificial Neural Networks	17





    2.3.2 Ground Surface Estimation	18





  2.4 Database Tool	20





  2.5 Waste Estimation Spreadsheet Tool	22





3.0 System Requirements	25





                                                                                 Page iii

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4.0 Instructions for Generating Waste Estimate	26





  4.1 Instruction for Operating the RDD Waste Estimation Spreadsheet Tool	44





5.0 Results -Liberty RadEx Example	60





6.0 Conclusions	64





  6.1 Looking Forward	64





7.0 References...                                                                     ..66
                                                                                Page iv

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                                   List of Figures




Figure 1. Data Aggregation Methodology	1




Figure 2. Graphical Depiction of Methodology	2




Figure 3. Liberty RadEx Plume Shapefiles	9




Figure 4. Preliminary Data Aggregation Methodology	10




Figure 5. Graphical Depiction of Methodology	12




Figure 6. Surface Color Palette	15




Figure 7. Surface Media Classification	16




Figure 8. Feed Forward Neural Network	18




Figure 9. Hazus-MH Database Tool Output	22




Figure 10. Example Inventory Relationship of Model Building Type and Occupancy Class [3] 24




Figure 11. Liberty RadEx Plume Zones	27




Figure 12. Hazus-MH Startup	28




Figure 13. Accessing WEST	29




Figure 14. Set Default Directory Button	29




Figure 15. Create Neural Network Training Set Button	30




Figure 16. Train Neural Network Button	31




Figure 17. Show/Hide ArcToolBox Window Button	31




Figure 18. Add WEST Toolbox	32




Figure 19. Unload Table To Text Properties	32




Figure 20. Clear Selected Features Button	33




Figure 21. Add Data Button	33




Figure 22. World Imagery Layer	33





                                                                               Page v

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Figure 23. Repair Geometry Location	34




Figure 24. Rejuvenate 1 Script	34




Figure 25. Rejuvenate 2 Script	35




Figure 26. Zoom To Selected	36




Figure 27. Export TTF Menu	36




Figure 28. Image Zone 1 Script	37




Figure 29. Export BMP Menu	38




Figure 30. Intersect 1 Script	39




Figure 31. Intersect 2 Script	40




Figure 32. Convert Square Footages Button	40




Figure 33. Hazus Database Tool Button	41




Figure 34. Select Hazus Folder	41




Figure 35. Select Inventory	42




Figure 36. Hazus Database Tool	43




Figure 37. ID Surfaces Button	43




Figure 38. RDD Waste Estimation Spreadsheet Tool Main Screen	45




Figure 39. Security Alert-Macro Screen	45




Figure 40. Waste Estimation Spreadsheet Tool Main Screen Start Button	46




Figure 41. RDD Waste Estimation Spreadsheet Tool Home Screen	46




Figure 42. Scenario Basic Information Screen	48




Figure 43. File Import Status Screen	51




Figure 44. Partitioning and Remaining Activity Screen - Activity at Deposition	51




Figure 45. Partitioning and Remaining Activity Screen - Remaining Activity at Time t	52





                                                                                Page vi

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Figure 46. Source Partitioning Factors and Weathering Correction Factors Screens	53




Figure 47. Accessing Decon/Demo Parameters Screen from Partitioning and Remaining Activity




Screen	54




Figure 48. Decontamination/Demolition Parameters Screen	54




Figure 49. Accessing Default Parameter Screens	56




Figure 50. Accessing Waste Results from Decontamination/Demolition Parameters Screen	57




Figure 51. Waste Results Screen	57




Figure 52. Accessing Waste Graphs from Waste Results Screen	58




Figure 53. Waste Graphs Screen	58




Figure 54. Save Scenario Option	59
                                                                               Page vii

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                                   List of Tables




Table 1. List of WEST GIS Scripts	13




Table 2. Media segregation parameters used in the Liberty RadEx Scenario	61




Table 3. Example Waste Quantity Estimation from Liberty RadEx Scenario	62




Table 4 Example Waste Activity Estimation from Liberty RadEx Scenario (|iCi/m3)	63
                                                                             Page viii

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                      Acronyms, Abbreviations, and Glossary




AI - Artificial Intelligence




ANN - Artificial Neural Network




ArcGIS - A complete software system, published by ESRI, for designing and managing




solutions through the application  of geographic knowledge




Beta Test - A limited release testing phase




BP - Back Propagation




Bq - Becquerel (a measure of radioactivity)




C&D - Construction and Demolition




CBRN - Chemical, biological, radiological, and nuclear




Census Tract - Small relatively permanent geographical subdivisions of a county




Chernobyl disaster - A nuclear disaster that occurred at the Chernobyl Nuclear Power Plant in




Ukraine on April 26th, 1986




Ci - Curie(s) (a measure of radioactivity - 1 Ci = 37 billion Bq)




Comprehensive Data Management System - A complementary tool for Hazus-MH that




provides users with the capability to update and manage statewide datasets.




Contiguous  Albers Equal Area  Conic Projection - A conical equal area map projection that




uses two established parallels.




Cs-137 - Radioactive isotope of cesium with a half-life  of 30 years




CSV - A file format based on comma-separated values or character-separated values




DHS -U.S. Department of Homeland Security




Dirty Bomb - A radiological weapon that combines explosives with radioactive material




DoD - U.S. Department of Defense





                                                                               Page ix

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DoE - U.S. Department of Energy




EPA - U.S. Environmental Protection Agency




ESRI -  Geographic information systems mapping software company based in Redlands,




California




FEMA - Federal Emergency Management Agency




FLIR - Forward looking infrared




FRMAC - Federal Radiological Monitoring and Assessment Center




Fukushima Disaster - A nuclear disaster that occurred at the Fukushima Daiichi Nuclear Power




Plant in Japan on March 11th, 2011




G - Graphical Programming Language




GAO - U.S. Government Accountability Office




Geospatial - Relating to or denoting data that are associated with a particular location




GIS - Geographic Information System




GPS - Global Positioning System




GUI - Graphical User Interface




Hazus-MH Database Tool - A database tool used to query the Hazus-MH databases based on




census tract data.




Hazus-MH - Hazus-MH is a nationally applicable standardized methodology, published and




supported by FEMA, which is used to estimate potential losses from earthquakes, floods, and




hurricanes.




1C - Incident Commander




IND - Improvised Nuclear Device
                                                                              Page x

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Lab VIEW - A graphical programming environment published by National Instruments




Corporation of Austin, Texas




Land Cover - Physical material located on the earth's surface




Landsat - a series of Earth-observing satellite missions jointly managed by NASA and the




USGS




Layer - Set of thematic data characterized and stored in a map library




Liberty RadEx - A national Tier 2 full-scale exercise conducted in April 2010, based on a




fictional terrorist attack involving a radiological dispersal device in the city of Philadelphia, PA.




LLRW - Low Level Radioactive Waste




MLP - Multi-Layer Perceptron




MSW - Municipal Solid Waste




NARAC -National Atmospheric Release Advisory Center




NASA -National Aeronautics and Space Administration




Neural Network - A data analysis and pattern-recognition tool that mimics the behavior of




neurons found in the nervous system




Neuro-fuzzy Method - A combination of artificial networks and fuzzy logic




NHSRC - EPA National Homeland Security Research Center




NI - National Instruments




NRC - United States Nuclear Regulatory Commission




NRF - National Response Framework




NSSIPC - National Security Staff Interagency Policy Coordination




OEM - EPA Office of Emergency Management




ORD - EPA Office of Research and Development





                                                                               Page xi

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ORIA - EPA Office of Radiation and Indoor Air




ORISE - Oak Ridge Institute for Science and Education




OSC - On-Scene Coordinator




PAGs - Protective Action Guides




PE - Processing Element




Python - General-purpose, high-level programming language




QA - Quality Assurance




QAPP - Quality Assurance Project Plan




QC - Quality Control




RDD - Radiological Dispersal Device




RGB - Red, Green, and Blue




Shapefile - A geospatial file format that stores non-topological geometry and attribute




information for the spatial features in a data set




SQL - Structured Query Language, an international standard database manipulation query




language




TAD - Threat Agent Disposal (workgroup)




Thematic Mapping - A map designed to portray a particular theme




TM - Thematic mapping




TXT - file format used to designate a text file




US - United States




USACE - U.S. Army Corps  of Engineers




USGS-U.S. Geological  Survey




VB - Visual Basic, an event  driven programming language developed by Microsoft
                                                                              Page xii

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VI - Virtual Instruments




WARRP - Wide Area Recovery and Resiliency Program




WEST - Waste Estimation Support Tool
                                                                            Page xiii

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                                  Executive Summary

       Historically, Radiological Dispersal Device (RDD) planning scenarios have primarily

focused on response efforts, giving little attention to the recovery and management of debris and

waste that would likely consume significant state and federal resources. The U.S. EPA's RDD

Waste Estimation Support Tool (WEST) is a planning tool for estimating the potential volume and

radioactivity levels of waste generated by a radiological incident and subsequent decontamination efforts.

WEST supports decision makers by generating a first-order estimate of the quantity and characteristics of

waste resulting from a radiological incident, and allows the user to evaluate various

decontamination/demolition strategies to examine the impact of those strategies on waste generation.

       The WEST is composed of two processes, preliminary data aggregation and the

generation of waste inventories (separately known as the Waste Tool) as depicted in Figure 1. To

function properly, the waste tool requires three important inputs from the preliminary data

aggregation process: geographic information, surface media, and building stock (i.e., building

quantity, size, square footage, and construction materials).
                                 Preliminary Data Aggregation
                          Geographic
                        Information (GI5)
Building Stock
  (HAZUS)
                            Figure 1. Data Aggregation Methodology
                                                                              Page 1 of 68

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       As shown in Figure 2, the WEST utilizes multiple platforms to assess the environmental

and structural composition of an area to estimate the quantity, characteristics, and activities of

waste and debris. The general approach to creating an RDD scenario begins by classifying

geographical areas by level of contamination (i.e., using a dispersion plume shapefile). Based on

the underlying building stock inventory and outdoor surface media, the waste tool calculates the

amount and characteristics of debris resulting from the initial RDD blast and waste/debris

resulting from building demolition and/or ground surface and selected decontamination

techniques, including estimates of wastewater. The resulting data support the development of

integrated response strategies that take different considerations into account (e.g., demolition,

decontamination, and disposal) within a relatively short period of time.

                         Methodology
               Plume
                and
              Deposition
                Maps

                                                                  Sensitivity
                                                                   Analysis
                                                                  (Crystal Gall)
              HAZU5
              Database
            Extraction Tool
   fault Data
   Surface
 Deposition,
 Mass, Area of
 Materials, in
 Impact Areas
Building Data
 Processing
   Script
                                                        Override
                                                       Default Data
                                                        (optional)
      Waste
     Estimates
      -Mass
     -Volume
     -Activity
Demolition,
  Decon
 Decisions
                        Figure 2. Graphical Depiction of Methodology
                                                                                Page 2 of 68

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1.0 Introduction




       Radioactive materials have a wide range of benevolent uses, especially in the purviews of




medicine, industry, and research. However, conventional radioactive materials can also be used




for sinister purposes such as radiological dispersal devices (RDDs) [1]. An RDD is a type of




chemical, biological, radiological, and nuclear (CBRN) weapon in which radioactive material is




combined with a dispersal device e.g., explosive. When detonated, the RDD, coupled with




atmospheric transport, has the potential to disperse radioactive material over a wide area,




contaminating exposed surfaces [1]. RDDs differ from traditional nuclear weapons: where




nuclear weapons are capable of instantly incinerating a measurable area, RDDs are typically




armed with a conventional explosive, resulting in a much smaller area of direct blast damage.




However, both are capable of spreading radioactive particulates over a large area. Casualties




from an RDD would initially remain relatively low [1]. Decontamination and remediation are the




most arduous tasks associated with  detonation of an RDD. As the radioactive paniculate matter




settles, its behavior will be influenced by the type of surface material. Depending on the




radionuclide, permeable surfaces can  act as a sponge, absorbing the radionuclide, making it




difficult to decontaminate [2]. Decontamination resulting from a RDD that uses cesium may be




financially exhaustive, potentially requiring extended recovery efforts. Efforts to mitigate the




risk arising from RDDs entail securing radioactive sources, developing and deploying detection




measures, and utilizing intelligence and counterterrorism resources [1]. Measures used to plan or




prepare for detonation of an RDD are complex in number and typically involve event modeling




in addition to response and recovery exercises. [1, 3, 4]




       The modeling of atmospheric products generated by an RDD is described as one of the




key planning factors by the Planning  Guidance for Response to a Nuclear Detonation Report





                                                                             Page 3 of 68

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developed by the National Security Staff Interagency Policy Coordination (NSSIPC)




Subcommittee [3]. The NSSIPC further recommends that, in uncertain situations where technical




information is limited, modeling should be used to the fullest possible extent [3]. Predictive




plume and deposition models, however, are limited and tend to use postulated environmental




inputs, which inhibit accuracy [4]. Accuracy in modeling, specifically in expedited response




scenarios, is typically forfeited. Exploring capabilities for autonomous prediction of




environmental inputs to aid in the generation of CBRN models addresses a major knowledge




gap.




      Modeling the distribution of the radionuclides in the plume is only the beginning of the




remediation process. Contaminated areas are better defined through sampling and




characterization processes that eventually supersede the initial plume modeling. However, a




number of days or weeks may elapse before the affected area is fully characterized and, to




minimize remediation timelines, initial development of remediation strategies must start




immediately following the contamination event. This process includes identification of the




materials found in both the indoor and outdoor portions of the affected areas and developing




approaches for optimal cleanup of those surfaces and materials. Supplying the incident




commander (1C) with decision making tools to prioritize  remediation processes as soon as




possible is a key element of a rapid, effective remediation that minimizes economic and health




impacts to the affected community.




      The Waste Estimation Support Tool (WEST) supports this process by exploiting plume




models distributed by the National Atmospheric Release  Advisory Committee (NARAC)




depicting deposition and concentration levels, land  cover classification capabilities using feed-




forward neural network derived pattern recognition algorithms, and building stock values





                                                                            Page 4 of 68

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including square footage and building counts and composition estimates as generated by the




Federal Emergency Management Agency's (FEMA's) Hazus-MH software [5]. Using these




modules, researchers have developed a suite of applications for rapidly estimating waste




inventories and levels of radioactivity generated by detonation of an RDD as a function of user-




defined decontamination and demolition approaches. This report begins by describing the




background of the WEST and the need for estimating waste inventories generated by a RDD.




Furthermore, this report describes the WEST and its supporting applications.




1.1 Background




       For emergency planners and federal responders to scope out the waste and debris




management issues resulting from a radiological response and recovery effort, it is critical to




understand not only the quantity, characteristics, and level of contamination of the waste and




debris but also the implications of response and cleanup approaches regarding waste generation.




Until recently, pre-operational efforts, considering a large scale radiological event, were focused




on the immediate response and early recovery phases, ignoring the issues associated with long




term recovery. Though the activities  associated with disaster response are crucial, the resulting




recovery efforts tend to be the most arduous and time consuming in nature, especially in the




purview of remediation.




       In response to these shortfalls, the EPA conducted a series of exercises focusing on the




longer-term recovery issues in addition to the formation of the Threat Agent Disposal (TAD)




workgroup which examined the disposal of chemical, biological, and radiological threats. One of




the most prominent national level exercises, Liberty RadEx, held in Philadelphia in April of




2010, was labeled as  a drill to test the country's capability to clean up and help communities
                                                                             Page 5 of 68

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recover from a dirty bomb terrorist attack. The WEST was developed to generate first-order




estimates of a waste inventory for the RDD described in the exercise scenario.




1.2 Purpose




       The purpose of this report is to describe the need for estimating the waste inventory




generated by an RDD event, how the WEST and its supporting applications function, and lastly




how to operate the tool itself. The recovery phase of an RDD event has largely been




underestimated, particularly in the realm of debris management. Without proper planning, the




management of debris would likely exhaust state and federal resources [6]. Further, waste




management decisions are often controversial and need to be supported with the best information




available. The WEST provides a better understanding of the recovery process by generating




qualitative and quantitative estimates of debris and waste resulting from an RDD.




       The detonation of an RDD in an urban area by terrorists is one of the National Planning




Scenarios for which the U.S. Department of Homeland  Security (DHS) is coordinating activities




of various government agencies with response preparation requirements [7]. A recent survey by




the Government Accountability Office (GAO) found that almost all  city and state governments




would be overwhelmed by an RDD response and would request aid  from the Federal government




[6]. Roles and responsibilities of the various government agencies during emergency response




activities are described in the National Response Framework (NRF) [6, 8]. Under the NRF, the




EPA is the lead agency for cleanup activities in the aftermath of an RDD event, including




decontamination and waste disposal. Other Federal agencies, including the U.S. Department of




Energy (DOE), U.S. Department of Defense (DoD) through the U.S. Army Corps of Engineers




(USAGE), and the U.S. Nuclear Regulatory Commission (NRC) also have major roles in an




RDD cleanup [9],





                                                                           Page 6 of 68

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       Numerous exercises have been performed by agencies at the federal, state, and local level




to help prepare for an RDD incident. However, GAO noted that in spite of over 70 RDD and




improvised nuclear device (IND) exercises over the last several years prior to 2009, only three




have included interagency recovery discussions following the exercise, and none have directly




included activities related to the disposal of contaminated waste and debris in the exercise




activities [6],




       An integrated RDD response will require inclusion of many competing considerations,




including risk to occupants and residents from post-cleanup radiation levels, prioritization of




cleanups, costs associated with cleanups, speed of cleanup, decisions  to demolish/remove or




decontaminate, economic impacts created from denial of access to facilities and businesses,




waste/debris treatment, transportation, and disposal costs. Determination of waste characteristics




and whether the generated waste is considered to be construction and demolition (C&D) debris,




municipal solid waste (MSW), hazardous waste, mixed waste,  or low level radioactive waste




(LLRW), and characterization of the wastewater that is generated from the incident or




subsequent cleanup activities will  influence the cleanup costs and timelines. Selected




decontamination techniques to meet the cleanup level goals, whether they involve chemical




treatment, strippable coatings, abrasive removal, or aqueous washing, will also influence the




types and amounts of waste generated and associated cleanup costs and timelines. For emergency




planners and  federal responders to scope out the waste and debris management issues resulting




from an RDD response and recovery effort, it is critical to understand not only the quantity,




characteristics, and level of contamination of the waste and debris, but also the implications of




response and cleanup approaches regarding waste generation. This lesson has been learned




during recent cleanups of naturally-occurring Bacillus anthracis resulting from contaminated





                                                                             Page 7 of 68

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animal hides. The best course of action in the cleanup was determined to be to produce as little


waste as possible during the response and recovery. As the waste management issues are raised


to a heightened degree of visibility from a planning standpoint, there is a critical need to scope


out the magnitude and characteristics of the waste and debris so that staging/storage areas and


treatment/disposal pathways can be identified. This report describes an effort to develop a first


order estimate of a waste inventory based on the RDD scenario and plume maps utilized in the


Liberty RadEx National Level Exercise from April 2010 [10].


1.1.1. Liberty RadEx


       The Liberty RadEx drill, a national Tier 2 full-scale RDD exercise conducted in


Philadelphia in April of 2010, was the largest drill of its kind to test the country's capability to


clean up and help communities recover from a dirty bomb terrorist attack.  The scenario involved


a large truck bomb carrying 2,300 curies (Ci) of Cs-137 in the form of cesium  chloride that was


hypothetically detonated in downtown Philadelphia, with ensuing atmospheric transport and


deposition creating a large area of contamination. Some of the products developed by the 1C,


using the NARAC prior to and during the exercise, were the GIS shapefiles which described the


predicted deposition plume from the RDD as it moved downwind from the blast event. These


shapefiles included predictions of ground-level deposition of Cs-137 in terms of aerial activity,


or the activity of the ground surface following deposition in terms of microcuries per square

            r\
meter (uCi/m ). The predicted deposition activities were segregated into three different levels

                                                                              r\
designated high,  medium, and low, reflecting the isopleths at 37,  8.8, and 4.1 MBq/m (1,000,


240, and 112 uCi/m2) predicted surface activities. These surface activities  are designated in the


tables below as "Zone 1," "Zone 2," and "Zone 3," respectively, and are shown in Figure 3.  The


outer two zones in Figure 3 are based on Protective Action Guides (PAGs) which represent



                                                                             Page 8 of 68

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radiation levels that help state and local authorities make radiation protection decisions, such as
evacuations.
                                                     Zone 1 (Red) 1,000 |jCi/m2
                                                     Zone 2 (Orange) 2 Year PAG 240 ±iC\/m2
                                                     Zone 3 (Yellow) 50 Year PAG 112 uCi/m2
                             Figure 3. Liberty RadEx Plume Shapefiles
                                                                                  Page 9 of 68

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2.0 Description

       The WEST is fundamentally composed of two processes, preliminary data aggregation

and the generation of waste inventories (separately known as the Waste Tool) as depicted in

Figure 4. To function properly, the waste tool requires three important inputs from the

preliminary data aggregation process: geographic information, surface media, and building stock.
                                Preliminary Data Aggregation
                          Geographic
                        Information (GIS)
Surface Media
Building Stock
  (HAZUS)
                                        Waste!
                  Figure 4. Preliminary Data Aggregation Methodology

The preliminary data aggregation process generates the following:

   •   Surface media statistics

   •   Building counts

   •   Building square footage

   •   Census tract/zone intersect percentages

   •   Zonal plume area

   The Hazus-MH tool also produces supplemental infrastructure data, not used by the WEST

directly. The supplemental infrastructure data are potentially important to the user and may be

used in future versions of WEST to enhance the analysis of decontamination strategies.
                                                                           Page 10 of 68

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       Each of the three processes requires a separate application to generate the required




output. The preliminary data aggregation processes in addition to the Waste Tool are explained




in greater detail further on in this section.




2.1 Approach




The general approach that was used for developing the WEST is as follows [11]:




   •   Define the geographical areas affected by the hypothetical radiological contamination




       incident and subsequent radionuclide deposition using the geographic information system




       (GIS) shapefiles created during exercise modeling efforts by the Federal Radiological




       Monitoring and Assessment Center (FRMAC) supporting the Liberty RadEx exercise;




   •   Generate an inventory of building structures and other items within the affected




       geographical areas using the Hazus-MH software developed by FEMA;




   •   Estimate the outdoor ground media (asphalt, concrete, vegetation/soils) surface area using




       overhead satellite imagery;




   •   Based on the inventory of buildings, outdoor areas, and other items, use a database and




       spreadsheet to calculate an estimate of the amount and characteristics of debris resulting




       from the initial ROD blast and waste/debris resulting from building demolition and/or




       ground surface and selected decontamination techniques, including estimates of




       wastewater; and




   •   Since this approach uses MS Excel spreadsheets to perform the calculations of




       decontamination and demolition decisions, Excel plug-ins like Crystal Ball (Oracle Inc.,




       Santa Clara, CA) can be used to perform sensitivity analysis on the parameters to find out




       which decontamination option had the largest influence on cost or waste quantities.




   A comprehensive depiction of the methodology behind the tool is shown in Figure 5.




                                                                            Page 11 of 68

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                   Methodology
ft&
                      Satellite
                       Image
                      Processing
                        Tool
                                                                 Sensitivity
                                                                  Analysis
                                                                (Crystal Ball)
                                      Default Data
                                       Surface
                                      Deposition,
                                     Mass, Area of
                                      Materials in
                                      Impact Areas
                      Waste
                     Estimates
                      -Mass
                     -Volume
                     -Activity
                                                     Override
                                                    Default Data
                                                     (optional)
               Demolition,
                 Decon
                Decisions
                     Figure 5. Graphical Depiction of Methodology

2.2 GIS Data Analysis Tools

       When working with wide area events, it is important to understand the infrastructure and

geographical qualities of a specific area. The entire process begins by generating a geographic

area that completely encompasses the event. This process is often referred to as geospatial

analysis and is systematically automated using a geographic information system such as ESRI's

ArcGIS (ESRI Inc., Redlands, CA). ArcGIS has various extensions available to extend its

functionality. One of the most acclaimed extensions for modeling potential loss of infrastructure

is FEMA's Hazus-MH. Formally used to model earthquakes, floods, and hurricanes, Hazus-MH
                                                                          Page 12 of 68

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operates using building stock databases that are applicable to other large scale disasters including




those that involve radiological events.




       Due to the steep learning curve associated with Hazus-MH and ArcGIS, the process of




generating a scenario has been extensively automated by creating a script, otherwise known as a




Toolbox in ArcGIS, to generate the needed results quickly with minimal input from the end user.




The script can easily be installed as an add-on feature within ArcGIS by using the "Add




Toolbox" function. Two inputs are needed for the script to function, a census layer derived from




Hazus-MH and a plume layer.




The Toolbox houses seven scripts that perform three basic functions:




   •   Geometry and attribute modifications




   •   Census and geometry extraction




   •   Satellite imagery extraction




Table 1 provides a brief synopsis of each script within the Toolbox.




Table 1. List of WEST GIS Scripts
Script Name
Rejuvenate 1

Rejuvenate 2

Intersect 1



Intersect 2







1.
2.
1.
2.
1.
2.
3.
4.
1.
2.
3.
4.
5.
6.
7.
Summary
Merge three plume shape files into one.
Add new field titled "Line_ID" for identification.
Create Identifiers for the Line ID field.
Assign zones 001 - 003 for future reference.
Project both plume and census shapefiles.
Establish area of plume before and after intersect.
Establish area of census tract shapefile.
Area of plume is exported using the unload table to text
Create new field for recording duplicates.








script.

Execute "loCount" script to record the number of duplicates.
Delete duplicates.
Export all census tracts in the table as a .csv file.
Execute "iDup" script to record fields with equal areas.
Delete duplicates.
Export reaming (diverging) census tracts as a .txt file.






                                                                            Page 13 of 68

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 Image Zone 1        1.  Select and clip levelOOl from plume.
                     2.  User selected satellite imagery is clipped using levelOOl plume.
	3.  Resulting image is saved at user's preference.	
 Image Zone 2        1.  Select and clip Ievel002 from plume.
                     2.  User selected satellite imagery is clipped using Ievel002 plume.
	3.  Resulting image is saved at user's preference.	
 Image Zone 3        1.  Select and clip levelOOS from plume.
                     2.  User selected satellite imagery is clipped using levelOOS plume.
	3.  Resulting image is saved at user's preference.	
        Although the GIS portion of the WEST is specific to the United States (US), since Hazus-

 MH is used to generate the building stock data needed for the waste estimate, the waste

 estimation spreadsheet itself is generic and applicable to a wide variety of situations. To use the

 WEST on an area not in the US, the geospatial data needed for import would have to be

 reproduced from whatever source the user has access to and reformatted to be suitable for import

 into the waste estimation spreadsheet.  The use of census tracts as the smallest unit area for

 estimating waste is not hard coded into the WEST; other geographical units could be used.

 2.3 Image Analysis Tool

        A key component of estimating decontamination, demolition, and waste/debris disposal

 options from a wide area radiological event is to be able to classify outdoor media in an

 expedited manner. By analyzing satellite imagery of a selected area, the Image Analysis Tool

 classifies outdoor surface areas by type, e.g.,  soil, asphalt, or foliage. As demonstrated in Figure

 6, surface classification is achieved by measuring the range fluctuations between Red, Green,

 and Blue (RGB) color codes for each individual  pixel within a satellite image. These values

 range from 0 to  255, providing 16,581,375 color variations for the satellite image processing tool

 to examine.
                                                                              Page 14 of 68

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                               Color
Red
128
                                      150
                                      51
                                      255
                                      204
                                      192
                                      153
                                      51
                                      51
                                      30
                                      40
                                      45
                                      204
                                      153
                                      51
                                      51
                                      51
Green
 128
       150
       51
                                            204
       192
                                            128
       153
                                            12S
                                             51
       51
       12S
      255
                                            153
                                            2:o
                                            204
      204
       102
      204
                                            102
                                             51
       51
Blue
 128
       150
        51
             204
             204
             153
       192
             128
       102
       204
             153
             51
             255
       204
             204
                                                   128
             102
       153
 Surface
ASPHALT
       ASPHALT
       ASPHALT
                                                         CON-CRETE
             CONCRETE
             CONCRETE
             CONCRETE
       CONCRETE
                                                         CONCRETE
                                                        VEGETATION
             VEGETATION
                  VEGETATION
      VEGETATION
                  VEGETATION
                  VEGETATION
             VEGETATION
      VEGETATION
             VEGETATION
             VEGETATION
                    WATER
               WATER
               WATER
               WATER
        WATER
                                                          WATER
               WATER
                                                          WATER
                    WATER
               WATER
        WATER
                                 Figure 6. Surface Color Palette

       Using the GIS tools described above to generate the imagery, the user uploads the

resulting bitmap to the Image Analysis Tool. The tool then decodes the bitmap into an RGB

format. Once the color ranges have been segmented and calibrated, the image is then redrawn

according to surface type. The tool individually redraws each surface material that was pre-

trained or defined by the user. An example is shown in Figure 7.
                                                                             Page 15 of 68

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                              Carved
                              Satellite
                               Image
Segmented
 Concrete
                          Figure 7. Surface Media Classification1

       The Image Analysis Tool functions using a form of artificial intelligence called Artificial

Neural Networks (ANNs). ANNs are well known as pattern recognition algorithms.

Understanding the composition of surfaces within the contours of a plume resulting from an

RDD is essential when assessing the makeup of debris,  establishing decontamination parameters,

and ultimately plays a key role in the remediation process. Though the classification of surfaces

is crucial when determining waste characteristics, the process of manually analyzing wide area

events is nearly impossible to accurately accomplish in  a short period of time. However, by

harnessing machine vision utilizing an ANN, surfaces can quickly be analyzed and classified

based on color. By automating surface classification, the composition of surfaces over a wide

area can quickly be determined,  providing a more accurate estimation of surface contamination.
1 The carved multispectral Landsat image depicts a plume covering Denver, Colorado. The segmented concrete
image is the result of processing the carved satellite image using the Image Analysis Tool. The black pixels in the
carved satellite image represent concrete, while the white pixels represent non-concrete surfaces.

                                                                               Page 16 of 68

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Both ANNs and the image classification process are explained in greater detail in the following




sections.




2.3.1 Artificial Neural Networks




       Formally designed as a data analysis and pattern recognition tool that mimics the




behavior of neurons found in the nervous system, ANNs outperform all  other traditional




classification methods and have been widely used in the realm of pattern recognition [12, 13]. By




means of computerized artificial intelligence (AI), ANNs offer pattern recognition similar to




human intelligence in addition to managing fallible data [14, 15]. Visually speaking, a neural




network can be depicted graphically using numerical values coupled with nodes that utilize




message-passing algorithms to identify patterns. The nodes within the graph act as input or




output sources, while the graph itself works as a medium for networking or linking the various




nodes. In essence, the architecture of a neural network mimics the architecture of a statistical




processor by making  analytical conjectures about data, capable of computing various




relationships in a short duration with the convenience of decreased execution time compared  to




other means [16].




       Nature-inspired and modeled based on the human brain, neural networks are composed of




interconnecting nodes called processing elements (PEs) [14, 17].  Each PE exhibits a distinct




behavior based an assigned parameter and linkage [17]. The linkages between the PEs are




assigned weights that act as constants, which can be adjusted using a learning algorithm [13].




There are many types of ANNs; one of the simplest being the feed-forward network, which is




utilized by the Image Analysis Tool. The feed-forward network operates using one input layer,
                                                                            Page 17 of 68

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hidden layer(s) also known as weights, and one output layer as shown in Figure 8.
                        Figure 8. Feed Forward Neural Network




ANNs fundamentally learn by environmental exposure (comparison of known inputs and known




outputs) and adjustment of interneuron synaptic weights. There are various learning methods




available, each with its own specialty. The Image Analysis Tool for example, utilizes a




backpropagation learning algorithm.




2.3.2 Ground Surface Estimation




       As previously mentioned, the ability of ANNs to classify surface composition is a crucial




component in the purviews of RDD waste estimation; however, the task of associating a group of




symmetrically related pixels retaining analogous colors is primarily a human concept, easily




expressed as linguistic terms and often a matter of postulation [18]. Significant improvements




have been made in the realm of machine vision and image processing technology in the past few





                                                                          Page 18 of 68

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years, reducing the amount of speculation and time associated with manually classifying imagery




[16].




       A body of research exists on both the classification of satellite imagery using neural




networks and texture analysis based on pixel values. The ANN backed Image Analysis Tool




works specifically at the pixel level, detecting discrete changes in color values in satellite




imagery, often referred to as texture classification [15]. A generic term, texture classification is




defined as the process of segmenting images into homogeneous textured sections based on a




sequence of trained textures [19]. Texture has been described as having two separate dimensions:




one for describing primitive features and the other for representing interactions between those




features [15]. By applying dimensional separations, classification networks are able to segment




textures based on learned samples.




       Neural Networks have been widely used in the classification of land cover for the




purposes of monitoring and planning for land use. One particular study focused on developing an




automated ANN classification system using a supervised Multi-Layer Perceptron (MLP) network




module, one of the most commonly used modules in land cover classification.  The MLP-based




ANN was engineered to classify urban areas, forest, planted crop fields, grass, fallow areas,




transitional areas, wetlands, and water features from Landsat imagery. Training was completed




using the supervised back propagation (BP) algorithm, which consisted of one input layer, one or




more hidden layers, and one output layer that used a total of 3,360 training pixels and 360 testing




pixels. Upon completion, the MLP network module had a classification accuracy of 88.13%.




Researchers noted that the module was suitable for land cover mapping using remotely sensed




data, and would be particularly favorable when the distribution of the data are not normal [12,




16].





                                                                            Page 19 of 68

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       The ability of ANNs to work with poorly organized datasets in an expedited manner




makes them perfect solutions for classifying land cover. Applying the proficiencies of ANNs to




resolve land cover to estimate debris resulting from CBRN weaponry is a relatively new concept.




One of the few studies that employed a neural network is the work of Kanvesky et al., (1996)




using an ANN to predict radioactive fallout resulting from the Chernobyl disaster. This study,




however, failed to address surface deposition. To date, models that address the deposition of




radioactive particles largely omit the specific identification of surface media found within a




study area, instead assigning generic environmental conditions for a specified area (e.g., wooded




or urban settings) [20]. ANNs have demonstrated obvious  successes in identification of terrain




by means  of remote sensing imagery, indicating an opportunity to apply ANN texture




classification capabilities to RDD deposition and debris modeling [18]. In the absence of




literature,  vast research and development opportunities exist for the application of ANNs to




CBRN dispersion modeling.




2.4 Database Tool




       Possibly the most arduous element of the waste estimation process is the acquisition and




analysis of building stock data (i.e., building quantity, size, square footage, and construction




materials) over a wide area. The Hazus-MH Database Tool confronts this issue by utilizing




FEMA's Hazus-MH building  stock database. Hazus-MH, FEMA's loss estimation software, is




considered the leading entity for estimating building stock counts for rural and urban




environments. Originally designed to estimate the loss inflicted by floods, hurricanes, and




earthquakes, the Hazus-MH building stock data is used by WEST to generate square footage and




building count estimates. One of the unique functions of the Hazus-MH Database Tool is the




ability to extract building stock data directly from the Hazus-MH databases automatically





                                                                            Page 20 of 68

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without navigating Hazus-MH or FEMA's Comprehensive Data Management System. By




automating the building stock extraction process, the time required to produce the waste




estimates is greatly reduced, and the universe of potential users is expanded beyond those with




significant GIS expertise.




       The Hazus-MH Database Tool functions as a standalone executable using the Lab VIEW




runtime engine. By applying census tracts derived from the previously mentioned GIS functions,




the Database Tool queries over sixty tables for matching census identifications located in various




databases (a complete listing of table and database names is found in Appendix B). Once




allocated and filtered, the results are uploaded to local tables for further examination by the user.




The Database Tool also queries a number of databases relating to infrastructure and




demographics. A complete listing of the exported data is shown in Figure 9. Upon execution of




the Database Tool, two general building stock databases are exported to the Waste Tool: a)




Square Footage by Building Type; and b) Building Count by Building Type. Additional




infrastructure and demographic information is provided for informative purposes only, and to




date, is not used by the tool, although this information may be used in the future.
                                                                           Page 21 of 68

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  Essential
  Facilities
  High
Potential
  Loss
Facilities
Transport
 Systems
Lifeline
 Utility
Systems
    State
Boundaries
General
Building
  Stock
   Fire Station
  Police Station
                    Hazardous
                    Materials
                    Facilities
                                     Airport
                                    Facilities
                                   Bus Facilitie
                                    Highway
                                     Tunnels
                                    Light Rail
                                     Bridges
                                    Light Rail
                                    Facilities
                Port Facilities
                                     Railway
                                     Bridges
                                   Rail Facilities
                                   Potable
                                   Water
                                 Distribution
                                  Pipelines
                                                   Potable Water
                                                     Facilities
                                                   Waste Water
                                                     Facilities
                                                  Communication
                                                     Facilities
                                 Waste Water
                                 Distribution
                                   Sewers
                                   Electnc
                                   Power
                                  Facilities
                  Natural Fas
                  Distribution
                   Pipelines
                                 Natural Gas
                                  Facilities
                                                   Oil Facilities
                                                                     Building
                                                                     Count bv
                                    Square
                                  Footage by
                                  Occupancy
                                 Demographics
                                                                   Square
                                                                  Footage by
                                                                  Building
                                                                    Type
                                                                           I
                                  Building
                                  Count by
                                  Building
                                   Type
                         Figure 9. Hazus-MH Database Tool Output

2.5 Waste Estimation Spreadsheet Tool

       The RDD Waste Estimation Spreadsheet Tool (Waste Tool) is a Microsoft Excel 2007

application that was created to process the data generated using the GIS data analysis tools (see
                                                                                   Page 22 of 68

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Section 2.2), the Image Analysis Tool (see Section 2.3), and the Hazus-MH Database Tool (see




Section 2.4). The Waste Tool will use those data to generate waste estimates.  The Waste Tool




consists of two separate Microsoft Excel files, a calculation file and an application (user




interface) file.  The Waste Tool provides a simple and intuitive interface for users to specify




various required inputs and to modify preprogrammed default parameters. The Waste Tool




performs numerous calculations based on the data described above and additional user inputs to




describe waste tradeoffs by:




          •  Total number and total square footage of all affected structures in each




             contamination zone (Hazus-MH);




          •  Interior surface areas of buildings (Hazus-MH);




          •  Exterior surface areas of buildings (Image Analysis Tool);




          •  Quantities of structural and non-structural demolition debris (WEST);




          •  Quantities of waste resulting from decontamination activities (WEST); and




          •  Initial radionuclide activity on various building and ground surfaces (WEST) -




             based on initial deposition estimates from NARAC.




       The Waste Tool also contains reference tables consisting of default data and information




derived from Hazus-MH on:




          •  Descriptions of model building type and specific occupancy type as  defined by




             Hazus-MH. An example of available building and occupancy types is shown in




             Figure 10;
                                                                            Page 23 of 68

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                       Residential
                          Commercial
                               Industria
               Occupancy Class
                  Wood
              Steel
          Concrete
     Masonry   Model Building Type
Mobile Home                   ' *
 Figure 10. Example Inventory Relationship of Model Building Type and Occupancy Class


                                            [3]

           •   Debris factors;


           •   Typical building heights; and


           •   Typical number of stories for each model building type.

Default data for decontamination technologies, surface material densities, building geometry


calculations, and unit conversion factors are also included in the tool.


       The Waste Tool performs the following calculations based on the total square footage


and building counts for each model building type (i.e., in terms of building use, occupancy class,


and structural system) located in each census tract that crosses one or more of the three

contamination zones:


           •   Average square footage per building;


           •   Roof area per building;


           •   Interior floor area per building;


           •   Exterior surface area per building, excluding roof area;
                                                                            Page 24 of 68

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          •  Interior surface area per building, excluding floors; and




          •  Structural and non-structural debris for each debris type (brick, wood, and




             reinforced concrete and steel) and for each model building type.




   Once the preliminary data have been generated and imported into the tool, users can specify




the type of decontamination technology to be used in each deposition zone, or can choose to




model the demolition of all buildings in any given zone. Once the demolition and/or




decontamination parameters have been specified, the Waste Tool estimates the amount of




contaminated waste that would be generated. The waste estimates include building materials and




ground surface materials, as well as the water that is generated during decontamination activities.




3.0 System Requirements




The following specifications are required in order to run the WEST and its supporting software.




Operating the WEST below the suggested user requirements may cause system errors or freezes.




Required software:




   •   Hazus-MHMR52.0




   •   ArcGIS 9.3




   •   Microsoft Office 2007 or later




   •   Lab VIEW 2010 runtime (included)




   •   Waste Estimation Support Tool (included)




   •   Google Earth (optional)




Suggested system requirements:




   •   Processor: Pentium 4/M or equivalent




   •   RAM: 2 GB








                                                                          Page 25 of 68

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   •   Screen Resolution: 1024 x 768 pixels




   •   Operating System: Windows XP




   •   Disk Space: 45 GB (includes required software)




4.0 Instructions for Generating Waste Estimate




The following text describes a general approach for generating preliminary datasets used by the




Waste Tool. The subsequent procedures should take approximately one hour.




   1.   Retrieve shapefiles from provided source.




   2.   Create Hazus-MH Scenario encompassing study region.




   3.   Set up the WEST folder.




   4.   Load the WEST Scripts into ArcGIS.




   5.   Combine plume shapefiles.




   6.   Generate satellite imagery of plume shapefiles.




   7.   Process study regions to generate square footage and building stock info.




   8.   Process satellite imagery to  generate outdoor surface estimates.




   9.   Import building count and outdoor surface descriptor files into RDD Waste Estimation




       Spreadsheet.




Plume Shapefiles




       Retrieve shapefiles for the provided scenario (e.g., LRE or WARRP) from an appropriate




source, such as NARAC. The plume must be segmented into three zones (the maximum that can




be handled by the current version of WEST). If four or more zones  exist within the plume, delete




the unused contours so that three remain. Figure 11 shows the plume used in the Liberty RadEx




scenario.









                                                                         Page 26 of 68

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  ZoneS
                        Figure 11. Liberty RadEx Plume Zones
HAZUS Scenario
       Before generating a scenario in Hazus-MH, be sure to extract the necessary state




inventory file from the Data Inventory DVD. To make the default inventory data accessible to




Hazus-MH (in order to create new study regions), do the following:




    1.   Navigate to the compressed state data file on your DVD.




    2.   Select the file (CA.exe for example) and double-click to uncompress it.




    3.   When prompted for the 'Extract to' folder, enter the path to the Hazus-MH Data Path




       folder. By default, this folder is C:\Program Files\HAZUS-MH\Data Inventory.
                                                                         Page 27 of 68

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From the Hazus-MH startup menu, create an earthquake scenario at the county level that

encompasses the plume (tip: by selecting "Show map" you can view/select the preferred state

and county). By adding the plume shapefile using the  add data button from the "Show map"

screen, you can view the underlying county(s). Be sure that the entire plume lies within the study

region. Figure 12 (below) depicts the  necessary steps for creating a study region (be sure to

select "Earthquake" as  hazard type).
                       Welcome to HAZUS-MH.

                       In order to use HAZUS-MH, you need to define the study region to be
                       Please select the desired option below, and a wzaid will guide yot
                       through the necessary steps.
                           a

                           '  Open a region

                           ''  Delete a region

                           !~ Duplicate a legion

                             Export/Backup a region

                           •"" import aiegion
  u
 o
'CiD
 CL>
ai
 >~
T3
 Z3
+->
l/l
 c
 0)
 Q.
o
        HAZUS MH Startup
                       Please setect the desiied option below, and a wizard will guide you
                       through the necessary steps.
                             Create a new region
                           r Ddete a region

                           (" Duplicate a region

                           '""" Expat/Backup 3 region

                           ''" import a region
                                                                       Create New Region
                                                                       Hazaid Type
                                                                         The hazard lype controls the type and amoum of data lhat vdl be aggiegaied.
                                                                         The hazard lype selected affect; the analysis options lhat wi be available
                                                                         Your study region can include one or mote ol Ihe following hazards. Check below the
                                                                         hazaid($) you ate interested in
                                                                           F Flood

                                                                           F Hurricane
                                                                         Notes
                                                                         1. Selection of hazards listed above depends upon the hazaid modules installed.

                                                                         2 Once a study ieg>on is built with a given hazardfs). it cannot be modified later on, in
                                                                         olher words, you cannot add another hazard to it. Alternatively, you may re-create a
                                                                         similai legion with different haj*d[s)
                       In older to use HAZUS-MH, you reed to define the study region to be
                       used in the analysis.
                                                                       Select Region
                                                                         The study legion selection seis the rejon lhat will be opened
                                                                                                                     D
Select the study region you want to open from Ihe let ol study regions you have created
to to.
                                                                                                              | Cieated
                                                                          Liberty RadEx
                                                                                                   
-------
WEST. Graphical User Interface (GUI)
The WEST GUI functions as a "point and click" interface intended to guide the user through the
data aggregation process using a series of icons that function as application shortcuts. The WEST
GUI can be accessed by clicking "Start-^AH Programs-^WEST"
                                    HxD Hex Editor
                                    Adobe Reader X
                              Figure 13. Accessing WEST
WEST Folder
The following procedures describe the steps necessary to establish the WEST directory. The
directory will be used to store files associated with the WEST.
   1.  Create a folder to receive all the data - (e.g., Desktop\WEST).
   2.  To establish a WEST default directory/folder, click the Set Default Directory button.
                         Figure 14. Set Default Directory Button
   3.  Select the folder created in Step 1.
Copy/Train Neural Network
                                                                           Page 29 of 68

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The following procedures describe the steps necessary to copy or create a new neural network




training set. It is important to note that a pre-trained neural network is included with the WEST.




Step 2 only applies if you want to create a custom training set.




   1.  Copy the provided WESTTrainingSet.txt and WESTTrainingSet-Trained.txt files




       (located in default WEST installation directory) into the WEST folder.




   2.  Alternatively, if the training sets are unavailable, you may create your own.




          a.  To create  a neural network training set that will be used to train the neural




             network, click the Create Neural Network Training Set button.
                 Figure 15. Create Neural Network Training Set Button




          b. When prompted to select a surface color map click Default (alternatively you




             may create your own color map by selecting Custom; however, this process tends




             to be complex and tedious and is beyond the scope of this document).




          c. Save the file as "WESTTrainingSet.txt" within the WEST installation directory




          d. To train the neural network that will be used to classify the satellite imagery, click




             the Train Neural Network button.
                                                                           Page 30 of 68

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                       Figure 16. Train Neural Network Button




          e.  The Train Neural Network application will open and begin training the neural




             network by accessing the WESTTrainingSet.txt file created in the previous step.




             Once the training has been completed, save the file as "WESTTrainingSet-




             Trained.txt" within the WEST installation directory.




Load Scripts




The following procedures explain how to add the WEST Toolbox, a suite of ArcGIS scripts used




to automate the geospatial processes.




   1.  Open the scenario you just created in Hazus-MH.




   2.  Toggle the "Show/Hide ArcToolBox Window" button to display the ArcToolBox pane.
                   Figure 17. Show/Hide ArcToolBox Window Button




   3. Right click ArcToolbox, select "Add Toolbox" and add the WEST Toolbox (in the




      WEST Apps folder).
                                                                        Page 31 of 68

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                                     i ArcToo"

                                      j& 3D     New Toolbox


                                      3h Anil
                                               Add Toolbox,
                                    +  & Cor    Environments,.,


                                    +  ^ Dat
                                      :!£    ^  Hide Locked Tools



                                    El  ^ Gee

                                    +  3|| Get
           Save Settings



+ ^ Lint    !-oad Settings
                                    +  ^ Mobile Tools



                              Figure 18. Add WEST Toolbox



    4.  In ArcToolbox, expand WEST Toolbox, right click "unload table to text'



    5   Select "Properties"



    6   Select Source Tab



    7.  Navigate to "unload table to textpy" script (in the WEST Apps folder).
               Unload Table To Text Properties
                                   ?  X
                 General  Source | Parameters 1 Validation 1  Help j



                  Script File:
                  f~ bhow command window when executing script



                  p" Run Python script in process





                        Figure 19. Unload Table To Text Properties



    8.  Hit "Apply" then OK.



Combine Shapefiles



The subsequent procedures are used to intersect the plume and census shapefiles within Hazus-



MH. By combining the shapefiles, data within the shapefiles are merged for easier analysis.
                                                                              Page 32 of 68

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1.  Clear selected features by pressing the "Clear Selected Features" button. A grayed out


   button indicates that no features are currently selected. Be sure that no features are


   selected before and after each script is executed.
                    Figure 20. Clear Selected Features Button


2.  Using the "Add Data" button, load the plume shapefile(s) (Shapefiles are not provided,


   you must either create or own or retrieve them from an official source e.g., NARAC).
                           Figure 21. Add Data Button


3.  Select "Add Data" and load the provided satellite imagery (Located in default WEST


   installation directory or alternatively select "File-^Add Data From ArcGIS Online" if


   you don't have it).


                                     Worldjmagery.lyr
                                     ArcGIS Layer
                                     37KB


                        Figure 22. World Imagery Layer


4.  Validate the integrity of the shapefiles.


       a   Run ArcGIS Script "Data Management Tools->Features->Repair Geometry"


          on each shapefile.
                                                                       Page 33 of 68

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                                              + i
                                              + i
                                              + i
                                              + i
                                              + i
                                              + i
                                              - i
ArcToolbox
  3D Analyst Tools
i; | Analysis Tools
  Cartography Tools
  Conversion Tools
  Data Interoperability Tools
  Data Management Tools
    Data Comparison
    Database
    Disconnected Editing
    Distributed Geodatabase
    Domains
    Feature Class
    Features
    f* Add XY Coordinates
    jfr Adjust 3D Z
    ^ Check Geometry
    f* Copy Features
    ^ Delete Features
       Multipart To Singlepart
                         Figure 23. Repair Geometry Location

5.   If the plume shapefiles you got from NARAC for Zones 1-3 are already combined into a

    single shape file then skip to Step 8, otherwise continue with Step 6.

6   Run "WEST Toolbox -> Rejeuvenatel"

        a.  WEST Folder: the WEST folder you created.

        b.  Select plumes: corresponding to Zones 1, 2, and 3 - make sure Zone 3 is largest,

           Zone 2 is second largest, and Zone 1 is smallest and click "OK".
•• Rejuvenate 1
j V'..'est Directory
I
, Zone 3
I
, Zone 2
I
, Zone 1
1
*l

n

i

1
                                       OK      Cancel   Environments...   «Hide Help
                             Figure 24. Rejuvenate 1 Script
                                                                                  Page 34 of 68

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   7.  Select "Add Data" and import the newly created shape file that is in the WEST folder. It




       will be named the same as the Zone 3 plume shape file with the word "merge" following.




   8.  Run Rej euvenate2.




          a.  WEST Folder: the WEST folder you created.




          b.  "Shapefile_Merge": the merged shapefile from Step 5.
                Rejuvenate 2
               _, V'/EST Directory
               j Plume Shapeflle

                                            Cancel  | Environments,,,  «Hide Help I
                             Figure 25. Rejuvenate 2 Script




   9.  A merged shapefile with all the plumes has now been created in the WEST directory.  It




       is named the same as the previous merged shape file.




Satellite Imagery




The next steps describe how to dissect satellite imagery from the zonal areas. The resulting




imagery will subsequently be classified according to surface type.




   1.  Confirm the merged shapefile created during Step 8 "Run Rejuvenate2" has been added.




   2.  Right click on the merged shapefile and select "Open Attribute Table"; Right click on




       the left box on the line for Zone 1  (line ID = LevelOOl) and select "Zoom to Selected";




       Close window.
                                                                           Page 35 of 68

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                                  FID  Shape   LINEJD
                                    C
                                    1
       Polygon  LevelOOS
       Polygon  Level002
       Polygon  LevelQCH
••*•• Flash
(*i Zoom To
f) Pan To
O Identify1.,,
13 Select/Unselect
                                  Zoom To Selected
                               ITI Clear Selected
                               HE) Copy Selected
                               X Delete Selected
                           Figure 26. Zoom To Selected
3.  Hide all Layers except "Imagery"; you should now see the satellite image area
   encompassing Zone 1.
4  Select Menu File-»"Export Map"; Export the image as a TIF file at 200 dpi
   resolution, with the "Write GeoTIFF Tags" option checked on the "Format" tab; Name
   the file "Zonel";  Save the file into the WEST folder.
«
IMy Netwo*
Places

General Format
Color Mode:
Compression:
Deflate Quality:
Background Colo


Filename: |Zonel| HI Save
Save as type: 1 TIFFr.tif; »|| Cancel

1
24-bit True Color _^J
|None _^J
r. Dl'j
|P Write GeoTIFF Tags]

                           Figure 27. Export TIF Menu
                                                                         Page 36 of 68

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5.  Select "Add Data" and import the Zonel.tif file you just created.

6.  Under the ArcToolbox, go to "WEST Toolbox-Mmage Zonel".

       a.  Plume: the merged shapefile.

       b  Satellite Image: Zonel tif

       c.  Save Image As: "Zonel .img" - use the file dialog to save that into your WEST

          folder.

       d.  WEST directory: your WEST directory you created.
                Image Zone 1
               j Plume
               % Satellite Image
               j Save Image As [Use Extension .img e.g. Plume 1.img}
               ., WEST Directory
Ml
Ml


                                      OK     Cancel  | Environments... |  «Hide Help |
                         Figure 28. Image Zone 1 Script

7.  Select "Add Data" and import the Zonel .img file that was created in your WEST folder.

8.  Hide all layers except Zonel.img; — you should see the satellite imagery for the

   irregularly shaped Zone 1.

9  Select Menu File->"Export Map"; Export the image as a BMP file at 200 dpi

   resolution; Name the file "Zonel.bmp".
                                                                       Page 37 of 68

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                          File name:
[Zonel
                          Save as type:    | BMP f*.bmp)
Save



Cancel
                             |200
                              |1625



                              11740
                                      pixels
                 I? Write World File
                              Figure 29. Export BMP Menu




    10. Repeat this process for Zones 2 and 3 (Zone 2 line ID = Level002 and Zone 3 line ID =




       LevelOOS).




Process Study Regions




The following procedures describe how to process the study regions using the intersect scripts.




Upon execution of the scripts, a statistical reference is derived for calculating the building stock.




    1.  Under the ArcToolbox, go to "WEST Toolbox-^ Intersect 1".




          a.  Census Data: Study Region Tract.




          b.  Plume Data: the merged shapefile.




          c.  WEST Folder: the WEST folder you created.




          d.  PLUMEAREA.CSV  : save the file as "PLUMEAREA.csv" in your WEST folder.
                                                                            Page 38 of 68

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               ^ Census Data
               » West Directory
               ..PIUMEAREA.csv gave As;

                                             Cancel  | Environments,,, |  «Hide Help |
                           Figure 30. Intersect 1 Script




2.  Intersectl created a new shapefile in the WEST Directory called




   "hztract_Project_Intersect.shp".  Add this file using the "Add Data" button.




3.  Under the ArcToolbox, go to "WEST Toolbox-^ Intersect 2".




       a.  Intersected Shape File: hztract_Project_Intersect.




       b.  OUTPUT.csv: save the file as "OUTPUT.csv" in your WEST folder.




       c.  CENSUS.txt:  save the file as "CENSUS.txt" in your WEST folder.
                                                                         Page 39 of 68

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                   __, Inte^ecte^hapefile
                   _, OUTPUT.csv rSave As}
                   j CENSU5.txt £ave As)

                                                 Cancel  | Environments... |  «Hide Help
                               Figure 31. Intersect 2 Script




Convert Zone Square Footages




The following procedures describe how to convert the square footages extracted during the GIS




portion.




   1.  To convert the zone square footages, click the Convert Zone Square Footages button.
                       Figure 32. Convert Square Footages Button




   2.  The Convert Zone Square Footages application automatically locates and converts the




       required values. Click the Ok button to close the application.




Process Building Stock




The following procedures describe how to extract the building stock inventory using the Hazus




Database Tool.
                                                                            Page 40 of 68

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1.  To process building stock inventories, click the Hazus Database Tool button.
                      Figure 33. Hazus Database Tool Button

2.   Step 1: locate Hazus-MH directory.

       a.  Select the Hazus-MH Folder: default location: C:\Program Files\HAZUS-MH

          (tip: to select the folder currently being viewed, select the "Select Current

          Folder" button.)

       b.  If Hazus-MH folder is located outside of default directory, check box and select

          your "HazusData" folder, otherwise click "OK" to continue.



                        Select the Hazus-MH Folder
                        C;'f rogram Files \HAZUS-MH
                        My Hazus-MH region subfolders are stored
                        outside of the Hazus-MH default directory

                        Select HazusData Folder
                                                      _l
                          Figure 34. Select Hazus Folder

3.   Step 2: select state inventory and region.

       a.  Select State Data Inventory Database: the state of your study region.

       b.  Check Include General Building Stock.

       c   Check Export Data to WEST
                                                                         Page 41 of 68

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       d.   Select Region: the name of the study region you created in Step 2.

       e.   Click Execute.
                      Hazus-MH Version:  MRS 2.0
                      Select State Data Inventory Database
                      |co                  v|
Indude General Building Stock (Requires Hazus-MH)
Export Data to WEST: T
Select Region
| WARRP Demo 10-24


H


Execute



J

                            Figure 35. Select Inventory

4.   The required building stock files, i.e., building count and square footage values are

    extracted to the pre-established working directory. Optionally, the Database Tool has

    embedded functionality to further assist in site assessment:

       a.  Browse critical infrastructure and building stock.

       b.  Export infrastructure and building stock tables for separate analysis by clicking

          the Export Table to Excel button

       c.  Plot infrastructure and building stock data in Google Earth by clicking the View

          Features in Google Earth button (must have Google Earth installed).
                                                                          Page 42 of 68

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Home Essential Facilities High Potential Loss Facilities Transporta
bon Systems Lifeline Utility Systems State Boundaries
General Building Stock [Requires HAZUS-MH) |
Fire Station | Medical Police Station School
School
Tract
03031001101
03031001102
03031001500
03031001600
03031001702
03031001300
03031001900
03031002000
03031002403
03001003505
03001003507
03001003503
03001003524
OSOO 1003 525
03001003529
03001003530
0300 100353 1
03001003534
03031000201
03031000202
03031000401
03031000402
03031000600
03031003500
03001003901
03001003952
03001009001
08001009002
03001009003
Name
HORACE MANN MIDDLE SCHOOL
BRYAr-fT WEBSTER ELEMENTARY SCHOOL
GARDEN PLACE ELEMENTARY SCHOOL
INNER-CITY CHRISTIAN SCH PARTN
EMILY GRIFFITH OPPORTUNITY SCHOOL
DEL PUEBLO ELEMENTARY SCHOOL
GREENLEE/METRO LAB ELEMENTARY SCHOOL
P.S.1CHARTER SCHOOL
GILPIN ELEMBJTARY SCHOOL
HULSTROM ELEMENTARY SCHOOL
MALLEY DRIVE ELEMENTARY SCHOOL
WOODGLEN ELEMENTARY SCHOOL
BRIGHT HORIZONS PRE-KINDERGARTEN SCHOOL
STARGATE CHARTER SCHOOL
CHILDRENS WORLD
SHADOW RIDGE MIDDLE SCHOOL
CHERRY DRIVE ELEMENTARY SCHOOL
RIVERDALE aEMENTARY SCHOOL
BEACH COURT ELEMENTARY SCHOOL
REMINGTON ELEMENTARY SCHOOL
COLUMBIAN ELEMENTARY SCHOOL
CONTEMPORARY LEARNING ACADEMY HIGH SCHOO
FRED N THOMAS CAREER EDUCATION CENTER
SWANSEA ELEMENTARY SCHOOL
ADAMS CITY MIDDLE SCHOOL
MAPLETON PRESCHOOL
MONTEREY ELEMENTARY SCHOOL
CORONADO HILLS ELEMENTARY SCHOOL
SKYVIEW NEW TECHNOLOGY HIGH SCHOOL
Address
4130 NAVAJO STREET
36350JJIVASST
4425 LINCOLN STREET
2609 LAWRENCE STREET
12SO WaTON STREET
750 GALAPAGO
1150 LIP AN STREET
1030 DELAWARE STREET
2949 CALIFORNIA STREET
10604 GRANT DRIVE
1300 EAST MALLEY DRIVE
11717 NORTH MADISON STREET
5321 EAST 136TH AVENUE
39S1 CQTTONWQOD LAKES BOULEVAR
12290 PENNSYLVANIA ST
12551HOLLYSTREET
11500 CHERRY DRIVE
10 724 RM DRIVE
4950 BEACH COURT
473 5 PECOS STREET
2925 WEST40TH AVENUE
221 1 WEST 27TH AVENUE
2650 ELIOT STREET
4650 COLUMBINE STREET
445 1 EAST 72ND AVENUE
602 EAST 54TH AVENUE
2201 MC EL WAIN BOULEVARD
3 300 DOWNING DRIVE
1200 E 73TH AVENUE
City Zip code
DENVER 30211
DENVER 30211
DENVER 30216
DENVER 30205
DENVER 30204
DENVER 30204
DENVER 30204
DENVER 30204
DENVER 30205
NORTHGLENN 80233
NORTHGLENN 30233
THORNTON 30233
BRIGHTON 30601
THORNTON 30241
THORNTON 30241
THORNTON 30602
THORNTON 302 3
THORNTON 302 3
DENVER 302 1
DENVER 302 1
DENVER 302 1
DENVER 302 1
DENVER 302 1
DENVER 30216
COMMERCE CITY 30022
DENVER 30229
DENVER 80229
THORNTON 30229
DENVER 30229
State Contact
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
i

                            Figure 36. Hazus Database Tool




Process Satellite imagery




Once the satellite images have been dissected according to zone, the resulting imagery must now




be classified according to surface type.




    1.  To process satellite imagery, click the ID Surfaces button.
                             Figure 37. ID Surfaces Button




          a.   Select the Zonel .bmp file created during the Satellite Imagery process.




          b.   When it asks you if the study region is rectangular select the "No" option.




          c.   Repeat this process for Zones 2 and 3.




Import Files
                                                                           Page 43 of 68

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Up to this point, all files used to create a scenario within the waste tool have been generated.




Before continuing, ensure the following files have been created in the WEST directory:




   •   Ground Surface Percentage Data = RDD Tool Ground Surface Data.csv




   •   Building Count Data = BldgsinCensusTract.csv




   •   Census Tract/Zone Percentage Data = TRACT_AREAS.CSV




   •   Building Square Footage Data = SqFtofBldgsinCensusTract.csv




   •   Zone Area Data = Plumearea. csv




TRACT_AREAS.csv, BldgsinCensusTract.csv, and SqFtofBldgsinCensusTract.csv should




contain the same number of entries. Four bitmap files have also been generated.  Check images




for classification accuracy.






4.1 Instruction for Operating the RDD Waste Estimation Spreadsheet Tool




Once the generated files have been checked for compatibility (i.e., the number of records in the




import CSV files are the same, the data structures of the import CSV files are consistent with




what is needed by the spreadsheet), they are now ready to be uploaded to the waste tool. The




following steps explain how to install  and operate the Waste Tool.




1.  Install the two RDD Waste Estimation Spreadsheet Tool files into the same directory of your




   choosing:




             RDDToolApp 20120815 V1.2.xlsm




             RDDToolData.xlsx




2.  Open the RDDToolApp_20120815_V1.2.xlsm file. The following screen will appear.
                                                                         Page 44 of 68

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                Figure 38. RDD Waste Estimation Spreadsheet Tool Main Screen

3.  Enable Macros. Click the Options... box.  The Microsoft Office Security Options window

    appears.
                                  Microsoft Office Security Options
                                       Security Alert - Macro
                                   Macro
                                     Macros have been d-satfed. Macros might contain viruses or other security hazards. Do
                                     not enable tins content unless you trust the source of th*s file,

                                     Warning: It is not possible to determine that this content came from a
                                     trustworthy source. You should kave this content disabled unless the
                                     content provides critical functionality and vou trust its source.
                                     We Path: C:\...

                                     O Help crotect me from unknown content (recommended)
                              Figure 39. Security Alert - Macro Screen

4.  Click the Enable this content radio button, then click the OK button.

5.  Click Start on the  top left side of the Microsoft Excel toolbar ribbon.
                                                                                              Page 45 of 68

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          Figure 40. Waste Estimation Spreadsheet Tool Main Screen Start Button




6.  The RDD Waste Estimation Tool Home window appears.
                    jjj, Add Scenario   \_g Edit Scenario   ^ Copy Scenario [_£ Delete Scenario   ^ Help   @i About    [«J Exit
                     t:;Tf?r!iive Decon
                    Ground Surface Percentage Data (RDD Tool Ground Surface Data.csv)
                    Building Count Data (BldgsinCensusTract.csv)
                    Census Tract/Zone Percentage Data (TRACT_AREA5.CSV)
                    Building Square Footage Data (SqFtoFBldgsinCensusTract.csv)
                    Zone Area Data (Plurnearea.csv)
                                     |£j Open Scenario
              Figure 41. RDD Waste Estimation Spreadsheet Tool Home Screen




Two pre-existing scenarios are provided in the Tool: Extensive Decon and Limited Decon. Any




other user created scenarios will also be listed in the Scenarios list on the Home window.  The




two default scenarios cannot be deleted. From the Home window, you can:
                                                                                      Page 46 of 68

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       •  Add a new scenario.




       •  Edit an existing scenario.




       •  Copy an existing scenario.




       •  Delete an existing scenario.




       •  Open an existing scenario.




       •  Save an existing scenario.




You do not need to import data to add, edit, copy, or delete an existing scenario.  You can




create multiple scenarios and import different data sets to apply to one or more of the scenarios.




When you Open or Save a scenario, you must import the five data files created from previous




steps in the methodology.




    a.   To add a new scenario from the Home window, click the Add Scenario button. The




       Scenario Basic Information window appears.
                                                                           Page 47 of 68

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       ROD Waste Estimation Spreadsheet Tool
              ROD Waste Estimation Spreadsheet Tool

               Scenario Basic Information
           Home     -J Save    "> Undo     fy. Help
                                                                     Version 1.2
                                                        New Scenario
        Scenario Name


        Comments
                                 0 days


                                 1
Time Elapsed Since Initial Deposition


Tntal Affected Area Scaling Factor   |


                      Initial Ground Surface Activity at Deposition


        Select area activity unit I Select -  _lJ  Per
                                              Select..!
4fe
•->' Radionuclide Zone 1 Activity Zone 2 Activity Zone 3 Activity

Am-241 0
Ba-140/La-HO 0
Ce-141 | 0
|Ce-144/Pr-144/Pr-144m | 0
Cf-252 0
0 | 0
0 | 0
0 | 0
0 0
0 | 0
A Activity
- Includes Daughter
r
r

                 Figure 42. Scenario Basic Information Screen


i.   Give the scenario a unique name.


ii.  Enter the number of days that have elapsed since initial deposition.


iii.  The default affected area scaling factor is  1. Changing this factor allows you to adjust


    the total area of each affected zone by the factor specified. For example, if the total


    affected area is 1,000,000 m2, entering a scaling factor of 1.5 will adjust the total

                                 r\
    affected area to 1,500,000 m .  All subsequent calculations will be based on the


    scaled area.


iv.  Specify the areal activity units that will be associated with the activity values that will


    be entered for each radionuclide.
                                                                             Page 48 of 68

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   v.  Specify the radionuclides present at deposition by entering the ground surface activity




       for those radionuclides for each zone. If the activity includes the contribution from




       the daughter product(s), then check the Activity Includes Daughter box. If this box




       is not checked, the tool will calculate the activity contribution from any daughter




       products.  See the Technical Documentation or click on the Help button for more




       information on which daughters are included in the calculations.




   vi.  Once all of the information has been entered, click the Save button.  To return to the




       Home window, click the Home button.




b.  To edit an existing scenario, highlight the scenario name in the Scenarios box and click




   Edit Scenario. The Scenario Basic Information window will appear. Make any desired




   changes to the scenario and then click the Save button.  To return to the Home window,




   click the Home button.




c.  To copy an existing scenario, highlight the scenario name in the Scenarios box and click




   Copy Scenario. A new scenario will automatically be created and will be listed in the




   Scenarios box with the default scenario name "Copy of..." To change the name of the




   copied scenario or to make any other changes to the scenario basic information, highlight




   the copied scenario in  the Scenario box and then click the Edit Scenario button. The




   Scenario Basic Information window will appear. Make any desired changes to the




   scenario and then click the Save button.  To return to the Home window,  click the Home




   button.




d.  To delete an  existing  scenario, highlight the scenario name in the Scenarios box and




   click the Delete Scenario button. This action will permanently delete a scenario and




   cannot be undone.





                                                                       Page 49 of 68

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7.  Open or Save a Scenario




       a.  To open or save a scenario, you must have at least one scenario created and available




          in the Scenarios box. The procedure for opening or saving a scenario is as follows:




       b.  Highlight the scenario in the Scenarios box to which you want to apply the




          geographic data.




       c.  The five geographic data files that must be imported and applied to the scenario were




          created in previous steps and were saved in a directory. The files must be provided in




          the following order:




               •  Ground Surface Percentage Data = RDD Tool Ground Surface Data.csv




               •  Building Count Data = BldgsinCensusTract.csv




               •  Census Tract/Zone Percentage Data = TRACT_AREAS.CSV




               •  Building Square Footage Data = SqFtofBldgsinCensusTract.csv




               •  Zone Area Data = Plumearea.csv




       d.  Import each of those five files by clicking on the respective Select File... button at




          the bottom right of the Home window. A Select File dialogue box will appear.




          Navigate to the location of the data file and select the data file to import. Then click




          Open.  The directory path and filename will appear on the Home window.




       e.  Once the five geographic  data files have been selected, click the Open Scenario




          button or the Save Scenario button. If you choose to save a scenario, a Save File




          dialogue window opens where you can specify the location to export a copy of the




          Microsoft Excel data file.




       f.  A status window will appear that will  show the progress of the data import.










                                                                         Page 50 of 68

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                      RDD Waste Estimation Spreadsheet Tool
                        Opening Limited Decon...
                        Status
                          Propagating Zone data.,.
                          Filling data for zone: Z3.S3
                                            24%
                           Figure 43. File Import Status Screen




Once the data import is complete, the geographic data are applied to the scenario. If you chose




to save the scenario, the Microsoft Excel data file was exported to the directory that you




specified in Step 7.e above.




If you chose to open a scenario, the Partitioning and Remaining Activity window appears.

IS^S RDD Waste Estimation Spreadsheet Tool
|a*ij«g| Partitioning and Remaining Activity
'•r^Home II

<* Zone 1 r zone 2 f~ Zone 3

1 Decon/Demo Parameters

Limited Decon

<• Activity at Deposition C Remaining Activitv at t


Streets Streets
Radronuclide Asphalt Sidewalks /Concrete Soil Exterior Walls Roofs Interior Floors Interior Walls
|Cs-137 | 1.GOE-HJ3
j Ba-137m 9.46E+02
View or Modify Source Partitioning Factors

1.00E4Q3 | 1, DOE 403 j 5.00E402 | 1.00E-HJ3 ] 1.00E402 | 5.00E-K)1
9.46E402 9.46E402 j 4
View or Modify Weathering Correction Factors

73E402 | 9.46E402 j 9. -WE 401 | 4.73E401

      Figure 44. Partitioning and Remaining Activity Screen - Activity at Deposition




This window presents the results for the activity at deposition and the activity remaining at the




number of days specified since initial deposition for all radionuclides for which an initial ground




surface activity was specified on the Scenario Basic Information window.  The deposition and
                                                                              Page 51 of 68

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remaining activities are calculated for all three zones and for various structural and non-




structural surface types.

S*SJ ROD Waste Estimation Spreadsheet Tool
IjSJiiJgJI Partitioning and Remaining Activity


rzooe
*• Zone 1 r Zone 2 <~ Zone 3



r"1™
f" ActivityatDepGSitn-.i, * TV ,-v,i,-i -.cb r. ;,i r
1 _ 	 	 	 	 	

Streets Streets
Radtonucltde Asphalt Sidewalks/Concrete Soil Exterior Walls
Cs-137 | 8.60E402 |

View or Modify Source Partitioning Factors

3.60E+02 | 9.80E+02 | 4.73E+02 f

View of Modify Weathering Correction Factors

Limited Decon



Roofs Interior Floors Interior Walls
9.90E+02 3.60E+01 | 4.73E+01


   Figure 45. Partitioning and Remaining Activity Screen - Remaining Activity at Time t




The activities are calculated based on the specified initial ground surface activity, source




partitioning factors, and weathering correction factors. For more information on these factors and




details on the activity calculations, please refer to Appendix D.




8.  To view or modify the default source partitioning factors, click the View or Modify Source




   Partitioning Factors button.




9.  To view or modify the weathering correction factors, click the View or Modify Weathering




   Correction Factors button.
                                                                             Page 52 of 68

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 ROD Waste Estimation Spreadsheet Tool
          ROD Waste Estimation Spreadsheet Tool
             Partitioning and Remaining Activity
                                                      Limited Decon
             Partitioning & Remaining Activity
                                    Decon/Demo Parameters
    Zone

     f* Zone 1
                                    View
                Zone 2
                         Zone 3
Activity at Deposition   <~ Remaining Activity at t
    Activity at Deposition

     Cs-137
Streets
Asphalt
i nnF-nm
Streets
Sidewalks/Concrete Soil

i nnF-t-m i nnF-4-n
Exterior Walls Roofs Interior Floors Interior Walls

^ 1 =; mF4.n? 1 1 nnF*m i fff±fr> II s nflf-un
     |  Ba-137rn9.46E+02  |       9.46E+B2       9.46E+02  f   4.73E+OZ  |   9.46E+02  |   9.46E+01  [    4.73E+01
  I View or Moctfy Source Partitioning Factors  I I View or Modify Weathering Correction Factors I

                \
                   \
 ROD Wain tuinwlton Spfcadihoel Tool
       Source Partitioning Factors
             QOdseftCmitl  ^ Kesun De«»* v*i«
                                                   ROD Waste Estimation Spreadsheet Tool
                                                           Weathering Correction Factors
                                                      ,JCic«8
-------
ROD Waste Estimation Spreadsheet Tool
§
ramra ROD Waste Estimation Spreadsheet Tool
Kp^jj Partitioning and Remaining Activity Limited Decon

-------
clicking the desired radio button at the top left side of the screen. The data input screens for each




zone are exactly the same and are organized as follows:




              A.  Ground Surfaces.




                    a.  Percent of Total Ground Area Comprised of Asphalt, Concrete, and




                        Soils.




                    b.  Decontamination Parameters for Ground Surface Media.




                            i. Streets - Asphalt.




                           ii. Streets/Sidewalks - Concrete.




                          iii. Soil.




              B.  Buildings




                    a.  Percentage of Buildings to Decontaminate.




                    b.  Percentage of Buildings to Demolish.




                    c.  Decontamination Parameters for Building  Surfaces.




                            i. Exterior Walls.




                           ii. Roofs.




                          iii. Interior Floors.




                          iv. Interior Walls.




Certain parameters are global and apply to all zones.  These parameters include:




   •   Surface material densities;




   •   Decontamination technique parameters;




   •   Building parameters; and




   •   Dust suppression technology parameters.










                                                                            Page 55 of 68

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11. You can view or modify parameters for each of the above four categories by selecting the

    appropriate button on the Decontamination/Demolition Parameters window. The View or

    Modify Building Parameters and View or Modify Dust Suppression Technology

    Parameters buttons are available only when entering data for buildings.
 ROD Waste Estimation Spreadsheet Tool
      ROD Waste Estimation Spreadsheet Tool
        Decontamination/Demolition Parameters
                                 Waste Results  L^I Waste Graphs
                                                                          Clow » Ssve  0 Cl™ a C«,™l  ^r prSo,e Defa* v&jts y, m* and Rel
   Zone
   '"• Zone I  '" Zone 2  <~ Zone 3
                      View v Modfy Surface Material Properties 11 View or Modify DecontamnaOon Tedwique Propert
    I View or Mod*y Dust Suppression Technology Parametet
                                                                         ; Close & Sa,*  00M-(.C*xo(  |g
         I 0 Close»Cancel I ^ Restore Default Values I
                                              0 CbseStCancd |g» Restore Defadt Vahios I r<
  Quit Suppresston Technology	Water Use

  Rre Hose rx«st Suwession          1-9 m3/m3

  Automated Pre«ure/Noirlf Spray System      "
                        Figure 49. Accessing Default Parameter Screens

12. Once all of the parameters have been entered or modified, click Waste Results.
                                                                                         Page 56 of 68

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                        ROD Waste Estimation Spreadsheet Tool
                          Decontamination/Demolition Parameters
                    jf Home   Partitioning & Remaining Activity
Limited Decon
                   r:
                    '•• Zone 1   <~ Zone 2  r Zone 3
                                          View or Modify Surface Material Propertie-
                                                               View or Modify Decontamination Technique Propertie
                   Ground Surfaces I Buildings I

Asphalt | 51 %
Concrete [ 3cT %
Soils 1 18" %

•®f ff Streets - Asphalt
^ C Streets/Sidewalks - Concrete
0 ^Soil
Enter Data






 Figure 50. Accessing Waste Results from Decontamination/Demolition Parameters Screen

Waste results are presented in three formats: summary, demolition detail, and decontamination

detail. Users can choose to view the results in various mass, volume, and activity units.
                     te Estimation Spr
                       RDD Waste Estimation Spreadsheet Tool
                         Waste Results
                  gg Home  I Partitioning & Remaining Activity  Oecon/Demo Parameters
                                                                                 Limited Decon
                  Show Mass in jshortton  _^J  Show Volume in (gallon   _*j Show Activity |uCi    _^J per |m3


                  Summary | Demolition Detail ] Decontamination Detail |

                                                 Mass      Volume
                               ( Liquid Waste
                                   Figure 51. Waste Results Screen

Waste results can be graphically represented by clicking the Waste Graphs button.
                                                                                             Page 57 of 68

-------
                ROD Waste Estimation Spreadsheet Tool
                      ROD Waste Estimation Spreadsheet Tool
                        Waste Results
                       I partitioning & Remaining Activity  Decon/Demo Parameters
                                                                             Limited Decon
                       jshortton _^J  Show Volume in jgallon   -»j  Show Activity |


                      | Demolition Detail j Decontamination Detail |

[Decontamination Waste
| Solid Waste
| Liquid Waste
Demolition Waste
| Solid Waste
[ Liquid Waste
| Total
Mass
4.87E+06
] 1.61E-J-06
3.27E-KI6
| 1.32E+06
| 7.47E-1-05
5.73E+05
6.19E+06
Volume
1 .Q4E+Q9
2.60E+06
7.S2E+08
2.26E4-08
8.85E+07
1 .37E+08
1.27E+09
                Figure 52. Accessing Waste Graphs from Waste Results Screen

Waste results are graphed based on four outputs: solid waste volume percentage, liquid waste

volume percentage, estimated solid waste activity, and estimated aqueous waste activity.
                          isle Estimation Spreadsheet Tool
                            ROD Waste Estimation Spreadsheet Tool
                              Waste Graphs
                                                                       Limited Decon
                        [.) Close      view I I***) Waste Voline Percentage • Al Zones
                                 Liquid Waste Volume Percentage - All Zones
                                                                • Decontamination Liquid Waste
                                                                • Demolition Liquid Waste
                                 Figure 53. Waste Graphs Screen

13. To return to the tool home screen, click Close to return to the Waste Results window and

    click Home.

14. To export the graphs/spreadsheet for further analysis, click the Save Scenario button.
                                                                                        Page 58 of 68

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 |_£ Add Scenario  |  [^ Edit Scenario    [jfj Copy Scenario  [jj Delete Scenario     ty Help     £$ About
Ground Surface Percentage Data (ROD Tool Ground Surface Data.csv)
r
Building Count Data (BldgsinCensusTract.csv)
Census Tract/Zone Percentage Data (TRACT_AREA5.C5V)
Building 5quare Footage Data (5qFtofBMgsinCensusTract.csv)

Zone Area Data (Plumearea.esv)
                           jrj Open Scenario     I |.r^" Save Scenario  I
                   Figure  54.  Save Scenario  Option
                                                                                                       Page  59  of 68

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5.0 Results - Liberty RadEx Example




       In the event of an RDD incident, several options for decontamination of building and




urban materials exist, including strippable coatings, chemical decontamination technologies,




washing and cleaning, and various abrasive techniques such as scabbling.  Each of these




techniques removes the contaminated material and potentially some of the underlying substrate,




producing varying amounts of waste in solid and/or liquid form. There is a complex relationship




between decontamination method selection, waste generation rates, as well as technical,




regulatory, and political considerations that drive the selection of the remediation strategy that




results in the most cost-effective and rapid return to normalcy. The decision-making process for




the overall remediation effort will need to consider several issues, including human health risk,




effectiveness of the decontamination technology, cost of application of the decontamination




technology, rate at which materials can be decontaminated using that technology, and the




quantity of waste (and level of contamination) produced by that technology and associated




disposal costs. Some decontamination parameters may be defined by practical limits that occur




during operational activities (e.g., minimum amount of soil that could be removed is six inches




due to the degree of control operators have over the typical heavy equipment used for soil




excavation).




Based on several decontamination technologies that EPA has identified that are likely to be used




(the tool currently allows a user to select from strippable coatings, abrasive removal, washing, a




"no decontamination" option, as well as a user-defined decontamination technology option) for




various surface types, decontamination waste quantities and characteristics were estimated using




a combination of default and user-adjustable parameters in the spreadsheet tool [21]. The




estimates include:





                                                                            Page 60 of 68

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     •  Contaminated material (e.g., the layer of radioactive material that must be removed from




        structures, roads, soil, etc);





     •  Residues from the decontamination technologies (e.g., removed strippable coatings); and





     •  Wastewater and sludges from onsite decontamination efforts.





        Based on the Liberty RadEx scenario, a number of "best guess" assumptions were made




  for a hypothetical mitigation strategy for three affected geographical zones shown previously in




  Figure 3, including the fraction of buildings to be demolished versus the fraction to be




  decontaminated, as well as a potential mix of decontamination technologies that might be




  deployed. This process is demonstrated below in Table 2.  The decontamination and demolition




  options selected in no way reflect EPA policy or even likely strategies that may be used in a real




  ROD incident.




Table 2. Media segregation parameters used in the Liberty RadEx Scenario
Media
Asphalt
Concrete
Soil
External Walls
Roofs
Interior Walls
Zone 1:
90% demolition, 10%
decontamination
1" removal
1" removal
6" removal
1 mm removal
1 mm removal
1 mm removal
Zone 2:
10% demolition, 90%
decontamination
1" removal - 70%
Wash - 30%
1" removal - 70%
Wash - 30%
6" removal
1 mm removal - 20%
Wash - 80%
1 mm removal - 20%
Wash - 80%
1 mm removal - 20%
Wash - 30%
Strippable Coating - 50%
Zone 3
10% demolition, 90%
decontamination
1" removal - 70%
Wash - 30%
1" removal - 70%
Wash - 30%
6" removal
Wash
1 mm removal - 20%
Wash - 80%
1 mm removal - 20%
Wash - 30%
Strippable Coating - 50%
                                                                            Page 61 of 68

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 Floors
1" removal
1" removal
1" removal - 50%
Wash - 50%
 Based on the assumptions and analyses described above and in Section 2, the waste estimation

 spreadsheet produces an estimate of both waste quantity and activity. The results of the

 estimated waste quantities from this example scenario are shown in Table 3, and estimates of

 activity are shown in Table 4. Estimations of certain quantities (e.g., liquid wastes) make no

 assumptions as to the availability of resources (e.g., wash water) necessary to produce those

 quantities of wastes. In fact, one of the useful outputs of the tool is a gross indication of the

 theoretical viability of certain strategies (e.g., where water supplies are limited, using washing as

 a decontamination option may not be possible).

       Table 3 demonstrates the amount of waste generated by demolition and decontamination

 measures. Note the total waste produced (approximately  1.3 million metric tons) and the amount

 of liquid waste generated as a result (approximately 41 billion liters).

Table 3. Example Waste Quantity Estimation from Liberty RadEx Scenario

Solid Waste
Demolition
Decontamination
Total
Liquid Waste
Demolition
Decontamination
Total
Zone 1

66,883
22,060
88,943

52,948,845
-
52,948,845
Zone 2

82,548
308,651
391,199

65,350,416
16,425,394,718
16,490,745,134
Zone 3

142,110
681,265
823,375

112,503,382
24,797,444,633
24,909,948,015
Total

291,540
1,011,976
1,303,516

230,802,643
41,222,839,351
41,453,641,994
Units

metric
tons
metric
tons
metric
tons

liters
liters
liters
                                                                            Page 62 of 68

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       Table 4 depicts the amount of waste radioactivity by media type. Overall, activity is




minimal, demonstrating the possible use of LLRW or MSW depositories.
Table 4 Example Waste Activity Estimation from Liberty RadEx Scenario (uCi/m3)
Media
Demolition
All Debris
Liquid Waste
Decontamination
Asphalt
Concrete
Soils
Exterior Walls - Porous
Exterior Walls - Nonporous
Roofs - Porous
Roofs - Nonporous
Interior Walls - Porous
Interior Walls - Nonporous
Interior Floors
Liquid Waste
Coating Waste
Zone 1

4.62E+01
5.62E+03

3.82E+04
3.82E+04
6.56E+03
4.98E+05
4.91E+05
9.98E+05
9.98E+05
4.98E+04
4.91E+04
3.82E+03


Zone 2

1.53E+01
1.87E+03

9.18E+03
9.18E+03
1.57E+03
1.19E+05
1.18E+05
2.40E+05
2.40E+05
1.19E+04
1.18E+04
9.18E+02
3.87E+01
4.41E+03
Zone 3

6.63E+00
8.10E+02

4.28E+03
4.28E+03
7.34E+02


1.12E+05
1.12E+05
5.58E+03
5.50E+03
4.28E+02
1.45E+01
2.06E+03
                                                                         Page 63 of 68

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6.0 Conclusions




       The EPA has developed a GIS-based tool to estimate the quantity, characteristics, and




activities of waste and debris resulting from an RDD or other radiological release event. The tool




uses a combination of the Hazus-MH software, Microsoft Access, and a suite of internally




developed tools to produce the waste inventories. Adjustable parameters allow the user to




estimate the impacts on the waste streams of different demolition and decontamination strategies.




Characteristics of waste and wastewater generated from the incident or subsequent cleanup




activities will influence the cleanup costs and timelines.  Federal responders and decision makers




using this tool may be better able to implement an integrated response by effective analysis of




many competing considerations, resulting in optimal decision making capabilities. Use of this




tool may be a useful task to include with cities' planning activities to accompany the background




radiation surveys that are being performed.






6.1 Looking Forward




       Multiple avenues for future enhancements exist from aggregating the preliminary data to




calibrating the estimates produced by the tool. In addition to being a waste estimation apparatus




for radiological events, the underlying methodology remains the same relative to chemical and




biological events as well, ultimately enabling the WEST to function as a CBRN waste estimation




tool.




       In light of recent events in Japan, the application of the WEST to incidents outside the




United States is pragmatically evident. The tool utilizes infrastructure databases that are




specifically attuned to the United States, so international compatibility is currently not possible.
                                                                            Page 64 of 68

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However, efforts are being made to resolve this issue. Additional future enhancements to the




tool include:




   •   Evaluation of available decontamination options per scenario.




   •   Costs and time associated with each decontamination method.




   •   Transportation cost, logistics, and time according to destination.




   •   Ability to update the image analysis pattern recognition algorithm for improved accuracy.




   •   Customizable surface detection for increased classification capacity.




   •   Automated building stock aggregation using remote sensing resources.




   •   Topographic outputs for geospatial interpretation.
                                                                            Page 65 of 68

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7.0 References




1.      Medalia, I.E., Dirty Bombs: Background in Brief, in CRS Report for Congress,




       R418912QII, Library of Congress. Congressional Research Service




2.      Andersson, K.G., Airborne Radioactive Contamination in Inhabited Areas. 2009:




       Elsevier Science.




3.      National Security Staff Interagency Policy Coordination Subcommittee, Planning




       Guidance for Response to a Nuclear Detonation, 2010.




4.      Yu, C., et al., Preliminary Report on Operational Guidelines Developed for Use in




       Emergency Preparedness and Response to a Radiological Dispersal Device Incident,




       2009.




5.      FEM A. The Federal Emergency Management Agency's (FEMA 's) Methodology for




       Estimating Potential Losses from Disasters. 2009  [cited September 28], 2009; Available




       from: http://www.fema.gov/protecting-our-communities/hazus.




6.      Government Accountability Office, Combating Nuclear Terrorism: Preliminary




       Observations on Preparedness to Recover from Possible Attacks Using Radiological or




       Nuclear Materials, 2009: Washington, DC.




7.      U.S. Department of Homeland Security. National Preparedness Guidelines. 2007  [cited




       2009 October 27]; Available from:




       http://www.dhs.gov/xlibrary/assets/National  Preparedness  Guidelines.pdf




8.      U.S. Department of Homeland Security. National Response Framework. 2008  [cited




       2009 October 27]; Available from: http://www.fema.gov/pdf/emergencv/nrf/nrf-core.pdf
                                                                          Page 66 of 68

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9.     Demmer, R.L., Large Scale, Urban Decontamination; Developments, Historical




      Examples and Lessons Learned, in Proceedings of the WM07 Conference2QQ7: Tucson,




      AZ




10.    U.S. EPA. Liberty RadEx. 2010 May 26, 2011]; Available from:




      http ://www. epa.gov/libertyradex/.




11.    Lemieux, P., et al. A First-Order Estimate of Debris and Waste Resulting from a




      Hypothetical Radiological Dispersal Device Incident, in Proceedings of the WM2010




      Conference. 2010. Phoenix, AZ.




12.    Yuan, H., C. Van Der wiele, and S. Khorram, An Automated Artificial Neural Network




      System for Land Use/Land Cover Classification from Landsat TM Imagery. Remote




      Sensing, 2009. 1(3): p. 243-265.




13.    Jordan, M.I. and C.M. Bishop, Neural Networks. ACM Computing Surveys, 1996. 28(1):




      p. 73-75.




14.    Mas, J.F. and JJ. Flores, The Application of Artificial Neural Networks to the Analysis of




      Remotely Sensed Data. Int. J. Remote Sens., 2008. 29(3): p. 617-663.




15.    Miller, D.M., EJ. Kaminsky, and S. Rana, Neural Network Classification of Remote-




      Sensing Data. Comput. Geosci., 1995. 21(3): p. 377-386.




16.    Yang, C.-C., et al., Application of Artificial Neural Networks in Image Recognition and




      Classification of Crop and Weeds. Canadian Agricultural Engineering, 2000. 42(3): p.




      147-152.




17.    Aleksander, I. and H. Morton An Introduction to Neural Computing. 1995: International




      Thomson Computer Press. 284.
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18.     Stathakis, D. and A. Vasilakos, Satellite Image Classification Using Granular Neural




       Networks,. International Journal of Remote Sensing, 2006. 27(18).




19.     Greenspan, H. and R.M. Goodman, Remote Sensing Image Analysis via a Texture




       Classification Neural Network, in Advances in Neural Information Processing Systems 5,




       [NIPS Conference]1993, Morgan Kaufmann Publishers Inc. p. 425-432.




20.     Hill, A., Using the Hazard Prediction and Assessment Capability (HPAC) Hazard




       Assessment Program for Radiological Scenarios Relevant to the Australian Defence




       Force, 2003, DSTO Platforms Sciences Laboratory: Victoria.




21.     Drake, J., R. James, and R. Demmer. Performance Evaluation of Decontamination




       Technologies for Dirty Bomb Cleanup, in Proceedings of the WM 2010 Conference.




       2010. Phoenix, AZ.
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