&EPA
Environmental Protection
Agency
tnvironmentai Monitoring
and Support Laboratory
P.O. Box 15027
Las Vegas NV 89114
EPA-600 4-79-060
September 1979
Research and Development
Detecting Landfill
Leachate
Contamination Using
Remote Sensors
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, US Environmental
Protection Agency, have been grouped into nine series These nine broad categories
were established to facilitate further development and application of environmental
technology Elimination of traditional grouping was consciously planned to foster
technology transfer and a maximum interface in related fields The nine series are
1 Environmental Health Effects Research
2. Environmental Protection Technology
3 Ecological Research
4 Environmental Monitoring
5 Socioeconomic Environmental Studies
6 Scientific and Technical Assessment Reports (STAR)
7 Interagency Energy-Environment Research and Development
8. "Special' Reports
9 Miscellaneous Reports
This report has been assigned to the ENVIRONMENTAL MONITORING series.This series
describes research conducted to develop new or improved methods and instrumentation
for the identification and quantification of environmental pollutants at the lowest
conceivably significant concentrations It also includes studies to determine the ambient
concentrations of pollutants in the environment and/or the variance of pollutants as a
function of time or meteorological factors
This document is available to the public through the National Technical Information
Service. Springfield, Virginia 22161
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EPA-600/4-79-060
September 1979
DETECTING LANDFILL LEACHATE CONTAMINATION
USING REMOTE SENSORS
AWBERC LIBRARY
U.S. EPA
26 W. MARTIN LUTHER KING
CINCINNATI, OHIO 45268
Dwight A. Sangrey
and
Warren R. Philipson
School of Civil and Environmental Engineering
Cornell University
Ithaca, New York 14853
Contract No. 68-03-2438
Project Officer
Vernard Webb
Environmental Photographic Interpretation Center
Vint Hill Farms Station
Warrenton, Virginia 22186
ENVIRONMENTAL MONITORING AND SUPPORT LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
LAS VEGAS, NEVADA 89114
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DISCLAIMER
This report has been reviewed by the Environmental Monitoring and
Support Laboratory-Las Vegas, U.S. Environmental Protection Agency, and
approved for publication. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use.
11
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FOREWORD
Protection of the environment requires effective regulatory actions that
are based on sound technical and scientific information. This information
must include the quantitative description and linking of pollutant sources,
transport mechanisms, interactions, and resulting effects on man and his
environment. Because of the complexities involved, assessment of specific
pollutants in the environment requires a total systems approach that transcends
the media of air, water, and land. The Environmental Monitoring and Support
Laboratory-Las Vegas contributes to the formation and enhancement of a sound
monitoring data base for exposure assessment through programs designed to:
• develop and optimize systems and strategies for
monitoring pollutants and their impact on the
environment
• demonstrate new monitoring systems and technologies
by applying them to fulfill special monitoring needs
of the Agency's operating programs
This report describes the use of aerial photography and multispectral
scanners for detecting environmental anomalies that may indicate contamination
of ground and surface waters from landfill leachate. Such remote sensing
techniques can provide perspective and cost effectiveness not always available
with other investigative techniques for monitoring landfills for environmental
impact. The report can be used by novice and experienced individuals alike
to plan and guide selection of sensors and data collection and analysis
procedures. Governmental and commercial agencies should find it useful in
considering and managing landfill monitoring activities.
George B/ Morgan £/
"Director
Environmental Monitoring and Support Laboratory
Las Vegas
111
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CONTENTS
Page
Foreword iii
Figures vi
Tables vii
Acknowledgements viii
1. Introduction 1
2. Summary 3
3. Conclusions 4
4. Recommendations 5
5. Remote Sensing of Leachate 9
6. Illustrations of Remote Sensing Applications to
Detect Leachate 45
References 60
Appendix A 63
Appendix B 66
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FIGURES
Number Page
5.1 Fluctuation of a Typical Leachate Characteristic (Iron)
with Time, at Four Sampling Points, at a Landfill in
Solon, N.Y. 11
5.2 Landfill Water Balance (after Wehran Engineering Corp. and
Geraghty & Miller, Inc., 1976) 12
5.3 Typical Temperature Variation Around a Landfill (after
Sangrey et al., 1976) 17
5.4 Electromagnetic Spectrum with Types of Sensors (after
Holter, 1971) 18
5.5 Spectral Reflectance of Typical Vegetation, Soil and Snow;
and Attenuation Coefficients of Water 20
5.6 Spectral Irradiance of Sun and Absorption Bands of Atmospheric
Constituents (after Valley, 1965) 22
5.7 Spectral Radiance of a Blackbody (after Wolfe, 1965) 22
5.8 Relation Between Aerial Photograph and Ground Surface 28
5.9 Distortion Pattern of Unit Grid by Frame Camera, A, Panoramic
Camera, B, and Scanner, C (after Masry and Gibbons, 1973) 29
5.10 Geometry of Airborne Scanning Radiometer (Scanner) 31
VI
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TABLES
Number Page
5.1 Leachate Indicators 10
5.2 Classification of Landfill Sites for Application of
Remote Sensing to Monitor Leachate Contamination 14
5.3 Chemical Characteristics of Leachate 15
5.4 Spatial and Spectral Indicators of Leachate 23
5.5 Spectral Bands for Detecting Leachate Through Reflected
Radiation 23
5.6 Ground Area Imaged by Different Format Photographs of
Different Scales 30
5.7 Photographic Camera and Scanner Systems for Leachate
Detection 33
5.8 The Potential for Detecting Leachate under Different
Vegetative and Seasonal Conditions 36
5.9 Exposing Radiation Viewed when Color and Color-Infrared
Transparencies are Examined over White Light Through
Different Spectral Filters 40
VII
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ACKNOWLEDGMENTS
Support for the field work reported in this project was provided by the
New York State Department of Environmental Conservation (Contract C-79273)
and the NASA-sponsored Remote Sensing Program at Cornell (Grant NGL 33-010-171)
Remote sensing missions were supported by EPA/EPIC.
Preliminary analysis of these data was done by W. L. Teng under the
direction of Professor T. Liang from the School of Civil and Environmental
Engineering at Cornell University.
The authors appreciate the work of W. R. Sawbridge who assisted in
preparation of graphics and Mrs. D. A. Tripp who typed the manuscript.
Vlll
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SECTION 1
INTRODUCTION
Remote sensing as a means for identifying contamination of
ground and surface water by landfill leachate has potential for a wide range
of applications. Most of these applications can be grouped as some type of
regulatory monitoring. This term needs to be defined very broadly, however,
to encompass a range of applications from a local environmental group's study
of a single landfill through a state or federal program of conformance moni-
toring. The objective of regulatory monitoring is to ascertain whether a
particular landfill or other waste disposal site is contributing to ground or
surface water pollution by leachate. Since regulatory monitoring is basically
an adversary relationship, there may be need for additional verification of
contamination by specific sampling and testing of water bodies suspected of
being contaminated.
A second general area of applications is in control monitoring where
the objective is to define what would otherwise be unknown sites of pollu-
tion. Control monitoring would usually be done for an owner/operator group
or its agent and would be justified as the most effective or least-cost method
for gathering information on leachate contamination. Unlike regulatory
monitoring which applies only to existing disposal sites, control monitoring
is an appropriate part of the design and development activities for a land-
fill. As such, the limit of control monitoring would be the use of remote
sensing data in site evaluation prior to development.
The amount of leachate produced at a particular waste disposal site, and
the subsequent distribution of the leachate on and off the site, depend on
a wide range of site-specific characteristics. The nature of the waste ma-
terial, as well as many design and management procedures, can influence the
quantity of leachate produced and its distributuion; but the two most impor-
tant characteristics of the site are the climate and geological setting. In
some areas there is little if any potential for leachate production from
waste disposal. Here there may be little need or justification for monitoring
using remote sensors. In humid areas of moderate to heavy rainfall, on the
other hand, most land disposal areas will produce leachate. Depending upon
the effectiveness of leachate control systems, the impact on ground and surface
water quality can range from none to very severe.
Compared with alternatives, remote sensing methods have the potential to
monitor the impact of leachate on ground and surface water quality at lower
cost and increased convenience. Remote sensing will often be only a part of
the total pollution evaluation procedure, however. On-site sampling for veri-
fication will usually be appropriate or necessary.
An advantage of the remote sensing approach is in the complete areal
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coverage provided. Leachate contamination of surface water near the land dis-
posal site can usually be identified by almost any monitoring approach; but
contamination away from the site, especially if this is associated with sub-
surface flow of groundwater, often goes undetected. Remote sensing has par-
ticular application to this problem, both in regulatory and control monitoring.
The objective of this report is to describe a remote sensing approach
for detecting contamination of ground and surface waters by landfill leachate.
The report addresses a number of specific elements of a remote sensing appli-
cation as well as the overall methodology. Among the topics covered, Section
5, are:
a) leachate indicators for sensing
b) spatial and temporal aspects of leachate detection
c) sensor evaluation and selection
d) flight parameters and mission design
e) analysis and interpretation of remotely sensed data
In Section 6 a group of illustrations of remote sensing applications to
detect leachate is presented. These illustrations are taken from the data
collected during a research program of remote sensing missions supported by
the National Aeronautics and Space Administration (NASA) and the Environmental
Protection Agency (EPA). Preliminary funding of this research program were
reported by Sangrey et al., (1976). The research program flights were conducted
over a group of approximately twenty landfills representing a broad range of
management and geological settings. All of the study sites were from the
same general climatological setting, however, which was typical of the humid
northeastern United States. Although all of the illustrations are from this
type of area, the report has been prepared for general application regardless
of climate or geological conditions.
The conclusions and recommendations for establishing a remote sensing
monitoring program are presented in Sections 3 and 4.
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SECTION 2
SUMMARY
A methodology for using remote sensing to detect landfill leachate con-
tamination of ground and surface water is described. The problem is addressed
without regard to specific geographical or climatological regions.
Among the topics covered are leachate indicators, spatial and temporal
aspects of leachate detection, sensor selection, flight design and data in-
terpretation. Specific methodologies for using remote sensing to detect lea-
chate under various situations are described. These range from survey moni-
toring of individual landfills to comprehensive programs for regulatory moni-
toring of many landfills.
Data from a field research and demonstration project are used to illus-
trate the use of remote sensors to detect leachate.
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SECTION 3
CONCLUSIONS
Remote sensing systems can be effective in detecting contamination of
ground and surface waters by leachate. The major advantages are the lower
cost and increased convenience and effectiveness of remote sensing techniques
compared with alternatives.
Several direct or indirect characteristics of leachate pollution serve
as the best indicators for detection if they can be related spatially to the
landfill. These include wetness, gaps in a vegetative or snow cover, and
other spectrally reflective or emissive anomalies from water, soil, rock,
vegetation or snow.
Spatial, spectral as well as temporal characteristics of leachate con-
tamination influence the selection of a particular sensor and the design and
flight parameters for a mission. Aerial photography at a scale of 1:5,000
or larger is recommended for most monitoring programs, although a variety of
film-filter combinations might be used. Pre-dawn, thermal infrared coverage
may be a useful complement to the photographic data.
Certain temporal factors such as time of day, season of the year and
climate are important elements in design of a remote sensing program to
detect leachate.
The specific objective of a monitoring program, the number of sites to
be studied, and the intended use of the acquired information all influence
the specific elements of a monitoring program. From the standpoint of cost
effectiveness, the most important application of remote sensing is to provide
an indication of where to look for leachate contamination. Ground sampling
and analysis will usually be necessary to confirm the condition.
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SECTION 4
RECOMMENDATIONS
The following recommendations are made for implementing a remote sensing
monitoring program to detect leachate contamination of ground and surface
water.
Leachate Indicators for Sensing
From among a large group of potential indicators of leachate contamina-
tion, several are most important in detection using remote sensors. Leachate
contamination is most consistently evidenced by the occurrence of either
gaps or wetness on the ground surface. Gaps in snow or vegetative cover can
be closely associated with a landfill or at some distance. They are usually
caused by wetness, toxicity or heat.
As with gaps, wetness patterns can radiate from the landfill or occur in
isolated spots at various distances away from the disposal area.
Spectral anomalies from conditions such as uniquely colored water or
vegetation have potential for use in detecting leachate but are not as consis-
tent indicators as gaps or wetness. Similarly, stressed vegetation and thermal
anomalies have some particular usefulness but not as a consistent indicator.
Sensors
The most generally applicable sensor for detecting leachate contamination
is aerial photography at a scale of 1:5,000 or larger. Several film formats
can be used in different situations ranging from 35 mm to 23 by 23 cm. Car-
tographic quality mapping cameras may not be required for leachate monitoring
programs, but can provide higher quality imagery than others.
A variety of film-filter combinations could be used to detect leachate,
with ultraviolet, visible and near-infrared spectral wavelengths potentially
useful for detecting certain indicators. Conventional color film, color
infrared film and panchromatic film with spectral filters could be used. Color
infrared film is the most generally applicable if only one camera is available.
Multispectral scanners could be used in place of photographic systems,
but this is probably not a least cost or most effective sensor. Thermal in-
frared scanners may have practical applications in selected cases where the
leachate is significantly hotter than other water bodies. Thermal scanner
data should be collected during pre-dawn periods to maximize contrast of the
target.
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Scale and Flight Parameters
The photographic scale of 1:5,000 should permit detection of leachate
contamination features of about one meter in minimum dimension. The necessary
flying height above ground and the areal coverage will vary with camera focal
length. Larger film formats are clearly preferred for major monitoring pro-
grams-.
Photographic sensing for leachate should be conducted with high sun
angles to minimize shadows and to maximize the amount of reflectance.
Flight parameters for a thermal scanner should be selected for a target
as small as one-half meter in size and with a net temperature difference of
approximately 3°C compared with the background. Thermal scanner missions
should be flown in pre-dawn periods.
Temporal Aspects
There is a clear advantage to conducting a leachate detection program
during certain seasons of the year; in general, when there is a maximum
production of leachate and a minimum of interference from other surface fea-
tures such as vegetation or heavy snow. Since weather and climate are the
major determinants of leachate production for a particular landfill design,
the greatest potential for detection is during wet periods, with dry and
frozen periods having the least potential.
The ideal season will depend on the climate and location. In temperate
humid areas, the best time for a sensing program will usually be early spring,
prior to heavy vegetation. In warmer southern areas, midwinter may be best;
while in dry arid regions, there may be no appreciable potential for detec-
ting leachate because little or none is produced.
Thermal scanners may be particularly effective in winter.
Analysis of Data
Photographic transparencies or prints can be analyzed individually or in
pairs if stereoscopic coverage is available. Magnification, especially through
variable magnification stereoscopes, is desirable.
Several enhancement procedures can be used with photographic film data,
including density slicing, additive color viewing, and subtractive color
viewing with diazo. In general, the more costly computer analysis procedures
will not necessarily provide a proportional increase in information.
Detection Methodology
The specific objective of a remote sensing program will determine the
most appropriate detection methodology. Two cases can be defined. One is
typical of regulatory monitoring where a general survey of a large number of
waste disposal sites is conducted to evaluate conformance to regulations. The
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major elements in this type of methodology are:
Step 1. Obtain topographic maps which locate landfills to be monitored,
Step 2. Fly 1:5,000 scale, aerial photographic coverage of each land-
fill using film-filter combinations which record ultraviolet,
blue, green, red, and near-infrared radiation.
Alternative A
Step 3A. Analyze photographs to identify the most probable locations
of leachate breakout or contamination.
Step 4A. Field check these most probable locations.
Step 5A. Take appropriate action based on verification of leachate
contamination.
Alternative B
Step 3B. Fly pre-dawn thermal infrared scanner coverage of all land-
fills.
Step 4B. Analyze thermal and photographic data.
Step 5B. (see Step 4A).
Step 6B. (see Step 5A).
Alternative C
Step 3C. (see Step 3A).
Step 4C. Based on the photographic analysis, select landfills to be
overflown with pre-dawn thermal infrared scanner coverage.
Conduct this sensing at a dry or frozen, low vegetation
period to maximize effectiveness of this sensor. Field check
other landfills as outlined in Steps 4A and 5A.
Step 5C. (see Step 4B).
Step 6C. (see Step 4A).
Step 7C. (see Step 5A).
The second general type of detection methodology applies to comprehen-
sive control monitoring. The major elements in this type of monitoring are:
Step 1. Obtain all available background information on the landfill
site, including topographic, soil and geologic maps and re-
ports.
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Step 2. Obtain aerial coverage of the undeveloped landfill site and
coverage flown periodically during the development of the
site.
Step 3. Analyze available aerial coverage, together with background
information, to identify the most probable locations of
leachate breakout or contamination.
Step 4. Field check the landfill site(s), concentrating on those
locations identified in Step 3.
Step 5. Fly new aerial photographic coverage of the landfills using
one or more film-filter combinations which are appropriate
for the expected spectral leachate indicators.
Step 6. Analyze the new photographs, together with the other aerial
and background data, to identify to most probable locations
of leachate breakout or contamination.
Step 7. Field check the landfill site(s).
Step 8. Upon verification of leachate contamination, plan remedial
measures.
(Steps 9 through 12 are optional extensions)
Step 9. Fly pre-dawn, thermal infrared coverage of the landfills.
Step 10. Analyze the thermal infrared data, together with all photo-
graphic and background data, to identify any additional
locations of suspected leachate breakout or contamination.
Step 11. Field check any new locations of suspected leachate.
Step 12. If required, modify planned remedial measures.
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SECTION 5
REMOTE SENSING OF LEACHATE
5.1 AN INTRODUCTION TO LAND DISPOSAL OF SOLID WASTE
Landfilling is a common and appropriate means for disposing of a wide
variety of solid waste. Materials commonly placed in a landfill include
municipal and industrial solid waste, construction and demolition debris,
sludges and dredging spoil as well as many unique substances peculiar to
certain locations. The major advantages of landfill disposal methods are low
cost, convenience and a lack of acceptable alternatives. Among the major dis-
advantages is the production of leachate with potential for contamination of
ground and surface water. Other methods of land disposal of solid waste, in-
cluding open dumping, may also develop leachate and, in most cases, the me-
thodology presented in this manual can be applied in these situations as well.
Leachate, as used in this report, is an extremely variable liquid consti-
tuent of landfill or other waste disposal (EPA, 1975). Leachates can be char-
acterized by their physical, chemical or biological properties, Table 5.1.
However, it is important to appreciate that the variability of leachate is
dependent upon the specific organic and inorganic substances dissolved in the
leachate at a particular time and place. To a large degree the particular
characteristics of a leachate depend on the source material at the land dis-
posal site. The characteristics of a leachate change, however. There is a
general tendency to change with time or age of the landfill and there may
also be a significant seasonal change or fluctuation, Figure 5.1.
Leachates can be positively controlled at the site of land disposal, or
they can flow from the site as part of the ground and surface water regime.
The extent to which leachate becomes an unacceptable pollutant of ground or
surface water is primarily dependent upon the quantity of leachate and the
effectiveness of various attenuation mechanisms, including dilution, decom-
position and several fixation mechanisms, particularly in the soil (Roberts
et al., 1976). In most cases it is not only leachate but also leachate-con-
taminated waters which are the objective of a monitoring program.
To provide a basis for considering the application of remote sensing tech-
nology to monitoring leachate it is appropriate to illustrate how and where
leachate is produced, Figure 5.2. The amount of leachate produced by direct
decomposition of wastes is usually insignificant. Most leachate is produced
when water flows through the waste either as a result of infiltration of pre-
cipitation or through irrigation from ground or surface waters. Unless a
control system is used, leachate will exit a landfill in several ways. Surface
runoff is often contaminated by leachate, as illustrated in Figure 5.2. Seeps
from the side or toe of a landfill are also common and are a major source of
contamination in surface waters. Groundwater is contaminated by leachate when
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TABLE 5.1. LEACHATE INDICATORS
Physical
Chemical
Biological
Appearance
pH
Oxidation-Reduction
Potential
Conductivity
Color
Turbidity
Temperature
Odor
ORGANIC
Phenols
Chemical Oxygen
Demand (COD)
Total Organic
Carbon (TOC)
Volatile Acids
Tannins, Lignins
Organ!c-N
Ether Soluble
(oil & grease)
MBAS
Organic Functional
Groups as Required
Chlorinated
Hydrocarbons
INORGANIC
Total Bicarbonate
Solids (TSS, TDS)
Volatile Solids
Chloride
Sulfate
Phosphate
Alkalinity and
Acidity
Nitrate-N
Nitrite-N
Ammonia-N
Sodium
Potassium
Calcium
Magnesium
Hardness
Heavy Metals (Pb, Cu,
Ni, Cr, Zn, Cd, Fe, Mn,
Si, Hg, As, Se, Ba, Ag)
Cyanide
Fluoride
Biochemical
Oxygen Demand
(BOD)
Coliform
Bacteria
(Total, fecal;
fecal strepto-
coccus)
Standard Plate
Count
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350
300
250
o»
c
o
200
o 150
o
100
50
Aug
Oct
Dec Feb
Apr
Jun
Month
FIGURE 5.1. FLUCTUATION OF A TYPICAL LEACHATE CHARACTERISTIC
(IRON) WITH TIME, AT FOUR SAMPLING POINTS, AT A
LANDFILL IN SOLON, N.Y.
11
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Precipitation
+ irrigation
Surface
runoff
w Evapotranspiration
Percolation ^v/y Natural land
Direction of grouno water flow
FIGURE 5.2. LANDFILL WATER BALANCE (AFTER WEHRAN
ENGINEERING CORP. AND GERAGHTY &
MILLER, INC., 1976)
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the water table intersects a landfill or when leachates flow to the ground-
water without sufficient attenuation. In this case the flow and ultimate
destination of the contaminated groundwater is of concern.
A variety of methods is used to control the production of leachate in
a landfill including surface or subsurface drains and low permeability
blankets or barriers (American Society of Civil Engineers, 1976). These
devices can significantly alter the flow of leachate as well as ground and
surface water around a land disposal site and must be considered when using
remote sensing systems. In many situations it is also appropriate to
conduct a more quantitative analysis of the hydrogeologic regime associated
with a land disposal site as part of a total monitoring program (Wehran
Engineering and Geraghty & Miller, Inc., 1976}. The methodology for doing
such an analysis is well-developed and can be found in numerous references.
In general a quantitative analysis of the water balance (Chow, 1964; EPA,
1975), surface and subsurface hydrology of site (Landon, 1969) requires spe-
cific on-site study by a professional geologist or groundwater engineer. A
qualitative description of the general flow regime is usually helpful as part
of a remote sensing program, however, and may not require the assistance of
other professionals.
5.1.1 Classification of Land Disposal Sites
Leachate contamination may occur in many ways, depending on the climate,
geological setting and control methods used. The effectiveness of remote
sensing systems to monitor leachate contamination under these different
conditions varies widely. If leachate is abundant and contamination of water
at a specific location can be anticipated, detection through remotely sensed
data is very straightforward. In other cases, however, the amount of leachate
contamination at or near the ground surface is small, Or the breakout may be
quite remote from the actual land disposal site. The use or usefulness of
remote sensors under these conditions will be very different. When evaluating
the application of remote sensing systems to monitor leachate contamination,
it is important to appreciate under what conditions these systems can be used
effectively and under what conditions it is unreasonable to expect positive
results.
The potential for leachate contamination from a land disposal site, and
the related potential for applying remote monitoring technology, can be used
as the basis for a classification system applied to the sites and their mode
of operation. As outlined in Table 5.2, these classification units will be
used in the development of the methodology in this report.
A detailed discussion of remote sensing applications in this classifi-
cation system is presented in the body of this report. In general, however,
the potential for applying remote sensing can be anticipated. Units A and B
present no problem from leachate contamination, and if contamination develops
in C, it will be undetectable using remote sensors. These three units are,
therefore, one set with little or no potential for monitoring leachate con-
tamination using remote sensing systems. For an inundated fill, D, there may
or may not be a detectable expression of leachate pollution, while for condi-
tions classified as E, F, or G there is a leachate contamination problem which
can be identified using remote sensors. Conditions of subsurface flow away
from a site, E, may be the most important application of remote sensing
13
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to define previously unknown problems, whereas F and G may be common condi-
tions for monitoring to check conformance to regulations.
Table 5.2. Classification of Landfill Sites
for Application of Remote Sensing
to Monitor Leachate Contamination
Unit Site Description
A. No leachate production
B. Effective positive leachate
control and removal
C. High permeability subsoil
draining to a very deep
groundwater
D. Inundated land disposal with
drainage into water
E. Subsurface flow of leachate
away from the site to break-
out at ground surface
F. Breakout through seep at the
landfill toe
G. Breakout through seep on the
face or top of the landfill
cover material
5.1.2 Characteristics of Leachate Detectable Using Remote Sensors
Leachate-contaminated water has several physical and chemical charac-
teristics which are potentially detectable using a variety of remote sensors.
Few of these chemical characteristics of leachate, Table 5.3, have any poten-
tial for direct measurement using remote sensors, however, many indirect
consequences of the leachate chemistry are detectable. The chemical nature
of leachate can cause stress in biota. Biological stress can be either posi-
tive, in which case it encourages growth, or it can be negative and toxic.
Changes in the surface and subsurface hydrology near a land disposal area
can also cause vegetative stress. This stress can be independent of leachate
pollution, as in the case of surface drainage changes upstream of a landfill,
or the vegetative stress can be a result of both contamination and hydrologic
change. Regardless of the cause, vegetative stress can often be detected using
remote sensors. The problem is to separate stress caused by leachate pollution
from other stresses.
Leachates are sometimes distinctive because of color. The red-orange
color of ferric iron compounds is one example while the unique color of some
biological growths in leachate-contaminated water may be another. Although
these colors can be detected using various sensors, the colors themselves are
14
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TABLE 5.3. CHEMICAL CHARACTERISTICS OF LEACHATE
4-
CONSTITUENT
Chloride (Cl)
Iron (Fe)
Manganese (Mn)
Zinc (Zn)
Magnesium (Mg)
Calcium (Ca)
Potassium (K)
Sodium (Na)
Phosphate (P)
Copper (Cu)
Lead (Pb)
Cadmium (Cd)
Sulfate (SO )
Total N
Conductivity (Vmhos)
TDS
TSS
PH
Alk as CaCO
Hardness tot.
BOD
COD
RANGE*
(mg/1)
34-2,800
0.2-5,500
.06-1,400
0-1,000
16.5-15,600
5-4,080
2.8-3,770
0- 7,700
0-154
0-9.9
0-5.0
1-1,826
0-1,416
0-42,276
6-2,685
3.7-8.5
0-20,850
0-22,800
9-54,610
0-89,520
RANGEt
(mg/1)
100-2,400
200-1,700
—
1-135
—
—
—
100-3,800
5-130
—
—
—
25-500
20-500
—
—
—
4.0-8.5
200-5,250
—
100-51,000
RANGE!-
(mg/l)
600-800
210-325
75-125
10-30
160-250
900-1,700
295-310
450-500
—
0.5
1.6
0.4
400-650
—
6,000-9,000
10,000-14,000
100-700
5.2-6.4
800-4,000
3,500-5,000
7,500-10,000
16,000-22,000
LEACHATE
FRESH
742
500
49.
45
277
2,136
—
—
7.35
0.5
—
—
—
989
9,200
12,620
327
5.2
—
—
14,950
22,650
OLD
197
1.5
—
0.16
81
254
—
—
4.96
0.1
—
—
--
7.51
1,400
1,144
266
7.3
—
—
--
81
§
WASTE WATER
50
0.1
0.1
—
30
50
—
—
10
—
—
—
—
40
700
--
200
8.0
—
—
200
500
§
RATIO
15
5,000
490
—
9
43
—
—
0.7
—
—
--
—
25
13
—
1.6
—
--
—
75
45
*Office of Solid Waste Management Programs, Hazardous Waste Management Division. An environmental assessment
of potential gas and leachate problems at land disposal sites. Environmental Protection Publication SW-110
of. [Cincinnati], U.S. Environmental Protection Agency, 1973. 33 p. [Open-file report, restricted distri-
bution] .
tSteiner, R. C., A. A. Fungaroli, R. J. Schoenberger, and P. W. Purdom. Criteria for sanitary landfill
development. Public Works, 102(2): 77-79, Mar. 1971.
^Gas and Leachate from land disposal of municipal solid waste; summary report. Cincinnati, U.S. Environ-
mental Protection Agency, Municipal Environmental Research Laboratory, 1975. (In preparation).
§Brunner, D. R., and R. A. Carnes. Characteristics of percolate of solid and hazardous waste deposits.
Presented at AWWA American Water Works Association 94th Annual Conference, June 17, 1974. Boston, MA 23 p.
-------
not unique in the natural environment and neither are there certain unique
colors associated with all leachates. Many leachates and leachate-contamin-
ated waters are clear. There is, nevertheless, potential for using certain
spectral bands in leachate detection under some conditions.
Leachate-contaminated water can also have surface coatings of lipids or
biological growths which can be detected using remote sensors. This may be
a particularly important target for inundated land disposal areas (Classi-
fication D) where few other indicators can be used.
There is lively biological activity in both landfill and leachates which
produces excess heat. Leachates can have a very high temperature and leachate-
contaminated ground or surface water can have a distinctive temperature even
when some distance from the land disposal site. From the standpoint of
remote sensing potential, the significance of heat in leachate is the re-
sulting difference between the temperature of leachate-contaminated and
uncontaminated ground and surface waters. As illustrated in Figure 5.3, the
temperature of leachate-contaminated water can be a potential target under
certain conditions of time and climate.
The potential for using remote sensing systems to indicate certain char-
acteristics of leachate-contaminated waters is summarized in Table 5.4. The
remainder of this report will critically evaluate this potential. It is im-
portant to realize that remote sensing is only part of a total monitoring
system. For a general survey to check compliance with certain regulations,
there is considerable potential for using remote sensors. Similarly there
are clearly applications to areas of complex geological setting. There is
little potential, however, for collecting legally admissible conformance
data using remote sensors. From the standpoint of cost effectiveness, the most
important application of remote sensing is to provide an indication of where
to look for leachate contamination. Ground sampling and analysis will usually
be necessary to confirm the condition.
5.1.3 Examples of Applications
Illustrations of the successful application of remote sensing to the detec-
tion of leachate-contamination are presented in Section 6. The illustrations,
and particularly the photographic plates, will be referenced in this section
where the theoretical limits to application of the sensors and methods are
described.
16
-------
10
8
6
4
0
-2
-4
-6
-8
8 10 12 2 4 6
21 April 22 April
8 10 12
Legend:
Temperature
sampling point
- Seep
- Pond
- Stream
- Soil
- Air
2
3
4
4
FIGURE 5.3. TYPICAL TEMPERATURE VARIATION
AROUND A LANDFILL (AFTER SANGREY
ET AL., 1976)
17
-------
5.2 THEORETICAL POTENTIAL FOR REMOTE DETECTION OF LEACHATE
If leachate is to be identified directly or indirectly with remotely
sensed data, then leachate or a leachate-related feature must, at the time
of sensing, appear spectrally different from its surroundings or have some
unique or identifiable spatial characteristic. The spectral and spatial
indicators of leachate can be examined from the standpoint of detection with
data acquired by airborne sensors of electromagnetic radiation. A variety
of sensors can be used depending on the characteristics of the target,
Figure 5.4.
Multispectrai scanners
IR
film
Active radar
Passive
microwave
Ordinary
film
Infrared
instruments
XX
Ultraviolet
Infrared
I mm I Ocm Im
_, Millimeter
and
microwave
Scale variable
FIGURE 5.4. ELECTROMAGNETIC SPECTRUM WITH
TYPES OF SENSORS (AFTER HOLTER, 1971)
5.2.1 Object Detection Through Sensing of Spectral Differences
In general, radiation from the ground that reaches an airborne sensor has
been reflected or emitted into the sensor's field-of-view and transmitted
through the atmosphere. The amount of radiation received by the sensor is
directly proportional to the amount of radiation reflected or emitted by ob-
jects on the ground. Ground objects which reflect or emit different amounts
*A comprehensive treatment of all facets of remote sensing can be found in the
American Society of Photogrammetry1s Manual of Remote Sensing (Reeves, 1975).
18
-------
of radiation of the wavelength being sensed are potentially separable with
data acquired by the sensor—even if the objects are identical in spatial
characteristics. For example, if a stressed tree reflects or emits different
levels of radiation than an unstressed tree, then the trees can be differen-
tiated. Similarly, a wet soil site will be distinguishable from a dry soil
site if the two reflect or emit different amounts of radiation to a sensor.
The amount of radiation that will be reflected by an object, and thus
potentially sensed, is determined by the incoming radiation and the surface
characteristics of the object. The amount, incidence angle, wavelength and
polarization of the incoming radiation are significant. An object's reflec-
tance refers to the proportion of incoming radiation that will be reflected,
the remaining radiation being absorbed or transmitted by the object.
The amount of radiation that will be emitted by an object is determined
by the object's temperature and emissivity. All objects at a temperature
above absolute zero (-273.15°C) emit radiation; the higher the temperature,
the greater the amount of radiation emitted. Two objects at the same temper-
ature will emit different levels of radiation if their emissivities differ.
The emissivity of a material is, in effect, an efficiency factor, the ideal
emitter (blackbody) having an emissivity of 1.0. In the infrared region,
for example, most non-metals have emissivities greater than 0.8 and, commonly,
over 0.9 (Wolfe, 1965).
The capacity for detection or separation is not limited to those objects
that reflect or emit different total amounts of radiation. Objects may also
be distinguishable when the total amounts of radiation they reflect or emit
are identical. As long as the objects reflect or emit in at least one dif-
ferent wavelength or wavelength interval, which is capable of being sensed,
the objects are potentially separable. For example, while a blue water body
and green water body may reflect like amounts of radiation overall, the two
are distinguishable if radiation in the blue and/or green can be sensed
separately. Analogously, separating stressed from unstressed trees, or wet
from dry sites, might be accomplished by sensing in certain wavelengths but
not in others.
In this context, it is important to note that an object's reflectance
and emissivity normally vary with wavelength. Objects can be characterized
by their spectral reflectance or spectral emissivity, the former being
applied in characterization more commonly than the latter, Figure 5.5.
When considering reflected radiation and an object's spectral reflectance,
one must be conscious of the sources of radiation. The principal source for
passive, airborne sensing of reflected radiation is the sun, the spectral
distribution of which is shown in Figure 5.6. As can be seen, objects may re-
flect little radiation at wavelengths longer than, say, l.Sym simply because
relatively little solar radiation is available for reflection. In fact, at
wavelengths longer than about 3 to 4ym, the amount of radiation that natural
objects emit usually exceeds the amount of radiation that they reflect.
The maximum amount of radiation that any object can emit, at any tem-
perature and wavelength, is described by Planck's Equation. As illustrated
19
-------
o
o
"o
—
«*-
0)
90
80
70
60
50
40
30
20
10
0
Snow
(Kondratyev, 1969)
Absorption
by water
(Kondratyev, 1969)
Vegetation
{CORSPERS, 1976)
30
20
E
o
c
0)
'o
a>
o
o
10 £
.5
.6
.7
Blue
Green
Red
.8
Near infrared
.9
0
0
Wavelength, /xm
FIGURE 5.5. SPECTRAL REFLECTANCE OF TYPICAL VEGETATION, SOIL
AND SNOW; AND ATTENUATION COEFFICIENTS OF WATER
20
-------
in Figure 5.7, objects at temperatures normally encountered on the earth's
surface emit maximum radiation near lOym. The ideal maximum emission, given
by Planck's Equation, is reduced for any real object because of the object's
spectral emissivity.
One final point on airborne sensing of radiation concerns atmospheric
transmission. If reflected or emitted radiation passes from ground to sensor,
it will be affected (scattered, absorbed) by moisture, gases and various sub-
stances in the atmosphere (aerosols). In sensing of ground objects, one nor-
mally takes advantage of certain wavelength intervals of relatively high
transparency, "windows," that characterize the atmosphere, Figure 5.6. Yet
some effect is usually observed, especially from higher altitudes.
5.2.2 Leachate Indicators for Sensing
The spatial and spectral indicators of leachate are listed in Table 5.4.
They include observable features of leachate itself—wetness or an anomalous
spectral response from snow, water, soil or rock—and observable effects of
leachate—gaps in a vegetative or snow cover, or an anomalous spectral re-
sponse from grass or taller vegetation. The most useful wavelength intervals
for identifying leachate indicators with reflected solar radiation are indi-
cated in Table 5.5.
If large or small gaps in snow or a vegetative cover can be related
spatially to a landfill, they often signal the presence of leachate (see
Plate 2). Caused by the leachate1s wetness, toxicity or heat, the gaps can
be isolated (Classification G)or they can radiate from the landfill (Clas-
sification E or F). Since heat would dissipate rather quickly with dis-
tance, heat-caused gaps should be found close to the landfill. In contrast,
gaps caused by wetness or toxic substances can occur at longer distances from
the landfill, 500 meters being quite reasonable.
Vegetative gaps which expose bare soil or rock would be easily detected
in the visible or near-infrared regions. The spectral reflectance of vege-
tation is relatively high in the green and low in the red, while the spectral
reflectance of soil is high in both, Figure 5.6. The near-infrared reflec-
tance of vegetation and soil are both relatively high, but the reflectance
of vegetation is normally much higher.
In the thermal infrared and microwave regions, the emissive properties
of most taller vegetation are sufficiently different from those of bare
soil that gaps would be distinguishable (Reeves, 1975); however, gaps in
a grass cover are likely to go unnoticed. In contrast, active microwave
sensing (by radar) should detect most vegetative-soil gaps that are not
obscured from view (Matthews, 1975).
Compared to vegetation, snow presents an even greater contrast with soil
or rock (Rango, 1975). The spectral reflectance of snow is high over the
visible and near-infrared wavelengths, and the spectral emissivity of snow
is different from that of soil in both the thermal infrared and microwave
regions. Given the difference in electrical properties of snow and soil,
gaps in a snow cover might also be detectable by virtue of microwave
21
-------
0.25
0.20-
CM
0.15-
E
u
CD
u
TJ
O
0.10-
- 0.05 -
o
CO
Solar irradiation outside atmosphere
Solar irradiation at sea level
1.0
Wavelength,
2.0
3.0
FIGURE 5.6. SPECTRAL IRRADIANCE OF SUN
AND ABSORPTION BANDS OF ATMOSPHERIC
CONSTITUENTS (AFTER VALLEY, 1965)
1.5
CM
E
£ 1.0
FIGURE 5.7. SPECTRAL RADIANCE OF
A BLACKBODY (AFTER WOLFE, 1965)
8
0.5
CD
a.
CO
40°C
22
25 10 15
Wavelength, p.m
20
-------
TABLE 5.4. SPATIAL AND SPECTRAL INDICATORS OF LEACHATE
BACKGROUND/ GAP IN ANOMALOUS SPECTRAL RESPONSE
SURROUNDINGS COVER* WETNESS* REFLECTIVE EMISSIVE
soil/rock with XXX X
grass cover
soil/rock with XX X
little or no
grass cover
snow X X
water X X
taller vegetation X XX
*A1though observable because of their spectral response, wetness and gaps
in a vegetative or snow cover are listed separately for ease of discussion.
Wetness ranges from damp areas to puddled water.
TABLE 5.5. SPECTRA BANDS FOR DETECTING LEACHATE THROUGH REFLECTED RADIATION
LEACHATE INDICATOR PRIMARY SECONDARY
Gaps
Vegetation/Soil, Rock Infrared, Red
Snow/Soil, Rock Blue, Green
Wetness
Soil Infrared Red
Soil with Grass Infrared
Spectral Anomalies
In Water Red, Green Blue
On Water (lipids) Ultraviolet Blue, Infrared
On Soil Red, Green Infrared
On Grass Red Infrared, Green
Stressed Vegetation Infrared Green, Red
23
-------
reflectances.
Overall, recognition of a gap in a vegetative or snow cover should be
easily accomplished through airborne sensing. Since these gaps are not
limited to leachate-affected sites, the primary task would be to relate the
gap to the landfill. Topographic and, to the extent possible, geologic
analyses are normally required.
Wetness
Similar to gaps, any damp, saturated or puddled sites that can be re-
lated spatially to a landfill are potentially contaminated by leachate (see
Plate 3). As with gaps, wetness can radiate from the landfill or occur in
small or large isolated spots, or seeps, the distance and direction from the
landfill being highly variable. Wetness can often be deduced from the
vegetative types. If not, its spectral characteristics are sufficiently
distinct that wetness is detectable over the entire electromagnetic spectrum.
In the red and near-infrared regions, for example, the reflectance of
bare soil is relatively high while water usually exhibits increasing absorp-
tion from the green to the near-infrared (Fritz, 1967; Kondratyev, 1969).
Under most circumstances, reflective differences between dry sites and
saturated or puddled sites will be easily observed in the near-infrared and
red regions. Although damp sites will not present as obvious a contrast as
saturated or puddled sites, at least the wetter sites will be separable.
With increasing soil moisture, soil reflectance decreases throughout the
visible and near-infrared wavelengths (e.g., Bowers and Hanks, 1965).
The affect of a grass cover on the observed soil-water reflectances
will be more pronounced as the density of the grass increases. Although soil
reflectance decreases with increasing moisture, the green and especially the
near-infrared reflectance of unstressed grass will tend to offset the effects
of soil moisture. During drier periods, the wetter, grass-covered sites
might be distinguished by their higher green and near-infrared reflectance
if the surrounding grass cover is stressed by a moisture deficiency. The
reverse effect might be observed if the grass at the wetter sites is stressed
by excessive moisture.
In the thermal infrared region, water could be differentiated from soil or
grass at the same temperature because of its higher emissivity. More signifi-
cantly for sensing, however, the thermal properties (diffusivity and inertia)
of water, soil and rock are such that land normally heats and cools more rap-
idly than water bodies. From midday to late afternoon and from late night to
pre-dawn hours, the temperature of water will usually be at or approaching
equilibrium with the surrounding land. At other times, the water will appear
warmer (evening) or cooler (morning) than the land, Figure 5.3. Damp or satu-
rated sites will not be as distinguishable as sites of standing water, but
their apparent temperatures (emissions) should fall between those of water and
land (Myers et al., 1970; Blanchard et al., 1974). Detection of wetness at
microwave wavelengths can be accomplished with passive or active sensors. If
observed directly, standing water is separable from its surroundings by virtue
of its higher emission, at comparable temperatures, or by virtue of its
specular reflective properties. Under certain conditions, fair correlation
24
-------
has also been demonstrated between levels of soil moisture and microwave
emission or scattering coefficients (Schmugge et al., 1976; Ulaby et al. ,
1974) .
Other Spectral Anomalies
Leachate will sometimes produce an anomalous spectral response besides
that associated with wetness or gaps. Although these spectral anomalies
usually provide a more positive indication of leachate than gaps or wetness,
they must still be traceable to the landfill.
The spectrally reflective anomalies listed in Table 5.4 arise from the
possible differences in reflectance between leachate and soil, grass, snow
or water, and between leachate-stressed and unstressed vegetation (see
Plate 4). As an example, leachate may exhibit an unusually high red reflec-
tance because of its high ferric iron content (Section 5.1.2). Although this
is not unique to leachate, the response contrasts markedly with that from
grass, snow or btherwise clear water, and, to a lesser extent, with that from
soil or rock (see Plate 5).
In a similar manner, lipid coatings on leachate-contaminated water
should, like oil, be detectable through passive or active sensing in the
ultraviolet, blue, thermal or microwave regions, or at various Fraunhofer lines
in the visible region (Kennedy and Wermund, 1971; Vizy, 1974; Watson et al.,
1975). Also, the spectral reflectance of positively or negatively stressed
taller vegetation might show anomalies at any visible or near-infrared wave-
length, though the near-infrared wavelengths are apparently more sensitive
to a broader range of stresses (CORSPERS, 1976).
The spectrally emissive anomalies listed in Table 5.4 arise from the
possible differences in temperatures and/or emissivities between leachate
and soil, with or without grass cover; between leachate-affected and unaffected
water; and between leachate-stressed and unstressed vegetation. Sensing for
spectrally emissive anomalies can be conducted in the thermal infrared or
microwave regions.
5.2.3 Temporal Aspects of Leachate Detection
Two categories of temporal factors must be considered in a leachate
detection program. The first relates to the value of monitoring the develop-
ment of the landfill from its initial stages to the present; the second re-
lates to the effect of season and time of day on the capacity to detect lea-
chate.
For many landfills, the prevailing drainage conditions were established
prior to the development of the site, and they have been changed little by
the landfill operation. In other cases, the development of the landfill causes
significant change at the site proper, but does not affect subsurface drainage
which surfaces at a distance from the site. Seldom will the development of
a landfill alter the drainage so completely that it will be totally different
from pre-landfill, or at least early-landfill, conditions. Consequently,
as discussed in Section 5.4.1, examination of remotely sensed images (e.g.,
25
-------
aerial photographs) of the undeveloped and developing site will normally pro-
vide valuable information regarding where to expect leachate (see Plate 1).
It should be obvious that since weather and climate are major deter-
minants of the amount of leachate produced, as well as the amount of vegeta-
tion or snow present to hinder detection, seasonal factors become especially
important. In general the potential for leachate production is high during
wet periods and low during dry or frozen periods. The potential for leachate
detection is normally lowest during times with deep snow or full canopies
of taller vegetation (see Plate 7).
Among other effects of season (and latitude) is the amount of shadows
which may obscure leachate indicators from overhead detection. As is ob-
vious, sun shadows are also associated with the time of day. In most in-
stances high sun angles at midday are best for detecting leachate indicators.
Although the water surface glint that accompanies higher sun angles may
obscure an anomalous spectral response, it will, at least, facilitate the
identification of wetness. In contrast, sensing of emitted radiation might
best be conducted during non-daylight hours (Section 5.2.2).
5.3 DEVELOPMENT OF A LEACHATE DETECTION PROGRAM
Landfill leachate has been described with emphasis placed on spatial and
spectral features that might serve as direct or indirect indicators for detec-
tion. With this background, the elements of a leachate monitoring program
can be reviewed.
5.3.1 Sensor Selection—Spatial Considerations
In developing a program for remote sensing of landfill leachate, one
early consideration is the sensor. Of the many possible sensors that might
be applied, which can provide data sufficient to detect leachate, and
which is the best sensor or combination of sensors?
For leachate detection, a sensor must provide data which allow an assess-
ment of the spatial relationships between indicators of leachate and the land-
fill under study. This requirement can only be filled effectively with
an imaging sensor; spectrometers, radiometers and other non-imaging sensors
cannot supply sufficient data unless numerous cross sections are flown.
In general, four types of imaging sensors would be judged applicable at
this time: (1) photographic film cameras, frame (still or movie) or panoramic;
(2) television or imaging tube cameras, (3) scanning radiometers ("scanners");
and (4) side-looking radars. From among these sensors, still or panoramic
film cameras and scanners would be favored for a leachate detection program.
Certain television, image tube and movie cameras are reasonable alternatives;
however, their resolutions (spatial and/or spectral) or sensitivities, are
usually inferior, and their outputs are not as conveniently processed or an-
alyzed for detail (Baker et al., 1975). Similarly, side-looking radar data
are costly to acquire, and the higher resolution, synthetic aperture radars
require special facilities for data processing (Matthews, 1975). In addition,
the spatial resolution of available radar imagery is insufficient to detect
smaller features.
26
-------
Photographic Cameras
The spatial aspects of camera selection call for a trade-off among
camera focal length, photographic scale, film format and ground coverage,
Figure 5.8. The photographic scale at any point in a vertical aerial photo-
graph is:
S = f/(H - h)
where f = camera focal length
H = camera height above datum
h = height of point above datum
For example, in Figure 5.8,
photo scale at A = Sa = f/(H - ha)
photo scale at B = Sj-, = f/(H - h,)
Denoting the ground distance between points A and B by Dab,
°ab = [(VV - (W]2 + [(W - (VSa)]2
where x , y and x , y are the photographic coordinates of points A and B
(based on a Cartesian coordinate system defined by the fiducial marks).
As an approximation,
D = (photo distance, a to b)/(average scale, A and B)
ab
Commonly available aerial frame cameras have film formats of 23 by 23 cm
(mapping or reconnaissance), 11.5-by-11.5 cm (13 cm reconnaissance), and
5.7 by 5.7 cm (70 mm reconnaissance); and the format of a 35 mm camera is
2.4 by 3.6 cm (Slater, 1975). While any of these cameras could be employed
to acquire a desired scale of photography, the larger the format the greater
the ground area imaged per photograph for the same scale, Table 5.6. Regard-
less of the scale, a photograph obtained with a 23-cm format camera will cover
approximately 16 times the area covered by the same scale 70-mm photograph.
Available maps of a site can be a factor in camera selection. If a
topographic map of the landfill site is already in existence (e.g., U.S.
Geological Survey 7.5 minute map), a cartographic quality mapping camera
would not be required for monitoring. Any of the reconnaissance cameras re-
ferred to above might be selected. Two other types of reconnaissance cameras
that might also be considered are panoramic and multiband (multi-lens) cameras.
Panoramic cameras are typically high resolution, 13-cm or 70-mm film
cameras. The angular coverage of most exceeds 100° and may reach from horizon
to horizon. The disadvantage of panoramic cameras is that the photographs are
systematically distorted in scale, there being substantially more ground area
imaged along the horizon than along the line of flight. The characteristics
of the image and distortion with various sensors are illustrated in Figure 5.9.
Most multiband cameras have four lenses, each of which forms a separate
image (8.9 by 8.9 cm or 5.7 by 5.7 cm) on the same 24-cm film. By using
27
-------
Photo
Elevation
Above datum = H
Above A: H; = H-hc
.Above B: H' = H-h
B
FIGURE 5.8. RELATION BETWEEN AERIAL PHOTOGRAPH
AND GROUND SURFACE
28
-------
Line of flight
Line of flight
Line of flight
c.
FIGURE 5.9. DISTORTION PATTERN OF A UNIT GRID
BY FRAME CAMERA, a, PANORAMIC CAMERA,
b, AND SCANNER, c (AFTER MASRY AND GIBBONS
1973)
29
-------
TABLE 5.6. GROUND AREA IMAGED BY DIFFERENT FORMAT
PHOTOGRAPHS OF DIFFERENT SCALES
CAMERA AND GROUND COVERAGE (meters) AT DIFFERENT SCALES
FORMAT (cm) 1:1,000 1<5,000 1:10,000
23-by-23
(mapping or
reconn.)
230x230
1150x1150 2300x2300
11.5-by-11.5 115x115
(13 cm reconn.)
575x575 1150x1150
8.9-by-8.9
(multiband)
89x89
445x445
890x890
5.7-by-5.7
(70 mm reconn.
or multiband)
57x57
285x285
570x570
2.4-by-3.6
(35 mm)
24x36
120x180
240x360
different spectral filters on each lens, and a black-and-white film sensitive
to visible and near-infrared radiation, four different black-and-white spec-
tral images (e.g., blue, green, red, near-infrared radiation) of the same
scene may be acquired simultaneously. The spectral images can be viewed
individually or together, as will be discussed in Section 5.3.2.
Scanners
Thermal infrared, multispectral and microwave scanners might all provide
valuable data in a leachate monitoring program. Only thermal and multispec-
tral scanners will be considered, however, since few microwave scanners are
in existence, and their resolutions are inadequate for detecting most leachate
indicators. In contrast, several potentially effective thermal and multi-
spectral scanners are available commercially (Lowe et al., 1975) (see Plate
6).
The most common scanners are optical-mechanical sensors which use a mirror
or prism to focus radiation from the ground to one or more detectors. The
mirror revolves, scanning a line of incoming radiation perpendicular to the
aircraft's direction. Figure 5.10. New, adjacent lines are scanned as the
aircraft moves ahead.
The spatial aspects of a scanner which are of primary concern for sensing
leachate are the scanner's instantaneous field-of-view (a-by-a in Figure 5.10),
its total field-of-view (9), and the ratio of its maximum allowable velocity
to its height above ground [(V/H) , angular velocity with respect to a around
target]. max
30
-------
FIGURE 5.10.
GEOMETRY OF AIRBORNE SCANNING
RADIOMETER (SCANNER)
31
-------
The total field-of-view of a scanner is the scanner's lateral coverage.
It is analogous to the angular coverage of an aerial camera in the direc-
tion perpendicular to the aircraft's flight direction. Unlike a camera,
however, a scanner does not collect radiation over its total field-of^view
at one instant of time. As noted, the scanner mirror covers the total
field-of-view by "looking" sequentially at numerous, adjacent ground spots
(resolution elements) along one scan line. This ground spot is the smallest
area that the scanner can "see"; all radiation emanating from the spot is
integrated and seen as a single level of radiation for each wavelength in-
terval sensed. The size of the ground spot is determined by the scanner's
instantaneous field-of-view, its height above ground, and the scan angle 3,
the angle between the ground spot and the aircraft nadir.
To illustrate, a typical scanner might have a square instantaneous field-
of-view of 2.5 milliradians on a side, and a total field-of-view, 6, of 120°,
or 60° to either side of the aircraft. Approximating the length of the ground
spot as the arc of a circle whose center is at the scanner, an angle of 2.5
milliradians would intercept an arc of 0.0025 times the radius. For every
1,000 meters of aircraft height above ground, the size of the ground spot
viewed directly below the aircraft would increase by 2.5 meters (R = H = 1,000)
The corresponding increase for ground spots away from the aircraft nadir
would be larger because the distance between the scanner and spot (the radius
of the circle) is longer. For every 1,000 meters, other ground spots would
increase by 2.5/cosB, where 3 is the scan angle. If the instantaneous field-
of-view were square (2.5 milliradians on each side), the area of the ground
spots would increase by (2.5/cos3) .
5.3.2 Sensor Selection—Spectral Considerations
Leachate indicators—gaps in a vegetative or snow cover, wetness, and
other spectral anomalies that can be related spatially to a landfill—were
discussed in Section 5.2.2. Sensors for identifying these indicators were
reviewed in Section 5.3.1, where several types of photographic cameras and a
multispectral or thermal scanner were judged most applicable on the basis of
spatial factors. The spectral features of leachate indicators allow further
refinement in sensor selection. Specifically, they provide the basis for
selecting the most effective film-filter combinations and sensing bands for
the cameras and scanners respectively.
The most useful wavelength intervals, or spectral bands, for detecting
leachate indicators through reflected solar radiation are listed in Table 5.5.
As shown in Table 5.7, these bands can be sensed by various photographic
films, singly or in combination, and by a multispectral scanner. Although a
multispectral scanner could be applied successfully in place of photographic
camera systems, photographs are less expensive to acquire, process and analyze,
and they are normally of higher spatial resolution. If photographic systems
have the spectral capacity to monitor leachate in the ultraviolet, visible
and near-infrared regions, the unique data acquirable by multispectral scanner
are limited to the infrared region, particularly the thermal infrared. Thermal
data can best be acquired during non-daylight hours at a time when the other
possible multispectral scanner data would not be obtainable. Consequently,
a thermal infrared scanner would seem preferable to a multispectral scanner
with a thermal channel, Table 5.7.
32
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TABLE 5.7. PHOTOGRAPHIC CAMERA AND SCANNER.SYSTEMS FOR LEACHATE DETECTION
SENSING OPTION
METHOD OF
SENSING
BANDS SENSED
AND RECORDED
SEPARATELY
COMMENTS
1. Photography
a. color film
single camera;
single image
B, G, and R* recorded as
B, G, and R, respectively
UV can be sensed if recorded with
B**; contrast of B layer will be
lowered; proper exposure for UV and
B will likely underexpose GSR
b. color infra-
red film
Idem
G, R, and IR recorded as
B, G, and R respectively
UV and B cannot be sensed without
affecting G, R, and IR
c. panch romati c
film (black &
whi te)
Multilens camera
or several cam-
eras, with spec-
tral filters; mul-
tiple images
UV, B, G, and R, each
recorded as black & white
Lower contrast of UV image will not
affect other spectral images
U)
d. black & white
infrared film
Idem
UV, B, G, R, and IR, each
recorded as black & white
Most multilens cameras have 4 lenses;
lower contrast of UV image will not
affect other spectral images
2. Multispectral
scanner
Single scanner; Any reflected or emitted
magnetic tape, bands from UV, visible &
with or without IR, including thermal;
image of one band each band recorded as di-
off cathode ray gital or analog signal on
tube or similar tape; if recorded in aircraft,
monitor one band as black & white film
Analog or digital data for any band
or combination of bands can be prin-
ted on paper, displayed on video, or
converted to photographic film
3. Thermal scanner
Single scanner; Commonly 8-14ym and/or 3 - Idem, if recorded on tape
magnetic tape Sum; recorded as digital
and/or image of or analog signal on tape, or
one band off cath- as black & white film
ode ray tube or
^^__ similar monitor
*B-Blue, G-green, R-red, IR-infrared, UV-ultraviolet
**Sensing of ultraviolet radiation will be limited by glass lens to wavelengths longer than about 0.36pm.
-------
Selection of a photographic system is dependent upon the number and
types of landfills to be monitored and the availability of equipment, facili-
ties and/or funds. To illustrate, a local environmental group might wish to
monitor a single landfill. This group would likely choose one photographic
film for use with a hand-held 35-mm camera. A color infrared film would
be more generally applicable than other films (Tables 5.5 and 5.7). But,
if monitoring an inundated landfill (Classification D), where lipids might
be expected, a black-and-white film filtered to receive ultraviolet and blue
radiation might also be considered.
In contrast, a county environmental or health agency might employ one
or more 70-mm or 13-cm cameras, loaded with spectrally filtered, black-and-
white films or with some combination of color and black-and-white films.
A state monitoring agency might prefer the flexibility of a four-lens multi-
band camera, as outlined in Table 5.7. The U.S. Environmental Protection
Agency, which has limited familiarity with the specific landfills in a
region to be overflown, might try to allow for all spectral and spatial in-
dicators of leachate by carrying a 23~cm format camera, loaded with color
infrared film, and smaller format cameras, loaded with other films (in-
cluding one imaging blue and ultraviolet radiation). Overall, many com-
binations are possible and effective.
At this point, the value of thermal infrared data might be questioned.
If leachate indicators can be identified with photographic systems, are
thermal data really necessary? In general, thermal data may:
(1) confirm or refute the interpretation/existence of a photo-
identified indicator (e.g., enhance wetness);
(2) provide some indication of the status of leachate contamin-
ation (e.g., if it is hot, a wet area is likely contamin-
ated) ;
(3) detect other indicators which were overlooked or undetectable
with photographic systems (e.g., very small hot spots or
wet spots in a forested area); or
(4) provide no additional information.
Thermal data thus provide complementary and supplementary information
which is of maximum value in limiting field checks to the most probable
sites of leachate contamination.
5.3.3 Flight Parameters
The design of an aircraft mission for detecting leachate is governed
largely by the sensor(s) utilized and the spatial, spectral and temporal
characteristics of leachate. For a given sensor, the size and/or spectral
response of leachate indicators and the size of the leachate-affected area
set limits on the flight height. The seasonal and diurnal characteristics
of the indicators as well as the local weather set limits on the optimum
time for sensing.
34
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Photographic Sensing
Leachate-related gaps in a vegetative or snow cover, and damp, saturated
or puddled sites, are quite variable in size. Most, if not all, leachate
problems would be discovered, at least potentially, if the photographic
sensing could detect gaps and wetness of one meter across (see Plates 2
and 3) .
If one-meter gaps or wet spots were spectrally distinct they should be
detectable with photographic scales of about 1:5,000 or larger. On a 1:5,000
scale photograph, a one-meter ground spot would be 0.2 mm, which is easily
seen with magnification. A scale of 1:5,000 could be obtained with a 150-mm
focal length camera by flying at 750 meters above ground, while shorter
focal lengths would require lower flying heights (H = 5,000f, where f =
focal length in meters).
The ground areas photographed by different size films, at a scale of
1:5,000, are listed in Table 5.6. Although the size of landfills and their
potentially affected areas vary (compare E, F, and G in Table 5.2), it is
probable that several flight lines would be required to obtain the required
coverage at 1:5,000 scale with 35-mm or 70-mm photography. The advantages
of larger format photography are obvious, and these advantages may increase
if stereoscopic coverage of the landfill is desired. Smaller film formats
would require faster camera cycling or slower aircraft to obtain 1:5,000
scale photographs which overlap by at least 50% from any given flight height.
As described in Section 5.2.3, photographic sensing for leachate should
be conducted with high sun angles. The likelihood of detecting potential
sites of contamination with photographic sensors should increase as the
amount of vegetative or snow cover decreases or as the amount of leachate
increases. The optimum seasons and conditions for photographic and thermal
sensing of leachate are summarized in Table 5.8. Ratings in the table
are subjective and relative for photographic or thermal sensing^ the two
sets of ratings should not be considered as one.
Thermal Sensing
The temperature of leachate near a landfill may be several degrees
Celsius higher than uncontaminated waters in the vicinity. Figure 5.3.
Thermal infrared scanners can detect apparent temperature differences of
less than a degree (Lowe et al., 1975). Nevertheless, two objects which
emit different amounts of radiation because they are at different temperatures
will be differentiated only if they are seen separately (i.e., if they are
within the scanner's instantaneous field-of-view at different times).
As noted in Section 5.3.1, all radiation within the scanner's instan-
taneous field-of-view (IFOV) is integrated, such that a weighted average of
radiation is sensed.
35
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TABLE 5.8. THE POTENTIAL FOR DETECTING LEACHATE UNDER
DIFFERENT VEGETATIVE AND SEASONAL CONDITIONS
VEGETATIVE COVER
SEASONAL
CONDITIONS
Wet
Dry or
Frozen
Partial
or Light
Snow
Full or
Heavy Snow
MODE OF
SENSING
photo
thermal
photo
thermal
photo
thermal
photo
thermal
NONE
E*
E-G
E-G
E
F
E
F-P
G
GRASS
E
E-G
G
E
F
E
F-P
G
PARTIAL
CANOPY
G-F
F
F
G
F
G
P
G-F
FULL
CANOPY
F-P
P
P
P
P
P
P
P
*Ratings of Excellent (E), Good (G), Fair (F), and Poor
(P) are subjective for midday photographic or pre-dawn
thermal sensing. The two ratings are not equivalent.
To illustrate, if an anomalously hot leachate seep fills the scanner's
IFOV, its level of radiation (higher proportionately than the background
radiation) would lead to detection. If the seep filled only a part of the
scanner's IFOV, the radiation sensed would still exceed that from the back-
ground alone, but the difference may not be detectable, or discriminated,
by the scanner's detector.
A general equation for estimating flight and scanner parameters required
for detecting a leachate "target1' with a thermal infrared scanner is (see
derivation in Appendix A):
4 4 As(V/H)V2(6)1/2(4F)
geT -geT >
yt t ys s s
t, s
f
V/H
a
e
a
A
2 1/2
A a (cosg)DD* (2py) CTTT
= subscripts denoting target and surroundings, respectively
= fractions of total radiation emitted in spectral interval being
sensed
= spectral emissivities
= temperatures (°K)
= ratio of aircraft velocity to height (radians/sec)
= instantaneous field-of-view of scanner (radians)
= total angular coverage of scanner; total field-of-view (radians)
= Stefan-Boltzmann constant = 5.67 x 10~8 Watts/m2°K4
= area (m2) within instantaneous field-of-view
2
= area (m ) of target, where A is less than A
t s
= angle (degrees) between aircraft nadir and target
36
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D
T
T
0
P
Y
D*
- aperture ratio of scanner optical system, where F = focal
length/D
= diameter (meter) of collecting aperture
= spectral transmissivity of atmosphere
= spectral transmissivity of scanner optical system
= number of detecting elements; number of lines scanned per sweep
= scan duty cycle or efficiency
= spectral detectivity of detector (m/Watt-sec )
A simple, single-mirror scan system might have the following design values
(Lowe et al., 1975):
F = 2
D = 8 cm = 0.08 m
V/H = 0.2 radians/sec
6 = 120° =2.1 radians
a = 0.003 radians
T = 0.6
o
p = 1
Y = 120°/360° = 0.333
D* = 108 m/Watt-sec1/2
Substituting these values into the equation, results in the following:
g e T -geT4> (2.59 x 1Q6)(A )/(A rcos3)
tttsss st
g and g vary with the spectral interval being sensed
The fractions
and the temperature of the radiator (e.g., Siegel and Howell, 1972).
the target and surroundings are at temperatures of approximately 10°C (283°K)
and if the emissions are being sensed over the 8 to 14-ym interval, g and
g are both approximately 0.36. Further, while atmospheric transmissivity,
T, is highly variable and wavelength dependent, a reasonable estimate is
0.8. With these values, the equation becomes:
- e T4
S S
> (9.00 x 10
(A )/(A cosB)
S L
To use this equation for estimating the maximum height that an aircraft
could fly and still detect a thermal target, one could replace A with H using
the following relationship (Appendix A):
22 2
A = H a /cos 3
S
In estimating H, an average value for 3 would be 30°, and a was given as
0.003 radians. With these values, the equation could be written:
4
- e T
s s
_ _ > 124.72H /A
t t s s t
This equation provides estimates for how much different the temperature of
a target and it surroundings must be (T vs T ) before a specific size
target (A ), located at a specific distance from the scanner (H/cosg), can
be detected by the scanner. To determine the maximum flight height, one
needs estimates for the temperatures and emissivities of the target and its
surroundings, and the size of the target.
As noted in Section 5.1.2, the highest temperature leachate and con-
taminated water will be near the landfill. At the point of breakout from
the landfill or ground surface, the seep is usually at its smallest size, and
designing for a 0.5-meter (0.25m ) target seems reasonable.
37
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A substantial temperature difference between a leachate seep and its
surroundings would be observed in the evening (Sec. 5.2.2). But, at this time,
all waters might appear equally warm. To optimize target detectability,
the thermal mission should be flown just before sunrise (i.e., pre-dawn).
At this time, warmer leachate seeps should be separable from other waters
as well as from their vegetative and soil surroundings. While the tempera-
ture difference might be large or small, for design, a difference of 3°C would
seem reasonable.
During the spring months, for example, the temperature of the seep might
be at 10°C while the surroundings are at 7°C. The emissivity of the seep
would be that of water, approximately 0.97, and the emissivity of the sur-
roundings might be that of a soil-vegetation complex, say, 0.91.
With these values, the aircraft would have to fly less than 1,580 meters
above ground to detect the 0.5 meter seep located at a scan angle, B, of
30°-
5.4 ANALYSIS OF REMOTELY SENSED DATA FOR LEACHATE
The specific technique(s) applied in analyzing remotely sensed data for
leachate indicators are dependent upon the form of remotely sensed data
and the available equipment, time and/or funds for analysis-.- More sophis-
ticated or costly analysis techniques are not synonymous with more information.
Whatever the approach to analysis, the results must be applicable in the
field; suspected sites of leachate must be located in the field, via maps or
photographs, as well as in or on the analyzed data.
If the recommendations of previous sections were followed, several
forms of data might be available for analysis: (1) panchromatic contact
prints, (2) black-and-white transparencies of different visible and near-
infrared spectral bands, (3) color and/or color infrared transparencies,
(4) black-and-white transparencies of one or two thermal bands, and (5)
magnetic tape containing digital or analog thermal data.
5.4.1 Panchromatic Contact Prints
Most of the existing remotely sensed data depicting pre-landfill and
developing conditions at a landfill site (Section 5.2.3) will be in the
form of 23 by 23 cm, panchromatic contact prints, at scales of about 1:20,000.
The panchromatic films, though sensitive to ultraviolet and all visible ra-
diation, were likely exposed through a filter which absorbed the ultraviolet
and most of the blue wavelength radiation. The black-and-white prints,
therefore, depict the combined levels of green and red radiation. Analysis
of these prints should be performed with pairs of overlapping photographs,
using a lens or mirror stereoscope (Colwell, 1960). The stereoscopic analy-
sis of topography and geology should aim at defining the drainage pattern
and wet areas (dark tones associated with sites of lower reflectance, Sec-
tion 5.2.2). The drainage information can be delineated directly on the
photographs or on acetate overlays. This information will be compared to
more recent images and/or maps. As desired, selected details may be trans-
ferred visually or with the aid of various types of equipment (e.g.,
Bausch & Lomb Zoom Transfer Scope).
38
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5.4.2 Black-and-white Spectral Transparencies
The black-and-white spectral images, acquired simultaneously and at the
same scale, can be examined individually or in combinations. Analysis of
individual black-and-white spectral images can be conducted visually, as
with panchromatic contact prints, though stereoscopic images may not be
available. Since the images are film transparencies, a light table or pro-
jection device will be required for viewing. If the images were acquired
stereoscopically, a variable magnification (zoom) stereoscope, attached to
a light table, would be desirable.
One means for enhancing tones in the separate black-and-white images is
to use a "density slicer." This is a device which electronically breaks
the range of black to white film densities into as many as 32 increments, or
levels, and subsequently assigns a different color to each level. Similar
tones (densities) throughout the image will thereby be depicted with the
same color, and slight tone differences will be enhanced.
In an effort to increase the information derived through analysis of
single images, the different spectral images can be combined by: (1) over-
laying various combinations of positive and negative images, (2) using a
color-additive viewer, or (3) using diazo, a subtractive color process.
By "sandwiching" and registering different positive and negative spec-
tral images of the same scene, and viewing the composite of transparencies
over a source of white light, one can enhance or subdue various features in
the scene (Simonett, 1974). For example, vegetative gaps would appear as
light areas on a composite of a positive red image and a negative green
image, and levels of wetness might be highlighted if a negative infrared
image could be balanced with a positive red image (Sec. 5.3.2).
A color-additive viewer is a device which projects as many as four
spectral images onto the same screen, where they can be registered to one
another (Smith, 1968). The different images are placed behind or in front
of one of four filters (blue, green, red or clear) such that registering
the images on the screen will produce a multi-colored scene. Altering the
intensity of any of the four projection lamps or changing the filter assign-
ments will serve to enhance various spectral features.
In subtractive color enhancement with diazo, different color diazo foils
are printed in contact with the different spectral images of a single scene.
The resultant color densities of each diazo foil correspond to the gray-tone
densities of the original spectral image. Registering the different color
diazo, particularly yellow, magenta and cyan, over a white light will produce
a multi-colored representation of the original scene. As with color-additive
viewing, a wide range of color enhancements can be obtained by varying
the color intensities of the diazo foils or the specific color-spectral image
assignments. On the other hand, the preparation of appropriate diazo is
too time-consuming and inefficient an approach to be considered for monitoring
more than a few landfills.
Other analysis techniques, involving densitometric or digital methods,
can be implemented with black-and-white spectral images. These techniques
39
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will be described in later sections.
5.4.3 Color and Color Infrared Transparencies
Color and color-infrared image transparencies can be projected or trans-
ferred onto a base map or another image, for comparison or recording of
new information. If acquired stereoscopically, color and color-infrared
transparencies can be examined on a light table with a stereoscope, pre-
ferably a zoom stereoscope. Moreover, much information can be derived through
spectral analysis of single images with or without a stereoscope.
The emulsions of nearly all color and color infrared films consist of
three layers (Smith, 1968). Each layer is sensitive to radiation of
different spectral intervals, and each layer is separable, or "viewable,"
in the developed image through an appropriate filter. Consequently, the
relative amounts of blue, green, red and/or near-infrared radiation that
exposed the various layers of a color or color-infrared film can be ex-
amined by viewing the developed film through the proper spectral filter
(Table 5.9). The film must be placed over, or projected by, a source of
white light. If the aerial data were in the form of 35-mm or 70-mm trans-
parencies, for example, they could be projected onto a white screen using
a 35-mm or lantern-slide projector, and the spectral filters could be held
in front of the projector lens.
Table 5.9. EXPOSING RADIATION (COLOR) VIEWED WHEN
COLOR AND COLOR-INFRARED TRANSPARENCIES
ARE EXAMINED OVER WHITE LIGHT THROUGH
DIFFERENT SPECTRAL FILTERS
POSITIVE FILM
TRANSPARENCY
COLOR
COLOR
INFRARED
SPECTRAL FILTER
BLUE GREEN RED
blue green red
green red infra-
red
YELLOW
green &
red
red &
infrared
MAGENTA
blue &
red
green &
infrared
CYAN
blue &
green
green
& red
5.4.4 Densitometric Analyses
The black-and-white, color or color-infrared films can be calibrated
if they have been exposed with a sensitometer (Thomas, 1973) . The sensi-
tometer "images" a stepwedge of regularly varying densities on the film.
After controlled processing and development, the stepwedge can be read
with a densitometer to obtain a characteristic curve, which relates density
to relative exposure. This can apply to a black-and-white spectral film,
or for each color (blue, green, or red) or color-infrared (green, red or
infrared) film layer. The black-and-white or color layer density of any
point on a black-and-white, color or color-infrared image can thereby be
measured with a densitometer. Through the appropriate characteristic
curve, the density can be converted to a precise Value of the relative amount
of exposing spectral radiation.
40
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Relative exposures are informative in themselves (e.g., in determining
dry versus wet soil), yet the ratios of exposures may provide even more in-
formation (Billingsley, 1973; Wagner et al., 1973). Working with color
photography, for example, Piech and Walker (1974) found the ratio between
the red and blue reflectances of soil to be useful for discriminating between
soil moisture and texture variations. They also showed that densitometric
readings, nominally point measurements, could form the basis for additional
image processing in which whole images are ratioed photographically.
5.4.5 Thermal Infrared Image Transparencies
Black-and-white transparencies of one or two thermal infrared bands
(8 to 14 ym, with or without 3 to 5pm) can be examined like photographic
black-and-white spectral images (Section 5.4.2 and Plate 6). Normally,
however, the scanner-derived imagery will be distorted spatially (Figure
5.9), and it will not be available in stereoscopic form. A Bausch & Lomb
Zoom Transfer Scope, which has an image "stretch" capability, is especially
useful for transferring data from aircraft scanner imagery to maps or other
images.
Because densities in quantitative thermal imagery correspond to apparent
temperatures, density slicing of thermal imagery provides an expedient means
for identifying objects and features of comparable apparent temperature
(Section 5.4.2). Further density slicing provides a rapid means for sep-
arating slight density differences, as might be associated with leachate-
contaminated versus uncontaminated waters.
5.4.6 Magnetic Tape
The thermal data may have been recorded on magnetic tape in analog or
digital form. The primary advantage of collecting (and analyzing) data
in this form is that the maximum spatial and spectral resolution afforded
by the sensor has been recorded, much more data than can normally be shown
on a single black-and-white film. A second advantage is that, in this form,
the data are easily enhanced or otherwise manipulated.
The disadvantage of having the data on magnetic tape is cost. Special
equipment is required to display the analog or digital data, or to convert
them to photographic film. If the data are not first converted to film,
a computer is required for their analysis, and special routines or facilities
are required for printing or displaying the analyzed data.
In general, computer analysis of remotely sensed data is an extremely
powerful and flexible approach to data analysis, whether the aim is to
enhance or automatically recognize certain features in the data (Simonett,
1974). For this reason, one might consider digitizing any of the black-
and-white, color or color-infrared photographs. Although the conversion
of pictorial data to numerical form is an appropriate step for certain under-
takings, for the requirements of a leachate detection program it is likely
to be a poor alternative to collecting digital data with a multispectral
scanner in the first place. As noted in Section 5.3.2, multispectral
scanners are probably not required or desired for most leachate detection
programs.
41
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5.5 LEACHATE DETECTION METHODOLOGIES
Two general approaches to monitoring for landfill leachate are appro-
priate, depending on the objective. The first approach would be applicable
by those groups that must monitor many landfills to check conformance to
regulations and, consequently, have insufficient time to conduct a thorough
examination of each.
The second would be applicable by those groups that are monitoring a
limited number of landfills on a continual or control basis, and that
have time to conduct a comprehensive study of each.
5.5.1 Typical Regulatory Monitoring Program
Step 1. Obtain topographic maps which locate landfills to be monitored.
Step 2. Fly 1:5,000 scale, aerial photographic coverage of each
landfill, using film-filter combinations which record ultra-
violet, blue, green, red, and near-infrared radiation (Sec-
tions 5.3.2 and 5.4.2). A panoramic camera might be used
as a backup system to ensure complete coverage, though a
23 by 23-cm format camera, with color infrared film, is re-
commended as the primary sensor. The photographic flight
should be conducted near midday during a wet, low vegetation
period (e.g., spring in the northeastern United States).
(Alternative A)
Step 3A. Analyze the photographs to identify the most probable
locations of leachate breakout or contamination (Sections
5.4.2 and 5.4.3).
Step 4A. Field check those landfills at which possible leachate break-
out or contamination has been identified. The locations of
any seeps encountered in the field should be marked on the
field maps or photographs. The temperature of each seep should
be measured, and a water sample taken for laboratory testing.
Step 5A. Upon verification of leachate contamination, take appropriate
action.
(Alternative B)
Step 3B. Fly night-time/pre-dawn, thermal infrared coverage of all
landfills overflown with photography. The thermal coverage
should be acquired as quickly as possible after the photo-
graphic mission, and preferably, that same night. Flight
parameters should allow for detection of a 0.25m2 seep,
about 3°C warmer than its surroundings (Section 5.3.3).
Step 4B. Analyze the photographic and thermal data to identify
the most probable locations of leachate breakout or
contamination (Section 5.4).
42
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Step 5B. (see Step 4A).
Step 6B. (see Step 5A).
(Alternative C)
Step 3C. (see Step 3A).
Step 4C. Based on the photographic analysis, select landfills to
be overflown with pre-dawn, thermal infrared scanners.
Conduct this sensing during a dry or frozen, low vegetation
period to maximize effectiveness of this sensor. Field check
other landfills as outlined in Steps 4A and 5A.
Step 5C. (see Step 4B).
Step 6C. (see Step 4A).
Step 1C. (see Step 5A).
5.5.2 Comprehensive Control Monitoring for Landfill Leachate
Step 1. Obtain all available background information on the landfill
site, including topographic, soil and geologic maps and
reports.
Step 2. Obtain aerial coverage of the undeveloped landfill site
and, as available, coverage flown periodically during the
development of the site (Appendix B for list of sources).
Step 3. Analyze available aerial coverage, together with background
information, to identify the most probable locations of
leachate breakout or contamination (Sections 5.2.3 and 5.4.1).
Step 4. Field check the landfill site(s), concentrating on those
locations identified in Step 3. The locations of any seeps
encountered in the field should be marked on the field maps
or photographs. The temperature of each seep should be
measured, and a water sample taken for laboratory testing.
Step 5. Fly new aerial photographic coverage of the landfills using:
one or more film-filter combinations which are appropriate
for the expected spectral leachate indicators (Sections
5.2.2 and 5.3.2); a photographic scale and film format which
are in line with the size of the landfill-affected area and
indicators (Sections 5.3.1 and 5.3.3); and a photographic
system which is compatible with the aircraft, expected data
analyses (Section 5.4) and available funds. The photographic
flight should be conducted at midday during a wet, low vege-
tation period (e.g., spring in the northeastern United States)
Step 6. Analyze the new photographs, together with the other aerial
and background data, to identify the most probable locations
of leachate breakout or contamination (Section 5.4).
43
-------
Step 7. Field check the landfill site(s), as in Step 4.
Step 8. Upon verification of leachate contamination, plan remedial
measures.
(Steps 9 through 12 are optional extensions)
Step 9. Fly pre-dawn, thermal infrared coverage of the landfills.
Flight parameters should allow for detection of a 0.25'Di
seep, about 3°C warmer than its surroundings (Section 5.4.3).
Step 10. Analyze the thermal infrared data, together with all
photographic and background data, to identify any additional
locations of suspected leachate breakout or contamination
(Sections 5.4.6 and 5.4.7).
Step 11. Field check any new locations of suspected leachate.
Step 12. If required, modify planned remedial measures.
44
-------
Section 6
Illustrations of Remote Sensing
Applications to Detect Leachate
Illustrations of the use of remote sensors to detect leachate
contamination are presented in this section. The following
examples are included, using photographic plates and a de-
scriptive text for each:
1. Use of existing photographs
2. Gaps in vegetation and snow
3. Wetness
4. Stressed vegetation
5. Color anomalies
6. Thermal scanner data
7. Temporal effects
45
-------
PLATE 1. USE OF EXISTING PHOTOGRAPHS
la. May 1955, Black and White
Ic. May 1967, Black and White
le. March 1975, Color Infrared
Existing black-and-white (panchromatic) aerial photographs can be an
important source of information, for both planning new landfill sites and
detecting leachate contamination from existing landfills. Most areas
have been covered by aerial photographs which are available to the public
at low cost. Often there has been periodic coverage dating back thirty
years or more. The historic nature of this photography enables the inter-
preter to define the conditions which existed at the site prior to its
development as a landfill. This information is particularly valuable in
assessing the sources and distribution of ground and surface water flow.
In the example on Plate 1, the 1955 photograph is pre-landfill (la),
solid waste is being placed on the site in 1967 (Ic), and the final
illustration is taken five years after the site was closed (le). As
illustrated by the wetness patterns (Ib and Id), the movement of ground
and surface water around the site can be defined quite clearly in the
older photographs. Based on this interpretation, it would be reasonable
to expect leachate contamination of all those areas bracketed by the
arrows on Plate le. There is a definite indication of this contamination
from the color infrared photograph (le), and this was confirmed by
analysis of samples taken on the ground.
46
-------
,,,,-• -
"S^*^^^s"i " ,/ "
la.
Ib.
*&, ^
IT*--
Id.
Ic.
Plate 1
le.
47
-------
PLATE 2. GAPS IN VEGETATION AND SNOW
2a. June, Color 2b. Ground-level illustration of 2a
2c. December, Color 2d. Ground-level illustration of 2c
If large or small gaps in snow or vegetative cover can be related
spatially to a landfill, they often indicate the presence of leachate.
Gaps can be caused by increased wetness, toxicity or heat, and they can
be isolated or radiate from a landfill. The significance of a remotely
sensed gap is increased when it also demonstrates some other character-
istic such as anomalous color, increased wetness or high thermal
emission.
Gaps in vegetation are usually most apparent when the vegetation
is low, as illustrated by the arrow in the center of Plate 2a. A
ground-level illustration of this feature (2b) shows the grass and low
brush which has been affected by the leachate. Only rarely will gaps
show in heavy vegetation, as illustrated in the upper right hand
corner of Plate 2a. In this case the gap was produced by severe leachate
flooding which killed the large trees.
Gaps in a light snow cover are often a dramatic indication of
leachate (2c). The combination of heat and salinity in the leachate can
melt a light snow cover. If this can be associated spatially with a
landfill, it is a logical location for sampling to confirm the contami-
nation (2d) .
48
-------
ID
2c.
Plate 2
-------
PLATE 3. WETNESS
3a. March, Color
3b. March, Color Infrared
Any wet area that can be related spatially to a landfill is
potentially contaminated by leachate. Consequently, wetness is a pri-
mary leachate indicator. Wetness can normally be deduced from the type
of vegetation or the spectral characteristics of the wet area. Although
sensors operating in many parts of the electromagnetic spectrum might be
applied to detect wetness, cameras with color or color infrared film
are the sensors that would most likely be used in a leachate detection
program. The reflective differences between water and soil or vegeta-
tion are particularly high in the infrared spectral region (reference
Figure 5.5), where absorption of radiation by water results in a blue to
black color on a color infrared photograph.
The illustrations on Plate 3 are typical in that the majority of
wet areas can be detected on both the color (3a) and color infrared (3b)
photographs. The wet areas related spatially to the landfill (arrows)
are areas of probable leachate contamination. These two images also
illustrate that infrared photography gives a better indication of wetness,
particularly for small features, shallow water and damp areas.
50
-------
3b.
Plate 3
3a.
SI
-------
PLATE 4. STRESSED VEGETATION
4a. June, Color Infrared 4b. June, Color
4c. June, Color Infrared 4d. June, Color
4e. June, Color Infrared 4f. June, Color
Vegetative stress, when produced by leachate, can usually be de-
tected more easily with color infrared than with color photography.
However, leachate may or may not produce a vegetative stress, and the
stress may be positive or negative. Leachate toxicity and drowning of
root systems are common causes of negative stress, but increased nutri-
ents and moisture levels may enhance vegetative growth.
The examples on Plate 4 illustrate the advantages of color infra-
red over color photography. The large, negatively stressed areas on
Plate 4a are the result of excessive rates of application in a spray
irrigation project. Vegetation near the center of the photograph has
been drowned, while vegetation toward the lower left corner (downhill)
has been affected by excess moisture and toxicity-
Much more subtle, negative stress effects are illustrated on Plates
4c and 4e (arrows). These often involve only one to several trees, and
they are very difficult to use as leachate indicators unless they are in
close spatial association with the landfill.
An illustration of a positive vegetative stress is the vigorous
vegetation (bright red) going upward from the left center of Plate 4e.
52
-------
*
4c.
I
Plate 4
53
-------
PLATE 5. COLOR ANOMALIES
5a. March, Color 5b. Ground-level illustration of 5b
5c. April, Color 5d. Ground-level illustration of 5c
Color anomalies are among the most distinctive leachate features
that can be detected using remote sensors. Almost all of these
anomalies are a consequence of the high iron content of most leachates
and the resulting red or red-orange reflectance of ferric iron. The
iron can be dissolved in the leachate or precipitated on the bottom of
ponds or streams. Even for seasonally dry, leachate breakout areas,
the red-stained soils can be distinctive.
The red leachate seeps shown in Plate 5a (arrows) are typical and
in contrast to the uncontaminated springs in the same area. In this
illustration, the leachate-contaminated water has travelled several
hundred meters underground before surfacing. A ground-level photograph
(5b) indicates the size of these features.
The color of leachate-contaminated water (5c) is distinctive only
when the contamination is at relatively high levels and when the iron
is in the form of ferric oxide or similar compounds. Seasonal variation
in the proportion of leachate being contributed to a water body may
limit the distinctive color to certain times of the year, as illustrated
in Plate 7.
Sometimes the anomalous color may be indirectly related to water
in the form of a scum or biological growth on the water surface (5d).
Snow may also be stained with a distinctive color anomaly (7a).
54
-------
t
P
5b.
5c.
5d.
Plate 5
-------
PLATE 6. THERMAL SCANNER DATA
6a. December, Thermal (pre-dawn)
6b. April, Thermal (pre-dawn)
6c. April, Color
Although thermal data are useful for detecting wet areas, their
principal value is for differentiating higher temperature leachate
from uncontaminated ground and surface water. The difference in
emissions between leachate and its surroundings is likely to be maximum"
at certain seasons of the year (late winter and early spring) and at
night. To optimize target detectability, the thermal scanner should be
flown just before sunrise (reference Figure 5.3).
In the illustration, leachate breakout is occurring along the
landfill perimeter (arrows). It is necessary to have this spatial asso-
ciation to define the leachate because there are other, similarly
emitting targets on the image.
Snow cover during December (6a) masks some of the temperature and/
or emissivity differences which show on the April data (6b). Leachate
is ponding on parts of the landfill in April.
Plate 6c is a reference color photograph of this area. The landfill
is being actively filled at the time these data were collected.
56
-------
Plate 6
57
-------
PLATE 7. TEMPORAL EFFECTS
7a. December, Color 7b. March, Color
7c. April, Color 7d. June, Color
Temporal factors are extremely important in planning a leachate
detection program since the production of leachate, as well as the
interference by vegetation and heavy snow cover, are highly dependent
on season and climate. Remote sensing missions to detect leachate
should be planned for a time which optimizes the production of leachate
and minimizes the interference from snow and heavy vegetation. In
general, the potential for leachate production is high during wet
periods and low during dry or frozen periods. Depending on the climate
of a particular region, the wet periods may occur at different seasons
or may not occur at all.
The illustration in Plate 7 is typical of a northern temperate
region. Heavy snow cover during winter (7a) covers the leachate except
where the higher temperature melts the snow and produces a gap.
During late winter and early spring, the production of leachate will
usually be near its annual maximum because of heavy rain and snow melt.
Ideal conditions for detecting leachate will occur between the melting
of snow, with its interference (7b), and the growth of new spring
vegetation (7c). By late spring (7d), the full canopy of taller vege-
tation will obscure many of the features which could be detected
earlier in the season.
In some regions there will be a period during the late autumn or
winter when the vegetation canopy will be gone and there will be no
snow cover. When there is sufficient moisture to produce leachate,
this can be an ideal season, comparable to the conditions illustrated in
Plate 7b.
58
-------
u:
7a.
-
^^"
7c.
s»
, :\
*• '
\ •-
« >r
Plate 7
7d.
w
i
-------
REFERENCES
1. American Society of Civil Engineers. 1976. Sanitary landfill. ASCE
Manuals and Reports on Engineering Practice No. 39. Amer. Soc. Civil
Engrs., N.Y. various pagings.
2. Baker, L. R., R. M. Scott, K. J. Ando, D. S. Lowe and H. Luxenberg.
1975. Electro-optical remote sensors with related optical sensors.
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Soc. Photogrammetry, Falls Church, Va.
3. Billingsley, F. C. 1973. Some digital techniques for enhancing ERTS
imagery, p. 284-293. In Proc. of Symp. on Management and Utilization
of Remote Sensing Data.' Held Sioux Falls, So. Dak. Amer. Soc. Photo-
grammetry, Falls Church, Va.
4. Blanchard, M. B., R. Greeley and R. Goettelman. 1974. Use of visible,
near-infrared, and thermal infrared remote sensing to study soil moisture.
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6. Chow, V. T. (Editor). 1964. Handbook of applied hydrology; A compendium
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7. Colwell, R. N. (Editor). 1960. Manual of photographic interpretation.
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D. C-) 868 pp.
8. Committee on Remote Sensing Programs for Earth Resource Survey (CORSPERS).
1976- Resource and environmental surveys from space with the Thematic
Mapper in the 1980's. National Academy of Sciences, Washington, D. C.
122 pp.
9. Condit, H. R. 1970. The spectral reflectance of American soils.
Photogrammetric Eng'g. 36:9:955-966.
10. Environmental Protection Agency (EPA). 1975. Use of the water balance
method for predicting leachate generation from soil waste disposal sites.
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11. Environmental Protection Agency (EPA). 1976. Gas and leachate from
landfills; Formation, collection, and treatment. EPA-600/9-76-004.
E.P.A., Washington, D.C.
12. Fritz, N. 1967. Optimum methods of using infrared-sensitive color
films. Photogrammetric Eng'g. 33:10:1128-1136.
13. Holter, M. R. 1971. The interpretation of spectral data. p. 305-
325. In Int'l. Workshop on Earth Resources Survey Systems. Held at
Univ. of Mich. NASA SP-283. Nat'l. Aeronautics & Space Admin.,
Washington, D. C.
60
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14. Kennedy, J. M., and E. G. Wermund. 1971. oil spills, ir and microwave.
Photogrammetric Eng'g. 37:12:1235-1242.
15. Kondratyev, K. Ya. 1969. Radiation in the atmosphere. Academic Press,
N.Y. 912 pp.
16. Landon, R. A. 1969. Application of hydrogeology to the selection of
refuse disposal sites. Ground Water 7:6:9-13.
17. Lowe, D. S., B. O. Kelly, H. I. McDevitt, G. T. Orr and H. W. Yates.
1975. Imaging and nonimaging sensors. p. 367-397. In_ Manual of Remote
Sensing. ( R. G. Reeves, Editor). Amer. Soc. Photogrammetry, Falls
Church, Va.
18. Masry, S. E.,and J. G. Gibbons. 1973. Distortion & rectification of ir.
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NASA SP-376. Nat'l. Aeronautics & Space Admin., Washington, D. C.
502 pp.
20. McDowell, D. Q.,and M. R. Specht. 1974. Determination of spectral
reflectance using aerial photographs. Photogrammetric Eng'g.
40:5:559-568.
21. Myers, V. I., M. D. Heilman, R. J. Lyon, L. N. Namken, D. Simonett,
J. R. Thomas, C. L. Wiegand and J. T. Woolley. 1970. Soil, water,
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Reference to Agriculture and Forestry. National Academy of Sciences,
Washington, D. C.
22. Piech, K. R.., and J. E. Walker. 1974. Interpretation of soils. Photo-
grammetric Eng'g. 40:1:87-94.
23. Rango, A. (Editor). 1975. Operational applications of satellite snow-
cover observations. Proc. of Workshop held in South Lake Tahoe, Calif.
NASA SP-391. Nat'l. Aeronautics & Space Admin., Washington, D. C.
430 pp.
24. Reeves, R. G. (Editor). 1975. Manual of remote sensing. 2 vols.
Amer. Soc. Photogrammetry, Falls Church, Va. 2047 pp.
25. Roberts, K. J., G. W. Olson, and D. A. Sangrey. 1976. Attenuation of
sanitary landfill leachate in soils of New York State. Report to N.Y.S.
Dept. Environmental Conservation. Contract C97-915. Dept. Environ.
Conservation, Albany, N.Y. 107 pp.
26. Sangrey, D. A., W. L. Teng, W. R. Philipson and T. Liang. 1976.
Remote sensing of ground and surface water contamination by leachate
from landfill. Paper 15-1. ^n_ Proc. Int'l. Conf. Environmental
Sensing and Assessment. Held Sept. 1975, Las Vegas. Inst. Electrical
& Electronics Engineers, New York.
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27. Schmugge, T,, T. Wilheit, W. Webster, Jr., and P. Gloersen. 1976.
Remote sensing of soil moisture with microwave radiometers—II. NASA
Technical Note D-8321. Nat'l. Aeronautics & Space Admin., Washington,
D. C. 34 pp.
28. Siegel, R., and J. R. Howe11. 1972. Thermal radiation and heat transfer.
McGraw-Hill Book Co., N.Y. 814 pp.
29. Simonett, D. S. 1974. Quantitative data extraction and analysis of
remote sensor images, p. 51-82. In Remote Sensing: Techniques for
Environmental Analysis. (Estes, J. E. and L. W. Senger, Editors).
Hamilton Press, Santa Barbara, Calif.
30. Slater, P. N. 1975. Photographic systems for remote sensing, p. 235-
323. In_ Manual of Remote Sensing. (R. G. Reeves, Editor). Amer. Soc.
Photogrammetry, Falls Church, Va.
31. Smith, Jr., J. T. (Editor). 1968. Manual of color aerial photography.
Amer. Soc. Photogrammetry, Falls Church, Va. 550 pp.
32. Thomas, Jr., W. 1973. SPSE handbook of photographic science and
engineering. John Wiley & Sons, N.Y. 1416 pp.
33. Ulaby, F. T., J. Cihlar and R. K. Moore. 1974. Active microwave
measurement of soil water content. Remote Sensing of Environment
3:185-203.
34. Valley, S. L. (Editor). 1965. Handbook of geophysics and space environ-
ments. U.S. Air Force Cambridge Research Labs. McGraw-Hill Book Co.,
N.Y. various pagings.
35. Vizy, K. N. 1974. Detecting and monitoring oil slicks with aerial
photos. Photogrammetrie Eng'g. 40:6:697-708.
36. Wagner, T. W., R. Dillman and F. Thomson. 1973. Remote identification
of soil conditions with ratioed multispectral data. p. 721-738. In
Remote Sensing of Earth Resources. Vol. II. (F. Shahroki, Editor).
Univ. Tenn. Space Inst., Tullahoma, Tenn.
37. Watson, R. D., W. R. Hemphill and R. C. Bigelow. 1975. Remote sensing
of luminescing environmental pollutants using a Fraunhofer line discrimi-
nator (FLD). p. 203-222. In_ Proc. 10th Int'l. Symp. on Remote Sensing
of Environ. Held at Univ. of Mich. Environ. Research Inst. of Mich.,
Ann Arbor, Mich.
38. Wehran Engineering Corp. and Geraghty & Miller, Inc. 1976. Procedures
manual for monitoring solid waste disposal sites. U.S. Environmental
Protection Agency Contract 68-01-3210 OSWMP. E.P.A. Washington, D.C.
39. Wolfe, W. L. (Editor). 1965. Handbook of military infrared technology.
Office of Naval Research, Dept. of Navy, Washington, D. C. 906 pp.
62
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APPENDIX A
In Section 5.3.3, the general equation for estimating flight and scanner
parameters required for detecting a thermal target was derived as follows
(refer to Reeves, 1975, p. 340 and 377):
1/2
NEP = (AdB) /D* (1)
and, B = [(v/H)e]/[2a2py] (2)
where, NEP = noise equivalent power of detector
B = electrical bandwidth
\ Ad = area of detector
D* = detectivity
V/H = ratio of sensor platform velocity to height
6 = total field-of-view; angular coverage
a = angular resolution; instantaneous field-of-view in one
direction (assume square field)
p = number of detecting elements
Y = scan duty cycle or efficiency
Since a = Ad/f , where f = focal length of optical system
then, NEP = [f(V/H)1/2(6)1/2]/[(2pY)1/2D*] (3)
The radiant power, P, which enters the optical system and ultimately
strikes the detector is:
2
P = TT a A L cosg (4)
o c s
where, T = transmissivity of atmosphere
T = transmissivity of optical system
L = radiance from source, A
s s
8 = angle between nadir (vertical) and source
A = area of collector optics
c
In order that two adjacent resolution elements can be distinguished, the
difference between the power received at the detector from the two elements
63
-------
must exceed the NEP of the detector, or
P - P > NEP (5)
2 2
Then, (TT a A L cosgl - (TT a A L cosg) > NEP (6)
ocs 1 ocs 2
or, L cosg - L cos60 > NEP/(Tt a2A ) (7)
s 1 s 2 o c
For adjacent resolution elements, g is approximately equal to
32- Letting, B1=32=:0' then,
2
L - L > NEP/(TT a A cosg) (8)
Sl S2 ° C
Assuming the target and surroundings are Lambertian radiators,
radiating into a hemisphere of space,
L = M./TT ; L = M /TT
BI 1 s2 2
where, M = radiant exitance (or emittance) .
2
Substituting in equation 8, Mn - IVL > TT(NEP)/(TT a A cosg) (9)
12 o c
The radiant exitance from the resolution element that contains a
hot target will be
where, M , M = exitance from the target and background area
U- S
within the instantaneous field-of-view (IFOV)
A ,A = area of target and background within IFOV
A = area within IFOV; A = A + A
s s t b
The radiant exitance from an adjacent resolution element will be M ,
and the area will be approximately A .
Substituting in equation 9,
2
[ (M A + M A, ) /A ] - M > Tf(NEP)/(TT a A cosg) (10)
t t s b s s oc
Solving,
2
M - M > A Tf(NEP)/(A TT a A cosg) (11)
t s s toe
Substituting equation 3 into equation 11,
64
-------
A TT[f
M - M > —
A TT a2A cosg[(2pY)1/2D*]
to c
Since,
2
A = TTD /4 and F = f/D
c
where,
D = collector diameter
F = aperture ratio of optical system
thSn' A (V/H)1/2(e)1/2(4F)
M - M > -^-5 - r— - (13)
5 A a (cosg)DD*(2py) TT
t 0
In general, from the Stefan-Boltzmann law,
4
M = gaeT
where,
T = absolute temperature of body
e = emissivity of body
a = Stefan-Boltzmann constant
g = fraction dependent upon T and wavelength interval being
sensed (e.g., determined from tables; see Siegel and Howell,
1972) .
Further, an alternative form of equation 13 would be presented by re-
placing A , the ground area of the resolution element seen at a scan
angle of $. In general, from the solid angle relationship,
2 , 2
a = A /R
s
where,
R = radial distance between resolution element and scanner.
Since,
R = H/cosg
then,
22 2
A = H a /cos 3
s
65
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APPENDIX B
SOURCES OF AERIAL PHOTOGRAPHS AND OTHER
REMOTELY SENSED DATA
TYPE OF COVERAGE
1.
2.
3.
4.
5.
Aerial photographs acquired
by federal agencies, other
than military, prior to
about 1942
Aircraft data acquired
by federal agencies,
other than military
and USDA; also, Landsat
and Skylab satellite
data
Aerial photography acquired
under U.S. Dept of Agriculture;
usually by county
a. Acquired by Agricultural
Stabilization and Conser-
vation Service
b. Acquired by Soil Conser-
vation Service
Aircraft data acquired
by the U.S. Environmental
Protection Agency
Aircraft data acquired
by state agencies
PRIMARY SOURCE
National Archives and Records Service
Cartographic Branch
8 Pennsylvania Avenue, N.W.
Washington, D.C. 20408
EROS Data Center
U.S. Geological Survey
Sioux Falls, South Dakota 57198
Agricultural Stabilization and
Conservation Service
U.S. Dept. of Agriculture
205 Parley's Way
Salt Lake City, Utah 84109
Soil Conservation Service
U.S. Dept. of Agriculture
Cartographic Section
6505 Delcrest Road
Hyattsville, Maryland 20782
EPA/EPIC
P.O. Box 1587
Vint Hill Station
Warrenton, Virginia 22186
EPA/EMSL-Las Vegas
P.O. Box 15027
Las Vegas, Nevada 89114
Varies with state; information is
commonly available through the
state department of transportation
66
-------
TYPE OF COVERAGE
6. Aircraft photography
acquired for tax mapping
7. Other (e.g., commercial or
non-government research
data)
PRIMARY SOURCE
Usually by county; information
normally available through county
assessment office
Variable; list of most commercial
firms available from American
Society of Photogrammetry, 105
Virginia Ave., Falls Church, Virginia;
also, information often available
through major universities in
region
67
* U.S. GOVERNMENT PRINTING OFFICE: 1980-684-996
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
. REPORT NO.
EPA-600/4-79-060
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
DETECTING LANDFILL LEACHATE CONTAMINATION USING
REMOTE SENSORS
5. REPORT DATE
September 1979
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
Sangrey, Dwight A., and Philipson, Warren R.
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Sciiool of Civil and Environmental Engineering
Cornell University
Ithaca, NY 14853
10. PROGRAM ELEMENT NO.
1HD883
11. CONTRACT/GRANT NO.
68-03-2438
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency — Las Vegas, NV
Office of Research and Development
Environmental Monitoring Systems Laboratory
Las Vegas,NV 89114
13. TYPE OF REPORT AND PERIOD COVERED
Project Report
14. SPONSORING AGENCY CODE
EPA/6?0/07
15. SUPPLEMENTARY NOTES
Project Officer: Vernard H. Webb, Chief, EPA Environmental Photographic Interpreta-
tion Center, Vint Hill Farms, Virginia
16. ABSTRACT
A methodology for using remote sensing to detect landfill leachate contami-
nation of ground and surface water is described. Among the topics covered are
leachate indicators, spatial and temporal aspects of leachate detection, sensor
selection, flight design and data interpretation. Specific methodologies for using
remote sensing to detect leachate under various situations are described. These
range from survey monitoring of individual landfills to comprehensive programs for
regualtory monitoring and landfills.
Data and imagery from a field research and demonstration project are used to
illustrate the use of remote sensors to detect leachate.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS C. COSATI F;ield/Group
Landfills
Leachate
Groundwater
Remote Sensing
Aerial Photography
Thermal Scanning
48G
63C
68D
18. DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
19. SECURITY CLASS (This Report)
UNCLASSIFIED
21. NO. OF PAGES
68
20. SECURITY CLASS (This page)
UNCLASSIFIED
22. PRICE
EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION is OBSOLETE
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