Prepared in cooperation with the U.S. Environmental Protection Agency

An Evaluation of Remote Sensing Technologies for the 

Detection of Fugitive Contamination at Selected 

Superfund Hazardous Waste Sites in Pennsylvania

By E.Terrence Slonecker and Gary B. Fisher

Open-File Report 2014–1081

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

Sally Jewell, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2014

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Suggested citation:

Slonecker, E.T., and Fisher, G.B., 2014, An evaluation of remote sensing technologies for the detection of fugitive 

contamination at selected Superfund hazardous waste sites in Pennsylvania: U.S. Geological Survey Open-File 

Report 2014–1081, 23 p., http://dx.doi.org/10.3133/ofr20141081/.

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ISSN 2331-1258
iii

Contents

Executive Summary.................................................................................................................................................... 1

Introduction................................................................................................................................................................. 2

Background ................................................................................................................................................................ 3

Remote Sensing of Hazardous Waste........................................................................................................................ 4

Remote Sensing of Vegetation Stress .................................................................................................................... 6

Metal Contamination in Soils................................................................................................................................... 7

Methodology ............................................................................................................................................................... 7

Remote Sensing Data Collection and Analysis ....................................................................................................... 7

Site Visit Data Collection and Analysis.................................................................................................................. 10

Analysis and Quality Control ................................................................................................................................. 11

Criteria for Elevated Metal Concentrations............................................................................................................ 11

Results of Analysis ................................................................................................................................................... 12

Summary and Conclusions....................................................................................................................................... 17

References Cited...................................................................................................................................................... 19

Glossary ................................................................................................................................................................... 22

Figures

1. Map showing the locations of the 16 deleted Superfund test sites in Pennsylvania ...................................... 3

2. Hyperspectral images are collections of hundreds of bands of coregistered imagery ................................... 5

3. When processed, the image cube can be analyzed with conventional spectroscopic analysis methods—

hence, the term “imaging spectroscopy”........................................................................................................ 6

4. Photographs showing the combined hyperspectral techniques used in this report........................................ 9

5. The solar-reflected electromagnetic spectrum coverage of the Civil Air Patrol’s Airborne Real-Time 

Cueing Hyperspectral Enhanced Reconnaissance system and Analytical Spectral Devices instruments ..... 9

6. Photograph showing soil sampling and field X-ray fluorescence screening................................................. 10

7. Photograph showing Office of the Inspector General evaluators standing next to a large debris pile 

during a site visit to Taylor Borough Dump.................................................................................................. 14

8. A, Hyperspectral image analysis of vegetation and debris stress and B, ground photo of large trash 

pile at Taylor Borough Dump ....................................................................................................................... 15

9. Bruin Lagoon: A, Panchromatic image on left and B, hyperspectral anomaly detection image on right. ..... 16

10. Continuum-removed plot of normal vegetation and a vegetation anomaly, showing loss of 

photosynthetic band depth around 680 nanometers and a general “red-edge” shift of 8–12 nm, 

consistent with previously published results on natural gas stress .............................................................. 17

Tables

1. The deleted Superfund (SF) sites in an evaluation of remote sensing technologies for the detection of 

fugitive contamination at selected SF hazardous waste sites in Pennsylvania.............................................. 2

2. Listing for the background, residential-, and industrial risk-based concentrations (RBC) of selected 

metals.......................................................................................................................................................... 12

3. A summary of the results of the detection of fugitive contamination at selected Superfund hazardous

waste sites in Pennsylvania......................................................................................................................... 12
iv

Conversion Factors

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

Abbreviations

AMD acid mine drainage

ARCHER Airborne Real-Time Cueing Hyperspectral Enhanced Reconnaissance

As arsenic

AVIRIS Airborne Visible/Infrared Imaging Spectrometer

ASD Analytical Spectral Devices

CAP Civil Air Patrol

Cd cadmium

CERCLA Comprehensive Environmental Response Compensation and Liability Act (also known as “Superfund”)

CERCLIS Comprehensive Environmental Response, Compensation, and Liability Information System

Co cobalt

Cr chromium

Cu copper

EMR electromagnetic radiation

EPA U.S. Environmental Protection Agency

FR Full (spectral) Range (400–2500 nm)

Hg mercury

HSI hyperspectral imagery

HRS hyperspectral remote sensing

HyMap Hyperspectral MAPper

JPL Jet Propulsion Laboratory (National Aeronautics and Space Administration)

mg/kg milligrams per kilogram

nm nanometer

Ni nickel

NPL National Priorities List

OIG Office of Inspector General

Pb lead

RBC risk-based concentration

RI remedial investigation

Sb antimony

SF Superfund (see “CERCLA” above)

USGS U.S. Geological Survey

VNIR visible and near infrared

XRF X-ray fluorescence

Zn zinc
1

An Evaluation of Remote Sensing Technologies for the 

Detection of Fugitive Contamination at Selected 

Superfund Hazardous Waste Sites in Pennsylvania

By E. Terrence Slonecker and Gary B. Fisher

Executive Summary

This evaluation was conducted to assess the potential for using both traditional remote sensing, 

such as aerial imagery, and emerging remote sensing technology, such as hyperspectral imaging, as 

tools for postclosure monitoring of selected hazardous waste sites. Sixteen deleted Superfund (SF)

National Priorities List (NPL) sites in Pennsylvania were imaged with a Civil Air Patrol (CAP) 

Airborne Real-Time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) sensor between 2009

and 2012. Deleted sites are those sites that have been remediated and removed from the NPL. The 

imagery was processed to radiance and atmospherically corrected to relative reflectance with standard 

software routines using the Environment for Visualizing Imagery (ENVI, ITT–VIS, Boulder, Colorado) 

software. Standard routines for anomaly detection, endmember collection, vegetation stress, and spectral 

analysis were applied. 

Onsite visits and field work were conducted at 12 of the 16 sites. Field work consisted of the 

collection of soil samples; a general inspection of site conditions; the collection of sediment and water 

samples where conditions indicated possible contaminants; and informal interviews with local officials, 

residents, and property owners. Laboratory analysis consisted of hyperspectral data collection and 

analysis, spectral image-processing techniques, and X-ray fluorescence (XRF) analysis of soil and 

sediments for metals. At four sites, access could not be obtained in a timely manner or other technical 

issues precluded site visits. Each of the remaining 12 sites was analyzed for land use setting, physical 

security, imagery anomalies, points of interest, and spectral identifications. Soil sampling was 

conducted at each site with a XRF analyzer, and soil samples were collected for confirmation and 

additional analysis in the laboratory using an Analytical Spectral Devices (ASD) Full Range (FR) 

spectroradiometer (Analytical Spectral Devices Inc., Boulder, Colorado).

Remote sensing and field visits indicated that there were operations and maintenance issues at 

four sites: Aladdin Plating, Hranica Landfill, Publicker Industries, and Taylor Borough Dump. These 

issues consisted of discarded equipment and general industrial debris. At Taylor Borough, there were 

large mounds of debris and general waste material. At the Hranica Landfill, there was a discharge of 

rust-colored leachate.

In general, 9 of the 12 sites visited were relatively clean and without any detectable matters of 

concern regarding operations and maintenance, vegetation stress, or soil contamination. There were 

potential contamination concerns detected by hyperspectral analysis at Bruin Lagoon, Hranica Landfill, 

and Taylor Borough Dump. Bruin Lagoon displayed still unexplained vegetation anomalies; Hranica 

Landfill and Taylor Borough both contained considerable levels of trash and debris. Although the ability 

to monitor and detect potential problems at deleted SF sites was the objective of the study, the relatively 
2

“clean” condition of most of the sites did not result in a thorough evaluation of remote sensing 

technology under a variety of site conditions. Research on the remote sensing of contaminants relies on 

the existence of those contaminants on or near the surface. Future remote sensing research should 

consider utilizing areas of known contamnination.

Introduction

This report describes a remote sensing research effort conducted by the U.S. Geological Survey 

(USGS), in cooperation with the U.S. Environmental Protection Agency (EPA), Office of Inspector 

General (OIG). The objective of the research was to explore the capability of remote sensing as a 

technology for the OIG to use in planning and conducting evaluations of the adequacy of the EPA’s 

postclosure monitoring of hazardous waste sites as defined under the Comprehensive Environmental 

Response Compensation and Liability Act, also known as “Superfund” (SF), and to evaluate possible 

contamination at specific sites.

Sixteen deleted SF sites in Pennsylvania were imaged with a hyperspectral sensor from 

September 2009 to April 2012. Twelve of the 16 sites were subsequently visited for inspection of 

general site conditions and for the collection of soil and water samples and spectral measurements with 

field-portable spectrometers. Figure 1 shows the geographic locations of the 16 sites.

The 16 deleted SF sites are listed in table 1 below:

Table 1. The deleted Superfund (SF) sites in an evaluation of remote sensing technologies for the detection of 

fugitive contamination at selected SF hazardous waste sites in Pennsylvania.

Name CERCLIS ID Municipality or Township

1. Aladdin Plating PAD075993378 Clarks Summit.

2. Berkley Products Dump PAD980538649 Denver.

3. Berks Landfill PAD000651810 Sinking Spring.

4. Brodhead Creek PAD980691760 Stroudsburg.

5. Bruin Lagoon PAD980712855 Bruin.

6. Helbelka Auto Salvage1 PAD980829329 Upper Macungie Township.

7. Hranica Landfill PAD980508618 Buffalo Township.

8. Lackawanna Refuse PAD980508667 Old Forge.

9. Lansdowne Radiation1 PAD980830921 East Lansdowne.

10. McAdoo - Blaine PAD980712616 McAdoo.

11. McAdoo - Kline PAD980712616 McAdoo.

12. Metropolitan Mirror1 PAD982366957 Frackville.

13. Publicker Industries PAD981939200 Philadelphia.

14. Taylor Burrough Dump PAD980693907 Taylor.

15. Voortman Farms1 PAD980692719 Ladark.

16. Wade ABM PAD980539407 Chester.

1 Sites not visited during field work.
3

Field work was undertaken at 12 sites. Technical failure of the remote sensing system occurred 

at one site (Voortman Farms), and timely access could not be obtained at three others (Helbelka Auto 

Salvage, Landsdowne Radiation, and Metropolitan Mirror). This research seeks to evaluate traditional 

and hyperspectral imagery (HSI) and field spectroscopic measurement techniques in the characterization 

and analysis of fugitive (anthropogenic and uncontrolled) contamination at previously remediated 

hazardous waste disposal sites.

Background

In 2007, the EPA OIG-issued Evaluation Report 2007-P-00039—“ Limited Investigation Led to 

Missed Contamination at Ringwood Superfund Site” (U.S. Environmental Protection Agency, 2007),

which documented problems of insufficient characterization and cleanup at the Ringwood, New Jersey, 

National Priority List (NPL) SF Site.

Figure 1. Locations of the 16 deleted Superfund test sites in Pennsylvania.

A key finding of the OIG report was that the failure to detect the extent of contamination at the 

Ringwood Site might have been avoided if the EPA had made greater use of available aerial 
4

photographs. Morphological characteristics of the landscape and landscape changes, as documented in 

historical aerial imagery, could have been used to detect the much larger extent of paint sludge and 

contamination than was thought to exist after the initial remedial investigation (RI) (Baker, 1984; U.S. 

Environmental Protection Agency, 2007). Based on the findings from the Ringwood investigation, the 

OIG asked the USGS to evaluate the potential use of current and emerging remote sensing technology in 

the investigations of deleted SF sites.

This research, summarized in USGS Open-File Report 2011–1050 (Slonecker and Fisher, 2011) 

found that two of five sites evaluated had detectable postclosure issues with site activity, soil metals, 

and onsite debris, most of which were identified by remote sensing in some form. This research is a 

follow-on effort for the deleted SF sites in Pennsylvania.

Remote Sensing of Hazardous Waste

Remote sensing is an increasingly important science for advancing understanding of 

environmental processes, conditions, and changes affecting both human and ecological health. 

Advancements in sensor technology and processing algorithms have resulted in technical capabilities 

that can record and identify earth surface materials, including waste products, based on the interaction 

of electromagnetic energy with the molecular structure of the material being sensed (Goetz and others, 

1985; Green and others, 1998; Clark 1999; Clark and others, 2009). Hyperspectral remote sensing 

(HRS) records reflected and emitted electromagnetic energy in hundreds of narrow wavelengths, which 

result in data that can be analyzed with the same chemical spectroscopic techniques that have been used 

by chemists and astronomers for over a century. Spectral reflectance of vegetation and other landscape 

conditions have received renewed interest by the remote sensing community during the past decade 

because of the development of this new class of imaging technology. Many of the early and definitive 

studies in spectral reflectance utilized spectroscopic measurement instruments in a laboratory setting 

(Horler and others, 1980; Chang and Collins, 1983; Milton and others, 1989). These instruments 

measured reflected energy and produced spectra that could be analyzed using standard spectral analysis 

techniques. The collection of hyperspectral imagery (HSI) in very narrow bandwidths across the solarreflected part of the electromagnetic spectrum [from 400 to 2,500 nanometers (nm)] results in a digital 

file of hundreds of bands of coregistered imagery, sometimes called an “image cube” (see fig. 2). After 

processing, the image cube represents an imagery version of the same energy and matter interactions 

measured in the laboratory, and can be analyzed with a variety of standard and emerging statistical 

methods in spectroscopy, signal processing, and remote sensing. Reflectance spectra can be used to 

identify certain compounds, materials, and their conditions based on the interaction of photons of light 

with the molecular structure of the target material (Vane and Goetz, 1988; Green and others, 1998; 

Clark 1999) (see fig. 3).

Spectroscopic analysis techniques can now be employed outside of the laboratory through the 

use of HRS-imaging techniques and portable field spectroradiometers. In addition, new analytical 

techniques are being developed and refined that permit the identification and analysis of key 

environmental processes, such as photosynthesis and nutrient cycling, which are important for the 

detection of anthropogenic stress that might be caused by soil or groundwater contamination. 
5 

Figure 2. Hyperspectral images are collections of hundreds of bands of coregistered imagery. Each band 

collects reflected energy in a slightly different wavelength location and results in what is often called an “image 

cube.” The image shown here, of Moffett Field, California, was collected on August 20, 1992, from a height of 

20,000 meters. [Image from the Jet Propulsion Laboratory-Airborne Visible/Infrared Imaging Spectrometer Web site 

http://aviris.jpl.nasa.gov/html/aviris.cube.html (National Aeronautics and Space Administration, 2010). 

Although imaging spectroscopy of plant and tree health has been an important research area for 

some time, recent research suggests that there is a spectral distinction between natural stress, such as 

drought, and anthropogenic stress, such as soil chemical contamination, due to different physiological 

responses of the plant (Zinnert and others, 2012). Further development of this capability would be an 

important aspect of hyperspectral research. 
6

Figure 3. When processed, the image cube can be analyzed with conventional spectroscopic analysis methods—

hence, the term “imaging spectroscopy.” [Image from the Jet Propulsion Laboratory-Airborne Visible/Infrared 

Imaging Spectrometer Web site (http://aviris.jpl.nasa.gov/html/aviris.concept.html)] (National Aeronautics and 

Space Administration, 2007).

Remote Sensing of Vegetation Stress

A key aspect in the study of fugitive hazardous waste in the environment is the effect that 

contaminants have on cover vegetation. In most cases, soil or groundwater contaminants, such as 

hydrocarbons, heavy metals, and organic chemicals, will have negative effects on the metabolism and 

growth of typical cover vegetation, such as trees or grasses. Remote sensing of vegetation stress has 

been, and continues to be, a key aspect of remote sensing research (Milton and others, 1989; Noomen 

and others, 2008; Zinnert and others, 2012).

As far back as 1879, researchers, using crude spectrographs, were documenting the differences 

in vegetation reflectance in different broad bands of the visible spectrum (Rood, 1879; Willstatter and 

Stoll, 1913, 1918). Schull (1929) studied and measured the reflectance of various leaves using a prism 

spectrophotometer to attempt to better explain leaf-energy interactions that occur in photosynthesis. As 

aerial photography, film, and camera systems became available and more sophisticated, applications for 

crop monitoring became routine agricultural practice and included a seminal paper from Colwell (1956) 

for identifying crop diseases from aerial photography.

As both spectroscopic and remote sensing systems developed further, specific patterns of 

vegetation stress began to emerge and spawned a flurry of research starting in the 1990s. The shift in the 

“red edge” of vegetation reflectance (680 nm to 730 nm), related to plant health and (or) stress, was 

identified and utilized in a number of research studies and is still used today in studying vegetation 

condition. A series of special spectral calculations, called “vegetation indices,” were developed to 

maximize and take advantage of high-spectral resolution and specific quality of vegetation growth and 

health (Thenkabail, 2000). They are derived from the spectral reflectance properties of vegetation and 

are designed to accentuate a specific property of vegetation, such as leaf moisture content. As hazardous 

waste sites that have been remediated and deleted on the SF NPL list are likely to have been reclaimed 
7

or revegetated, vegetation indices are a key component of assessing surface contamination of these sites

(Slonecker and others, 2010).

Metal Contamination in Soils

One of the primary concerns for remote sensing analysis of deleted SF sites is metal 

contamination in the soil. Both the direct reflectance of metals in the soil matrix and the effect of metals 

on vegetation reflectance are potential observables in this environment. Many naturally occurring metals 

are constituents of minerals and of the surficial and crustal properties of soils. In mineral form, such as 

galena [lead (Pb)] and sphalerite [zinc (Zn)], metals occur naturally throughout the Earth’s crust and can 

often be identified through field or imaging spectroscopy. However, when mined for the specific metal 

or used in industrial processes, waste metal concentrations in soils can be orders of magnitude higher 

than natural concentrations and become risks to human and ecological health.

The identification of metals and metal concentrations in soils generally involves wet chemical 

acid digestion and methods such as EPA Method 7421 for Pb and EPA Method 7060A for arsenic (As). 

In recent years, XRF methods (EPA Method 6200) have also become accepted field methods for the 

determination of metals in soils. Only XRF methods were used in this study.

All of the above-mentioned methods require the collection of samples and laboratory analysis or, 

in the case of XRF technology, physical contact with the soil. A remote sensing method that might 

identify soil contamination remotely could be a major new monitoring tool. Several studies have 

indicated the possibility of applying field and imaging spectroscopy in the identification of minerals 

containing heavy metals as an indicator of contamination in mining areas (Farrand and Harsanyi, 1997; 

Ferrier, 1999). Montero and others (2005) assessed the potential of abandoned mines for acid mine 

drainage (AMD) by characterizing waste rock associated with acid drainage.

Studies by Kemper and Sommer (2002) and Choe and others (2008) have demonstrated that 

direct, stand-off detection of high metal concentrations in soils is possible. Wu and others (2007) have 

shown that visible and near-infrared (VNIR) spectroscopy produced strong negative correlations with 

certain metals [As, cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), Pb, and Zn] in 

contaminated soils, depending on iron oxide and organic carbon content.

Choe and others (2008) demonstrated that a band ratio of 610 nanometers (nm)/500 nm and 

1,344 nm/778 nm correlated with concentration of Pb, Zn , and As in soils. Wu and others showed that 

continuum removed band depths at 610 nm and 830 nm were diagnostic for Cr and Cu in soil.

Methodology

Remote Sensing Data Collection and Analysis

Imagery was collected at sites defined by EPA. Sites were visited to collect additional spectra 

and soil samples as a ground truth for the remotely sensed data. Imagery and soils data were analyzed in 

the laboratory.

Remote sensing data were collected in two forms. First, hyperspectral data from the CAP’s 

ARCHER system were collected for each site between September 2009 and April 2012. Collection 

dates and times were not always optimal due to a number of administrative, programmatic, and weatherrelated issues and delays. The ARCHER system represents a low-cost alternative for high-spatial and 

spectral-resolution remote sensing data. In addition, soil samples were screened in the laboratory with 

an ASD FR field spectrometer for potential hydrocarbon and organic signatures that have been 

demonstrated in the near-infrared region by King and Clark (1989), Allen and Krekeler (2010), Cloutis 
8 

(1989), and Slonecker and others (2010). Figure 4 shows the different data collection strategies. 

Although the presence of hydrocarbons and other organics is unlikely under a postclosure site scenario, 

the combination of both ARCHER imagery and the ASD laboratory analysis represents a full analysis of 

potential signatures for hazardous waste that might exist in the solar-reflected portion of the 

electromagnetic spectrum from 400 to 2,500 nm. Figure 5 shows the coverage of the two sensors in the 

electromagnetic spectrum.

ARCHER utilizes a grating spectrometer and includes 52 bands covering the 500–1,100-nm 

spectral range. The system uses a special camera facing down through a quartz glass portal in the belly 

of the aircraft, which is typically flown at a standard mission altitude of 2,500 feet [800 meters (m)], 

100 knots (50 m/second) ground speed and a 1-m spatial resolution, and a 500-m image swath width. 

The ARCHER system has a 36-degree field of view and a 100:1 signal-to-noise ratio. ARCHER 

technical details can be found in Stevenson and others (2005). ARCHER combines a VNIR 

hyperspectral imaging system, a high-resolution, visible panchromatic imaging sensor; and an integrated 

geopositioning and inertial navigation unit with onboard real-time processing for data acquisition and 

correction, precision image georegistration (Civil Air Patrol, 2009).

 

 

A B 

C 
9 

D 

E 

Figure 4. The combined hyperspectral techniques used in this report: A, the Civil Air Patrol’s (CAP) Airborne 

Real-Time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) sensor; B, the CAP aircraft; C, imagery 

and spectra from the ARCHER sensor; D, full-range spectroscopy in the laboratory with the Analytical Spectral 

Devices (ASD) spectroradiometers; and E, an example spectra from the ASD system.

Figure 5. The solar-reflected electromagnetic spectrum coverage of the Civil Air Patrol’s Airborne Real-Time 

Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) system and Analytical Spectral Devices instruments

(from Slonecker and Fisher, 2011). 

XRF technology was used to measure the metal content of the soils at the field visit sites. XRF is 

an accepted method of soil elemental analysis by which X-ray-fluorescence emission of a material is 

measured after bombardment by high-energy gamma or X-rays (Thermo Scientific, 2013). Fieldportable units permit analysis of the metal content of soils in the field and can help identify areas where 

metals contamination is present (see fig. 6).

Hyperspectral imagery and analysis, often referred to as "imaging spectroscopy," is a meld of 

remote sensing and chemical analysis techniques that provide a powerful method for the identification 

of substances and conditions that maximize the informational content of VNIR spectroscopy, with the 

synoptic efficiency of overhead remote sensing. Many unique substances can be detected with imaging 

spectroscopy methods. One such example that is relevant to waste sites is that of hydrocarbons, such as 

waste oil that was detected previously. Hydrocarbons have distinctive absorption features at 1,200, 
10

1,731, and 2,310 nm, and they are a strong indicator of waste disposal activity. Another example of 

hyperspectral capabilities lies in the many vegetation indices that have been developed for specialized 

analysis. One such index is the photochemical reflectance index (PRI) that measures carotenoid 

pigments and thus, light use efficiency in plants, giving a measure of productivity and stress in the 

physiological status of the plant. PRI is computed from hyperspectral wavebands using the following 

formula: 

 W531 - W570

PRI = ------------------ , 

 W531 + W570

where W531 and W570 are the values at specific wavelengths in the reflected spectrum. Developed by 

Gamon and others (1992, 1997), this formula has proven successful at identifying subtle patterns of 

stress that could be caused by soil contamination. Although PRI is commonly used in vegetation stress 

scenarios, there are many other indicies that have been calculated and used effectively (Thenkabail and 

others, 2000). 

Site Visit Data Collection and Analysis

Field visits for site inspection and sample collection and analysis were conducted in 2012. 

Arrangements for site visits were coordinated through the EPA Regional Office and with the appropriate 

land owners and administrators. During visits, sites were reviewed for general conditions and visual 

appearance. Sampling was conducted using a grid pattern and at specific areas of interest based on the 

remote sensing analysis. Soil samples were screened and collected for metals analysis via portable XRF

technology. Figure 6 shows the handheld XRF instrument being used in the field. 

Figure 6. Soil sampling and field X-ray fluorescence (XRF) screening. 

(Photo by Gary Fisher, USGS.) 
11

Analysis and Quality Control

Soil samples were reprocessed in the laboratory using XRF methods. After soil samples were air 

dried, disaggregated, and sieved through a #10 (2-millimeter) mesh, they were reprocessed with an XRF 

analyzer for a minimum of 3 minutes. 

Soil samples were also analyzed with an ASD FR spectrometer for the presence of hydrocarbons 

in the soil. The spectrometer provides an analysis of spectral qualities in the near infrared beyond the 

spectral range of the ARCHER instrument and facilitated detailed spectral analysis in the solar-reflected

spectrum. When there were spectral or field indications of the presence of hydrocarbons, water, 

sediment, and soil samples were collected for hydrocarbon analysis. A complete description of the field 

work, sampling, and quality control procedures can be found in Slonecker and Fisher (2009). 

Criteria for Elevated Metal Concentrations

Heavy metals were contaminants of concern at most of the sites being evaluated. The ability of 

remote sensing to detect metal concentrations in soils is an important aspect of this study. All soils were 

analyzed in the laboratory with an ASD spectrometer for the relation between reflectance and soil metal 

concentrations. XRF technology was utilized to screen soil metals in the field and later, in the 

laboratory, to evaluate metals concentrations. 

The natural level of metals in soil is called the background concentration and has been reported 

in the literature by comprehensive scientific studies based on regional sampling (Shacklette and 

Boerngen, 1984). For this study, the background concentrations were the arithmetic mean 

concentrations for the Eastern United States (Shacklette and Boerngen, 1984). 

The risk-based concentration (RBC) of individual contaminants is a basic screening level that is 

also used when a potential site is initially investigated. The RBC is used to determine if potentially 

substantial levels of contamination are present to warrant further investigation, such as a Remedial 

Investigation and Feasibility Study (RI/FS). RBCs are a complex calculation of toxicity, exposure, and 

carcinogenic probabilities and are applied according to surrounding land use and exposure scenarios, 

whether residential or industrial. Table 2 lists the main metals of concern and their background 

concentration based on an arithmetic mean, and the residential and industrial RBCs. 

The general land use surrounding the site was used to determine the appropriate RBC screening 

level. While this approach to the site’s land use determination as residential or industrial may be 

debatable based on zoning classifications, the exposure scenario appeared to be primarily residential at 

most of the sites, and absent any clear evidence of current industrial land use, the residential RBC 

standard was used for reporting. The EPA regional RBCs for residential and industrial soil contaminants 

can be found at http://www.epa.gov/reg3hwmd/risk/human/rb-concentration_table/Generic_Tables/

(U.S. Environmental Protection Agency, 2013). 
12

Table 2. Listing for the background, residential-, and industrial risk-based concentrations (RBC) of selected 

metals.

[All measurements are listed in milligrams per kilogram. BG, background; R-RBC, residential-risk-based concentrations of 

metals in soil; I-RBC, industrial-risk-based concentration.] Background concentrations from Shacklette and Boerngen 

(1984). R-RBC and I-RBC from U.S. Environmental Protection Agency (2013).

Metal BG R-RBC I-RBC

Arithmetic Mean

Antimony (Sb) 0.76 31.0 410.0

Cadmium (Cd) 0.0 70.0 800.0

Chromium III (Cr) 52.0 12,000.0 31,000.0

Chromium VI (Cr) -- 29.0 56.0

Cobalt (Co) 9.2 23.0 300.0

Lead (Pb) 17.0 400.0 800.0

Manganese (Mn) 640.0 1,800.0 23,000.0

Nickel (Ni) 18.0 1,600.0 20,000.0

Selenium (Se) 0.5 390.0 5,100.0

Uranium (U) 2.7 230.0 3,100.0

Vanadium (V) 66.0 390.0 5,200.0

Zinc (Zn) 52.0 23,000.0 310,000.0

Results of Analysis

Analysis of the overhead remote sensing data and data derived from the field sampling indicated 

basic changes in land use and site morphology and detectable levels of metals in the soil at several sites. 

Hyperspectral analysis detected debris and vegetation stress at two sites: Taylor Borough Dump and 

Hranica Landfill. Spectral anomalies and unusual patterns of vegetation reflectance were observed at 

Bruin Lagoon. Conditions at the Bruin Lagoon site appear to have returned to normal (M. Hoffman,

Environmental Chemist, Pennsylvania Department of Environmental Protection,written commun., June 

13, 2013). Other issues are summarized in table 3 with a discussion following.

Table 3. A summary of the results of the detection of fugitive contamination at selected Superfund hazardous 

waste sites in Pennsylvania.

[LU, land use; NA, not applicable; O&M, operations and maintenance; Pb, lead]

Site name

Field 

visit

Physical 

security LU setting Imagery findings

Soil Samples 

detected above 

RBC

concentrations 

O&M 

issues Comments

Aladdin

Plating

Yes No Residential No No No -- 

Berkley

Products

Yes Yes Residential No No No
13

Table 3. A summary of the results of the detection of fugitive contamination at selected Superfund hazardous 

waste sites in Pennsylvania.—Continued

[LU, land use; NA, not applicable; O&M, operations and maintenance; Pb, lead]

Site name Field 

visit

Physical 

security LU setting Imagery findings

Soil Samples 

detected above 

RBC 

concentrations 

O&M 

issues Comments

Berks Landfill Yes Yes Industrial No Possible No Possible chromium

 issue.

Brodhead

 Creek

Yes Yes Industrial No No No

Bruin Lagoon Yes Yes Residential Yes No No

Helbelka Auto

 Salvage1, 2

No N/A Residential N/A N/A No

Hranica

 Landfill

Yes Yes Industrial Yes No Yes Leachate.

Lackawanna

 Refuse

Yes Partial Industrial No No No Damaged fence.

Lansdowne

 Radiation1, 2

No N/A Residential N/A N/A No

McAdoo

 Blaine

Yes No Residential No No No

McAdoo Kline Yes Yes Industrial No No No

Metropolitan

 Mirro1, 2

No N/A Industrial N/A N/A No

Publicker

 Industries

Yes Yes Industrial No No Yes Old equipment on 

site.

Taylor

 Borough

 Dump

Yes Partial Residential Yes 1-Pb1 Yes Damaged fence.

Voortman

 Farms1, 2

No N/A Residential N/A N/A No --

Wade ABM Yes No Residential No No No Site is now a park. 

 Most of site is 

 asphalt.

1

At the Taylor Borough Dump, one sample exceeded the industrial risk-based concentration for Pb.

2

Site was not visited during field work.

Physical security.—It was noted that there was inadequate or no physical security at five sites—

Aladdin Plating, McAdoo-Blaine, Taylor Borough Dump, Lackawanna Refuse, and Wade ABM. Taylor 

Borough Dump was fenced but major gaps in the fencing were observed. McAdoo-Blaine is a 

residential area and Wade ABM is now a park.
14

Operations and maintenance issues. —There were operations and maintenance issues at three

sites: Hranica Landfill, Publicker Industries, and Taylor Borough Dump. Generally, these issues 

consisted of discarded equipment and general industrial debris. There were large mounds of debris at the 

Taylor Borough Dump site (fig. 7). Evidence of all-terrain-vehicle useage was observed at both Taylor 

Borough Dump and Lackawanna Refuse. A rust-colored leachate-like discharge was observed at 

Hranica Landfill.

Figure 7. Office of the Inspector General evaluators standing next to a large debris pile during a site visit to 

Taylor Borough Dump. (Photo by Gary Fisher, USGS.)

Hyperspectral Anomalies.—Detectable hyperspectral issues were noted at Bruin Lagoon, 

Hranica Landfill, and Taylor Borough Dump. At Hranica Landfill and Taylor Borough Dump, 

substantial amounts of debris, metal equipment, and discarded material were highlighted by a 

hyperspectral anomaly detection algorithm (fig. 8). Vegetation stress anomalies were detected at Bruin 

Lagoon (fig. 9) and are discussed below.
15

A B 

Figure 8. A, Hyperspectral image analysis of vegetation and debris stress and B, ground photo of large trash pile 

at Taylor Borough Dump. (Photo by Gary Fisher, USGS.) 

Sampling Results.—The onsite soil sampling results indicated one sample exceeded the 

applicable residential or industrial RBC for Pb at the Taylor Borough Dump. Potentially high levels for 

Cr were detected at Berks Landfill and could pose a problem if the metal form is found to be Cr VI. 

However, if the form is found to be Cr III, then the levels of concentration are well within current 

screening level standards. Additional analysis of the soils in this area would be needed to confirm this 

evaluation. 

Vegetation Anomalies.—Potential vegetation anomalies were observed in the cover grass at 

Bruin Lagoon and are shown in figure 9. These anomalies, representing patches of dead vegetation, 

were not visually detectable during the field visit, metal or hydrocarbon sampling results were not 

detected, and there were no sampling results correlating with the anomalous areas. 
16

A B 

Figure 9. Bruin Lagoon: A, Panchromatic image on left and B, hyperspectral anomaly detection image on right. 

Vegetation stress and endmember analyses yielded the same basic patterns of dead vegetation, shown as white 

areas in image B. 

A hyperspectral reflight in November 2012 showed only traces of the dead vegetation anomalies. 

One of the possible explanations of this event is that gases may be moving upward from the original 

lagoon. Spectral analysis of these anomalous areas shows a pattern of vegetation stress manifested in the 

spectral signatures that is consistent with the published works of Noomen and others (2003, 2008), who 

investigated the effect of leaking natural gas on vegetation above pipelines. The continuum-removed 

spectra in figure 10 illustrate this natural gas effect on vegetation. 

Figure 10 contains a continuum-removed plot of normal vegetation (white) and the vegetation 

anomaly (red), showing loss of photosynthetic band depth at about 680 nm and a general "red-edge” 

shift of 8–12 nm, consistent with previously published results on natural gas stress. Although 

interesting, this finding is not conclusive because other factors could cause this type of spectral 

signature shift. From a technical perspective, further analysis is needed. An inspection of the site in 

June 2013 by Pennsylvania State officials indicated that the Bruin Lagoon site had revegetated normally 

and that no anomalies were present (M. Hoffman, Environmental Chemist, Pennsylvania Department of 

Environmental Protection, written commun., June 13, 2013). 
17

Figure 10. Continuum-removed plot of normal vegetation (white) and a vegetation anomaly (red), showing loss of 

photosynthetic band depth around 680 nanometers (nm) and a general “red-edge” shift of 8–12 nm, consistent with 

previously published results on natural gas stress (Noomen and others, 2003, 2008).

Summary and Conclusions

Important findings of this study include the following:

• Remote sensing did not identify potential contamination concerns at nine sites, and these findings

were subsequently confirmed with field visits. 

• Soil screening and sampling results indicated one sample exceeded the applicable residential- or 

industrial-risk-based concentration for Pb at the Taylor Borough Dump; Pb concentrations at 

approximately 1,500 milligrams per kilogram were detected and confirmed. Physical security and 

operations and maintenance issues were noted at several sites.

• Hyperspectral analysis identified potential contamination concerns at Hranica Landfill and Taylor 

Borough Dump, which were found to correlate with operations and maintenance issues and site 

conditions during field inspections.

• Hyperspectral analysis revealed an unusual pattern of vegetation stress at Bruin Lagoon, and 

subsequent hyperspectral overflights showed a continued pattern of unusual vegetation reflectance at 

this site. Recent visits by Pennsylvania officials indicate that onsite vegetation appears to be normal. 

Both from an operational monitoring and remote sensing research perspective, additional monitoring 

at this site is potentially important.
18

This research effort, and the work that preceded this study, utilized a suite of remote sensing 

tools, including conventional imaging, imaging spectroscopy, laboratory spectroscopy, and XRF, to 

evaluate the potential of this technology for postclosure status of deleted SF sites in EPA Region 3. 

Combined standoff and in situ approaches, such as utilizing laboratory spectrometers, were used to 

maximize the total range of the solar-reflected spectrum and to keep costs reasonable. The goal of this 

study was to simulate, as much as possible, the full range of the solar-reflected electromagnetic 

spectrum (from 400 to 2,500 nm). This technology, like many research technologies, is moving into an 

applications environment and monitoring costs are decreasing. Ideally, this research and the monitoring 

applications that follow will one day be conducted using a full-range overhead hyperspectral sensor, 

such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) or the Hyperspectral MAPper

(HyMAP) (HyVista Corporation, Castle Hill, Australia), which permits the complete utilization of a full 

solar-reflected range imaging sensor.

Several scientific lessons learned can be identified from this research, along with potential 

research opportunities.

• Operations and maintenance at several sites was an issue and hyperspectral anomaly detection has 

been shown to be effective in identifying discarded materials in this scenario. Trash, debris, and 

remnants of operational activities were found and often unsecured from public access.

• Vegetation stress is one of the most likely observables in the monitoring of hazardous waste sites. 

However, the vegetation cover and mix of species is likely to be different, depending on the nature 

of the sites' conditions. Similarly, the timing of hyperspectral imagery is different, depending on 

seasonal considerations. Sites with low-level cover vegetation are best imaged in the summer, and 

sites with extensive tree cover may have to be imaged in both leaf-on and leaf-off conditions.

• Grasses and low-level cover and forest stress are likely to show reflectance differences in specific 

vegetation indices, such as water content and light use efficiency, while grasses and low-level cover 

vegetation are more than likely sensitive to nitrogen content indices.

• Overall, this technology has now been tested on 21 deleted sites and has uncovered potential issues 

at five of those sites; these sites were all in EPA Region 3. Some type of extra-regional or national 

sample could be beneficial at the program level. Also, prescreening of sites for potential field work 

with existing overhead imagery could be cost-effective and reduce the resource expenditure for the 

use of a hyperspectral sensor. Many of the sites with operations and maintenance issues, might have 

been easily identified on freely available imagery and could have been used to rank sites for 

potential research issues.

This research provides only a limited range of potential hazardous waste applications. Better 

selection of site contamination profiles and use of better overhead sensors, which are becoming more

widely available, would have more potential for positive monitoring results. While the technical 

approach utilized in these sites was designed to permit a practical utilization of technological 

capabilities over a maximum number of sites, the eventual test will come with use of a full-range 

(400–2,500-nm) aircraft or satellite sensor and with little or no field work, only verification. This is the 

ultimate monitoring scenario that would be most helpful to the EPA. New sensors, including those 

mounted on an unmanned aerial system could now permit a practical application and could be 

considered in future applications.
19

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Glossary

Anomaly Detection Anomaly Detection (AD), in general terms, refers to detecting 

patterns in a given dataset that do not conform to an established 

normal behavior. It is also known statistically as “outlier 

detection” (Wikipedia). In spectral analysis, it is the identification 

of pixels that statistically deviate from the spectral profiles of 

surrounding pixels. In practice, it is used to identify situations, 

such as metal pieces of a downed aircraft or the disposal of metal 

wastes in a vegetation environment.

electromagnetic spectrum The electromagnetic spectrum (EM) is the range of all possible 

frequencies of electromagnetic radiation (EMR). The 

"electromagnetic spectrum" of an object has a different meaning, 

and is instead the characteristic distribution of EMR remitted or 

absorbed by that particular object. The electromagnetic spectrum 

extends from below the low frequencies used for modern radio 

communication to gamma radiation at the short-wavelength (highfrequency) end, thereby covering wavelengths from thousands of 

kilometers down to a fraction of the size of an atom. This study 

utilized the “solar-reflected” portion of the EM that included 

visible light and the near infrared wavelengths of approximately 

400 to 2,500 nanometers.

endmember In mineralogy, an endmember is a mineral that is at the extreme 

end of a mineral series in terms of purity. Minerals often can be 

described as solid solutions with varying compositions of some 

chemical elements, rather than as substances with an exact 

chemical formula. In imaging spectroscopy, endmembers are the 

purest pixels in hyperspectral imagery (HSI), and represent the key 

spectral profiles that affect other pixels in the dataset.

hyperspectral imagery A form of remote sensing in which imagery is collected in 

numerous (usually 50–200), contiguous, spectrally narrow, 

coregistered bands of imagery that can be analyzed with 

spectroscopic techniques.

hyperspectral imagery analysis Hyperspectral imagery analysis, also known as “imaging 

spectroscopy,” is a remote sensing technique that collects emitted 

or reflected energy in discrete, narrow wavelengths that are 

processed and analyzed with spectroscopic laboratory techniques 

as opposed to standard image analysis.

operations and maintenance A series of actions and monitoring measures that are designed to 

maintain the remedy at a hazardous waste site to ensure that the 

remedy remains protective of human health and the environment.
23

reflectance The measure of electromagnetic energy reflected from a surface 

relative to a standard, highly reflective surface, usually spectralon.

spectral analysis A generic name for a body of analytical techniques based on 

measuring the reflected or emitted energy of a material.

spectral analyst A specific set of processing steps that are utilized for general 

spectral analysis by the Environment for Visualing Imagery 

(ENVI) software program.

spectrometer A spectrometer (spectrophotometer, spectrograph, or 

spectroscope) is an instrument used to measure properties of light 

over a specific portion of the electromagnetic spectrum, typically 

used in spectroscopic analysis to identify materials (Butler and 

Laqua, 1995).

vegetation stress In imaging spectroscopy, a mathematical measure, or index value 

that is computed from band-specific reflectance values and relates 

to the physiological functions of a plant, indicating its relative 

health. There are many vegetation indices (VIs) that measure 

specific functions and biochemical concentrations. Widely 

accepted vegetation indices include the Normalized Difference 

Vegetation Index (NDVI) and the photochemical reflectance index 

(PRI).

X-ray fluorescence The emission of characteristic "secondary" (or fluorescent) X-rays 

from a material that has been excited by bombarding with highenergy X-rays or gamma rays. The phenomenon is widely used for 

elemental analysis and chemical analysis, particularly in the 

investigation of metals, glass, ceramics, and building materials, 

and for research in geochemistry, forensic science, and 

archaeology.
ISSN 2331-1258

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