U.S. Department of the Interior

U.S. Geological Survey

Fact Sheet 2013–3007

February 2013

Advanced and Applied Remote Sensing of Environmental Conditions

Introduction

“Remote sensing” is a general term for 

monitoring techniques that collect information 

without being in physical contact with the 

object of study. Overhead imagery from 

aircraft and satellite sensors provides the most 

common form of remotely sensed data and 

records the interaction of electromagnetic 

energy (usually visible light) with matter, such 

as the Earth’s surface (fig. 1).

Remotely sensed data are fundamental to 

geographic science. The U.S. Geological Survey’s (USGS) Eastern Geographic Science 

Center (EGSC) is currently conducting and 

promoting the research and development of 

several different aspects of remote sensing science in both the laboratory and from overhead 

instruments. Spectroscopy is the science of 

recording interactions of energy and matter 

and is the bench science for all remote sensing. 

Visible and infrared analysis in the laboratory 

with special instruments called spectrometers 

enables the transfer of this research from the 

laboratory to multispectral (5–15 broad bands) 

and hyperspectral (50–300 narrow contiguous 

bands) analyses from aircraft and satellite sensors. In addition, mid-wave (3–5 micrometers, 

μm) and long-wave (8–14 μm) infrared data 

analysis, such as attenuated total reflectance 

(ATR) spectral analysis, are also conducted. 

ATR is a special form of vibrational infrared 

spectroscopy that has many applications 

in chemistry and biology but has recently 

been shown to be especially diagnostic for 

vegetation analysis.

Spectral Analysis of Vegetation 

and Water

Because different materials absorb or 

reflect energy from different wavelengths 

of light in unique ways, the development of 

high spectral resolution sensors and analytical 

methods provides the ability to identify the 

presence or absence of target materials or 

conditions and to investigate the physical and 

chemical processes at the Earth’s surface. 

Vegetation health and water quality are 

two important scientific issues that will be 

investigated by using hyperspectral remote 

sensing techniques (fig. 2).

Hyperspectral refers to a variety of remote 

sensing techniques that collect reflected or 

emitted electromagnetic energy in hundreds of 

narrow, contiguous bands that record the interaction of photons with the molecular structure 

of the material being sensed. When processed, 

the resulting plot of these energy interactions, 

called spectra, can be used to identify unique 

elements, minerals, water-quality parameters, 

and parameters of vegetation health and stress.

Remote sensing analyses of vegetation 

and water provide indicators of overall 

ecosystem condition, environmental stress, and 

landscape change at local, regional, and global 

scales. Advances in remote sensing imaging 

systems and data processing technologies have 

led to an increase in the use of this information 

to answer scientific questions related to 

vegetation and water issues, including the 

following: 

• Detection of plant or water contaminants 

• Identification of plant species

• Detection of plant stress

• Determination of chemical concentrations in 

tree canopies or leaves

• Monitoring of agricultural processes 

• Correlation of plant chemistry with geology 

(geobotany and biogeochemistry)

• Monitoring changes in coastal and wetland 

areas

Combinations of techniques such as 

laboratory chemistry, field sampling, field 

spectroscopy, x-ray fluorescence (XRF), and 

overhead hyperspectral imaging are being 

used to detect the signatures of specific 

contaminants and stress conditions at local 

to regional scales (fig. 2). Studies include the 

spectral analysis of heavy-metal contamination 

in soils and vegetation.

Hyperspectral Detection of Contamination at Selected Superfund Sites

A recent study done by the EGSC used 

hyperspectral imagery collected from satellite, 

aircraft, and ground-based sensors to detect the 

presence of hydrocarbons, metal drums, waste 

Figure 1. Artist’s rendering of Landsat 7 satellite 

in orbit (U.S. Geological Survey, 2012a). Landsat 7 

was launched on April 15, 1999. The satellite is in 

sun-synchronous orbit 438 miles above the Earth. 

The Enhanced Thematic Mapper Plus (ETM+) 

sensor has eight multispectral bands, including a 

panchromatic band and two thermal bands. The 

Landsat Data Continuity Mission, the follow-on to 

Landsat 7, was launched on February 11, 2013, and is

anticipated to continue the 40 years of Landsat history 

of Earth observation (U.S. Geological Survey, 2012b). 

Figure 2. Multispectral and hyperspectral data 

collections from a variety of field and aircraft 

and satellite instruments are being used to 

analyze water and vegetation characteristics. 

A, National Aeronautics and Space Administration (NASA) ER-2 Earth resources, high-altitude 

aircraft (photo by Carla Thomas, NASA). 

B, As viewed from left to right, the photo shows 

the effects on ferns of low to increasingly 

high amounts of soil arsenic concentration 

(Slonecker and others, 2009). C, A NASA Terra 

satellite image of the Deepwater Horizon oil spill, 

May 24, 2010. 

A

B

C
metal, and leachate on five different Superfund 

sites. Each of the five Superfund sites was a 

location of previous industrial activity, such 

as electroplating, that had closed and then 

undergone environmental remediation to clean 

up hazardous waste still present on the site. 

After the remediation effort, each Superfund 

site was tested to determine if the remediation 

cleanup efforts removed the heavy metals, 

such as zinc, from the soil (Slonecker and 

Fisher, 2011). The hyperspectral imagery that 

was collected by aircraft for each Superfund 

site was acquired by a sensor known as 

Airborne Real-time Cueing Hyperspectral 

Enhanced Reconnaissance (ARCHER; Space 

Computer Corp., 2012). ARCHER collected 

both visible and hyperspectral imagery over 

each of the five Superfund sites (fig. 3). 

The ARCHER hyperspectral sensor, 

with 52 usable bands, a spectral range 

from 500 to 1100 nanometers (nm), and a 

spectral resolution of 11.5 nm, is mounted in a 

fixed-wing, prop-driven aircraft. Onboard the 

aircraft during image collection, hyperspectral 

detection algorithms were used to detect any 

anomalies on the ground such as metal bins, 

hydrocarbons, and heavy metals. In addition 

to the hyperspectral imagery collected by 

ARCHER, point-based field measurements of 

the concentration of heavy metals in the soil 

were taken using a hand-held device called an 

XRF spectrometer (fig. 4). The XRF is capable 

of detecting concentrations of heavy metals 

in concentrations as small as a few parts 

per million. 

A laboratory hyperspectral sensor 

operated by the USGS that is capable of 

collecting spectral signatures in the long-wave 

part of the electromagnetic spectrum (8,000 

to 14,000 nm) is the Nicolet (Thermo Nicolet, 

2012) (fig. 5). The Nicolet hyperspectral 

sensor collects data in either a directional 

hemispherical reflectance (DHR) mode or in 

an attenuated total reflectance (ATR) mode. 

Both methods produce spectral signatures 

in the thermal region that are sensitive to 

the structural components of leaves, such as 

cuticles and cell walls (Ribeiro da Luz and 

Crowley, 2007).

is creating a new level of remote sensing 

science with the ability to separate energy into 

very narrow wavelengths and measure the 

interaction of those narrow wavelengths with 

earth surface materials. Significant potential 

exists to improve the monitoring of hazardous 

waste fate and transport, to identify specific 

plants species and their chemical fingerprints, 

to better understand plant processes such as 

carbon sequestration, and to identify invasive 

and nuisance species. Through the use of both 

advanced and applied remote sensing tools, 

this research will help to address important 

societal and policy issues.

References Cited

Ribeiro da Luz, Beatriz, and Crowley, J.K., 

2007, Spectral reflectance and emissivity 

features of broad leaf plants—Prospects 

for remote sensing in the thermal infrared 

(8.0–14.0 μm): Remote Sensing of the Environment, v. 109, p. 393–405.

Slonecker, E.T., and Fisher, G.B., 2011, An 

evaluation of traditional and emerging remote 

sensing technologies for the detection of fugitive contamination at selected Superfund hazardous waste sites: U.S. Geological Survey 

Open-File Report 2011–1050, 16 p., available 

only at http://pubs.usgs.gov/of/2011/1050/.

Slonecker, Terrence, Haack, Barry, and Price, 

Susan, 2009, Spectroscopic analysis of 

arsenic uptake in Pteris ferns: Remote 

Sensing, v. 1, no. 4, p. 644–675.

Space Computer Corporation, 2012, ARCHER 

(Airborne Real time Cueing Hyperspectral 

Enhanced Reconnaissance): Space Computer Corporation Web page at https://www.

spacecomputer.com/systems/archer.html.

Thermo Nicolet, 2012, ThermoNicolet Nexus 

Fully Integrated FT-IR spectrometer: Thermo 

Nicolet Nexusspectrometers, Web page at 

http://www.thermoscientific.com/ecomm/

servlet/techresource?resourceId=88776&

storeId=11152&from=search#.

U.S. Geological Survey, 2012a, Landsat 7 

history: Landsat missions Web page at 

http://landsat.usgs.gov/about_landsat7.php.

U.S. Geological Survey, 2012b, Landsat 8 

(LDCM) history: Landsat missions Web page 

at http://landsat.usgs.gov/about_ldcm.php.

By E.T. Slonecker, G.B. Fisher, D.A. Marr, 

L.E. Milheim, and C.M. Roig-Silva

Figure 3. Two ARCHER 

images of a Superfund site. 

On the left is a standard 

infrared image. The circled 

area is the base of the 

landfill where, on the right, 

the hyperspectral anomaly 

detection outlines the 

drums and debris that were 

later discovered on field 

inspection (Slonecker and 

Fisher, 2011).

Figure 4. An x-ray fluorescence spectrometer 

being used to acquire metal concentrations.

Figure 5. The Thermo Nicolet Nexus 670 FT-IR 

spectrometer (Thermo Nicolet, Inc., 2012).

For further information, please contact:

E. Terrence Slonecker

Eastern Geographic Science Center

U.S. Geological Survey

521 National Center, 12201 Sunrise Valley Drive

Reston, VA 20192

703–648–4289 / tslonecker@usgs.gov

Please visit the Eastern Geographic Science Center 

Web page: http://egsc.usgs.gov

Any use of trade, product, or firm names in this publication 

is for descriptive purposes only and does not imply 

endorsement by the U.S. Government.

Summary

The consequences of climate and land 

use and land cover change, agricultural 

productivity, contaminants in the environment, 

and invasive species are all contemporary 

environmental issues that confront us today 

and that can be effectively and efficiently 

studied through the use of remote sensing 

science. Through programs such as Landsat, 

the USGS-coordinated National Aerial Photography Program (NAPP), and many others, 

remote sensing has been a fundamental part 

of the USGS science mission. This research 

seeks to ensure that remote sensing science 

is applied to new, emerging environmental 

issues such as phytoremediation, hazardous 

waste monitoring, and emergency response. In 

addition to continuing the long and productive 

history of applied USGS remote sensing, 

this research also focuses on advances in 

remote sensing technology itself. Research 

in laboratory and imaging spectroscopy 

Grass Lawn Residential

Area

Automobiles

House Shed

Anomalies