ENCYCLOPEDIA OF ENVIRONMENTAL SCIENCE AND ENGINEERING - REMOTE SENSING pptx

The 1990s have seen a further expan-sion of the field of remote sensing, with the appearance of new imaging radar satellites, imaging spectrometers, and high-resolution MSS systems, and

REMOTE SENSING

Remote sensing is the act of acquiring information about an

object from a distance Environmental applications of remote

sensing typically involve the collection of photographic or

electronic images of the Earth’s surface or atmosphere from

airborne or spaceborne platforms Visual interpretation or

com-puter processing can then be used to analyze these images

The history of remote sensing dates back to the 19th

cen-tury, when the first aerial photographs were taken from

bal-loons and kites The invention of the airplane provided a

better platform and aerial photography advanced rapidly

after World War I With the dawn of the Space Age in 1957,

the field of photographic remote sensing expanded to include

pictures taken from satellites and other space platforms, as

demonstrated by pictures taken with a variety of camera

types during the Apollo missions

At the same time, non-photographic remote sensing

sys-tems such as electronic multispectral scanners (MSS) were

developed for use on airborne platforms as well as on

meteo-rological satellites, Earth resources satellites, and other

spaceborne platforms The 1990s have seen a further

expan-sion of the field of remote sensing, with the appearance of

new imaging radar satellites, imaging spectrometers, and

high-resolution MSS systems, and with the improvement of

methods for computer processing of remotely-sensed data

TYPES OF REMOTE SENSING SYSTEMS

Several types of remote sensing systems can be differentiated

based on the principles employed for measuring

electromag-netic radiation The most common types fall into four broad

categories: photographic systems, videographic systems,

multispectral scanners, and imaging radar systems Within

these categories, particular instruments are designed to

oper-ate in specific portions of the electromagnetic spectrum The

Earth’s atmosphere scatters and absorbs many wavelengths

of electromagnetic radiation, limiting the portion of the

spec-trum that can be used for remote sensing

Photographic Systems

Many types of cameras have been used to acquire

photo-graphs of the Earth’s surface from airplanes and from space

Common formats include 35-mm, 70-mm, and 9 ⫻ 9-inch

film sizes, although specialized cameras that employ other

film sizes are also used Film types include black and white panchromatic, black and white infrared, color, and color infrared, covering the visible and near-infrared portions of the electromagnetic spectrum from approximately 0.4 to 0.9

µ m (Photography in the ultraviolet range, from 0.3 to 0.4

µ m, is also possible but is rarely done due to atmospheric

absorption and the need for quartz lenses.) Once the film has been processed, photographs can be electronically scanned

at a variety of resolutions for use in a digital environment

Photographic systems provide relatively high-resolution images, with the nominal scale of a vertical aerial photo-graph being dependent on the focal length of the camera and the flying height of the sensor. 1

Videographic Systems Video cameras can be used to record images in analog form

on videotape Video systems have been designed to operate

in the visible, near-infrared, and mid-infrared portions of the electromagnetic spectrum The advantages of video systems include low cost, near-real-time image availability, and the ability to collect and store many image frames in sequence

The primary disadvantage of video is its low spatial resolu-tion, with approximately 240 lines per image for standard video cameras. 2,3

Multispectral Scanners

MSS systems use electronic detectors to measure electro-magnetic radiation in selected bands of the spectrum from

approximately 0.3 to 14 m m, including the visible and near-,

mid-, and thermal-infrared regions These individual bands

may be fairly wide (greater than 0.2 m m in width) or quite

narrow (less than 0.01 m m in width) The designs used for

MSS systems fall into two categories Across-track scanners employ a rotating or oscillating mirror to scan back and forth across the line of flight Along-track (“push-broom”) scan-ners use a linear array of charge-coupled devices (CCDs) to scan in parallel along the direction of flight Distinct subcat-egories of MSS systems include thermal scanners, which measure emitted radiation in the thermal infrared portion of the spectrum, and imaging spectrometers, or “hyperspectral scanners,” which generally collect data in over 100 continu-ous, narrow spectral bands, producing a complete reflectance spectrum for every pixel in the image. 1,4

1062 REMOTE SENSING

Airborne and satellite MSS systems have become widely

used in many environmental science and resource management

applications Examples of different types of MSS system

include the following:

• The U.S Landsat satellite series includes two MSS

systems The original Landsat MSS (on board sys-tems launched between 1972 and 1978) includes four spectral bands in the visible and near-infrared portions of the spectrum, with a spatial resolution

of 80 m The Landsat Thematic Mapper (TM) instrument (since 1982) includes six bands in the visible, near-, and mid-infrared regions, with a spatial resolution of 30 m (and a thermal infrared band with a resolution of 120 m) Both instruments operate in an across-track configuration with a swath width of 185 km, and a current orbital repeat cycle of 16 days

• The HRV instrument on the French SPOT

satel-lite series can collect data in either a single wide

“panchromatic” band, with 10m resolution, or in three narrower bands in the visible (green and red) and near-infrared, with 20 m resolution The orbital repeat cycle is 26 days, but the sensor’s ability to be rotated (via ground command) up to 27°ᎏ left or right allows more frequent imaging

of a given location on the Earth’s surface The HRV is an along-track scanner, with a swath width of 60 to 80 km depending on the viewing angle Two identical HRVs are included on each SPOT satellite

Imaging Radar Systems

Whereas the previous types of remote sensing systems

oper-ate in the visible and infrared portions of the electromagnetic

spectrum, imaging radar systems operate in the microwave

portion of the spectrum, with wavelengths from

approxi-mately 1 cm to 1 m At these wavelengths, radar is

unaf-fected by clouds or haze (shorter wavelength systems are

used for meteorological remote sensing) In addition, radar

systems are active sensors, transmitting their own radiation

rather than passively measuring reflected solar or emitted

radiation; thus, they can be operated at any time of day or

night Imaging radar systems are sensitive to the geometric

structure and dielectric properties of objects, with the

pri-mary determinant of an object’s dielectric properties being

its liquid water content Current satellite radar systems

include the European ERS-series and the Canadian Radarsat,

which each have a single 5-cm wavelength band, and the

Japanese JERS-1 system with a 23-cm band Several

air-borne radar systems have been developed, such as the NASA/

JPL AIRSAR, which operates at multiple wavelengths. 5,6,7

Photographic cameras, video cameras, and multispectral

scanners can be operated in a vertical configuration to

mini-mize the geometric distortion of the image, or at an oblique

angle to provide a side view of the landscape Imaging radar

systems are not operated vertically, but in a side-looking configuration with a broad range of possible look angles

ENVIRONMENTAL APPLICATIONS OF REMOTE SENSING

Remote sensing has been used for a wide variety of applica-tions in the environmental sciences Among the earliest uses

of remote sensing was geologic mapping, including the dis-crimination of rock and mineral types, lineament mapping, and identifying landforms and geologic structures Today, many types of remotely-sensed data are used for geologi-cal applications at a variety of spatial sgeologi-cales, ranging from high-resolution aerial photography, to thermal-scanner images, to lower-resolution Landsat images covering large areas

Agricultural applications of remote sensing are also common Aerial photography and other remotely-sensed data are widely used as a base for soil mapping, while multispec-tral and thermal images are used for soil moisture mapping

Imaging radar systems, with their sensitivity to moisture-related dielectric surface properties, can also be used to mea-sure soil moisture Multispectral visible and infrared data are used for crop classification and assessment, including moni-toring the health and productivity of crops, with the goal of predicting yields and identifying areas of crop damage

In forestry, aerial photographs are used to delineate timber stands and to estimate tree heights, stocking densities, crown diameters, and other variables relating to timber volume Color infrared photography and multispectral imag-ery can be used to map forest types and to identify areas of stress due to pest infestations, air pollution, and other causes

Aerial and satellite imagery can be used to map the effects of wildfires, windthrow, and other phenomena in forested regions Wildlife habitat can be assessed using remote sens-ing at a variety of scales High-resolution aerial photography can also be used to assist in wildlife censuses in non-forested areas such as rangeland

Many aquatic and hydrological applications make use of remote sensing Water pollution can be monitored using aerial photography or MSS systems, and imaging radar can be used

to detect oil slicks Thermal imagery is used to study currents and circulation patterns in lakes and oceans Both optical and radar data are used to monitor flooding, including flooding beneath a forest canopy in the case of radar Wetlands delin-eation and characterization can both be assisted by remote sensing Radar systems are used to measure ocean waves, and both radar and optical images have been used to detect sea and lake ice

Remote sensing is often used to assist in site selection and infrastructure location, urban and regional planning, and civil engineering applications Aerial photographs are often acquired with a significant overlap between adjacent photos, allowing heights to be measured using the stereoscopic effect This process is extensively used for topographic map-ping and for creation of geometrically-correct orthorectified

REMOTE SENSING 1063 photographs to serve as base maps for other applications

Radar interferometry is also being used on an experimental

basis for topographic mapping

IMAGE INTERPRETATION AND ANALYSIS

Many environmental applications of remote sensing rely

solely on visual image interpretation In many cases, visual

analysis is improved by stereo viewing of overlapping pairs of

images Increasingly, however, some degree of digital image

processing is used to enhance and analyze remote sensing

data Simple image enhancement techniques include data

stretches, arithmetic operations such as ratioing and

differenc-ing, statistical transformations such as principal components

analysis, and image convolution, filtering, and edge

detec-tion More complex image processing techniques include

automated land use/land cover classification of images using

spectral signatures representing different land cover types. 8

Most remote sensing applications require the collection

of some form of reference data or “ground truth,” which is

then related to features or patterns in the imagery For

exam-ple, pixels in a remotely-sensed hyperspectral image might

be compared to a series of mineral spectra acquired from

ground samples Ground measurements of soil moisture,

crop productivity, or forest leaf-area index (LAI) could be

related to observed reflectance in a satellite image using

linear regression Often, ground truth locations are

estab-lished using the Global Positioning System (GPS) to

facili-tate the relation to a georeferenced image

One significant advantage of digital remotely-sensed

imagery, whether collected electronically or as scanned

pho-tographs, is the ability to use digital data in a geographic

information system (GIS) Once a digital image has been

georeferenced, it can be combined with a variety of other

types of spatial data This combination of image and

non-image data can be used for a wide range of purposes from

simple map updates to complex spatial analysis. 9,10,11,12

Remote sensing is a rapidly changing field, with more than twenty new satellite systems scheduled for launching

in the next decade Major sources of new data will be high-resolution (approximately 1 m) commercial systems and the various sensors comprising the Earth Observing System (EOS)

REFERENCES

1 Lillesand, T.M and R.W Kiefer, 1994 Remote sensing and image interpretation, John Wiley and Sons, Inc., New York

2 Mausel, P.W., J.H Everitt, D.E Escobar and D.J King 1992 Airborne

videography: current status and future perspectives Photogrammetric Engineering and Remote Sensing, vol 58, no 8, pp 1189–1195

3 Meisner, D.E 1986 Fundamentals of airborne video remote sensing

Remote Sensing of Environment, vol 19, no 1, pp 63–79

4 Vane, G and A Goetz, 1993 Terrestrial imaging spectrometry: current

status, future trends Remote Sensing of Environment, vol 44, no 2/3,

pp 117–126

5 Waring, R.H., J Way, E.R Hunt, Jr., L Morrissey, K Jon Ranson, J.F Weishampel, R Oren and S.E Franklin, 1995 Imaging radar for

ecosystem studies Bio-Science, vol 45, no 10, pp, 715–723

6 Way, J and E.A Smith, 1991 Synthetic aperture radar systems and

their progression to the EOS SAR, IEEE Transactions on Geosciences and Remote Sensing, vol.29, no 6, pp 962–985

7 Elachi, C., 1988 Spaceborne Radar Remote Sensing, IEEE Press,

New York

8 Jensen, J.R., 1986 Introductory Digital Image Processing: A Remote Sensing Perspective, Prentice-Hall, Englewood Cliffs, NJ

9 Pequet, D.J and D.F Marble, Eds 1990 Introductory Readings in Geographic Information Systems, Taylor and Francis, New York

10 Star, J and J Estes 1990 Geographic Information Systems, Prentice-Hall,

Englewood Cliffs, NJ

11 K Hsu, X Gao, S Sooroshian and H.V Gupta, 1997 Rainfall estima-tion from remotely sensed informaestima-tion using artificial neural networks

J Appl Meteorl., 36, 1176–1190

12 Sooroshian, S., S.K Shu, X Gao, H Gupta, B Imam and D Braithwaite,

2000 Evaluation of the PERSIANN system satellite-based estimates of

tropical rainfall, Bull Am Hydrometeorol Soc., 81, 2035–2046

JONATHAN CHIPMAN

University of Wisconsin