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Remote sensing: Using the spatial domain

Curran, P.J. (2001) Remote sensing: Using the spatial domain Environmental and Ecological Statistics, 8, (4), pp. 331-344.

Record type: Article

Abstract

Objects in the terrestrial environment interact differentially with electromagnetic radiation according to their essential physical, chemical and biological properties. This differential interaction is manifest as variability in scattered radiation according to wavelength, location, time, geometries of illumination and observation and polarization. If the population of scattered radiation could be measured, then estimation of these essential properties would be straightforward. The only problem would be linking such estimates to environmental variables of interest. This review paper is divided into three parts. Part 1 is an overview of the attempts that have been made to sample the five domains of scattered radiation (spectral, spatial, temporal, geometrical, polarization) and then to use the results of this sampling to estimate environmental variables of interest. Part one highlights three issues: first, that relationships between remotely sensed data and environmental variables of interest are indirect; second, our ability to estimate these environmental variables is dependent upon our ability to capture a sound representation of variability in scattered radiation and third, a considerable portion of the useful information in remotely sensed images resides in the spatial domain (within the relations between the pixels in the image). This final point is developed in Part 2 that explores ways in which the spatial domain is utilized to describe spatial variation in remotely sensed and ground data; to design optimum sampling schemes for image data and ground data and to increase the accuracy with which remotely sensed data can be used to estimate both discontinuous and continuous variables. Part 3 outlines two specific uses of information in the spatial domain; first, to select an optimum spatial resolution and second, to inform an image classification.

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Published date: 2001

Identifiers

Local EPrints ID: 16118
URI: http://eprints.soton.ac.uk/id/eprint/16118
PURE UUID: 6d6ddff2-a322-4a42-8b1f-22bdcf4fa08d

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Date deposited: 23 Jun 2005
Last modified: 17 Jul 2017 16:44

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Contributors

Author: P.J. Curran

University divisions

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