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Forestry
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Use of Landsat thematic mapper data for extracting topographic information of a rugged forested region in Indonesia
Waqar Ahmad
Department of Geographical Sciences and Planning
The University of Queensland, Brisbane, Australia
Abstract
The effects of shadows has been and major source of concern in the remotely sensed data classification of a rugged forested region. The severity of the problem magnifies especially in the developing countries where either the topographic maps are non-existent or the quality of the existing maps is extremely poor. In this paper an attempt have been made to evaluate the applicability of Landsat Thematic Mapper data fro extracting the topographic information. A radiance model used to reflectance is applied to a forested region of Indonesia to generate a topographic image.
Introduction
During the last two decades considerable research have been carried out towards the applicability of remotely sensed data for land cover mapping in various part of the world (Ahmad, 1986). Unfortunately, mapping land cover types had limited success in high relief areas. This is mainly because of the varying facet slope and orientation which causes marked variation in the spectral signatures appearing on the Landsat images. As a result cover types may have similar spectral reflectance but quite different radiances to the shading effect of topography. This makes the classification process extremely difficult.
Various researchers have used number of techniques to subdue the topographic effects. This includes the use of band ratioing ( Justice, 1978; and Holben and Justice, 1981, Ahmad, 1986). Some researchers used multidimensional analysis using digital topographic data as added dimensions and physical models which estimate the reflection of solar radiation from slopes (Smith et al. 1980) ; Kimes and Kirchner, 1981; Teillet and Good enough, 1982; Kalsh, 1987 and Lepricurand and Durand, 1988).
In this paper topographic effects have been analyzed using a radiance model suggested by (Ahmad et al. 1991). Underlying idea behind this approach is not only to define classes on the basis of both spectral similarity and illumination,, that is, sunlit versus shadowed but also the extraction of topographic information from the classification of Landsat Thematic Mapper data.
The image processing tasks of this project were carried out using micro BRIAN software at CSIRO, Division of Water Resources, Canberra, Australia. The micro BRIAN system is a microcomputer based image processing system. For further details on the system see Microprocessor Applications Ltd. ( 1987).
Study Area
The research was undertaken in the Mouton region of Indonesia. The northwest and southeast coordinates of the study area are 0° 45’ 05” N, 121°10’ 15” W and 0°40’ 10” S, 121°15 30” E. The major reason for its selection was the rugged nature of the study area and availability of aerial photographs of the study area. Moreover, non availability of the topographic maps of the area lead to its selection.
TM Data Classification using Landform information
The following section provides details of the various steps followed and the salient features of the mathematical model used.
Model Description
Consider a Landsat scene encompassed by N Pixels (i = 1 to N), nb banon (j = 1 to nb) and nc values of land cover (k = 1 to nc). In terms of lans cover, the total number of pixels in the scene (N) can be described as
Were Q k denotes the number of pixels in the scene which fall under land cover category k. Using this labelling convention, the satellite recorded radiance in pixel I, channel (or band j and cover type k (Y) has the following form:
Where T j is atmospheric transmission in band J, r jk is reflectance in band for cover type k, G j is irradiance in band j on a horizontal surface, C j, the topographic modulation factor, dj is atmospheric path radiance, and u j potentially an atmospheric inhomogeneity term (independent of wavelength).
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