DocumentCode
2680305
Title
An integrated geographical information system´s approach to land cover change assessment
Author
Mattikalli, N.M.
Author_Institution
Dept. of Geogr., Cambridge Univ., UK
Volume
2
fYear
1994
fDate
8-12 Aug. 1994
Firstpage
1204
Abstract
A new methodology has been developed for the land cover change assessment using the integrated GIS approach. Inherent shortcomings of raster change detection techniques have been identified for use with vector formatted land cover data. There was a need for an established procedure for the assessment of land cover change using a vector based GIS. In this paper, a methodology using mathematical concepts of sets and groups has been developed. Such a methodology was successfully implemented for the analysis of historical land cover change from 1931 to 1989 in the River Glen catchment, UK. Algorithms have been developed for automatic derivation of dynamic statistics of land cover. It has been demonstrated that this approach can be efficiently adopted for an operational use incorporating the products derived from both the coarse and fine resolution remotely-sensed satellite images.
Keywords
agriculture; geographic information systems; geophysical techniques; geophysics computing; remote sensing; AD 1931 to 1989; England Lincolnshire; River Glen catchment; UK; agriculture; automatic derivation; change detection; dynamic statistics; geophysical measurement technique; geophysics computing; integrated GIS; integrated geographical information system; land cover change assessment; land surface; mathematical concepts; raster method; remote sensing; satellite image; sets and groups; terrain mapping; vector method; vegetation; Algorithm design and analysis; Boolean algebra; Boolean functions; Computational Intelligence Society; Geographic Information Systems; Geography; Image resolution; Laboratories; Remote sensing; Rivers; Satellites; Statistical analysis; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 1994. IGARSS '94. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation., International
Print_ISBN
0-7803-1497-2
Type
conf
DOI
10.1109/IGARSS.1994.399385
Filename
399385
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