AGRICULTURAL LAND CHANGE DETECTING AND FORECASTING USING COMBINATION OF FEEDFORWARD MULTILAYER NEURAL NETWORK, CELLULAR AUTOMATA AND MARKOV CHAIN MODELS
This paper proposed a methodology for finding changes in agricultural land of Tehran during past years and simulating these changes for future years. The proposed method utilized the spatial GIS-based techniques and Landsat satellite imagery to predict agricultural land map for the future of Tehran....
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2019-10-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W18/153/2019/isprs-archives-XLII-4-W18-153-2019.pdf |