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Multi-source Classification Using Artificial Neural Network in a Rugged Terrain
Authors:Manoj Kumar Arora  Shashank Mathur
Institution:Department of Civil Engimcering , University of Roorkee , Roorkee, India , 247 667 E-mail: manojfce@rurkiu.ernet.in
Abstract:Abstract

This study advocates the use of GIS and remote sensing technologies to establish urban evolution maps and assess the impact of urbanization on agricultural areas over the last three decades. The target area is the city of Béni‐Mellal, located in central Morocco. The methodology adopted makes use of panchromatic SPOT images to survey the urban areas during the 1980s and 1990s. Available topographic maps provided the information for the 1970s. Maps and statistics of land use and urban growth for Béni Mellal were established after manually classifying images on a per-polygon basis and digitizing topographic maps using GIS capabilities. The results show an increase in dense urban area by 980.7 ha from the 1970s to the 1990s. This increase occurred at the expense of forests (24.7 ha), plantations (752.3 ha), rangeland (113.4 ha), non‐irrigated land (69.7 ha), and irrigated land (20.6 ha). During this period, scattered urban areas, predominantly suburbs, increased by 755.9 ha to the detriment of forests (14.9 ha), plantations (109.8 ha), rangeland (138.9 ha), non‐irrigated land(400.5 ha), and irrigated land (91.9 ha). These cartographic and statistic results are efficient decision‐making tools for protecting agricultural land and planning urban and suburban areas.
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