Remote sensing and GIS tools for the evaluation of land use effects on coastal waters

2008 ◽  
Author(s):  
Alessandra Marino ◽  
Mariano Ciucci ◽  
Mario Mariani ◽  
Antonio Moccaldi

The aim of the study was to evaluate the changes in land use and land cover (LULC) in Gummidipoondi and the surrounding areas in Thiruvallur district, Tamilnadu India.Spatio-temporal variation in the land use and land cover were analysed on a decadal basis for the period from 1990 to 2019 using remote sensing and GIS based tools. The Landsat 5 (TM) and Resource-Sat 2 (LISS-III) data was used for the LULC classificationin the study area. During the study period from 1990 to 2019, built-up area including industrial, urban and rural land use increased by about 147%. Predominant change was also noticed in the mudflat category where more than 95% of it was lost to various other land uses such as agriculture and marsh area. This observation calls for planning and conservation of sensitive ecosystems in the study area that may be lost due to anthropogenic pressures via pollution and undesirable conversion of LULC. The study revealed no significant changes in the extent of other LULC classes such as agriculture, forests, plantations, land with or without scrub, rivers and waterbodies in the study area


2001 ◽  
Vol 22 (11) ◽  
pp. 2095-2108 ◽  
Author(s):  
T. Sharma ◽  
P. V. Satya Kiran ◽  
T. P. Singh ◽  
A. V. Trivedi ◽  
R. R. Navalgund

Author(s):  
O. S. Olokeogun ◽  
K. Iyiola ◽  
O. F. Iyiola

Mapping of LULC and change detection using remote sensing and GIS techniques is a cost effective method of obtaining a clear understanding of the land cover alteration processes due to land use change and their consequences. This research focused on assessing landscape transformation in Shasha Forest Reserve, over an 18 year period. LANDSAT Satellite imageries (of 30 m resolution) covering the area at two epochs were characterized into five classes (Water Body, Forest Reserve, Built up Area, Vegetation, and Farmland) and classification performs with maximum likelihood algorithm, which resulted in the classes of each land use. <br><br> The result of the comparison of the two classified images showed that vegetation (degraded forest) has increased by 30.96 %, farmland cover increased by 22.82 % and built up area by 3.09 %. Forest reserve however, has decreased significantly by 46.12 % during the period. <br><br> This research highlights the increasing rate of modification of forest ecosystem by anthropogebic activities and the need to apprehend the situation to ensure sustainable forest management.


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