Remote sensing and GIS in land use change detection for the coastal stretch from Tharangambadi to Kollidam mouth Nagapattinam District Tamilnadu

Abstract

A study has been made to evaluate the changes occurred in the villages along the coastal stretch from Tharangambadi to Kollidam river mouth, Nagapattinam district, Tamilnadu using satellite imageries supplemented with GIS. The study area is accommodated between 10°58 and 11°18 N and 79°40 and 79°52 E. It covers 2 taluks including 13 revenue Villages, 5 in Tharangambadi and 8 in Sirkazhi. Since, such study has not been carried over so far in the selected study area, this study has been initiated. This study will be used to create the basis for conducting sustainable land use planning or setting up a sustainable development strategy in the study area. Since the study is carried out at village level, it will be useful for any researchers, scientists, planners and all the government organizations for any type of subsequent application in planning and further research in near future. newlineIRS 1A (LISS II), IRS 1C (LISS III), merged data of IRS P6 and IRS 1D (LISS IV and PAN) and IRS P6 (LISS III) satellite imageries in the scale of 1:50000 were availed, respectively for the years 1992, 1997, 2004 and 2006. These imageries were interpreted visually for land use and were categorized according to NRSA land use classification. The accuracy of interpretation was checked with ground truth information for the years 2004 and 2006 in the field. The spatial database of the land use maps interpreted was created using Arc Map and Geomatica GIS software. The spatial database of the land use created for the study area for years 1992, 1997, 2004 and 2006 were subjected to intersection analysis available in Geoprocessing Wizard of ArcMap. From the attribute table created for the intersected maps, the land use change matrices were derived using Microsoft Excel. The reasons pertaining to these changes were discussed in this thesis. The structural indices, shape indices and pattern indices were estimated using the GIS database of the land use maps for the years 1992, 1997 and 2004 and diversification of the land use categories were studi