4.2 Article

Coastal landuse and land cover change and transformations of Kanyakumari coast, India using remote sensing and GIS

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出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ejrs.2017.04.003

关键词

Landuse and land cover; Change detection; MLC algorithm; Remote sensing and GIS; South West coast of Kanyakumari, South India

资金

  1. DST-INSPIRE Division, Department of Science & Technology, Government of India [DST/INSPIRE/2011/IF110366]

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The coastal landuse and land cover features in the South West coast of Kanyakumari are dynamically regulated due to marine and terrestrial processes and often controlling by natural and anthropogenic activities. The primary objective of this study is to estimate the decadal changes and their transformations of landuse and land cover (LULC) features under Level II category of USGS-LULC Classification System using Landsat ETM+ and TM images using Maximum Likelihood Classifier (MLC) algorithm for the period 2000-2011. The classified LULC features are categorized as beachface land cover, cultivable lands, plantation and shrub vegetation, fallow land, barren land, settlements and built-ups, water bodies, and mining area, etc. The geo-database is prepared for LULC feature class with an attributes of name, location, area and spatial distribution, etc. It shows the larger area in beachface land cover (sandy beaches, foredunes, uplands, Teri dunes (laterite) and associated nearshore landforms), plantations, cultivable lands, fallows, and barren lands are converted into built-ups and it increases more than twice in the period of 10 years. Using GIS techniques, the analysis of change detection matrix reveals that the total area of 45.90 km(2) in different LULC features periodically shifted or transformed from one state to another one or more states, i.e. the beachface land cover area of 1.24 km(2) is encroached for built-ups and 0.63 km(2) for placer mining during the decade. Meanwhile, the area of 0.21 km(2) in this cover is transformed into wetlands and saltwater bodies. During the past decade, the expansion of area in the built-ups and settlements are directly proportional to the growth of population, which produces severe threat to the coastal resources. Accuracy assessment of classified images shows the overall accuracy is estimated as 81.16% and 77.52% and overall Kappa coeffient statistical values of 0.83 and 0.76 for the year 2000 and 2011 respectively. Ground truth verification of the extracted LULC features performed using 120 samples (10 samples per class) reveals that the accuracy of classified features is 89%. This indicates the acceptable accuracy of the classified LULC features for landuse and land cover change studies. The geodatabase of LULC features is used as primary source for sustainable land resource management in the coastal region. (C) 2017 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.

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