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Forest Cover Change Detection in Andaman and Nicobar Islands Using Remote Sensing and GIS Techniques


Affiliations
1 Department of Earth Sciences, Rajiv Gandhi Institute of Petroleum Technology, Rae Bareli, India
2 Indian Institute of Remote Sensing, Department of Space, Indian Space Research Organization, Dehradun, India
     

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Prior to the year 1978, issues related to forest encroachment in Andaman&Nicobar Islands, India have been resolved under the observation of Indian courts. However, forest encroachment continued post-1978 in various parts of the islands for several reasons. The paper discusses land use and land cover change detection analysis with reference to forest encroachment in Baratang Island of Andaman&Nicobar Islands. Careful selection of satellite imageries based on various attributes including radiometric resolution, spatial resolution, cloud-free coverage and time lapse among others, is warranted for change detection analysis. The study deals with the on-screen visual interpretation of multitemporal remotely sensed images of Landsat-5 Thematic Mapper (TM) with spatial resolution of 30 m, IRS-1D LISS-III (23.5 m) and Resourcesat-2 LISS-III (23.5 m) for the years 1989, 2003 and 2013 for studying forest encroachment post-1978. The geocoded data has been interpreted on the scale of 1:50,000. Ground truthing and delineation of the forest encroachment pockets were achieved with the help of Global Positioning System (GPS) readings combined with the remotely sensed images, in addition to the knowledge-base of forest encroachment in the area provided by the Forest Department of Andaman&Nicobar Islands. The study successfully detected forest encroachment area of 21.3 ha., 197.5 ha. and 201.3 ha. for the years 1989, 2003 and 2013, respectively.

Keywords

Land Use/Land Cover, Change Detection, Remote Sensing, On-Screen Visual Interpretation.
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About The Authors

L. K. Tiwari
Department of Earth Sciences, Rajiv Gandhi Institute of Petroleum Technology, Rae Bareli
India

S. K. Sinha
Department of Earth Sciences, Rajiv Gandhi Institute of Petroleum Technology, Rae Bareli
India

S. Saran
Indian Institute of Remote Sensing, Department of Space, Indian Space Research Organization, Dehradun
India


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  • Forest Cover Change Detection in Andaman and Nicobar Islands Using Remote Sensing and GIS Techniques

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Authors

L. K. Tiwari
Department of Earth Sciences, Rajiv Gandhi Institute of Petroleum Technology, Rae Bareli, India
S. K. Sinha
Department of Earth Sciences, Rajiv Gandhi Institute of Petroleum Technology, Rae Bareli, India
S. Saran
Indian Institute of Remote Sensing, Department of Space, Indian Space Research Organization, Dehradun, India

Abstract


Prior to the year 1978, issues related to forest encroachment in Andaman&Nicobar Islands, India have been resolved under the observation of Indian courts. However, forest encroachment continued post-1978 in various parts of the islands for several reasons. The paper discusses land use and land cover change detection analysis with reference to forest encroachment in Baratang Island of Andaman&Nicobar Islands. Careful selection of satellite imageries based on various attributes including radiometric resolution, spatial resolution, cloud-free coverage and time lapse among others, is warranted for change detection analysis. The study deals with the on-screen visual interpretation of multitemporal remotely sensed images of Landsat-5 Thematic Mapper (TM) with spatial resolution of 30 m, IRS-1D LISS-III (23.5 m) and Resourcesat-2 LISS-III (23.5 m) for the years 1989, 2003 and 2013 for studying forest encroachment post-1978. The geocoded data has been interpreted on the scale of 1:50,000. Ground truthing and delineation of the forest encroachment pockets were achieved with the help of Global Positioning System (GPS) readings combined with the remotely sensed images, in addition to the knowledge-base of forest encroachment in the area provided by the Forest Department of Andaman&Nicobar Islands. The study successfully detected forest encroachment area of 21.3 ha., 197.5 ha. and 201.3 ha. for the years 1989, 2003 and 2013, respectively.

Keywords


Land Use/Land Cover, Change Detection, Remote Sensing, On-Screen Visual Interpretation.

References