Version 1
: Received: 3 July 2023 / Approved: 3 July 2023 / Online: 4 July 2023 (10:16:10 CEST)
How to cite:
Kumar, P.; Mukherjee, S. Impact of Climate Change and Catastrophic Events on Forest Cover of Middle Andaman Using Remote Sensing, GIS and Support Vector Machine. Preprints2023, 2023070103. https://doi.org/10.20944/preprints202307.0103.v1
Kumar, P.; Mukherjee, S. Impact of Climate Change and Catastrophic Events on Forest Cover of Middle Andaman Using Remote Sensing, GIS and Support Vector Machine. Preprints 2023, 2023070103. https://doi.org/10.20944/preprints202307.0103.v1
Kumar, P.; Mukherjee, S. Impact of Climate Change and Catastrophic Events on Forest Cover of Middle Andaman Using Remote Sensing, GIS and Support Vector Machine. Preprints2023, 2023070103. https://doi.org/10.20944/preprints202307.0103.v1
APA Style
Kumar, P., & Mukherjee, S. (2023). Impact of Climate Change and Catastrophic Events on Forest Cover of Middle Andaman Using Remote Sensing, GIS and Support Vector Machine. Preprints. https://doi.org/10.20944/preprints202307.0103.v1
Chicago/Turabian Style
Kumar, P. and Saumitra Mukherjee. 2023 "Impact of Climate Change and Catastrophic Events on Forest Cover of Middle Andaman Using Remote Sensing, GIS and Support Vector Machine" Preprints. https://doi.org/10.20944/preprints202307.0103.v1
Abstract
Natural ecosystem of Islands and coastal region are vulnerable to climate change phenomena such as increasing temperature, fluctuating rainfalls, ocean acidification and tsunami. Andaman and Nicobar group of islands lies in Bay of Bangal facing such extreme climate phenomena. A spatial-temporal analysis of forest cover of middle Andaman region of the Andaman and Nicobar group of islands was done from 1990 to 2019 with an interval of 5-10 years. Support vector machine classifier, spectral indices such as Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index were used for the analysis of greenery, water resources, and urban land. Land surface temperature was estimated using split window algorithm for Landsat 8 and mono window algorithm for Landsat 5. The data showed relative contribution of forest region toward rising temperature in the island region. The research also showed that subsurface hydrology linked to interconnected lineaments provides a stable zone for forest cover. The open forest showed maximum fluctuation while minimum change was observed in Evergreen Forest. The spectral characteristics analysis using indices showed significant change except in 2005 due to Tsunami occurred in 2005. The land surface temperature showed fluctuation near to 30° C from 1990 to 2019.
Keywords
Climate change; Middle Andaman; Land use Land cover change analysis; Spectral indices; Support Vector Machine
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
