Quantitative Assessment of Land Cover Change Using Landsat Time Series Data: Case of Chunati Wildlife Sanctuary (CWS), Bangladesh

Journal Title: International Journal of Environment and Geoinformatics - Year 2016, Vol 3, Issue 2

Abstract

Due to inappropriate management and absence of land use planning, land cover change of developing country like Bangladesh is a common phenomenon. This land cover change phenomenon will have its tremendous effect if found at a greater extent on natural habitat area for numerous animal and tree species. In this study, land cover change of Chunati Wildlife Sanctuary (CWS) was assessed from (2005-2015) using Landsat TM (Thematic Mapper) and Landsat 8 OLI/TIRS (Operational Land Imager/Thermal Infrared Sensor). ArcGIS v10.1 and ERDAS Imagine v14 were used to process satellite derived imageries and assess other quantitative data for land cover change assessment of this study area. Land cover change of the area was identified using Normalized Difference Vegetation Index (NDVI) technique. Highest NDVI value was found in 2005 (0.71) which denotes presence of moderate-high vegetation cover at that time period. After 2005, highest NDVI value was found following a decreasing trend (0.56 in 2010 and 0.4 in 2015) which clearly represents the rapid vegetation cover change in the study area. Almost 7608 hectares of moderate to high density natural forest cover dominated the area during 2005 but was totally absent in 2015 which may be considered as a great threat regarding proper ecosystem functioning of CWS. From the findings of this research, it can be easily concluded that the sanctuary area has lost its valuable land cover both qualitatively and quantitatively.

Authors and Affiliations

Kamrul Islam, Mohammed Jasimuddin, Biswajit Nath, Tapan Kumar Narh

Keywords

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  • EP ID EP196250
  • DOI -
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How To Cite

Kamrul Islam, Mohammed Jasimuddin, Biswajit Nath, Tapan Kumar Narh (2016). Quantitative Assessment of Land Cover Change Using Landsat Time Series Data: Case of Chunati Wildlife Sanctuary (CWS), Bangladesh. International Journal of Environment and Geoinformatics, 3(2), 45-55. https://europub.co.uk/articles/-A-196250