NAAS Rating: 5.21 new
Journal of Pharmacognosy and Phytochemistry
Vol. 7, Special Issue 1 (2018)
Analysis of forest cover change detection (Remote Sensing and GIS) case area of pyin oo Lwin Township
Author(s): Thett Oo Eain, Htet Ne Oo, Hnin Hnin Htun and Aye Pwint Phyu
Abstract: Remote sensing and GIS can be applied for environmental monitoring and climate change detection. The proposed system is to detect land cover/land use changes especially forest observed in Pyin Oo Lwin township, Myanmar. The required three years (2010, 2014 and 2017) Landsat data of Pyin Oo Lwin are downloaded from United States Geological Survey (USGS). The land cover is classified into four classes: Forest, Vegetation, Water and Other. ArcGIS will be applied as analysis tools for classification and change detection. Maximum likelihood classification and NDVI classification will be applied respectively. Land surface temperature (LST) is an important factor in global climate change studies. Landsat Thematic Mapper and Enhanced Thematic Mapper Plus data of the year 2010, 2014 and 2017 are used to effects of land use/land cover changes on the surface temperature distribution. Land cover maps, land surface temperature and area of land cover changes will be obtained as the result of the system.
How to cite this article:
Thett Oo Eain, Htet Ne Oo, Hnin Hnin Htun and Aye Pwint Phyu. Analysis of forest cover change detection (Remote Sensing and GIS) case area of pyin oo Lwin Township. 2018; 7(1S): 444-448.