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  1. Technological University, Hmawbi
  1. Technological University, Hmawbi
  2. Department of Civil Engineering

Land Use and Land Cover Change Detection Using Remote Sensing and GIS Techniques: A Case Study of Belin Township in Thatone District

http://hdl.handle.net/20.500.12678/0000007834
http://hdl.handle.net/20.500.12678/0000007834
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4bf5039a-3bc1-49b8-85c0-61e3ca5cdb4c
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Ba Ba Nyar Oo (CE -2), Civil, TU ( Thanlyin ), Nov 7-8, 2019, P 109-113.pdf (401 KB)
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Publication type
Conference paper
Upload type
Publication
Title
Title Land Use and Land Cover Change Detection Using Remote Sensing and GIS Techniques: A Case Study of Belin Township in Thatone District
Language en
Publication date 2019-11-07
Authors
Ba Nyar Oo
Khin Phyu Phyu Aung
Khin Phyu Phyu Aung
Description
Nowadays, land use and land cover (LULC) changes due to both human beings and natural environment. Consequently, LULC changes impact on water resources such as forestry, water bodies, agriculture land, wetland, urbanization, industrialization and so on. The aim of this research is to detect LULC changes in Belin Township. ERDAS IMAGINE 2015 and ArcGIS 10.4.1 have been used to analyze the images processing and classification. LULC conditions of this area for the time periods 1999, 2009 and 2018 have been considered and downloaded from Landsat ETM+ satellites images. Maximum likelihood method has been conducted in supervised image classification technique. The ground truth data or reference points are used to classify the image classification applying Google Earth Pro. Moreover, forest, settlement, water bodies, agriculture and bare land of five LULC classes are identified in this study. Bare land and Settlement are significantly unchanged during two decades. Further, forest area was increased approximately 22.36% between 1999 and 2018. However, the water bodies of this study area were decreased slightly. LULC by agriculture land was decreased between 1999 and 2018. The finding results of this research paper can contribute effectively about LULC change detection and help decision makers to develop plan in this study area.
Keywords
LULC, Remote Sensing, GIS, Change Detection, Image Classification
Identifier ISBN 978-99971-0-733-6
Conference papers
2019-11-7-8
The 2nd International Conference on Engineering Education and Innovation, November 7-8, 2019, Myanmar
Room- 1, Technological University ( Hmawbi ), Yangon, Myanmar
Session 1
www.hbtu.edu.mm
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