Preliminary assessment on sustainable mountain environment using multi temporal and multi spectral landsat data: a case study of naungmon township, Putao District, Kachin state, Myanmar

Author ORCID Identifier

Chong Zheng:https://orcid.org/0000-0002-3681-305X

Publication Title

ACRS 2020 - 41st Asian Conference on Remote Sensing

ISBN

9781713829089

Document Type

Conference Proceeding

Abstract

Naungmon Township is located in the northern most township of Myanmar and northern most part of Kachin State. Mount Khakaborazi and Khakaborazi National Park is situated in this study area. It is the highest peak in Myanmar (19,315 feet or 5,887 meter) always covered with snow all the year round. This park is the most northerly, biggest and highest ecotourism site in Myanmar and Southeast Asia region (3,812 square kilometers). Mountains are among the most fragile environments on the earth. The purpose of this research was to study the environmental situation of mountain environment especially changes of land cover spatially and temporally (1995 and 2019). Landsat 5 TM and Landsat 8 OLI/TIRS image data with 6 reflective bands, 30 meter spatial resolution is very excellent data source for image classification and mapping. There have four major steps for this image data analysis: image data pre-processing, image classification, accuracy assessment and chage detection analysis. In this analysis, selection of classification algorithm, training areas and post classification was done for smoothening classified image. Editing and checking was applied by using google earth and UTM maps for the validation of result. The result of satellite image analysis showing over 20 percent of vegetation disappeared within 24 years indicated the deforestation of this study area from 1995 to the year 2019. Overall accuracy of classification is estimated over 77 percent. Therefore, remote sensing is an effective method to implement the objective of this research paper. According to this method, estimate the vegetation cover with high accuracy without doing field experiments. Methodology proposed in this research provides a good solution, save in time and money for the sustainable management of mountain environment.

Publication Date

1-1-2020

Keywords

Change detection, Image classification, Pre-processing, Remote sensing, Resolution

Department

Institute for the Study of the Environment, Sustainability, and Energy (Environmental Studies); Center for Southeast Asian Studies

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