International Journal of Environmental Science and Development

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Volume 8 Number 8 (Aug. 2017)

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IJESD 2017 Vol.8(8): 539-542 ISSN: 2010-0264
doi: 10.18178/ijesd.2017.8.8.1012

Integration of GIS and Remote Sensing for Evaluating Forest Canopy Density Index in Thai Nguyen Province, Vietnam

Duong Thi Loi, Tien-Yin Chou, and Yao-Min Fang
Abstract—Forests are an indispensable part of the natural environment and play a critical role in sustainable development. However, natural forests are being destroyed every year by human activities. Hence, forest management plays a critical role in the sustainable development. Forest canopy density (FCD) is a useful model to evaluate the forest status and changes in a certain period. The advanced vegetation (AVI), bare soil (BI) and canopy shadow (SI) are selected as parameters to study FCD. These parameters are figured out from satellite images. Landsat 8 OLI image - 2015 is first normalized and then manipulated in ENVI and ArcGIS software to calculate the FCD. The overall accuracy of classification result in comparison with the land cover map is 85.3%. The final result shows the distribution of forest canopy density in the study area, consists of dense forest density, moderate forest density, low forest density and non-forest.

Index Terms—Forest canopy density, advanced vegetation, bare soil, remote sensing.

Duong Thi Loi is with the GIS Research Centre, Feng Chia University, Taiwan. She is also with Hanoi National University of Education, Vietnam (e-mail: duongloi1710@ gmail.com).
Tien-Yin Chou and Yao-Min Fang are with GIS Research Centre, Feng Chia University, Taiwan (e-mail: jimmy@gis.tw, frankfang@gis.tw).

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Cite: Duong Thi Loi, Tien-Yin Chou, and Yao-Min Fang, "Integration of GIS and Remote Sensing for Evaluating Forest Canopy Density Index in Thai Nguyen Province, Vietnam," International Journal of Environmental Science and Development vol. 8, no. 8, pp. 539-542, 2017.