Journal cover Journal topic
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Volume 2
Abstr. Int. Cartogr. Assoc., 2, 23, 2020
https://doi.org/10.5194/ica-abs-2-23-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Abstr. Int. Cartogr. Assoc., 2, 23, 2020
https://doi.org/10.5194/ica-abs-2-23-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  08 Oct 2020

08 Oct 2020

Predicting Forest Change in Phu Phan National Park, Thailand Using Multi-Temporal Landsat Satellite Images

Jaturong Som-ard1,2, Savittri Ratanopad Suwanlee1,2, Worawit Jitsukka1,2, and Komin Cheunbanyen2 Jaturong Som-ard et al.
  • 1Department of Geography, Faculty of Humanities and Social Sciences, Mahasarakham University, Maha Sarakham Province, 44150, Thailand
  • 2Geography, Geoinformatics and Resources Management Research Unit, Faculty of Humanities and Social Sciences, Mahasarakham University, Maha Sarakham Province, 44150, Thailand

Keywords: predicting forest change, land use change, OBIA, Phu Phan national park

Abstract. The Royal Forest Department of Thailand has permitted people to use the resources in national parks since 2005. It leads to a decrease in forest areas. This study aims to monitor and predict forest land change in Phu Phan National Park using Landsat 5 TM images in 1998 and 2008, and Sentinel-2 MSI image in 2018. The atmosphere correction was conducted for satellite images. Land use changes were classified by object base image analysis (OBIA), include forest, agriculture, built-up, water and miscellaneous. The land use maps were measured, and then the CA-Markov model was applied to predict the forest change in a year of 2028. The results demonstrate that overall accuracy (OA) of land use maps is 85.6%, 88%, and 89.6% in 1998, 2008 and 2018, respectively. The land use map in 2018 is more accurate than others because the high-resolution image and current data input. Moreover, the use of reference data nowadays has high potential and reality for classification. During 1998 to 2008, forest and built-up extended 45.35% and 5.07%, respectively. Meanwhile, miscellaneous, agriculture, and water decreased by 41.38%, 21.92%, and 3.45%. During 2008 to 2018, agriculture, miscellaneous, and built-up slightly increased by 21.92%, 14.75%, and 12.26%, respectively while forest and water decreased by 48.82% and 2.24%, respectively. The predicted forest change in 2028 is a decrease by 10.49% due to land use change to miscellaneous, agriculture, built-up, and water area, as forest is likely to be trespassed for built-up and agriculture areas as a result of local population growth. The results of the study can be useful for planning and managing the national park in the future.

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