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FOREST RESOURCES WANAGEMENT ›› 2018›› Issue (3): 113-120.doi: 10.13466/j.cnki.lyzygl.2018.03.020

• Technical Application • Previous Articles     Next Articles

Design of Annual National Forest Resources Remote Sensing Monitoring System in Southeast Asia Countries—Taking Indonesia as an Example

LIU Qian1(), ZHANG Yuxing1(), WANG Xuejun1, WANG Shaojie2, YANG Ying1, I Nengah Suratijaya3, Dewayany Sutrisno4, Ita Carolita5   

  1. 1. Academy of Forest Inventory and Planning,SFA,Beijing 100714,China
    2. College of Forestry,Beijing Forestry University,Beijing 100083,China
    3. Faculty of Forestry,Bogor Agriculture University,Bogor,Indonesia
    4. Indonesian Society For Remote Sensing,Jakarta,Indonesia
    5. Indonesian National Institute of Aeronautics and Space,Jakarta,Indonesia
  • Received:2018-01-12 Revised:2018-06-11 Online:2018-06-28 Published:2020-09-20
  • Contact: ZHANG Yuxing E-mail:liuqian2@yahoo.com;zhangyuxing212@163.com

Abstract:

Based on 30m global land cover data in 2010 (GlobalLand30),145 and 604 grids are laid separately within Indonesia at 1°×1° and 0.5°×0.5° interval respectively.The coefficient of variation and precision of estimated forest area for 10 different size of plots by two different grid spacing are compared and analyzed.The optimized remote sensing large plots layout in Indonesia is selected based on analysis results.Meanwhile,ground survey plots are established to conduct precision verification.The result shows:1) large plot with the size of 4km×4km at 0.5°×0.5° spacing interval is the optimized sampling plan with consideration of coefficient of variation and precision as well as workload.2) taking Kalimantan Indonesia part as the demonstration site to verify the precision of forest area derived from the large plots layout.The verificaion result shows that the average precision of forest area monitoring is 94.89% using 0.5°×0.5° grid interval and 4km×4km design.The precision meets the national and regional requirement on forest area monitoring.

Key words: Indonesia, plot layout, coefficient of variation, sampling precision, forest resources monitoring

CLC Number: