DETECTION OF FOREST DISTURBANCE IN THE GREATER HINGGAN MOUNTAIN OF CHINA BASED ON LANDSAT TIME-SERIES DATA

被引：5
|
作者：
Chen, Wei [1 ]
Sakai, Tetsuro [1 ]
Cao, Chunxiang
Moriya, Kazuyuki [1 ]
Koyama, Lina [1 ]
机构：
[1] Kyoto Univ, Biosphere Informat Lab, Dept Social Informat, Grad Sch Informat, Kyoto 6068501, Japan
来源：
2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2012年
关键词：
Forest disturbance; Remote Sensing; Landsat images; Time-series; Disturbance index; TASSELED CAP;
D O I：
10.1109/IGARSS.2012.6351993
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The detection of forest disturbance, as a key process in monitoring terrestrial ecosystems, has been regarded as an effective approach for indicating the effect of various factors on biological communities. With the advancement of remote sensing technology in large-scale ecology research, we had developed a proposal to detect the change of forest community disturbance in the Greater Hinggan Mountain area of Northeast China using time-series remote sensing data. Firstly, four scenes of Landsat images from four periods of 1990-era, 2000-era, 2005-era and 2010-era were selected and pre-processed. Then, based on the Tasseled Cap transformation, the disturbance index (DI) was calculated and finally the resulting disturbance situations from different periods were analyzed. These results provided significant information on the monitoring and management of local forest.
引用
收藏
页码：7232 / 7235
页数：4
相关论文
共 50 条
  • [1] EXTRACTION OF BURNED FOREST AREA IN THE GREATER HINGGAN MOUNTAIN OF CHINA BASED ON LANDSAT TM DATA
    Chen, Wei
    Sakai, Tetsuro
    Moriya, Kazuyuki
    Koyama, Lina
    Cao, Chunxiang
    [J]. 2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2013, : 995 - 998
  • [2] Forest Disturbance Monitoring Based on Time Series of Landsat Data
    Zhong, Li
    Chen, Yunzhi
    Wang, Xiaoqin
    [J]. Linye Kexue/Scientia Silvae Sinicae, 2020, 56 (05): : 80 - 88
  • [3] Extraction of Forest Disturbance Parameters and Estimation of Forest Height Based on Long Time-Series Landsat
    Mao, Xuegang
    Yao, Yao
    Fan, Wenyi
    [J]. Linye Kexue/Scientia Silvae Sinicae, 2019, 55 (03): : 79 - 87
  • [4] An autoencoder-based model for forest disturbance detection using Landsat time series data
    Zhou, Gaoxiang
    Liu, Ming
    Liu, Xiangnan
    [J]. INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2021, 14 (09) : 1087 - 1102
  • [5] Forest Disturbance Mapping Using Dense Synthetic Landsat/MODIS Time-Series and Permutation-Based Disturbance Index Detection
    Frantz, David
    Roeder, Achim
    Udelhoven, Thomas
    Schmidt, Michael
    [J]. REMOTE SENSING, 2016, 8 (04)
  • [6] MAPPING FOREST DISTURBANCE TYPES IN CHINA WITH LANDSAT TIME SERIES
    Huo, Lian-Zhi
    Tang, Ping
    [J]. IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 3086 - 3089
  • [7] Examining Forest Disturbance and Recovery in the Subtropical Forest Region of Zhejiang Province Using Landsat Time-Series Data
    Liu, Shanshan
    Wei, Xinliang
    Li, Dengqiu
    Lu, Dengsheng
    [J]. REMOTE SENSING, 2017, 9 (05)
  • [8] Forest Age Mapping Using Landsat Time-Series Stacks Data Based on Forest Disturbance and Empirical Relationships between Age and Height
    Tian, Lei
    Liao, Longtao
    Tao, Yu
    Wu, Xiaocan
    Li, Mingyang
    [J]. REMOTE SENSING, 2023, 15 (11)
  • [9] An Automated Approach to Map the History of Forest Disturbance from Insect Mortality and Harvest with Landsat Time-Series Data
    Neigh, Christopher S. R.
    Bolton, Douglas K.
    Diabate, Mouhamad
    Williams, Jennifer J.
    Carvalhais, Nuno
    [J]. REMOTE SENSING, 2014, 6 (04) : 2782 - 2808
  • [10] Detecting and Attributing Drivers of Forest Disturbance in the Colombian Andes Using Landsat Time-Series
    Murillo-Sandoval, Paulo J.
    Hilker, Thomas
    Krawchuk, Meg A.
    Van Den Hoek, Jamon
    [J]. FORESTS, 2018, 9 (05):
12345