Detection of change in vegetation in the surrounding Desert areas of Northwest China and Mongolia with multi-temporal satellite images

被引:12
|
作者
Han, Kyung-Soo [1 ]
Park, Youn-Young [1 ]
Yeom, Jong-Min [2 ]
机构
[1] Pukyong Natl Univ, Dept Geog Engn, Busan, South Korea
[2] Korea Aerosp Res Inst, Taejon 305806, South Korea
关键词
Change detection; desertification; land-cover; NDVI; SPOT Vegetation;
D O I
10.1007/s13143-015-0068-3
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Vegetation monitoring is an important step in developing a better understanding of land use and its changes, due to the sensitivity of surface vegetation to changes in the global climate and environment. In this study, normalized difference vegetation index (NDVI) of the area surrounding the Gobi Desert in North Asia was multi-temporally interpreted by analyzing time-series Satellite Pour l'Observation de la Terre (SPOT) Vegetation (VGT) data, over a roughly nine-year period from January 1999 to November 2007. The study area was classified into eight classes, and compared to classified Moderate resolution Imaging Spectrometer (MODIS) global land-cover data to select desertification-sensitive areas. The study focused on three classes (barren land, open shrubland, grassland) due to their high sensitivity to climate change. The results showed significant extension of the barren land class from 1992 to 1999, with 47.8% of the open shrubland transformed into barren land. Among five terms (1999-2003, 2003-2005, 2005-2007, 1999-2005, 1999-2007) which are carefully selected from variations of the annual NDVI mean for each class over nine years, significant changes were observed for barren land from 1999-2003, and for open shrubland and grassland from 2005-2007. An analysis of the positive change (the change from sparse vegetation to dense vegetation) and negative change (or desertification) was conducted over the study period; the number of pixels corresponding to a positive change for barren land was similar to the number of negative change pixels. Human activity and afforestation over the study area were also captured in multitemporal satellite imagery. For open shrubland and grassland, the negative change area was bigger than the positive change area. Precipitation data over the nine-year period exhibited a pattern similar to that for the vegetation data, as expected.
引用
收藏
页码:173 / 181
页数:9
相关论文
共 50 条
  • [1] Detection of change in vegetation in the surrounding Desert areas of Northwest China and Mongolia with multi-temporal satellite images
    Kyung-Soo Han
    Youn-Young Park
    Jong-Min Yeom
    Asia-Pacific Journal of Atmospheric Sciences, 2015, 51 : 173 - 181
  • [2] Multi-temporal Satellite Images Change Detection Algorithm Based on NSCT
    Cui, Wei
    Jia, Zhenhong
    Qin, Xizhong
    Yang, Jie
    Hu, Yingjie
    INTERNATIONAL CONFERENCE ON ADVANCES IN ENGINEERING 2011, 2011, 24 : 252 - 256
  • [3] SEMANTIC INTERPRETATION OF MULTI-LEVEL CHANGE DETECTION IN MULTI-TEMPORAL SATELLITE IMAGES
    Radoi, A.
    Tanase, R.
    Datcu, M.
    2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2015, : 4157 - 4160
  • [4] MULTI-TEMPORAL CHANGE DETECTION BASED ON CHINA'S DOMESTIC HYPERSPECTRAL REMOTE SENSING SATELLITE IMAGES
    Lu, Xuanning
    Liu, Sicong
    Du, Kechen
    IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING XXVIII, 2022, 12267
  • [5] Change detection in multi-temporal satellite images based on spatial segmentation and gray analysis
    Center of Technology Development, Southwest China Institute of Electronic Technology, Chengdu 610036, China
    J. Inf. Comput. Sci., 2008, 1 (57-62):
  • [6] Change Detection Method with Multi-temporal Satellite Images based on Wavelet Decomposition and Tiling
    Arai, Kohei
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2021, 12 (03) : 56 - 61
  • [7] Change Detection-aided Single Linear Prediction of Multi-temporal Satellite Images
    Al Mamun, Md
    Mondal, Md Nazrul Islam
    Ahmed, Boshir
    2014 17TH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY (ICCIT), 2014, : 332 - 335
  • [8] UNSUPERVISED CHANGE DETECTION IN BUILT-UP AREAS BY MULTI-TEMPORAL POLARIMETRIC SAR IMAGES
    Pirrone, Davide
    De, Shaunak
    Bhattacharya, Avik
    Bruzzone, Lorenzo
    Bovolo, Francesca
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 4554 - 4557
  • [9] A SWIR-based vegetation index for change detection in land cover using multi-temporal Landsat satellite dataset
    Kumar S.
    Arya S.
    Jain K.
    International Journal of Information Technology, 2022, 14 (4) : 2035 - 2048
  • [10] Forecasting of Cyclone Using Multi-temporal Change Detected Satellite Images
    David, D. Beulah
    DoraiRangaswamy, Dr.
    2014 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (IEEE ICCIC), 2014, : 148 - 153