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
  • [41] A NEW METHOD FOR CHANGE ANALYSIS OF MULTI-TEMPORAL HYPERSPECTRAL IMAGES
    Du, Qian
    2012 4TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING (WHISPERS), 2012,
  • [42] Change vector analysis method for inundation change detection using multi-temporal multi-polarized SAR images
    Shen, Guozhuang
    Guo, Huadong
    Liao, Jingjuan
    REMOTE SENSING AND GIS DATA PROCESSING AND APPLICATIONS; AND INNOVATIVE MULTISPECTRAL TECHNOLOGY AND APPLICATIONS, PTS 1 AND 2, 2007, 6790
  • [43] CHANGENET: MULTI-TEMPORAL ASYMMETRIC CHANGE DETECTION DATASET
    Ji, Deyi
    Gao, Siqi
    Tao, Mingyuan
    Lu, Hongtao
    Zhao, Feng
    2024 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, ICASSP 2024, 2024, : 2725 - 2729
  • [44] METHODS FOR MONITORING THE DETECTION OF MULTI-TEMPORAL LAND USE CHANGE THROUGH THE CLASSIFICATION OF URBAN AREAS
    Alhaddad, B. I.
    Burns, M. C.
    Roca, J.
    28TH URBAN DATA MANAGEMENT SYMPOSIUM, 2011, 38-4 (C21): : 83 - 88
  • [45] An adaptive multiplicative decomposition of non stationary multi-temporal satellite images: Application to urban changes detection
    Ben Abbes, Ali
    Essid, Houcine
    Farah, Imed Riadh
    Barra, Vincent
    2014 FIRST INTERNATIONAL IMAGE PROCESSING, APPLICATIONS AND SYSTEMS CONFERENCE (IPAS), 2014,
  • [46] Development and Application of Multi-Temporal Colorimetric Transformation to Monitor Vegetation in the Desert Locust Habitat
    Pekel, Jean-Francois
    Ceccato, Pietro
    Vancutsem, Christelle
    Cressman, Keith
    Vanbogaert, Eric
    Defourny, Pierre
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2011, 4 (02) : 318 - 326
  • [47] Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images
    Du, Bo
    Ru, Lixiang
    Wu, Chen
    Zhang, Liangpei
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2019, 57 (12): : 9976 - 9992
  • [48] Effect of climate change on the seasonal variation in photosynthetic and non-photosynthetic vegetation coverage in desert areas, Northwest China
    Bai, Xuelian
    Zhao, Wenzhi
    Luo, Weicheng
    An, Ning
    CATENA, 2024, 239
  • [49] Urban vegetation land covers change detection using multi-temporal MODIS Terra/Aqua data
    Zoran, Maria A.
    Savastru, Roxana S.
    Savastru, Dan M.
    Dida, Adrian I.
    Ionescu, Ovidiu M.
    REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XV, 2013, 8887
  • [50] A feature based change detection approach using multi-scale orientation for multi-temporal SAR images
    Vijaya Geetha, R.
    Kalaivani, S.
    EUROPEAN JOURNAL OF REMOTE SENSING, 2021, 54 (sup2) : 248 - 264