A New Approach for Vegetation Change Detection in Urban Areas

被引:1
|
作者
Yu Hui [1 ]
Jia Yonghong [1 ]
机构
[1] Wuhan Univ, Sch Remote Sensing & Informat Engn, 129 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China
关键词
vegetation; change detection; change vector; mask;
D O I
10.1007/BF02826744
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Because of complex change in urban areas, modified CVA application based on mask techniques can minify the effect of non-vegetation changes and improve upon efficiency to a great extent. Moreover, drawing from methods in polar plots, the technique measures changes with absolute angular and total magnitude of PVI calculated on the basis of linear fit with least-square estimation and GVI calculated using 3D G-S transformation. Finally, this application is performed with Landsat ETM+ imageries of Wuhan in 2002 and 2005, and assessed by error matrix, in the way it could detect change pixels 94.91% correct, and the total consistent coefficient Kappa could reach to 0.85. The evaluation result demonstrates this new application trends as an efficient and effective alternative to urban vegetation change extraction.
引用
收藏
页码:298 / 305
页数:8
相关论文
共 50 条
  • [1] A New Approach for Vegetation Change Detection in Urban Areas
    YU Hui JIA Yonghong
    Geo-Spatial Information Science, 2006, (04) : 298 - 305
  • [2] Vegetation change detection for urban areas based on extended change vector analysis
    Yu Hai
    Jia Yonghong
    GEOINFORMATICS 2006: REMOTELY SENSED DATA AND INFORMATION, 2006, 6419
  • [3] Using Vegetation Indices to Characterize Vegetation Cover Change in the Urban Areas of Southern China
    Zhang, Yu
    Wang, Pengcheng
    Wang, Tianwei
    Li, Jingwei
    Li, Zhaoxia
    Teng, Mingjun
    Gao, Yunbing
    SUSTAINABILITY, 2020, 12 (22) : 1 - 18
  • [4] Tree segmentation and change detection of large urban areas based on airborne LiDAR
    Fekete, Anett
    Cserep, Mate
    COMPUTERS & GEOSCIENCES, 2021, 156
  • [5] Fusion of Difference Images for Change Detection Over Urban Areas
    Du, Peijun
    Liu, Sicong
    Gamba, Paolo
    Tan, Kun
    Xia, Junshi
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2012, 5 (04) : 1076 - 1086
  • [6] Change Detection Based on DSM and Image Features in Urban Areas
    LIU Zhifang ZHANG Jianqing ZHANG Zuxun FAN Hong LIU Zhifang
    Geo-Spatial Information Science, 2003, (02) : 35 - 41
  • [7] Change Detection in Peri-urban Areas Based on Contextual Classification
    Hermosilla, Txomin
    Gil-Yepes, Jose L.
    Recio, Jorge A.
    Ruiz, Luis A.
    PHOTOGRAMMETRIE FERNERKUNDUNG GEOINFORMATION, 2012, (04): : 359 - 370
  • [8] Change detection in urban landscapes: a tensor factorization approach
    S. Saritha
    G. Santhosh Kumar
    Spatial Information Research, 2019, 27 : 587 - 600
  • [9] Change detection in urban landscapes: a tensor factorization approach
    Saritha, S.
    Santhosh Kumar, G.
    SPATIAL INFORMATION RESEARCH, 2019, 27 (05) : 587 - 600
  • [10] LWIR Hyperspectral Change Detection for Target Acquisition and Situation Awareness in Urban Areas
    Dekker, Rob J.
    Schwering, Piet B. W.
    Benoist, Koen W.
    Pignatti, Stefano
    Santini, Federico
    Friman, Ola
    ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIX, 2013, 8743