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TUP.PC: Change Detection Techniques for Multispectral and Hyperspectral Images

Session Type: Poster
Time: Tuesday, July 28, 17:20 - 19:00
Location: Poster Area C
Session Chair: Yuliya Tarabalka, INRIA
 
  TUP.PC.1: COMPARISON OF CHANGE DETECTION TECHNIQUES FOR THE YUCATAN PENINSULA USING LANDSAT IMAGE TIME SERIES
         Rene R. Colditz; National Commission for the Knowledge and Use of Biodiversity (CONABIO)
         Ricardo M. Llamas; National Commission for the Knowledge and Use of Biodiversity (CONABIO)
         Steffen Gebhardt; National Commission for the Knowledge and Use of Biodiversity (CONABIO)
         Thilo Wehrmann; National Commission for the Knowledge and Use of Biodiversity (CONABIO)
         Julian Equihua; National Commission for the Knowledge and Use of Biodiversity (CONABIO)
 
  TUP.PC.2: A NOVEL METHOD TO RECONSTRUCT NORMALIZED DIFFERENCE VEGETATION INDEX TIME SERIES BASED ON TEMPORAL-SPATIAL ITERATION ESTIMATION
         Lili Xu; University of Chinese Academy of Sciences
         Baolin Li; State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences
         Yecheng Yuan; State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences
         Tao Zhang; University of Chinese Academy of Sciences
 
  TUP.PC.3: HYPERSPECTRAL CHANGE DETECTION BY USING IR-MAD AND SYNTHETIC IMAGE FUSION
         Jaewan Choi; Chungbuk National University
         Biao Wang; Chungbuk National University
         Guhyeok Kim; Chungbuk National University
         Youkyung Han; Fondazione Bruno Kessler (FBK) / University of Trento
 
  TUP.PC.4: CHANGE DETECTION FOR HYPERSPECTRAL IMAGES BASED ON TENSOR ANALYSIS
         Zhao Chen; Fudan University
         Bin Wang; Fudan University
         Yubin Niu; Fudan University
         Wei Xia; China Transport Telecommunications & Information Center
         Jian Qiu Zhang; Fudan University
         Bo Hu; Fudan University
 
  TUP.PC.5: APPLICATION OF A SEMI-AUTOMATIC UNSUPERVISED CHANGE DETECTION TO (SEMI-) NATURAL GRASSLAND LOSS AT VERY HIGH RESOLUTION
         Cristina Tarantino; National Research Council
         Palma Blonda; National Research Council
         Maria Adamo; National Research Council
 
  TUP.PC.6: MULTI-TEMPORAL APPROACH TO ATMOSPHERIC EFFECTS COMPENSATION IN HYPERSPECTRAL IMAGE CLASSIFICATION
         Nicola Acito; Accademia Navale di Livorno - Italian Navy
         Marco Diani; University of Pisa
         Stefania Matteoli; University of Pisa
         Giovanni Corsini; University of Pisa
 
  TUP.PC.7: OBJECT-BASED FEATURE EXTRACTION AND SEMI-SUPERVISED CLASSIFICATION FOR URBAN CHANGE DETECTION USING HIGH-RESOLUTION REMOTE SENSING IMAGES
         Bin Hou; Beihang University
         Qingjie Liu; Beihang University
         Yunhong Wang; Beihang University
 
  TUP.PC.8: AUTOMATED CHANGE DETECTION IN SATELLITE IMAGES USING MACHINE LEARNING ALGORITHMS FOR DELHI, INDIA
         Abhishek Bhatt; Indian Institute of Technology Roorkee
         Sanjay Kumar Ghosh; Indian Institute of Technology Roorkee
         Anil Kumar; Indian institute of remote sensing, dehradun
 
  TUP.PC.9: DETECTING CHANGES IN HIGH RESOLUTION REMOTE SENSING IMAGES USING SUPERPIXELS
         Hui Ru; Wuhan University
         Pingping Huang; Inner Mongolia University of Technology
         Xun Sun; Wuhan University
         Yan Liu; Wuhan University
 
  TUP.PC.10: AUTOMATIC CHANGE DETECTION OF URBAN LAND-COVER BASED ON SVM CLASSIFICATION
         Wei Li; Peking University
         Miao Lu; Wuhan University
         Xiuwan Chen; Peking University