@InProceedings{SeijmonsbergenAndeBout:2012:GeChDe,
               author = "Seijmonsbergen, Arie C. and Anders, Niels S. and Bouten, Willem",
                title = "Geomorphological change detection using object-based feature 
                         extraction from multi-temporal LiDAR data",
            booktitle = "Proceedings...",
                 year = "2012",
               editor = "Feitosa, Raul Queiroz and Costa, Gilson Alexandre Ostwald Pedro da 
                         and Almeida, Cl{\'a}udia Maria de and Fonseca, Leila Maria Garcia 
                         and Kux, Hermann Johann Heinrich",
                pages = "484--489",
         organization = "International Conference on Geographic Object-Based Image 
                         Analysis, 4. (GEOBIA).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Geomorphology, LIDAR, Multi-temporal, Change Detection, 
                         Classification, Segmentation.",
             abstract = "Multi-temporal LiDAR DTMs are used for the development and testing 
                         of a method for geomorphological change analysis in western 
                         Austria. Our test area is located on a mountain slope in the 
                         Gargellen Valley in western Austria. Six geomorphological features 
                         were mapped by using stratified Object-Based Image Analysis (OBIA) 
                         and segmentation optimization using 1m LiDAR DTMs of 2002 and 
                         2005. Based on the 2002 data, the scale parameter for each 
                         geomorphological feature was optimized by comparing manually 
                         digitized training samples with automatically recognized image 
                         objects. Classification rule sets were developed to extract the 
                         feature types of interest. The segmentation and classification 
                         settings were then applied to both LiDAR DTMs which allowed the 
                         detection of geomorphological change between 2002 and 2005. 
                         FROM-TO changes of geomorphological categories were calculated and 
                         linked to volumetric changes which were derived from the 
                         subtracted DTMs. Enlargement of mass movement areas at the cost of 
                         glacial eroded bedrock was detected, although most changes 
                         occurred within mass movement categories and channel incisions, as 
                         the result of material removal and/or deposition. The proposed 
                         method seems applicable for geomorphological change detection in 
                         mountain areas. In order to improve change detection results, 
                         processing errors and noise that negatively influence the 
                         segmentation accuracy need to be reduced. Despite these concerns, 
                         we conclude that stratified OBIA applied to multi-temporal LiDAR 
                         datasets is a promising tool for of geomorphological change 
                         detection.",
  conference-location = "Rio de Janeiro",
      conference-year = "May 7-9, 2012",
                 isbn = "978-85-17-00059-1",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP8W/3BSRQ45",
                  url = "http://urlib.net/ibi/8JMKD3MGP8W/3BSRQ45",
           targetfile = "130.pdf",
                 type = "Change Detection",
        urlaccessdate = "30 abr. 2024"
}