author = "Beuchle, Ren{\'e} and Raši, Rastislav and Bodart, Catherine and 
                         Vollmar, Michael and Seliger, R. and Achard, Fr{\'e}d{\'e}ric",
                title = "Updating an object-based pan-tropical forest cover change 
                         assessment by automatic change detection and classification",
            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 = "332--337",
         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 = "Global Forestry, Landsat, Object-based Change Detection, 
                         Classification, Segmentation, Sampling.",
             abstract = "The TREES-3 project of the European Commission\‟s Joint 
                         Research Centre is producing estimates of tropical forest cover 
                         changes during the period 1990 to 2010. Three reference years are 
                         considered: 1990, 2000 and 2010. This paper presents the method 
                         developed for the automatic processing of year 2010 with the 
                         assessment of performance of this method. The processing of 
                         imagery of year 2010 includes automatic segmentation, change 
                         detection and object spectral classification. The validated maps 
                         of forest cover changes for the period 1990-2000 are used as 
                         thematic input layer into the segmentation and classification 
                         process of the year 2010 images. Object-based change detection 
                         (OBCD) technique is applied using Tasselled Cap (TCap) parameters 
                         and spectral Euclidian Distances (ED). Objects detected as changed 
                         are classified by change vector analysis. The segmentation 
                         approach was tested on a subsample of 568 sample units over 
                         Brazil. The segmentation results for year 2010 are consistent with 
                         segmentation of imagery for the period 1990-2000, the segmentation 
                         statistics (number of objects, average objects size, average 
                         number of objects per sample site) remain stable between the two 
                         approaches. A two-step method of (a) change detection and (b) 
                         classification of changed objects was developed on basis of 
                         thresholding TCap variance and Euclidian Distance. The approach 
                         was tested over 281 sample units in the Brazilian biome of the 
                         Amazon, for which validated land cover information for the year 
                         2010 was already available. The resulting overall accuracy of 
                         classification for the 281 sample units was 92.2%.",
  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/3BT7KBE",
                  url = "http://urlib.net/rep/8JMKD3MGP8W/3BT7KBE",
           targetfile = "095.pdf",
                 type = "Forest Analysis",
        urlaccessdate = "25 jan. 2021"