@InProceedings{StaplesKoGrChGrGo:2017:DeVaFo,
               author = "Staples, Gordon C and Kooij, Marco W van der and Green, Graham R 
                         and Chen, Ji K and Gravelle, Shane I and Goodenough, David T",
                title = "Detection and validation of forest disturbances using RADARSAT-2 
                         data",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "7946--7953",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "RADARSAT 2 SAR data was used to develop a monitoring program for 
                         Canadian forest lands with the aim to provide information on 
                         forest harvesting. A study site in British Columbia, Canada, 
                         characterized by coniferous forest, was selected. RADARSAT-2 
                         MultiLook Fine mode, acquired from mid-June through mid-September, 
                         from 2011 to 2015 was analyzed with the aim to detect forest 
                         disturbances. Due to large data volumes and the need for 
                         efficiency, an automated end-to-end solution was implemented. The 
                         automated solution included image coregistration, temporal 
                         filtering, detection of forest disturbances, and delineation of 
                         the disturbances. To reduce the detection of false positives, a 
                         non-forest mask was developed that entailed a combination of 
                         CanVec data that delineated areas such as water bodies, roads, and 
                         urban/industrial areas and SAR-derived information such as layover 
                         and scattering from urban areas. To assess the performance of the 
                         change detection algorithm, the RADARSAT-2 changes were compared 
                         to tree-loss information from the Canadian Forest Service (CFS) 
                         and cut-block information from the BC Forest Service (BCFS). Since 
                         CFS and the BCFS information was representative of annual changes, 
                         but the RADARSAT-2 derived changes were representative of 
                         summer-only changes, there were discrepancies between the 
                         RADARSAT-2 data and the CFS/BCFS data. Notwithstanding these 
                         discrepancies, the detection performance was better than 80% for 
                         2011/12 and 2012/13. For 2013/15, however, due to the two-year gap 
                         between data acquisition, the detection performance was 74%.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59485",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMGMD",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMGMD",
           targetfile = "59485.pdf",
                 type = "Degrada{\c{c}}{\~a}o de florestas",
        urlaccessdate = "27 abr. 2024"
}