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		<isbn>978-85-17-00088-1</isbn>
		<label>59485</label>
		<citationkey>StaplesKoGrChGrGo:2017:DeVaFo</citationkey>
		<title>Detection and validation of forest disturbances using RADARSAT-2 data</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
		<numberoffiles>1</numberoffiles>
		<size>532 KiB</size>
		<author>Staples, Gordon C,</author>
		<author>Kooij, Marco W van der,</author>
		<author>Green, Graham R,</author>
		<author>Chen, Ji K,</author>
		<author>Gravelle, Shane I,</author>
		<author>Goodenough, David T,</author>
		<electronicmailaddress>gstaples@mda.ca</electronicmailaddress>
		<editor>Gherardi, Douglas Francisco Marcolino,</editor>
		<editor>Aragão, Luiz Eduardo Oliveira e Cruz de,</editor>
		<e-mailaddress>daniela.seki@inpe.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)</conferencename>
		<conferencelocation>Santos</conferencelocation>
		<date>28-31 maio 2017</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>7946-7953</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<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%.</abstract>
		<area>SRE</area>
		<type>Degradação de florestas</type>
		<language>en</language>
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