| 1. Identificação | |
| Tipo de Referência | Artigo em Revista Científica (Journal Article) |
| Site | mtc-m16.sid.inpe.br |
| Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identificador | 6qtX3pFwXQZ3r59YDa/Jy2p8 |
| Repositório | sid.inpe.br/iris@1916/2005/12.23.18.08 |
| Última Atualização | 2014:04.30.14.52.02 (UTC) marciana |
| Repositório de Metadados | sid.inpe.br/iris@1916/2005/12.23.18.08.30 |
| Última Atualização dos Metadados | 2018:06.05.01.16.42 (UTC) administrator |
| Chave Secundária | INPE--PRE/ |
| ISSN | 1087-3562 |
| Chave de Citação | MortonDeShAnEsHaCa:2005:RaAsAn |
| Título | Rapid assessment of annual deforestation in the Brazilian Amazon using MODIS data  |
| Ano | 2005 |
| Data de Acesso | 03 maio 2024 |
| Tipo de Trabalho | journal article |
| Tipo Secundário | PRE PI |
| Número de Arquivos | 1 |
| Tamanho | 321 KiB |
| 2. Contextualização | |
| Autor | 1 Morton, Douglas C. 2 DeFries, Ruth S. 3 Shimabukuro, Yosio Edemir 4 Anderson, Liana O. 5 Espírito-Santo, Fernando Del Bon 6 Hansen, Matthew 7 Carroll, Mark |
| Grupo | 1 2 3 DSR-INPE-MCT-BR |
| Afiliação | 1 University of Maryland 2 University of Maryland 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE) 5 Instituto Nacional de Pesquisas Espaciais (INPE) 6 South Dakota State University 7 University of Maryland |
| Endereço de e-Mail do Autor | 1 morton@geog.umd.edu 2 3 yosio@ltid.inpe.br |
| Revista | Earth Interactions |
| Volume | 9 |
| Número | 8 |
| Páginas | 1-22 |
| Histórico (UTC) | 2005-12-23 18:10:06 :: marciana -> administrator :: 2013-11-15 09:30:37 :: administrator -> marciana :: 2005 2014-04-30 14:52:05 :: marciana -> administrator :: 2005 2018-06-05 01:16:42 :: administrator -> :: 2005 |
| 3. Conteúdo e estrutura | |
| É a matriz ou uma cópia? | é a matriz |
| Estágio do Conteúdo | concluido |
| Transferível | 1 |
| Tipo do Conteúdo | External Contribution |
| Tipo de Versão | publisher |
| Palavras-Chave | deforestation Amazon MODIS remote sensing Brazil |
| Resumo | The Brazilian government annually assesses the extent of deforestation in the Legal Amazon for a variety of scientific and policy applications. Currently, the assessment requires the processing and storing of large volumes of Landsat satellite data. The potential for efficient, accurate, and less data-intensive assessment of annual deforestation using data from NASAs Moderate Resolution Imaging Spectroradiometer (MODIS) at 250-m resolution is evaluated. Landsat-derived deforestation estimates are compared to MODIS-derived estimates for six Landsat scenes with five change-detection algorithms and a variety of input dataSurface Reflectance (MOD09), Vegetation Indices (MOD13), fraction images derived from a linear mixing model, Vegetation Cover Conversion (MOD44A), and percent tree cover from the Vegetation Continuous Fields (MOD44B) product. Several algorithms generated consistently low commission errors (positive predictive value near 90%) and identified more than 80% of deforestation polygons larger than 3 ha. All methods accurately identified polygons larger than 20 ha. However, no method consistently detected a high percent of Landsat-derived deforestation area across all six scenes. Field validation in central Mato Grosso confirmed that all MODIS-derived deforestation clusters larger than three 250-m pixels were true deforestation. Application of this field-validated method to the state of Mato Grosso for 200104 highlighted a change in deforestation dynamics; the number of large clusters (>10 MODIS pixels) that were detected doubled, from 750 between August 2001 and August 2002 to over 1500 between August 2003 and August 2004. These analyses demonstrate that MODIS data are appropriate for rapid identification of the location of deforestation areas and trends in deforestation dynamics with greatly reduced storage and processing requirements compared to Landsat-derived assessments. However, the MODIS-based analyses evaluated in this study are not a replacement for high-resolution analyses that estimate the total area of deforestation and identify small clearings. |
| Área | SRE |
| Arranjo | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Rapid assessment of... |
| Conteúdo da Pasta doc | acessar |
| Conteúdo da Pasta source | não têm arquivos |
| Conteúdo da Pasta agreement | não têm arquivos |
| 4. Condições de acesso e uso | |
| URL dos dados | http://urlib.net/ibi/6qtX3pFwXQZ3r59YDa/Jy2p8 |
| URL dos dados zipados | http://urlib.net/zip/6qtX3pFwXQZ3r59YDa/Jy2p8 |
| Idioma | en |
| Arquivo Alvo | 18417721.pdf |
| Grupo de Usuários | administrator marciana |
| Grupo de Leitores | administrator marciana |
| Visibilidade | shown |
| Política de Arquivamento | denypublisher6 allowfinaldraft |
| Permissão de Atualização | não transferida |
| 5. Fontes relacionadas | |
| Unidades Imediatamente Superiores | 8JMKD3MGPCW/3ER446E |
| Divulgação | WEBSCI; PORTALCAPES; MGA. |
| Acervo Hospedeiro | sid.inpe.br/banon/2003/08.15.17.40 |
| 6. Notas | |
| Campos Vazios | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel doi e-mailaddress format isbn label lineage mark mirrorrepository month nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readpermission resumeid rightsholder schedulinginformation secondarydate secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url |