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@InProceedings{MelloMSSDSBSP:2002:ExBrMa,
               author = "Mello, Eliana Maria Kalil and Moreira, Jos{\'e} Carlos and 
                         Santos, Jo{\~a}o roberto dos and Shimabukuro, Yosio Edemir and 
                         Duarte, Valdete and Souza, Iris de Marcelhas e and Barbosa, 
                         Claudio Clemente and Souza, Ricardo Cartaxo Modesto de and Paiva, 
                         Jo{\~a}o Argemiro de Carvalho",
                title = "Prodes digital: experiencia brasileira no mapeamento automatizado 
                         do desflorestamento da Amaz{\^o}nia",
            booktitle = "Proceedings...",
                 year = "2002",
         organization = "Simp{\'o}sio Latino-Americano de Percepcion Remota Y Sistemas de 
                         Information Espacial, 10; Reunion Plenaria de SELPER, 21.",
             keywords = "ESTUDOS INTEGRADOS DO MEIO AMBIENTE, deforestation, Amazon, land 
                         use, land cover, dynamics, Geographic Information Systems, linear 
                         spectral mixing model, image segmentation, image classification.",
             abstract = "O INPE - Instituto Nacional de Pesquisas Espaciais, promove, 
                         atrav{\'e}s do projeto PRODES, a interpreta{\c{c}}{\~a}o de 
                         imagens do Sensor TM (Thematic Mapper)do sat{\'e}lite Americano 
                         Landsat, tendo como objetivo acompanhar a evolu{\c{c}}{\~a}o do 
                         desflorestamento bruto da Amaz{\^o}nia Legal, inicialmente 
                         utilizando o software SGI - Sistema Geogr{\'a}fico de 
                         Informa{\c{c}}{\~o}es e posteriormente o SPRING - Sistema de 
                         Processamento de Informa{\c{c}}{\~o}es Georrefer{\^e}nciadas 
                         (INPE-DPI, 2002), desenvolvidos pelo INPE. A partir de 1994 os 
                         pesquisadores e engenheiros da OBT- Coordenadoria de 
                         Observa{\c{c}}{\~a}o da Terra, das Divis{\~o}es de 
                         Sensoriamento Remoto e de Processamento de Imagens est{\~a}o 
                         desenvolvendo uma alternativa tem{\'a}tico realizado pelo INPE, 
                         com o intuito de introduzir automa{\c{c}}{\~a}o em algumas 
                         etapas do projeto de Monitoramento da Floresta Amaz{\^o}nica. 
                         Este projeto {\'e} conhecido como Prodes Digital. O presente 
                         trabalho estabelece o procedimento aplicativo, atualmente em uso 
                         pelo INPE, para identificar e mapear {\'a}reas desflorestadas na 
                         Amaz{\^o}nia Brasileira, atrav{\'e}s de processamento digital de 
                         imagens TM/Landsat. Para reduzir a dimensionalidade dos dados e 
                         consequentemente o tempo de processamento, utiliza-se o Modelo 
                         Linear de Mistura Espectral, implementado no Sistema de 
                         Processamento de Informa{\c{c}}{\~o}es Georreferenciadas - 
                         SPRING/INPE, que transforma as bandas originais TM3(0,63-0,69m m), 
                         TM4 (0,76- 0,90m m)e TM5(1,55-1,75m m), em 
                         imagens-fra{\c{c}}{\~a}o {"}sombra{"}, 
                         {"}vegeta{\c{c}}{\~a}o{"} e {"}solo{"}, numa abordagem que tem 
                         permitido automatizar a discrimina{\c{c}}{\~a}o das {\'a}reas 
                         de fisionomia florestal daquelas desflorestadas, resultante de um 
                         processo antropog{\^e}nico din{\^a}mico que vem se 
                         caracterizando ao longo das {\'u}ltimas d{\'e}cadas. Isso em 
                         raz{\~a}o do aumento da fronteira agropastoril ou mesmo, 
                         ocasionado pela explora{\c{c}}{\~a}o madeireira. A 
                         caracter{\'{\i}}stica amig{\'a}vel na opera{\c{c}}{\~a}o de 
                         manuseio do SPRING, o procedimento metodol{\'o}gico adotado e a 
                         s{\'e}rie de informa{\c{c}}{\~o}es geradas sobre o 
                         desflorestamento, de r{\'a}pida manipula{\c{c}}{\~a}o de 
                         an{\'a}lise, trazem um ganho de qualidade {\`a} comunidade 
                         t{\'e}cnico-cient{\'{\i}}fica que lida com as quest{\~o}es 
                         ambientais do pa{\'{\i}}s,sobretudo naqueles estudos que modelam 
                         as transforma{\c{c}}{\~o}es e seus efeitos em n{\'{\i}}vel 
                         global. ABSTRACT: For many years, the Brazilian Institute for 
                         Space Research, INPE, has been promoting the interpretation of 
                         images provided by Landsat satellite to monitor the evolution of 
                         the extent and rate of gross deforestation in the Brazilian 
                         Amazon. This effort has generated results for the period from 1978 
                         to 2001. INPE (2002)presents the study, covering the years of 2000 
                         (estimate based on the analysis of all scenes that cover the 
                         Brazilian Amazon)and 2001 (estimate basead on a sample), updates 
                         the historical series on the extent and rate of gross 
                         deforestation in the Amazon. It provides an updated insight on the 
                         deforestation issue and allows to explore the origins of 
                         deforestation offering indicators to guide the public policies in 
                         the region. In addition to the extent and rate of gross 
                         deforestation for the nine Amazon states, this study makes 
                         available information on the distribution of the mean rate of 
                         deforestation by large vegetation types and by classes of area 
                         size. Due to the geometric problems, appearing during the 
                         development of the manual interpretation of multitemporal TM 
                         images ( image hardcopies with different scales, overlays 
                         digitizing/scanning, complexity of deforestation pattern), the 
                         availability of these deforestation maps in a digital format have 
                         been restricted for some areas. During the last few years, an 
                         effort to find a methodology to overcome this problem has been 
                         successful. The objective of this work is to establish an 
                         operational procedure, actualy in use at INPE, to identify and map 
                         deforested areas in Brazilian Amazon based on digital 
                         classification of Landsat TM images. The Linear Spectral Mixing 
                         Model avaliable in the software package SPRING, developed at INPE, 
                         transforms the original Landsat bands: TM3 (0,63-0,69 mm), TM4 
                         (0,76-0,90mm)e TM5 (1,55-1,75mm)into shade vegetation and soil 
                         fraction-images in which forest and deforested areas present a 
                         large distinction. The Brazilian Amazon requires 229 Landsat TM 
                         images to cover the entire region, in order to demonstrate the 
                         operational feasibility of this approach, which is been applied to 
                         the critical region ( {"} ARCO DO DESFLORESTAMENTO{"} ), where 
                         governamental fiscalization actions have a highest priority.",
  conference-location = "Cochabamba, Bolivia",
      conference-year = "11-15 nov. 2002",
           copyholder = "SID/SCD",
                label = "10351",
             language = "pt",
           targetfile = "INPE 9425.pdf",
        urlaccessdate = "21 maio 2024"
}


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