@Article{ArasatoSanMalAmaRen:2012:DeMuPa,
               author = "Arasato, Luciana Satiko and Santos, Jo{\~a}o Roberto dos and 
                         Maldonado, Francisco Dar{\'{\i}}o and Amaral, Silvana and 
                         Renn{\'o}, Camilo Daleles",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universidad Aut{\'o}noma de Entre R{\'{\i}}os - UADER} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Detec{\c{c}}{\~a}o de mudan{\c{c}}a da paisagem a partir de 
                         an{\'a}lise multissensor e multitemporal em 
                         associa{\c{c}}{\~a}o com vari{\'a}veis geomorfom{\'e}tricas no 
                         dom{\'{\i}}nio da floresta atl{\^a}ntica / Change detection of 
                         landscape by multisensor and multitemporal analysis in association 
                         with geomorphometric variables in the Atlantic Forest domain",
              journal = "Revista Brasileira de Cartografia",
                 year = "2012",
               volume = "64",
               number = "4",
                pages = "475--486",
             keywords = "detec{\c{c}}{\~a}o de mudan{\c{c}}a, sensoriamento remoto, uso 
                         e cobertura da terra, Mata Atl{\^a}ntica, change detection, 
                         remote sensing, land-use and land-cover, Atlantic Forest.",
             abstract = "Este trabalho teve por objetivo detectar {\'a}reas onde ocorreram 
                         mudan{\c{c}}as no uso e cobertura da terra a partir da 
                         t{\'e}cnica de rota{\c{c}}{\~a}o radiom{\'e}trica controlada 
                         por eixo de n{\~a}o-mudan{\c{c}}a (RCEN) e imagens de 
                         sensoriamento remoto, em uma {\'a}rea da Floresta Atl{\^a}ntica, 
                         no Estado de S{\~a}o Paulo. Imagens do sensor TM/Landsat-5 de 
                         2004 e SPOT-5 XP de 2006 foram utilizadas para a 
                         aplica{\c{c}}{\~a}o da t{\'e}cnica de RCEN, a partir da qual 
                         foi poss{\'{\i}}vel identificar e classificar {\'a}reas de 
                         regenera{\c{c}}{\~a}o e de degrada{\c{c}}{\~a}o no 
                         per{\'{\i}}odo considerado. Como as {\'a}reas de Floresta 
                         Atl{\^a}ntica situam-se em terrenos acidentados, com 
                         varia{\c{c}}{\~o}es altitudinais de 0 m a 1650 m no caso da cena 
                         estudada, as imagens apresentam mais sombreamento, o que reduz o 
                         desempenho classificat{\'o}rio da detec{\c{c}}{\~a}o de 
                         mudan{\c{c}}as. Foram feitas an{\'a}lises das {\'a}reas de 
                         mudan{\c{c}}a em rela{\c{c}}{\~a}o {\`a}s vari{\'a}veis 
                         geomorfom{\'e}tricas para uma sub-regi{\~a}o da cena. As 
                         {\'a}reas com Floresta Densa Altimontana (acima de 1200 m) com 
                         declividade forte (12-50%) foram as regi{\~o}es que apresentaram 
                         as maiores {\'a}reas de mudan{\c{c}}as detectadas. ABSTRACT: 
                         This work aimed to detect land cover changes using the RCEN 
                         technique (radiometric rotation controlled by nonchange axis) over 
                         different sensors and multitemporal images. The study area 
                         comprises a region of Atlantic Forest, located in the State of 
                         S{\~a}o Paulo. Landsat-5 TM image from 2004 and SPOT-5 XP image 
                         from 2006 were used for the change detection procedure. The RCEN 
                         technique enabled to identify and to classify regeneration and 
                         degradation forest areas during the time period considered. The 
                         performance of RCEN technique is reduced when applied to images 
                         with shadowing areas, as observed for the hilly terrains at the 
                         study site, with altitudes values ranging from 0 m to 1650 m, 
                         approximately. Some adjustments are still required to apply this 
                         technique over sites of Atlantic Forest within mountainous 
                         terrains. Because of the high frequency of shaded areas in the 
                         images the performance for change detection was reduced. Analyses 
                         of change areas considering geomorphometric variables were made in 
                         a subset of the studied scene. Regions containing Altimontana 
                         Dense Forest (over 1200 m) and with high slope values (12-50%) 
                         presented largest areas of change detection.",
                 issn = "0560-4613",
                label = "lattes: 7712719010541171 5 ArasatoSanMalAmaRen:2012:DeMuPa",
             language = "pt",
           targetfile = "arasato_deteccao.pdf",
        urlaccessdate = "30 abr. 2024"
}