@Article{LuBaMoHeAlBr:2011:FrFoCo,
               author = "Lu, Dengsheng and Batistella, Mateus and Moran, Emilio and 
                         Hetrick, Scott and Alves, Diogenes Salas and Brondizio, Eduardo",
          affiliation = "Anthropological Center for Training and Research on Global 
                         Environmental Change (ACT), Indiana University, Bloomington, IN 
                         47405, United States and Brazilian Agricultural Research 
                         Corporation, EMBRAPA Satellite Monitoring, Campinas, S{\~a}o 
                         Paulo, Brazil and Anthropological Center for Training and Research 
                         on Global Environmental Change (ACT), Indiana University, 
                         Bloomington, IN 47405, United States and Anthropological Center 
                         for Training and Research on Global Environmental Change (ACT), 
                         Indiana University, Bloomington, IN 47405, United States and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         Anthropological Center for Training and Research on Global 
                         Environmental Change (ACT), Indiana University, Bloomington, IN 
                         47405, United States",
                title = "Fractional forest cover mapping in the Brazilian Amazon with a 
                         combination of MODIS and TM images",
              journal = "International Journal of Remote Sensing",
                 year = "2011",
               volume = "32",
               number = "22",
                pages = "7131--7149",
                month = "Nov.",
             abstract = "High deforestation rates in Amazonia have motivated considerable 
                         efforts to monitor forest changes with satellite images, but 
                         mapping forest distribution and monitoring change at a regional 
                         scale remain a challenge. This article proposes a new approach 
                         based on the integrated use of Moderate Resolution Imaging 
                         Spectroradiometer (MODIS) and Landsat Thematic Mapper (TM) images 
                         to rapidly map forest distribution in Rond{\^o}nia, Brazil. The 
                         TM images are used to differentiate forest and non-forest areas 
                         and the MODIS images are used to extract three fraction images 
                         (vegetation, shade and soil) with linear spectral mixture analysis 
                         (LSMA). A regression model is built to calibrate the MODIS-derived 
                         forest results. This approach is applied to the MODIS image in 
                         2004 and is then transferred to other MODIS images. Compared to 
                         INPE PRODES (Brazil's Instituto Nacional de Pesquisas Espaciais 
                         Programme for the Estimation of Deforestation in the Brazilian 
                         Amazon) data, the errors for total forest area estimates in 2000, 
                         2004 and 2006 are\ \−0.97%, 0.81% 
                         and\ \−1.92%, respectively. This research provides a 
                         promising approach for mapping fractional forest (proportion of 
                         forest cover area in a pixel) distribution at a regional scale. 
                         The major advantage is that this procedure can rapidly provide the 
                         spatial and temporal patterns of fractional forest cover 
                         distribution at a regional scale by the integrated use of MODIS 
                         images and a limited number of Landsat images.",
                  doi = "10.1080/01431161.2010.519004",
                  url = "http://dx.doi.org/10.1080/01431161.2010.519004",
                 issn = "0143-1161",
                label = "lattes: 9191097222405687 5 LuBaMoHeAlBr:2011:FrFoCo",
             language = "en",
           targetfile = "fractionalforestIJRS2011.pdf",
        urlaccessdate = "05 maio 2024"
}