%0 Journal Article
%4 dpi.inpe.br/plutao/2011/11.23.17.44.12
%2 dpi.inpe.br/plutao/2011/11.23.17.44.13
%@doi 10.1080/01431161.2010.519004
%@issn 0143-1161
%F lattes: 9191097222405687 5 LuBaMoHeAlBr:2011:FrFoCo
%T Fractional forest cover mapping in the Brazilian Amazon with a combination of MODIS and TM images
%D 2011
%8 Nov.
%A Lu, Dengsheng,
%A Batistella, Mateus,
%A Moran, Emilio,
%A Hetrick, Scott,
%A Alves, Diogenes Salas,
%A Brondizio, Eduardo,
%@affiliation Anthropological Center for Training and Research on Global Environmental Change (ACT), Indiana University, Bloomington, IN 47405, United States
%@affiliation Brazilian Agricultural Research Corporation, EMBRAPA Satellite Monitoring, Campinas, São Paulo, Brazil
%@affiliation Anthropological Center for Training and Research on Global Environmental Change (ACT), Indiana University, Bloomington, IN 47405, United States
%@affiliation Anthropological Center for Training and Research on Global Environmental Change (ACT), Indiana University, Bloomington, IN 47405, United States
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Anthropological Center for Training and Research on Global Environmental Change (ACT), Indiana University, Bloomington, IN 47405, United States
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress dalves@dpi.inpe.br
%B International Journal of Remote Sensing
%V 32
%N 22
%P 7131-7149
%X 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 Rondônia, 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.
%@language en
%3 fractionalforestIJRS2011.pdf