%0 Conference Proceedings
%4 sid.inpe.br/mtc-m21c/2019/08.01.15.23
%2 sid.inpe.br/mtc-m21c/2019/08.01.15.23.11
%T Assessment of land use cover in Brazil, South America using fraction images derived from Proba-V datasets
%D 2019
%A Shimabukuro, Yosio Edemir,
%A Arai, Egidio,
%A Duarte, Valdete,
%A Dutra, Andeise Cerqueira,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress yosio.shimabukuro@inpe.br
%@electronicmailaddress egidio.arai@inpe.br
%@electronicmailaddress valdete.duarte@inpe.br
%@electronicmailaddress andeise.dutra@inpe.br
%B International Geoscience and Remote Sensing Symposium (IGARSS)
%C Yokohama, Japan
%8 28 July - 02 Aug.
%I IEEE
%P 6401-6404
%S Proceedings
%K Remote Sensing, Image Processing, Deforestation, Forest Degradation, Burned Areas, Fraction Images, PROBA-V.
%X The objective of this paper is to present a method to assess the extent of annual land use/land cover in Brazil, South America. The proposed method applies the Linear Spectral Mixing Model (LSMM) to PROBA-V datasets to derive vegetation, soil and shade fraction images for global and regional analysis. We used 1 km composites of 10 days (S10-TOC - 10-daily global composites, Top-Of-Canopy) for the South America and 100 m composites of 5 days (S5-TOC - 5-daily global composites, Top-Of-Canopy) for the Mato Grosso State, Brazilian Amazon. Then we built the 1km and 100m composites corresponding to the three endmembers with the highest fraction values during the year 2015. In that manner we could detect and map the areas occupied by main crops in Brazil, during the 2015 year, using the vegetation fraction composites. Also, PROBA-V images were acquired in the dry season, on 21 June, 26 July and 11 August 2015 to show the potentiality of these images to assess the land cover changes due to deforestation and forest degradation by fire. The agricultural areas mapped using 1km dataset were compared with 100m results for the Mato Grosso State showing a difference of 12% (58,834 km2 and 66,490 km2 , respectively). The results are very important for the government and nongovernmental organizations for planning and management of the tropical environment.
%@language en
%3 shimabukuro_assessment.pdf