%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Li, Zhichao
%A Catry, Thibault
%A Dessay, Nadine
%A Roux, Emmanuel
%A Seyler, Frédérique
%T Mapping soil typologies using geomorphologic features extracted from DEM and SAR data : an environmental factor affecting malaria transmission in the Amazon
%B 2016 IEEE International Geoscience & Remote Sensing Symposium : proceedings
%C New York
%D 2017
%L fdi:010070439
%G ENG
%I IEEE
%@ 978-1-5090-3332-4
%K SOL ; TYPOLOGIE ; CARTE PEDOLOGIQUE ; TELEDETECTION SPATIALE ; PALUDISME ; TRANSMISSION ; DISTRIBUTION SPATIALE
%K AMAZONIE ; GUYANE FRANCAISE ; BRESIL
%M ISI:000388114603040
%P 3140-3143
%R 10.1109/IGARSS.2016.7729812
%U https://www.documentation.ird.fr/hor/fdi:010070439
%> https://www.documentation.ird.fr/intranet/publi/depot/2018-01-04/010070439.pdf
%W Horizon (IRD)
%X Soil typologies are characterized by different distribution and circulation of water, associated with specific water chemical properties, and thus potentially affects the distribution and density of malaria vectors in the Amazon. Based on a conceptual model of tropical soil evolution and distribution, the curvature of watershed slopes is a key indicator of soil typology. The average curvature of each subwatershed in our study area was identified using 30 m resolution SRTM data. PALSAR image with a spatial resolution of 12.5 m was used to implement a land cover map, including water and non-water surfaces. The nonwater surface was then integrated with the average curvature of subwatersheds for soil typologies mapping. An indirect approach of soil typologies prediction was proposed, which is complementary with the classical soil classification methods.
%S IEEE International Symposium on Geoscience and Remote Sensing IGARSS
%B IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
%8 2016/07/10-15
%$ 126TELAPP03 ; 052ANOPAL03