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United States Department of Agriculture

Agricultural Research Service


item Doraiswamy, Paul
item Mccarty, Gregory
item Venteris, Erik
item Doumbia, Mamadou
item Hunt, Earle - Ray

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 1/5/2004
Publication Date: 5/30/2004
Citation: Doraiswamy, P.C. McCarty, G.W., Venteris, E., Doumbia, M., Hunt, E.R. 2004. Remote sensing and modeling of soil carbon sequestration in agricultural lands of Mali [abstract]. Invited presentation of the Workshop on "Land Management for Carbon Sequestration in West Africa," February 2-4, 2004, Bamako, Mali. 2004 CDROM.

Interpretive Summary:

Technical Abstract: Agriculture in sub-Saharan Africa is a low-input low-output systems of agriculture which maintained Africa at subsistence levels but is no longer able to feed the people. In addition, there are the associated problems of land degradation accelerated by low-input systems which in some instances has exceeded the resilience threshold of soils. The Carbon from Communities Project in Mali was carried out in several sites to study the potential for increasing levels of soil carbon and the potential for increasing soil quality to improve crop production. The objective of this research was to use satellite remotely sensed imagery for mapping current landuse and to assess impact of different land management on soil productivity and crop yields. High resolution imagery from Quickbird in combination with lower resolution SPOT HRV and Landsat ETM imagery were used to develop a landuse classification for a study area (8x 8 km) near Konobougou. Ground truth data was acquired from site visits. Field sizes were small and the best available combination of temporal, spatial and spectral resolution imagery was utilized to develop a landuse map. Based on the classification, and available climate, soil texture, in-situ soil carbon measurements and crop statistics data, a soil carbon sequestration model was used to map the current and potential levels of soil carbon for the various landuse. Spatial parameters derived from remotely sensed data were integrated in models for crop yield and soil carbon simulations. Modeling techniques provide an opportunity to optimize production levels by adapting alternate management practices and predicting future crop yields and potential levels of soil carbon sequestration.

Last Modified: 06/22/2017
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