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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
earth and planetary sciences
Mapping fragmented agricultural systems in the sudano-sahelian environments of Africa using random forest and ensemble metrics of coarse resolution MODIS imagery
Photogrammetric Engineering and Remote Sensing, Volume 78, No. 8, Year 2012
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Description
We worked on the assumption that agricultural systems shaped the landscape through human cropping practices, and that the resulting landscape can be described with a set of coarse resolution satellite-derived metrics (spectral, textural, temporal, and spatial metrics). A Random Forest classification model was developed at the village scale in South Mali, based on 100 samples, with data on the main type of agricultural system in each village (three-class typology), and 30 MODIS-derived and socio-environmental metrics calculated on agricultural areas. The model was found to perform well (overall accuracy of 60 percent) and was stable. Class A (food crops) and B (intensive agriculture) displayed good producer's accuracy (70 percent and 67 percent, respectively), while class C (mixed agriculture) was less accurate (50 percent). The most important metrics were shown to be the annual mean of NDVI, followed by the phenology transition dates and texture metrics. However, when considering each set of metrics separately, texture emerged as the most discriminating factor (with 53 percent of global accuracy). This result, i.e., that even coarse resolution imagery contains textural information that can be used for crop mapping, is new. Such maps could be used in food security systems as an indicator of system vulnerability, or as spatial inputs for crop yield models. © 2012 American Society for Photogrammetry and Remote Sensing.
Authors & Co-Authors
Vintrou, Élodie
France, Montpellier
Territoires, Environnement, Télédétection et Information Spatiale
Soumaré, Mamy
Mali, Bamako
Ier
Bernard, Simon
France, Mont-saint-aignan
Université de Rouen Normandie
Bégué, Agnès
France, Montpellier
Territoires, Environnement, Télédétection et Information Spatiale
Baron, Christian
France, Montpellier
Territoires, Environnement, Télédétection et Information Spatiale
Lo Seen, Danny
France, Montpellier
Territoires, Environnement, Télédétection et Information Spatiale
Statistics
Citations: 20
Authors: 6
Affiliations: 3
Identifiers
Doi:
10.14358/PERS.78.8.839
ISSN:
00991112
Research Areas
Food Security
Study Locations
Mali