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Cartographie et caractérisation des systèmes agricoles au Mali par télédétection à moyenne résolution spatiale

Abstract : For food security systems, data on cultivated surfaces and yields are a prerequisite for agricultural production forecast. Moderate resolution satellite remote-sensing systems offer a synoptic vision that makes them a particularly appropriate information source for the estimation of such data. However, the estimation of cultivated surfaces is still challenging in West Africa, because of highly fragmented farmland, specific weather conditions resulting in high regional variability in terms of agricultural systems and practices, and synchronized phenology of crops and natural vegetation due to the rainfall regime. In this context, this thesis presents three original methodological approaches for the characterization of agricultural systems in West Africa by remote sensing. These methods were developed using MODIS time series (from 250 to 500 m spatial resolution) acquired for Mali. (i) The mapping of cultivated areas was carried out with spectral, spatial and textural indices derived from the images. Two approaches were chosen: one of ISODATA type following a segmentation of the territory based on MODIS imagery, and the other of data mining type based on ‘sequential patterns'. The crop map obtained showed a better precision than that of the existing land cover global products (70% vs 50% in average). Furthermore, it was shown that a significant part of user and producer errors (20 to 40%) could not be compressed due to farmland fragmentation. (ii) The mapping of agricultural system types first required the definition of a typology derived from an IER (Institute of Rural Economy in Mali) field survey data base on 100 villages. Three types of agricultural systems were determined at the village scale: mainly cereals (millet, sorghum), mainly intensive crops (maize, cotton) and a mixture of sorghum and cotton. The classification of agricultural systems using the aforementioned remote sensing indicators was carried out by a Random Forest type algorithm with an overall accuracy of 62%. Results bring to light the important part played by temporal NDVI and texture in agricultural system characterization. (iii) Finally, for crop monitoring, the MODIS phenological product was tested and assessed using phenological variables obtained from agro-meteorological simulations made by the SARRA-H plant model. Results show that this product contains inconsistencies due to the significant cloud cover linked with the start of the raining season. After the suppression of incongruous data, the phenological transition dates for crop land derived from MODIS were shown to be earlier by 20 days than the SARRA-H-simulated transition dates, due mainly to the ‘agro-ecosystem' mixed nature of surfaces at MODIS pixels scale. The results of this thesis highlight new possibilities for the combinination of remote sensing, field data and agro-meteorological modelling, delivering nonstop information in time and space on the characterization of “Sahel” farmland.
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  • HAL Id : pastel-00781223, version 1


Elodie Vintrou. Cartographie et caractérisation des systèmes agricoles au Mali par télédétection à moyenne résolution spatiale. Sciences agricoles. AgroParisTech, 2012. Français. ⟨NNT : 2012AGPT0013⟩. ⟨pastel-00781223⟩



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