Analysis of agro-pastoral systems in regions suffering from environmental degradation (-)

Start-End  - 
Programme TELSAT 2
Contract TELSAT/II/08
Objective Three major research topics were studied:
- to generalise the spatial analysis performed at the regional scale to other regions of West Africa, by integrating exogenous variables to remote sensing, such as socio-economic variables;
- to analyse the evolution of the environment due to human action;
- to gain a thorough knowledge of a basic agro-pastoral systems parameter : agricultural production. Research concerns more precisely the development of a method to estimate and monitor the agricultural areas by studying the agrarian system.
Method
Result - Research carried out in Fouta Djallon (Guinea) has highlighted three relevant analysis scales of the agro-pastoral systems. At the production scale, talks with the villagers and the household survey have enabled the fluctuation of the production systems to be grasped; a production system typology is proposed to the operators of the rural development of the study region. At a local scale, different parameters of the agro-pastoral system have been assessed, such as the land use and population. High resolution satellite data and aerial photographs calibrated with ground surveys have been used as measurements of indirect indicators. At a regional scale, space can be subdivided according to a logical interpretation using the different information levels of a geographical information system.
- References of existing multi-temporal methods reviewed. The analysis is mainly based on the comparison of land cover maps for different dates. The change detection methods based on unclassed satellite data were tested.
- The application of geostatistical methods to the assessment of agricultural areas has been as accurate as, or more accurate than the results reached with the classical inference.
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Team
Project Leader: UCL - Georges LemaƮtre Centre for Earth and Climate Research
Location Fouta Djallon (Guinea)
Sensors used
Applications Agriculture
Environment & Ecology
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Datasets used