Disentangling factors of landscape changes in Burkina Faso, the nexus between spatial modeling and remote sensing
Rural areas of West Burkina Faso have seen notable transformations these last two decades due to high population growth and farming systems evolution. Satellite images acquired frequently and covering large areas are essential for detecting such landscape changes and long term trends. However, these images generally have coarse spatial resolutions and can only provide information about changes in the main vegetation patterns. The factors causing these changes are more difficult to determine, although there are essential for monitoring landscape evolution. We hereby present a method based on multi-scalar modelling of past landscape dynamics crossed with changes in vegetation trends identified from coarse resolution satellite images. The aim of our presentation is to use the model to simulate and illustrate how land cover and land use changes may impact vegetation response by improving the qualification and understanding of the observed trends. The cropping systems dynamics of the study area, the Tuy province of West Burkina Faso, were modelled with the Ocelet Modelling Platform over the last fifteen years through a multi-scalar model. The model was validated at local scale with information derived from high resolution images. At the same time, vegetation trends were analysed using Ordinary Least Square regressions based on MODIS NDVI time series. Simulated cropland change maps were then used to decompose the remote sensing-based trends. This allowed the spatial identification of factors responsible for the vegetation changes. The original approach we proposed here opens new opportunities for the understanding and monitoring of landscape changes using time series of coarse resolution satellite images.
| Main Authors: | , , , , , |
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| Format: | conference_item biblioteca |
| Language: | eng |
| Published: |
AgMIP
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| Subjects: | B10 - Géographie, P01 - Conservation de la nature et ressources foncières, U30 - Méthodes de recherche, E90 - Structure agraire, |
| Online Access: | http://agritrop.cirad.fr/582575/ http://agritrop.cirad.fr/582575/6/ID582575.pdf |
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| Summary: | Rural areas of West Burkina Faso have seen notable transformations these last two decades due to high population growth and farming systems evolution. Satellite images acquired frequently and covering large areas are essential for detecting such landscape changes and long term trends. However, these images generally have coarse spatial resolutions and can only provide information about changes in the main vegetation patterns. The factors causing these changes are more difficult to determine, although there are essential for monitoring landscape evolution. We hereby present a method based on multi-scalar modelling of past landscape dynamics crossed with changes in vegetation trends identified from coarse resolution satellite images. The aim of our presentation is to use the model to simulate and illustrate how land cover and land use changes may impact vegetation response by improving the qualification and understanding of the observed trends. The cropping systems dynamics of the study area, the Tuy province of West Burkina Faso, were modelled with the Ocelet Modelling Platform over the last fifteen years through a multi-scalar model. The model was validated at local scale with information derived from high resolution images. At the same time, vegetation trends were analysed using Ordinary Least Square regressions based on MODIS NDVI time series. Simulated cropland change maps were then used to decompose the remote sensing-based trends. This allowed the spatial identification of factors responsible for the vegetation changes. The original approach we proposed here opens new opportunities for the understanding and monitoring of landscape changes using time series of coarse resolution satellite images. |
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