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首页> 外文会议>International Geoscience Remote Sensing Symposium >A Land Cover Change Synthesis Study for the GLOWA Volta Basin in West Africa using Time Trajectory Satellite Observations and Cellular Automata Models
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A Land Cover Change Synthesis Study for the GLOWA Volta Basin in West Africa using Time Trajectory Satellite Observations and Cellular Automata Models

机译：利用时间轨迹卫星观测和蜂窝自动机模型对西非的Glowa Volta盆地的陆地覆盖综合研究

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Quantifying the regional effects of land cover change is imperative to improve future hydrological budget estimates within large river basins. In this study we aim to utilize binary logistic regressions models within a cellular automation (CA) modeling environment to find causalities for satellite remote sensing measured land cover change (LCC). We used 30-meter Landsat and 250-meter MODIS time-series observations to map LCC for different time trajectories in two large study areas in Burkina Faso and Ghana. We used the FAO Land Cover Classification System (LCCS) legend to map LCC processes from the satellite trajectories. Socio-economic data on population density, distances to roads, and biophysical data sets were processed in the CA model. The neighborhood effect of the change predictors were accounted for by using an enrichment factor. The relationship between the satellite derived LCC and the major biophysical and socio-economic drivers showed that population density, and the increase of cropland areas are responsible for the conversion of forests and woodlands. This was observed for both study areas.
机译：量化土地覆盖变革的区域效应必须提高大河盆地内未来的水文预算估计。在本研究中，我们的目标是在蜂窝自动化（CA）建模环境中利用二元逻辑回归模型，以找到卫星遥感测量的陆地覆盖变化（LCC）的因果区。我们使用了30米的Landsat和250米的Modis Time-Series观测来映射LCC在布基纳法索和加纳的两个大型学习区的不同时间轨迹。我们使用粮农组织土地覆盖分类系统（LCC）传说来从卫星轨迹映射LCC流程。 CA型号处理了关于人口密度的社会经济数据，对道路的距离和生物物理数据集。通过使用富集因子来计算变化预测因子的邻域效应。卫星衍生LCC与主要生物物理和社会经济司机之间的关系表明，人口密度，农田地区的增加负责森林和林地的转换。这两个研究领域都观察到这一点。

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