首页> 外文会议>Conference on Remote Sensing for Environmental Monitoring, GIS Applications, and Geology III; Sep 9-11, 2003; Barcelona, Spain >GIS and RS integration: Application of geostatistical techniques and environmental changes in the coastal zone in Kenya
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GIS and RS integration: Application of geostatistical techniques and environmental changes in the coastal zone in Kenya

机译:GIS和RS集成:地统计学方法的应用和肯尼亚沿海地区的环境变化

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Understanding the dynamics of land cover change has increasingly been recognized as one of the key research imperatives in global environmental change research. Scientists have developed and applied various methods in order to find and propose solutions for many environmental world problems. From 1986-1995 changes in Kenya coastal zone landcover, derived from the post-classification TM images, were significant with arid areas growing from 3% to 10%, woody areas decreased from 4% to 2%, herbaceous areas decreased from 25% to 20%, developed land increased from 2% to 3%. In order to generate the change probability map as a continuous surface using geostatistical method-ArcGIS, we used as an input the Generalized Linear Model (GLM) probability result. The results reveal the efficiency of the Probability-of-Change map (POC), especially if reference data are lacking, in indicating the possibility of having a change and its type in a determined area, taking advantage of the layer transparency of the GIS systems. Thus, the derived information supplies a good tool for the interpretation of the magnitude of the land cover changes and guides the final user directly to the areas of changes to understand and derive the possible interactions of human or natural processes.
机译:人们越来越认识到,了解土地覆被变化的动态是全球环境变化研究中的关键研究课题之一。科学家已经开发并应用了各种方法,以便为许多环境问题找到解决方案并提出解决方案。从1986年至1995年,肯尼亚TM海岸带土地覆被的变化非常显着,干旱地区的面积从3%增至10%,木本植物的面积从4%降至2%,草本面积从25%降低至10%。 20%的已开发土地从2%增加到3%。为了使用地统计方法-ArcGIS将变化概率图生成为连续表面,我们将广义线性模型(GLM)概率结果用作输入。结果揭示了变化概率图(POC)的效率,尤其是在缺少参考数据的情况下,它利用GIS系统的层透明性来指示在确定的区域中发生变化及其类型的可能性。 。因此,所获得的信息为解释土地覆盖变化的大小提供了一个很好的工具,并直接将最终用户引导到变化的区域,以了解和推导人类或自然过程的可能相互作用。

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