首页> 外文会议>Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on >The Research of the Quantitative Method of Desertification Assessment at Large Scale Based on MODIS Data and Decision Tree Model - A Case Study in Farming-Pastoral Region of North China
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The Research of the Quantitative Method of Desertification Assessment at Large Scale Based on MODIS Data and Decision Tree Model - A Case Study in Farming-Pastoral Region of North China

机译:基于MODIS数据和决策树模型的大规模荒漠化评价量化方法研究-以华北农牧区为例。

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摘要

China is one of the countries that seriously suffered desertification in the world, and it is very meaningful to develop a quantitative method to assess desertification at large scale. In this study, the MODIS images were selected as the data resources, and NDVI, land surface albedo, soil water index (the reflectance of MODIS band 7) were selected as the indicators for assessing desertification. Based on building the indicator rule sets of different desertification grades in different sub-regions, the authors developed a quantitative method for desertification assessment by using decision tree model. The results showed that, the method developed in this study that can reflect the heterogeneity of land surface at large scale, and the overall accuracy of the method can reach 85.5%, which was suitable to assess desertification at large scale. Based on using this method to assess the desertification in farming-pastoral region of north China in 2000 and 2010, the authors found that the areas of lands that experienced desertification reversion and desertification expansion were almost consistent, and the spatial distribution of these regions existed obvious differences.
机译:中国是世界上荒漠化严重的国家之一,开发定量评估荒漠化的定量方法具有重要意义。在这项研究中,选择MODIS图像作为数据资源,并选择NDVI,地表反照率,土壤水分指数(MODIS 7波段的反射率)作为评估荒漠化的指标。在建立不同分区的不同荒漠化等级指标规则集的基础上,作者开发了一种基于决策树模型的沙漠化评估定量方法。结果表明,该方法开发的方法能够大范围地反映土地表面的异质性,该方法的总体准确度可以达到85.5%,适用于大范围的荒漠化评价。在利用这种方法对华北农牧区2000年和2010年荒漠化进行评估的基础上,作者发现经历了荒漠化恢复和荒漠化扩展的土地面积几乎是一致的,而且这些区域的空间分布存在明显的差异。差异。

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