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Application of intelligent forewarning system for desertification in China

机译:智能预警系统在中国荒漠化的应用

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摘要

Based on the climatic, surface and human factors of desertification, an index system and an intelligent model of desertification forewarning are established for the downstream of Tarim River. Based on the remote sensing, climate, land surface, and human data in 1990, 2000, and 2006, the ArcGIS software is used to quantify and rasterize the data of each factor. The forewarning model reveals the distribution of desertification degree in the three study periods on a scale of 30 x 30 m and the results are used to conduct the correction and verification of model parameters. The development trend of desertification in the study area in 2015 is then forecasted under the conditions of "intermittent water conveyance" and "no water conveyance" respectively. Through the parameter correction, the accuracy of the simulated distribution of desertification degree can be more than 90%, showing a good performance of the model. The intermittent water conveyance plays a certain role in the reversal of desertification in the downstream of Tarim River, which is a necessary measure to prevent a complete desertification. However, the reversal effect is only confined to a limited extent along the river channel and cannot thoroughly change the current situation of desertification in the study area.
机译:基于荒漠化的气候,表面和人为因素,为塔里木河下游建立了荒漠化预警的指标体系和智能模型。基于1990年,2000年和2006年的遥感,气候,陆地表面和人类数据,ArcGIS软件用于量化和光栅化每个因素的数据。预先寻找模型揭示了三个研究期间的荒漠化程度的分布,规模为30×30米,结果用于进行模型参数的校正和验证。然后在“间歇水输送”和“无水输送”条件下预测2015年研究区荒漠化发展趋势。通过参数校正,荒漠化程度的模拟分布的准确性可以超过90%,显示出良好的模型性能。间歇的水运输在塔里木河下游的荒漠化逆转中起着一定的作用,这是防止完全荒漠化的必要措施。然而,逆转效应仅限于沿河渠道的有限范围,无法彻底改变研究区域的荒漠化现状。

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