| 基于MODIS遥感数据的呼伦贝尔土地荒漠化信息提取(英文) |
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| 引用本文： | 孟翔冲,姜琦刚,齐霞,王斌,吴阳春,李根军,杨佳佳.基于MODIS遥感数据的呼伦贝尔土地荒漠化信息提取(英文)[J].农业科学与技术,2012(1):233-237. |
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| 作者姓名： | 孟翔冲 姜琦刚 齐霞 王斌 吴阳春 李根军 杨佳佳 |
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| 作者单位： | 吉林大学地球探测科学与技术学院;沈阳地球物理勘察院;吉林大学综合信息矿产预测研究所;吉林大学地球科学学院 |
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| 基金项目： | Supported by the Special Fundation of China Geological Survey(1212010911084)~~ |
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| 摘 要： | 目的]基于MODIS遥感数据,对呼伦贝尔地区土地荒漠化信息进行提取。方法]基于空间分辨率为1km的MODIS遥感数据,选取可以反映不同荒漠化特征的5个指标进行反演,并采用决策树分类方法对呼伦贝尔地区土地荒漠化信息进行提取。结果]呼伦贝尔地区土地荒漠化面积为33862km2,占全区总面积的20.36%,且主要以沙质荒漠化为主;通过野外验证及高分辨率解译数据采点验证,此评价方法总体精度达89%以上。结论]使用文中评价方法进行荒漠化监测,不仅能够对大尺度的荒漠化地区进行监测,而且具有较好的评价效果。
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| 关 键 词： | 荒漠化 MODIS数据 遥感 决策树 反演 |
Extraction of Desertification Information in Hulun Buir Based on MODIS Image Data |
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| Xiangchong MENG,Qigang JIANG,Xia QI,Bin WANG,Yangchun WU,Genjun LI,Jiajia YANG.Extraction of Desertification Information in Hulun Buir Based on MODIS Image Data[J].Agricultural Science ＆ Technology,2012(1):233-237. |
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| Authors: | Xiangchong MENG Qigang JIANG Xia QI Bin WANG Yangchun WU Genjun LI Jiajia YANG |
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| Institution: | 1. College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China; 2. Shenyang Geophysical Exploration Institute, Shenyang 110121, China; 3. Mineral Resources Prediction Institute of Comprehensive Information, Jilin University, Changchun 130026, China; 4. College of Earth Sciences, Jilin University, Changchun 130061, China |
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| Abstract: | Objective] To extract desertification information of Hulun Buir region based on MODIS image data. Method] Based on MODIS image data with the spatial resolution of 1 km, 5 indicators which could reflect different desertification features were selected to conduct inversion. The desertification information of Hulun Buir region was extracted by decision tree classification. Result] The desertification area of Hulun Buir region is 33 862 km2, accounting for 24% of the total area, and it is mainly dominated by sandiness desertification. Though field verification and mining point validation of high-resolution interpretation data, the overall accuracy of this evaluation is above 89%. Conclusion] Evaluation method used in this study is not only effectively for large scale regional desertification monitoring but also has a better evaluation performance. |
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| Keywords: | Desertification MODIS image data Remote sensing Decision tree Inversion |
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