| 空气总悬浮颗粒物浓度的遥感信息模型研究 |
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| 引用本文： | 程承旗,常鹏飞,郭仕德,林旭东.空气总悬浮颗粒物浓度的遥感信息模型研究[J].水土保持研究,2006,13(6):243-246. |
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| 作者姓名： | 程承旗 常鹏飞 郭仕德 林旭东 |
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| 作者单位： | 北京大学遥感与地理信息系统研究所,北京,100871 |
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| 基金项目： | 国家863项目支持(项目编号:2003AA783060) |
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| 摘 要： | 空气总悬浮颗粒物遥感信息模型是使用遥感信息模型的方法来模拟空气总悬浮颗粒物在空间上的分布。通过对空气总悬浮颗粒物来源和分布影响的因子分析,认为地表覆盖情况因子对空气总悬浮颗粒物来源影响最大,降雨强度和风速因子对空气总悬浮颗粒物分布影响最大,因此根据此三个因子建立了空气总悬浮颗粒物遥感信息模型。然后根据对厦门市高分辨遥感的分类数据和空气总悬浮颗粒物的分布数据得到了空气总悬浮颗粒物遥感信息模型的地理参数。通过对公式结果验证认为该模型较好的模拟了空气总悬浮颗粒的分布,为空气总悬浮颗粒物浓度的分布研究提出一种新思路。
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| 关 键 词： | 空气总悬浮颗粒物浓度 遥感信息模型 遥感影像 |
| 文章编号： | 1005-3409（2006）06-0243-04 |
| 收稿时间： | 2005-12-20 |
| 修稿时间： | 2005年12月20 |
Research on Remote Sensing Information Model for Total Suspended Particles and Case Study |
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| CHENG Cheng-qi,CHANG Peng-fei,GUO Shi-de,LIN Xu-dong.Research on Remote Sensing Information Model for Total Suspended Particles and Case Study[J].Research of Soil and Water Conservation,2006,13(6):243-246. |
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| Authors: | CHENG Cheng-qi CHANG Peng-fei GUO Shi-de LIN Xu-dong |
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| Abstract: | Remote Sensing Information Quantificational Model for Total Suspended Particles Concentration is to simulate the spatial distribution of total suspended particles in air.The remote sensing information analysis approaches are employed in this model.Through combing remote sensing information modeling method and analysis source of TSP,three independent factors that influence significantly on the concentration and its variability of TSPC in both temporal and spatial distribution including total suspended particles productivity,rainfall intensity and wind velocity are selected to retrieve the TSP concentration.Some uncertain impact factors are also considered in this model.Some classified images from high-resolution remote sensed data and meteorologic data are applied to obtain those uncertain factors.Comparison of the simulated TSPC images the observation data by using multivariable regression method is implemented.The result shows that the RSIMTSPC is a useful model in simulating TSP spatial distributions. |
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| Keywords: | total suspended particles concentration remote sensing information model remote sensing image |
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