光学信息分解被动微波土壤湿度方法
The Method of Decomposing the Passive Microwave Soil Moisture Using Optical Information
查看参考文献25篇
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文摘
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土壤水分是一个重要生态参量,以被动微波反演土壤水分,不受天气影响,且其算法成熟。但是星载被动微波数据的空间分辨率较低,可适合大区域尺度研究。本文将1km分辨率光学数据MODIS和25km分辨率被动微波数据AMSR-E2级土壤湿度产品结合,利用NDVI-Ts特征空间,去除植被影响,结合前人提出的裸土蒸散模型,将研究区被动微波土壤湿度数据分解,得到1km分辨率土壤体积含水量。将其反演结果与1km温度植被干旱指数(TVDI)进行趋势和数值比较,其相关性达到0.569。同时,利用实测样点的土壤重量含水量,与得到的1km分辨率土壤体积含水量数据进行比较,其增减趋势一致,结果具有可信度。但对定量结果尚需进一步验证和提高。 |
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其他语种文摘
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The water held in the top few centimeters of the soil is a key variable in many hydrological, climatological and ecological processes. These data are difficult and costly to acquire through in situ measurements, especially at high temporal frequencies. Different types of remote sensing systems are currently used to infer soil moisture at different spatial and temporal scales, each with its specific characteristics and limitations. The soil moisture retrieval from passive microwave is not affected by the weather, and the algorithm is mature and reliable. But the spatial resolution of spaceborne passive microwave data is too low for many local applications, and the data are suitable for large scale studies. Optical sensors complemented with thermal infrared channels have, in spite of the strong atmospheric attenuation and the limited penetration depth of the used signal, received much attention as a source of information on soil moisture content and surface evaporation. The way the high spatial resolution surface evaporation information contained in optical/thermal sensors can be combined with relatively low resolution soil moisture. Selecting 1km resolution the Moderate Resolution Imaging Spectroradiometer (MODIS) optical data and 25km resolution the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) passive microwave data 2 level of soil moisture product, the authors used NDVI-Ts feature space to remove the vegetation effect, and decompose the passive microwave soil moisture through a soil evaporation model. At last the authors got the 1km resolution soil moisture. Through building scatter diagram, it could be found that the relevance between the inversion result and 1km Temperature Vegetation Drought Index (TVDI) reached 0.569. The quantitative results of the study still need further validation and improvement. |
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来源
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地球信息科学学报
,2012,14(5):652-657 【核心库】
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关键词
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土壤湿度
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被动微波
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MODIS
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TVDI
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土壤蒸散效率
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地址
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1.
首都师范大学, 城市环境过程与数字模拟国家重点实验室培育基地, 北京, 100048
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中国科学院遥感应用研究所, 北京, 100101
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语种
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中文 |
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ISSN
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1560-8999 |
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学科
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农业基础科学;自动化技术、计算机技术 |
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基金
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国家自然科学基金重点项目
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国家自然科学基金项目
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国家973计划
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文献收藏号
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CSCD:4661429
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