首页> 外文会议>IFIP TC 5/SIG 5.1 conference on computer and computing technologies in agriculture;CCTA 2011 >Large-Scale Microwave Remote Sensing of Retrieving Surface Multi-parameters Using Active and Passive Satellite Data: In the Tibetan Plateau Region of Maqu
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Large-Scale Microwave Remote Sensing of Retrieving Surface Multi-parameters Using Active and Passive Satellite Data: In the Tibetan Plateau Region of Maqu

机译:利用主动和被动卫星数据进行大规模微波遥感反演地表多参数:青藏高原玛曲

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To conduct with these land surface parameters inversion using microwave observations in the bare soil surface, it is needed to estimate soil moisture (SM), surface temperature (ST) and surface roughness changes with microwave observations. High-frequency passive microwave radiometer sensitivity of the roughness is very low, traditional ground truth can't provide an accurate large-scale roughness of pixel information, and active radar and scatterometer data for roughness of the high sensitivity, active and passive joint inversion of soil volumetric water content is the current hot research. The main objective of this research is to develop a suitable method instead of some traditional methods for the retrieval of SM and other parameters at large-scale, which is based on the synergistic use of AMSR-E and Quikscat/SeaWinds observations. Quikscat / SeaWinds can provide large-scale scatterometer data, first used in this study to establish AIEM simulation and backscattering coefficient of roughness between, and then estimate the roughness of the known information as auxiliary inversion surface AMSR-E temperature and soil volumetric water content. The retrieval results show that this proposed method is helpful to achieve a higher accuracy in the study region of Maqu.
机译:为了利用裸露的土壤表面中的微波观测来进行这些陆地表面参数的反演,需要利用微波观测来估算土壤湿度(SM),表面温度(ST)和表面粗糙度的变化。高频无源微波辐射仪的粗糙度灵敏度很低,传统的地面实况无法提供准确的大规模粗糙度的像素信息,而有源雷达和散射仪数据对于粗糙度的高灵敏度,有源和无源联合反演土壤体积含水量是当前研究的热点。这项研究的主要目的是基于AMSR-E和Quikscat / SeaWinds观测值的协同使用,开发一种适合的方法,而不是一些传统的方法来大规模地检索SM和其他参数。 Quikscat / SeaWinds可以提供大规模的散射仪数据,首先用于本研究中建立AIEM模拟和反向散射之间的粗糙度系数,然后估计已知的粗糙度信息,如辅助反演表面AMSR-E的温度和土壤体积含水量。检索结果表明,该方法有助于在玛曲研究区获得较高的精度。

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