近地表气温遥感反演研究进展

doi:10.11867/j.issn.1001-8166.2011.07.0724

高时间分辨率的近地表气温空间分布数据是许多陆面过程模型中非常重要的输入参数之一。在常规气象观测站点稀少或没有的情况下，利用遥感技术进行较高时空分辨率的近地表气温估算与反演，在理论方法与业务实践上都具有重要研究意义。根据地表能量平衡与辐射平衡原理，在气温遥感反演物理机制分析的基础上，总结了国内外近年来气温遥感反演的研究进展，主要方法可归纳为5类：单因子统计方法、多因子统计方法、神经网络方法、地表温度—植被指数方法和地表能量平衡方法，并从遥感反演气温的时空分辨率、反演模型中影响因子的考虑、模型的可移植性与实用性角度，讨论了已有研究方法中存在的困难与问题，最后对未来可能的研究方向做出了展望。

关键词: 近地表气温, 地表温度, 遥感, 反演

Spatially distributed near surface air temperature data with high temporal resolution is a very important input parameter for several land surface models. Such data are often lacking because there are few traditional meteorological stations. It is of great significance in both theoretical research and practical applications to retrieve air temperature data from remote sensing observations. According to the surface energy balance and the radiance balance theories, the paper summarizes the retrieval methods of near surface air temperature from remote sensing images based on analysis of physical mechanism. The main methods are as follows: ① Single factor statistical method. It builds a relation model between bright temperature of thermal infrared channels or land surface temperature and land surface air temperature. ② Multiple factors statistical method. In relation models, at least two influence parameters are included to retrieve land surface air temperature by multiple regression analysis. ③ Artificial neural network method. Using multiple influence parameters as the input and the air temperature as the output, artificial neural network models are trained and then built to retrieve air temperature. ④ Temperature-vegetation index method. The approach is based on the hypothesis that vegetation canopy temperature approximates near surface air temperature and regression parameters used to compute air temperature are determined within a moving window around a location. ⑤ Surface energy balance methods. On the basis of physical approach, the air temperature is derived after calculation or measurement of the needed parameters for the energy balance equation. And then problems within air temperature retrieval are discussed in terms of spatial-temporal resolution, influence factors as well as models portability and utility considered. Finally the probable research fields in the future are proposed.

Key words: Near surface air temperature, Land surface temperature, Remote sensing, Retrieval

中图分类号:

P407.8
TP79

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摘要

Progress in Near Surface Air Temperature Retrieved by Remote Sensing Technology