PROGRESS IN GEOGRAPHY ›› 2006, Vol. 25 ›› Issue (3): 96-105.doi: 10.11820/dlkxjz.2006.03.012

• Original Articles • Previous Articles     Next Articles

Progr ess in Land Sur face Temper atur e Retr ieval from Passive Microwave Remotely Sensed Data

JIA Yuanyuan1,2, LI Zhaoliang1   

  1. 1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographical Sciences and Natural Resources Research, CAS, Beijing 100101|
    2. Graduate School of the Chinese Academy of Sciences, Beijing 100049
  • Received:2005-12-01 Revised:2006-03-01 Online:2006-05-25 Published:2006-05-25


Land surface temperature (LST) is of considerable importance for many applications, notably global climatic, hydrological, ecological and biogeochemical studies. In the past two decades, a large number of methods and algorithms have been developed to retrieve cloud free LST from thermal infrared data. As for all optical remote sensing, the Earth observation can only be realized for cloud free condition. In order to get LST for all weather conditions, microwave remotely sensed data, instead of thermal infrared data, from space is commonly used due to its capability to penetrate clouds and to some extent rain. Although the passive microwave remote sensing has some advantages compared to the thermal infrared, there are few algorithms developed to retrieve LST from it, mainly because there are various factors affected the microwave signal. In this paper, we review almost all existing algorithms found in literature, which can be roughly categorized into the statistical- based and physics- based retrieval algorithms, to retrieve LST from passive microwave remotely sensed data. The merits and the disadvantages are summarized for each method respectively. Finally further possible improvement and development directions on the scaling transfer, the microwave radiative transfer modeling and the combination of the different remote sensing data are given for LST retrieval from passive microwave data.

Key words: land surface temperature, passive microwave remote sensing, radiative transfer model

CLC Number: 

  • TP722.6