Estimation of all-weather land surface temperature with remote sensing: Progress and challenges
- Vol. 27, Issue 7, Pages: 1534-1553(2023)
Published: 07 July 2023
DOI: 10.11834/jrs.20211323
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Published: 07 July 2023 ,
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丁利荣,周纪,张晓东,王韶飞,唐文彬,王子卫,马晋,艾丽皎,李明松,王伟.2023.全天候地表温度遥感获取进展与挑战.遥感学报,27(7): 1534-1553
Ding L R, Zhou J, Zhang X D, Wang S F, Tang W B, Wang Z W, Ma J, Ai L J, Li M S and Wang W. 2023. Estimation of all-weather land surface temperature with remote sensing: Progress and challenges. National Remote Sensing Bulletin, 27(7):1534-1553
如何获取全天候地表温度对促进相关研究具有十分重要的意义。卫星热红外遥感地表温度虽然在反演理论方法和科学数据产品等方面已相对成熟,但热红外难以穿透云雾的特点导致反演得到的地表温度在云下有大量缺失;被动微波遥感虽能获取云下地表温度,但由于物理机制和成像方式的限制,存在空间分辨率不足、精度较低、轨道间隙较大等问题。通过卫星单源遥感难以直接获取中等空间分辨率、不受云雾影响的全天候地表温度。从原理、方法、产品和应用方面回顾并归纳了当前全天候地表温度的研究进展和面临的主要问题。基于有效观测重构和多源数据集成是获取全天候地表温度的两种基本途径,前者可分为时空插值和基于能量平衡方程插值两类,后者则可分为热红外与被动微波遥感集成、热红外与再分析资料集成。多源数据集成可以整合热红外遥感、被动微波遥感、再分析资料各自的优势,具有较大的研究价值和潜力。在产品方面,分析了当前学术界已公开发布的5种全天候地表温度产品。在应用方面,虽然部分全天候地表温度产品已在土壤湿度、地表蒸散发估算与同化方面取得了一些应用成果,但其在其他领域的应用亟待挖掘。此外,对全天候地表温度的未来研究方向和重点进行了讨论和展望。
Land Surface Temperature (LST) is an important parameter for characterizing the surface–air exchange process
which plays an important role in climate change
ecological monitoring
hydrological simulation
and other studies. The traditional LST estimated from Thermal Infrared (TIR) remote sensing is mature in terms of retrieval methods
data production
and quality control. However
the TIR LST has considerable missing data under clouds because of the limitation that the TIR radiation from the ground surface cannot penetrate the clouds. In addition
Passive Microwave (PMW) remote sensing has disadvantages
such as strip gaps and coarse spatial resolution
because of the limitations of the physical mechanisms and imaging methods. Therefore
the all-weather LST unaffected by cloudiness must be obtained to support the subsequent studies. In the present study
we review and organize the basic principles and methods of the acquisition of all-weather LST. The methods are classified into two categories: (i) all-weather LST reconstruction from effective observation and (ii) multisource data integration.
The comparative analysis indicates that multisource data integration can combine the advantages of TIR
PMW
and reanalysis data. Thus
it has the highest research value and potential for further research. Multisource data integration can be employed to obtain global long-time all-weather LST products characterized by spatial and temporal continuity. The LST retrieved from PMW remote sensing suffers from coarse spatial resolution and strip gaps. However
it is still an effective method of obtaining land surface information under clouds and an important input parameter for multisource data integration. The reconstructions of all-weather LST based on effective observation only apply to small areas with cloud cover in short periods. They are not practicable for long-term cloudy areas.
From the analysis and conclusion
this study also collects and analyzes information about five currently released all-weather surface temperature products. The advantages and disadvantages of the existing products are also summarized. A global all-weather LST product with high quality and spatial resolution is urgently needed by the scientific community. After reviewing the all-weather LST products
we further summarize the applications of all-weather LST. Its applications are still in their infancy. Research on the applications of all-weather LST is relatively small in the current stage. However
all-weather LST has great potential for applications when its products further mature.
Finally
further study directions and theoretical development of all-weather LST are discussed and prospected. First
with PMW LST as the basis for all-weather LST
two issues must be addressed: (i) filling the PMW LST strip gap to make the PMW surface temperature a complete spatial coverage; (ii) correcting thermal sampling depth to make that PMW LST obtain the same physical meaning as TIR LST. The reason is that the inconsistent observation caused by the varying thermal sampling depth is the actual reason for the inconsistent physical meaning of PMW and TIR observation information. Second
we should further strengthen the study on estimating all-weather LST from multisource data. The current study of multisource data integration is still in the preliminary stage
and no systematic and effective integration strategy has been developed. Third
the scientific community should enhance the production
publication
and application of all-weather LST products. Few all-weather LST products can be directly applied by users. Generating all-weather LST products with global spatial and temporal continuity and high spatial resolution should be the task of an all-weather LST study. Besides improving the data quality and reliability of all-weather LST
focusing on the operability and cost of the method in practical applications is necessary to make the all-weather LST usable data
thereby truly promoting the progress of the related studies.
遥感全天候地表温度重构插值多源数据集成
remote sensingall-weather land surface temperaturereconstructioninterpolationmulti-source data integration
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