干旱区生态环境知识资源中心(Arid): Uncertainty quantification in land surface temperature retrieved from Himawari-8/AHI data by operational algorithms

Arid

DOI	10.1016/j.isprsjprs.2022.07.008
	Uncertainty quantification in land surface temperature retrieved from Himawari-8/AHI data by operational algorithms
	Yamamoto, Yuhei; Ichii, Kazuhito; Ryu, Youngryel; Kang, Minseok; Murayama, Shohei
通讯作者	Yamamoto, Y
来源期刊	ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
ISSN	0924-2716
EISSN	1872-8235
出版年	2022
卷号	191 页码:171-187
英文摘要	Himawari-8, a new-generation geostationary satellite, can retrieve sub-hourly land surface temperatures (LSTs) with moderate spatial resolution, providing a new scale for monitoring the thermal environment in Asia and Oceania. This study evaluated uncertainties of LSTs retrieved by three operational algorithms from Advanced Himawari Imager (AHI) data. We compared two nonlinear split-window algorithms (SOB and WAN algorithms) and one nonlinear three-band algorithm (YAM algorithm). First, the error characteristics of the retrieved LSTs caused by the input parameter errors were simulated under various land-atmospheric conditions using an atmospheric radiative transfer model. Thereafter, retrieved LSTs from actual AHI data were evaluated using in-situ observations from AsiaFlux and OzFlux networks and the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) LSTs. The simulated results showed that the YAM algorithm maintained the highest accuracy, whereas the WAN algorithm had the highest robustness to input errors. The YAM algorithm had the smallest total error including input errors over a wide range of retrieval conditions. Validation of the three algorithms via in-situ LSTs from 12 sites revealed nighttime mean RMSEs for all sites of similar to 1.7 degrees C, and daytime mean RMSEs for semi-arid and humid sites of approximately 3.0 degrees C and 2.0 degrees C, respectively. These are comparable to the accuracies reported for LST products with higher spatial resolutions, such as the Moderate Resolution Imaging Spectroradiometer and Landsat. Within the Himawari-8 disk, the estimation error of the YAM algorithm was similar to 1.0 degrees C lower than those of the SOB and WAN algorithms in regions with extremely high viewing angle, temperature, and humidity (e.g., northern China, Australia, and Southeast Asia). Furthermore, AHI LSTs showed closer agreement with ECOSTRESS compared to in-situ LSTs, suggesting the usefulness of ECOSTRESS for assessing the diurnal LSTs derived from geostationary satellites. The resulting LST products and the knowledge of their error characteristics have the potential to improve the collective understanding of terrestrial energy and water cycles based on improved accuracy and robustness.
英文关键词	Land surface temperature (LST) Advanced Himawari Imager (AHI) Himawari-8 ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) Validation
类型	Article
语种	英语
开放获取类型	hybrid
收录类别	SCI-E
WOS记录号	WOS:000834287400003
WOS关键词	EMISSIVITY SEPARATION ALGORITHM ; SPLIT-WINDOW ALGORITHM ; MARITIME CONTINENT ; MSG-SEVIRI ; ARID AREA ; MODIS ; PRODUCTS ; VALIDATION ; VIIRS ; RESOLUTION
WOS类目	Geography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/393244
推荐引用方式 GB/T 7714	Yamamoto, Yuhei,Ichii, Kazuhito,Ryu, Youngryel,et al. Uncertainty quantification in land surface temperature retrieved from Himawari-8/AHI data by operational algorithms[J],2022,191:171-187.
APA	Yamamoto, Yuhei,Ichii, Kazuhito,Ryu, Youngryel,Kang, Minseok,&Murayama, Shohei.(2022).Uncertainty quantification in land surface temperature retrieved from Himawari-8/AHI data by operational algorithms.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,191,171-187.
MLA	Yamamoto, Yuhei,et al."Uncertainty quantification in land surface temperature retrieved from Himawari-8/AHI data by operational algorithms".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 191(2022):171-187.