Arid
DOI10.1109/LGRS.2024.3366211
A Vegetation-Temperature-Radiation-Composite Method for Downscaling Soil Moisture
Kong, Xuechun; Meng, Xiangjin; Guluzade, Rufat; Hu, Penghua; Yang, Yingbao
通讯作者Yang, YB
来源期刊IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
ISSN1545-598X
EISSN1558-0571
出版年2024
卷号21
英文摘要To address limitations in regional-scale applications of passive microwave remote sensing soil moisture (SM) products, various downscaling methods have been proposed to enhance the spatial resolution of SM. Nonetheless, these downscaled methods, which are based on optical and thermal infrared data, face challenges in vegetated areas and are prone to inaccuracies due to cloud cover affecting ancillary data. In response to these challenges, we introduced a novel approach termed the vegetation-temperature-radiation-composite (VTRC) method. This method recognizes the robust interaction between vegetation and SM and also appreciates the high sensitivity of surface temperature variation to surface net solar radiation (SSR) in relation to SM. Besides, the VTRC method combines ERA5 data with its high temporal resolution and MODIS data to counteract data loss due to cloud coverage. Applied to downscale the ESA CCI SM products from 0.25 degrees to 0.01 degrees spatial resolution, the VTRC method is validated over Castilla y Leon (Spain) and Anhui province (China). The VTRC method demonstrates a significant improvement compared to the feature space-based downscaled method and the original ESA CCI products, achieving higher correlation coefficient ( $R$ ) of 0.56 and 0.66 $\text{m}<^>{3}/\text{m}<^>{3}$ in humid and semi-arid regions with ground observations, respectively. Furthermore, it maintains a consistent unbiased root mean square error (ub RMSE) of 0.05 $\text{m}<^>{3}/\text{m}<^>{3}$ in both regions. Additionally, the inclusion of vegetation information notably improves the accuracy in comparison to solely using land surface temperature (LST) and SSR. Significantly, evaluations across varying vegetation cover surfaces revealed enhanced accuracy, especially in regions with abundant vegetation.
英文关键词Vegetation mapping Spatial resolution Microwave theory and techniques Meteorology Land surface Indexes Optical sensors Downscaling ERA5 radiation information soil moisture (SM) vegetation cover
类型Article
语种英语
收录类别SCI-E
WOS记录号WOS:001173135800004
WOS关键词SURFACE-TEMPERATURE
WOS类目Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向Geochemistry & Geophysics ; Engineering ; 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/2XILL650/404135
推荐引用方式
GB/T 7714
Kong, Xuechun,Meng, Xiangjin,Guluzade, Rufat,et al. A Vegetation-Temperature-Radiation-Composite Method for Downscaling Soil Moisture[J],2024,21.
APA Kong, Xuechun,Meng, Xiangjin,Guluzade, Rufat,Hu, Penghua,&Yang, Yingbao.(2024).A Vegetation-Temperature-Radiation-Composite Method for Downscaling Soil Moisture.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,21.
MLA Kong, Xuechun,et al."A Vegetation-Temperature-Radiation-Composite Method for Downscaling Soil Moisture".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 21(2024).
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