Spatial Representativeness of Soil Moisture Stations and Its Influential Factors at a Global Scale

The spatial representativeness error of in situ soil moisture (SM) is recognized as a major source of uncertainty when validating satellite SM products with a spatial resolution of tens of kilometers. Site underrepresentation is primarily caused by environmental heterogeneity, but their relationship...

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Published in:	IEEE transactions on geoscience and remote sensing Vol. 63; pp. 1 - 15
Main Authors:	Peng, Chenchen, Zeng, Jiangyuan, Chen, Kun-Shan, Ma, Hongliang, Letu, Husi, Zhang, Xiang, Shi, Pengfei, Bi, Haiyun
Format:	Journal Article
Language:	English
Published:	New York IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Collocation methods Correlation coefficient Correlation coefficients Environmental factors Environmental variables Evaluation global scale Heterogeneity In situ measurement Laboratories Land cover Land surface Moisture content Northern Hemisphere Plant cover Reliability Ridges Satellites Sea measurements Sensors site representativeness Soil Soil measurements Soil moisture soil moisture (SM) Soil properties Soil texture Spatial discrimination spatial heterogeneity Spatial resolution Surface topography Texture validation Variability Vegetation
ISSN:	0196-2892, 1558-0644
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Abstract	The spatial representativeness error of in situ soil moisture (SM) is recognized as a major source of uncertainty when validating satellite SM products with a spatial resolution of tens of kilometers. Site underrepresentation is primarily caused by environmental heterogeneity, but their relationship remains poorly understood. Here, we assessed the spatial representativeness of in situ SM from 322 strictly screened stations worldwide relative to coarse-resolution (~0.25°) satellite footprint based on the extended triple collocation (ETC) method. We then evaluated the influence of the heterogeneity of four environmental factors (soil texture, land cover types, elevation, and vegetation coverage) on site representativeness. Moreover, we calculated SM variability within the satellite footprint based on 1-km SM data to explore its relationship with environmental heterogeneity. Results indicate that about 63% of the sites have relatively good spatial representativeness (ETC-derived correlation coefficient <inline-formula> <tex-math notation="LaTeX">\ge 0.7 </tex-math></inline-formula>). Soil texture and land cover exhibit greater heterogeneity across the mid and high latitudes of the Northern Hemisphere. The larger heterogeneity in elevation and vegetation coverage is primarily found in regions with significant ridges and dense vegetation, respectively. Land cover is the major factor influencing the spatial representativeness of SM sites, and the increase in the heterogeneity of land cover enhances SM variability, which negatively impacts site representativeness. The in situ SM can be more representative when the proportion of the land cover type where the site is located is higher or when there are fewer land cover types within the satellite footprint. Moreover, it is found that the newly proposed metric of the similar area ratio of sites, as a measure of land cover heterogeneity, can effectively reflect SM variability. This metric can also serve as a supplementary criterion for selecting representative sites, particularly in situations where sites are sparse and the ETC method is inapplicable. These findings provide useful references for robust evaluation of satellite SM products based on in situ measurements (e.g., in situ SM upscaling and SM site deployment).
AbstractList	The spatial representativeness error of in situ soil moisture (SM) is recognized as a major source of uncertainty when validating satellite SM products with a spatial resolution of tens of kilometers. Site underrepresentation is primarily caused by environmental heterogeneity, but their relationship remains poorly understood. Here, we assessed the spatial representativeness of in situ SM from 322 strictly screened stations worldwide relative to coarse-resolution (~0.25°) satellite footprint based on the extended triple collocation (ETC) method. We then evaluated the influence of the heterogeneity of four environmental factors (soil texture, land cover types, elevation, and vegetation coverage) on site representativeness. Moreover, we calculated SM variability within the satellite footprint based on 1-km SM data to explore its relationship with environmental heterogeneity. Results indicate that about 63% of the sites have relatively good spatial representativeness (ETC-derived correlation coefficient <inline-formula> <tex-math notation="LaTeX">\ge 0.7 </tex-math></inline-formula>). Soil texture and land cover exhibit greater heterogeneity across the mid and high latitudes of the Northern Hemisphere. The larger heterogeneity in elevation and vegetation coverage is primarily found in regions with significant ridges and dense vegetation, respectively. Land cover is the major factor influencing the spatial representativeness of SM sites, and the increase in the heterogeneity of land cover enhances SM variability, which negatively impacts site representativeness. The in situ SM can be more representative when the proportion of the land cover type where the site is located is higher or when there are fewer land cover types within the satellite footprint. Moreover, it is found that the newly proposed metric of the similar area ratio of sites, as a measure of land cover heterogeneity, can effectively reflect SM variability. This metric can also serve as a supplementary criterion for selecting representative sites, particularly in situations where sites are sparse and the ETC method is inapplicable. These findings provide useful references for robust evaluation of satellite SM products based on in situ measurements (e.g., in situ SM upscaling and SM site deployment). The spatial representativeness error of in situ soil moisture (SM) is recognized as a major source of uncertainty when validating satellite SM products with a spatial resolution of tens of kilometers. Site underrepresentation is primarily caused by environmental heterogeneity, but their relationship remains poorly understood. Here, we assessed the spatial representativeness of in situ SM from 322 strictly screened stations worldwide relative to coarse-resolution (~0.25°) satellite footprint based on the extended triple collocation (ETC) method. We then evaluated the influence of the heterogeneity of four environmental factors (soil texture, land cover types, elevation, and vegetation coverage) on site representativeness. Moreover, we calculated SM variability within the satellite footprint based on 1-km SM data to explore its relationship with environmental heterogeneity. Results indicate that about 63% of the sites have relatively good spatial representativeness (ETC-derived correlation coefficient [Formula Omitted]). Soil texture and land cover exhibit greater heterogeneity across the mid and high latitudes of the Northern Hemisphere. The larger heterogeneity in elevation and vegetation coverage is primarily found in regions with significant ridges and dense vegetation, respectively. Land cover is the major factor influencing the spatial representativeness of SM sites, and the increase in the heterogeneity of land cover enhances SM variability, which negatively impacts site representativeness. The in situ SM can be more representative when the proportion of the land cover type where the site is located is higher or when there are fewer land cover types within the satellite footprint. Moreover, it is found that the newly proposed metric of the similar area ratio of sites, as a measure of land cover heterogeneity, can effectively reflect SM variability. This metric can also serve as a supplementary criterion for selecting representative sites, particularly in situations where sites are sparse and the ETC method is inapplicable. These findings provide useful references for robust evaluation of satellite SM products based on in situ measurements (e.g., in situ SM upscaling and SM site deployment).
Author	Shi, Pengfei Letu, Husi Chen, Kun-Shan Zeng, Jiangyuan Bi, Haiyun Peng, Chenchen Zhang, Xiang Ma, Hongliang
Author_xml	– sequence: 1 givenname: Chenchen orcidid: 0000-0002-0173-4669 surname: Peng fullname: Peng, Chenchen organization: State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China – sequence: 2 givenname: Jiangyuan orcidid: 0000-0002-5039-6774 surname: Zeng fullname: Zeng, Jiangyuan email: zengjy@radi.ac.cn organization: State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China – sequence: 3 givenname: Kun-Shan orcidid: 0000-0001-7698-9861 surname: Chen fullname: Chen, Kun-Shan organization: Institute of Space Earth Science, Nanjing University, Suzhou Campus, Suzhou, China – sequence: 4 givenname: Hongliang orcidid: 0000-0002-8260-8030 surname: Ma fullname: Ma, Hongliang organization: State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China – sequence: 5 givenname: Husi surname: Letu fullname: Letu, Husi organization: State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China – sequence: 6 givenname: Xiang orcidid: 0000-0002-1017-742X surname: Zhang fullname: Zhang, Xiang organization: National Engineering Research Center of Geographic Information Systems, School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, China – sequence: 7 givenname: Pengfei surname: Shi fullname: Shi, Pengfei organization: Yellow River Engineering Consulting Company Ltd., Zhengzhou, China – sequence: 8 givenname: Haiyun surname: Bi fullname: Bi, Haiyun organization: State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing, China
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SubjectTerms	Collocation methods Correlation coefficient Correlation coefficients Environmental factors Environmental variables Evaluation global scale Heterogeneity In situ measurement Laboratories Land cover Land surface Moisture content Northern Hemisphere Plant cover Reliability Ridges Satellites Sea measurements Sensors site representativeness Soil Soil measurements Soil moisture soil moisture (SM) Soil properties Soil texture Spatial discrimination spatial heterogeneity Spatial resolution Surface topography Texture validation Variability Vegetation
Title	Spatial Representativeness of Soil Moisture Stations and Its Influential Factors at a Global Scale
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