Exploring the Spatial Autocorrelation in Soil Moisture Networks: Analysis of the Bias from Upscaling the Texas Soil Observation Network (TxSON)
Microwave remote sensing such as soil moisture active passive (SMAP) can provide soil moisture data for agricultural and hydrological studies. However, the scales between station-measured and satellite-measured products are quite different, as stations measure on a point scale while satellites have...
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| Format: | Article |
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MDPI AG
2022-12-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/15/1/87 |
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| author | Yaping Xu Cuiling Liu Lei Wang Lei Zou |
| author_facet | Yaping Xu Cuiling Liu Lei Wang Lei Zou |
| author_sort | Yaping Xu |
| collection | DOAJ |
| description | Microwave remote sensing such as soil moisture active passive (SMAP) can provide soil moisture data for agricultural and hydrological studies. However, the scales between station-measured and satellite-measured products are quite different, as stations measure on a point scale while satellites have a much larger footprint (e.g., 9 km). Consequently, the validation for soil moisture products, especially inter-comparison between these two types of observations, is quite a challenge. Spatial autocorrelation among the stations could be a contribution of bias, which impacts the dense soil moisture networks when compared with satellite soil moisture products. To examine the effects of spatial autocorrelation to soil moisture upscaling models, this study proposes a spatial analysis approach for soil moisture ground observation upscaling and Thiessen polygon-based block kriging (TBP kriging) and compares the results with three other methods typically used in the current literature: arithmetic average, Thiessen polygon, and Gaussian-weighted average. Using the Texas Soil Observation Network (TxSON) as ground observation, this methodology detects spatial autocorrelation in the distribution of the stations that exist in dense soil moisture networks and improved the spatial modeling accuracy when carrying out upscaling tasks. The study concluded that through TBP kriging the minimum root-mean-square deviation (RMSD) is given where spatial autocorrelation takes place in the soil moisture stations. Through TBP kriging, the station-measured and satellite-measured soil moisture products are more comparable. |
| first_indexed | 2024-03-09T09:38:03Z |
| format | Article |
| id | doaj.art-a8df5e317a914d61844dd3bb5a648eda |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-09T09:38:03Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-a8df5e317a914d61844dd3bb5a648eda2023-12-02T01:14:06ZengMDPI AGWater2073-44412022-12-011518710.3390/w15010087Exploring the Spatial Autocorrelation in Soil Moisture Networks: Analysis of the Bias from Upscaling the Texas Soil Observation Network (TxSON)Yaping Xu0Cuiling Liu1Lei Wang2Lei Zou3Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USAUrban Informatics and Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, ChinaDepartment of Geography & Anthropology, Louisiana State University, Baton Rouge, LA 70803, USADepartment of Geography, Texas A&M University, College Station, TX 77843, USAMicrowave remote sensing such as soil moisture active passive (SMAP) can provide soil moisture data for agricultural and hydrological studies. However, the scales between station-measured and satellite-measured products are quite different, as stations measure on a point scale while satellites have a much larger footprint (e.g., 9 km). Consequently, the validation for soil moisture products, especially inter-comparison between these two types of observations, is quite a challenge. Spatial autocorrelation among the stations could be a contribution of bias, which impacts the dense soil moisture networks when compared with satellite soil moisture products. To examine the effects of spatial autocorrelation to soil moisture upscaling models, this study proposes a spatial analysis approach for soil moisture ground observation upscaling and Thiessen polygon-based block kriging (TBP kriging) and compares the results with three other methods typically used in the current literature: arithmetic average, Thiessen polygon, and Gaussian-weighted average. Using the Texas Soil Observation Network (TxSON) as ground observation, this methodology detects spatial autocorrelation in the distribution of the stations that exist in dense soil moisture networks and improved the spatial modeling accuracy when carrying out upscaling tasks. The study concluded that through TBP kriging the minimum root-mean-square deviation (RMSD) is given where spatial autocorrelation takes place in the soil moisture stations. Through TBP kriging, the station-measured and satellite-measured soil moisture products are more comparable.https://www.mdpi.com/2073-4441/15/1/87soil moisture upscalingsoil moisture active and passive (SMAP)TxSONsoil moisture networkspatial autocorrelationblock kriging |
| spellingShingle | Yaping Xu Cuiling Liu Lei Wang Lei Zou Exploring the Spatial Autocorrelation in Soil Moisture Networks: Analysis of the Bias from Upscaling the Texas Soil Observation Network (TxSON) Water soil moisture upscaling soil moisture active and passive (SMAP) TxSON soil moisture network spatial autocorrelation block kriging |
| title | Exploring the Spatial Autocorrelation in Soil Moisture Networks: Analysis of the Bias from Upscaling the Texas Soil Observation Network (TxSON) |
| title_full | Exploring the Spatial Autocorrelation in Soil Moisture Networks: Analysis of the Bias from Upscaling the Texas Soil Observation Network (TxSON) |
| title_fullStr | Exploring the Spatial Autocorrelation in Soil Moisture Networks: Analysis of the Bias from Upscaling the Texas Soil Observation Network (TxSON) |
| title_full_unstemmed | Exploring the Spatial Autocorrelation in Soil Moisture Networks: Analysis of the Bias from Upscaling the Texas Soil Observation Network (TxSON) |
| title_short | Exploring the Spatial Autocorrelation in Soil Moisture Networks: Analysis of the Bias from Upscaling the Texas Soil Observation Network (TxSON) |
| title_sort | exploring the spatial autocorrelation in soil moisture networks analysis of the bias from upscaling the texas soil observation network txson |
| topic | soil moisture upscaling soil moisture active and passive (SMAP) TxSON soil moisture network spatial autocorrelation block kriging |
| url | https://www.mdpi.com/2073-4441/15/1/87 |
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