Validation of SMAP surface soil moisture products with core validation sites

Colliander, Andreas; Jackson, Thomas J.; Bindlish, Rajat; Chan, S.; Das, Narendra N.; Kim, S.B.; Cosh, Michael H.; Dunbar, R. S.; Dang, Lan; Pashaian, L.; Asanuma, Jun; Aida, Kô; Berg, Aaron; Rowlandson, Tracy; Bosch, David D.; Caldwell, Todd; Caylor, K. K.; Goodrich, David C.; Jassar, Hala Al; López-Baeza, Ernesto; Martínez-Fernández, José; González-Zamora, Ángel; Livingston, Stanley; McNairn, Heather; Pacheco, Anna; Moghaddam, Mahta; Montzka, Carsten; Notarnicola, Claudia; Niedrist, Georg; Pellarin, Thierry; Prueger, John H.; Pulliainen, Jouni; Rautiainen, Kimmo; Ramos, Judith; Seyfried, M. S.; Starks, Patrick J.; Su, Zhongbo; Zeng, Yijian; Velde, R. van der; Thibeault, M.; Dorigo, Wouter; Vreugdenhil, Mariëtte; Walker, Jeffrey P.; Wu, Xiaoling; Monerris, A.; O'Neill, Peggy E.; Entekhabi, Dara; Njoku, E. G.; Yueh, Simon

doi:10.1016/j.rse.2017.01.021

Cited by 523 publications

(414 citation statements)

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“…Several point-scale soil moisture sensors have been already used to evaluate airborne active and passive L-band retrievals [18,78,82] and to validate SMOS [18,83], ASCAT [83], and AMSR2 products [14]. Data are available from the International Soil Moisture Network (ISMN) [39] and the TEODOOR data base [84], and is directly delivered to NASA for SMAP validation [85]. The Rur catchment CRNP network comprises ten probes (CRS1000, HydroInnova LLC, 2009) which were installed in 2011 and 2012 [86].…”

Section: Tereno Site Rur Catchmentmentioning

confidence: 99%

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Validation of Spaceborne and Modelled Surface Soil Moisture Products with Cosmic-Ray Neutron Probes

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Section: Tereno Site Rur Catchmentmentioning

confidence: 99%

“…The soil moisture observation network design comprises multiple sites, each with a 10-30 node cluster taking measurements from up to 4 sensors installed at different depths. Tonzi Ranch is FLUXNET/AmeriFlux, SoilSCAPE site and SMAP validation site as well [85].…”

Section: Tonzi Ranch California Usamentioning

confidence: 99%

Validation of Spaceborne and Modelled Surface Soil Moisture Products with Cosmic-Ray Neutron Probes

et al. 2017

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“…Numerous evaluation studies have been conducted using in situ measurements and model simulations on regional and global scales [31][32][33]. However, limited studies have been conducted in spatial and temporal heterogeneities in the state of Texas (e.g., [34,35]).…”

Section: Introductionmentioning

confidence: 99%

Evaluation and Inter-Comparison of Satellite Soil Moisture Products Using In Situ Observations over Texas, U.S.

Ray

Fares

et al. 2017

Water

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Abstract:The main goal of this study was to evaluate four major remote sensing soil moisture (SM) products over the state of Texas. These remote sensing products are: (i) the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) (2002( -September 2011; (ii) the Soil Moisture Ocean Salinity system (SMOS, 2010-present); (iii) AMSR2 (2012-present); and (iv) the Soil Moisture Active Passive system (SMAP, 2015-present). The quality of the generated SM data is influenced by the accuracy and precision of the sensors and the retrieval algorithms used in processing raw data. Therefore, it is important to evaluate the quality of these satellite SM products using in situ measurements and/or by inter-comparing their data during overlapping periods. In this study, these two approaches were used where we compared each satellite SM product to in situ soil moisture measurements and we also conducted an inter-comparison of the four satellite SM products at 15 different locations in Texas over six major land cover types (cropland, shrub, grassland, forest, pasture and developed) and eight climate zones along with in situ SM data from 15 Mesonet, USCRN and USDA-NRCS Scan stations. Results show that SM data from SMAP had the best correlation coefficients range from 0.37 to 0.92 with in situ measurements among the four tested satellite surface SM products. On the other hand, SM data from SMOS, AMSR2 and AMSR-E had moderate to low correlation coefficients ranges with in situ data, respectively, from 0.24-0.78, 0.07-0.62 and 0.05-0.52. During the overlapping periods, average root mean square errors (RMSEs) of the correlations between in situ and each satellite data were 0.13 (AMSR-E) and 0.13 (SMOS) cm 3 /cm 3 (2010-2011), 0.16 (AMSR2) and 0.14 (SMOS) cm 3 /cm 3 (2012-2016) and 0.13, 0.16, 0.14 (SMAP, AMSR2, SMOS) cm 3 /cm 3 (2015-2016), respectively. Despite the coarser spatial resolution of all four satellite products (25-36 km), their SM measurements are considered reasonable and can be effectively used for different applications, e.g., flood forecasting, and drought prediction; however, further evaluation of each satellite product is recommended prior to its use in practical applications.

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“…With the recently launched SMAP mission, more focus has been placed on the validation of the new SMAP product (e.g., [23][24][25]), and the results generally showed a very promising performance of SMAP, though continued bias (e.g., the bias ranged from −0.088 m 3 m −3 to 0.072 m 3 m −3 in [24] calculated from 13 core validation sites) is observed in the product. Very limited studies examine the quality of the Chinese FY3B soil moisture product.…”

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Soil Moisture Mapping from Satellites: An Intercomparison of SMAP, SMOS, FY3B, AMSR2, and ESA CCI over Two Dense Network Regions at Different Spatial Scales

et al. 2017

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Abstract:A good knowledge of the quality of the satellite soil moisture products is of great importance for their application and improvement. This paper examines the performance of eight satellite-based soil moisture products, including the Soil Moisture Active Passive (SMAP) passive Level 3 (L3), the Soil Moisture and Ocean Salinity (SMOS) Centre Aval de Traitement des Données SMOS (CATDS) L3, the Japan Aerospace Exploration Agency (JAXA) Advanced Microwave Scanning Radiometer 2 (AMSR2) L3, the Land Parameter Retrieval Model (LPRM) AMSR2 L3, the European Space Agency (ESA) Climate Change Initiative (CCI) L3, the Chinese Fengyun-3B (FY3B) L2 soil moisture products at a coarse resolution of~0.25 • , and the newly released SMAP enhanced passive L3 and JAXA AMSR2 L3 soil moisture products at a medium resolution of~0.1 • . The ground soil moisture used for validation were collected from two well-calibrated and dense networks, including the Little Washita Watershed (LWW) network in the United States and the REMEDHUS network in Spain, each with different land cover. The results show that the SMAP passive soil moisture product outperformed the other products in the LWW network region, with an unbiased root mean square (ubRMSE) of 0.027 m 3 m −3 , whereas the FY3B soil moisture performed the best in the REMEDHUS network region, with an ubRMSE of 0.025 m 3 m −3 . The JAXA product performed much better at 0.25 • than at 0.1 • , but at both resolutions it underestimated soil moisture most of the time (bias < −0.05 m 3 m −3 ). The SMAP-enhanced passive soil moisture product captured the temporal variation of ground measurements well, with a correlation coefficient larger than 0.8, and was generally superior to the JAXA product. The LPRM showed much larger amplitude and temporal variation than the ground soil moisture, with a wet bias larger than 0.09 m 3 m −3 . The underestimation of surface temperature may have contributed to the general dry bias found in the SMAP (−0.018 m 3 m −3 for LWW and 0.016 m 3 m −3 for REMEDHUS) and SMOS (−0.004 m 3 m −3 for LWW and −0.012 m 3 m −3 for REMEDHUS) soil moisture products. The ESA CCI product showed satisfactory performance with acceptable error metrics (ubRMSE < 0.045 m 3 m −3 ), revealing the effectiveness of merging active and passive soil moisture products. The good performance of SMAP and FY3B demonstrates the

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Validation of SMAP surface soil moisture products with core validation sites

Cited by 523 publications

References 77 publications

Validation of Spaceborne and Modelled Surface Soil Moisture Products with Cosmic-Ray Neutron Probes

Validation of Spaceborne and Modelled Surface Soil Moisture Products with Cosmic-Ray Neutron Probes

Evaluation and Inter-Comparison of Satellite Soil Moisture Products Using In Situ Observations over Texas, U.S.

Soil Moisture Mapping from Satellites: An Intercomparison of SMAP, SMOS, FY3B, AMSR2, and ESA CCI over Two Dense Network Regions at Different Spatial Scales

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