{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T21:46:02Z","timestamp":1768686362184,"version":"3.49.0"},"reference-count":56,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,3,30]],"date-time":"2024-03-30T00:00:00Z","timestamp":1711756800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of Jiangsu Province","award":["BK20230603"],"award-info":[{"award-number":["BK20230603"]}]},{"name":"Natural Science Foundation of Jiangsu Province","award":["2022PGE002"],"award-info":[{"award-number":["2022PGE002"]}]},{"name":"Natural Science Foundation of Jiangsu Province","award":["2020Z223"],"award-info":[{"award-number":["2020Z223"]}]},{"name":"Natural Science Foundation of Jiangsu Province","award":["2208085QD108"],"award-info":[{"award-number":["2208085QD108"]}]},{"name":"Foundation of Anhui Province Key Laboratory of Physical Geographic Environment, P.R. China","award":["BK20230603"],"award-info":[{"award-number":["BK20230603"]}]},{"name":"Foundation of Anhui Province Key Laboratory of Physical Geographic Environment, P.R. China","award":["2022PGE002"],"award-info":[{"award-number":["2022PGE002"]}]},{"name":"Foundation of Anhui Province Key Laboratory of Physical Geographic Environment, P.R. China","award":["2020Z223"],"award-info":[{"award-number":["2020Z223"]}]},{"name":"Foundation of Anhui Province Key Laboratory of Physical Geographic Environment, P.R. China","award":["2208085QD108"],"award-info":[{"award-number":["2208085QD108"]}]},{"name":"Postdoctoral Research Funding Program of Jiangsu Province","award":["BK20230603"],"award-info":[{"award-number":["BK20230603"]}]},{"name":"Postdoctoral Research Funding Program of Jiangsu Province","award":["2022PGE002"],"award-info":[{"award-number":["2022PGE002"]}]},{"name":"Postdoctoral Research Funding Program of Jiangsu Province","award":["2020Z223"],"award-info":[{"award-number":["2020Z223"]}]},{"name":"Postdoctoral Research Funding Program of Jiangsu Province","award":["2208085QD108"],"award-info":[{"award-number":["2208085QD108"]}]},{"name":"Natural Science Foundation of Anhui Province","award":["BK20230603"],"award-info":[{"award-number":["BK20230603"]}]},{"name":"Natural Science Foundation of Anhui Province","award":["2022PGE002"],"award-info":[{"award-number":["2022PGE002"]}]},{"name":"Natural Science Foundation of Anhui Province","award":["2020Z223"],"award-info":[{"award-number":["2020Z223"]}]},{"name":"Natural Science Foundation of Anhui Province","award":["2208085QD108"],"award-info":[{"award-number":["2208085QD108"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Soil moisture (SM) is a crucial environmental variable, and it plays an important role in energy and water cycles. SM data retrieval based on microwave satellite remote sensing has garnered significant attention due to its spatial continuity, wide observational coverage, and relatively low cost. Validating the accuracy of satellite remote sensing SM products is a critical step in enhancing data credibility, which plays a vital role in ensuring the effective application of satellite remote sensing data across various fields. Firstly, this study focused on Henan Province and evaluated the accuracy of the SMAP Enhanced L3 Radiometer Global and Polar Grid Daily 9 km EASE-Grid Soil Moisture (SPL3SMP_E) product along with its application in agriculture. The evaluation was based on in situ SM data from 55 stations in Henan Province. The assessment metrics used in this study include mean difference (MD), root mean square error (RMSE), unbiased root mean square error (ubRMSE), and the Pearson correlation coefficient (R). The time span of this study is from 2017 to 2020. The evaluation results indicated that the SPL3SMP_E soil moisture product performs well, as reflected by an ubRMSE value of 0.045 (m3\/m3), which was relatively close to the product\u2019s design accuracy of 0.04 (m3\/m3). Moreover, the accuracy of the product was unaffected by temporal factors, but the product exhibited strong spatial aggregation, which was closely related to land use types. Then, this study explored the response of the SPL3SMP_E product to irrigation signals. The precipitation and irrigation data from Henan Province were employed to investigate the response of the SPL3SMP_E soil moisture product to irrigation. Our findings revealed that the SPL3SMP_E soil moisture product was capable of capturing over 70% of irrigation events in the study area, indicating its high sensitivity to irrigation signals in this region. In this study, the SPL3SMP_E product was also employed for monitoring agricultural drought in Henan Province. The findings revealed that the collaborative use of the SPL3SMP_E soil moisture product and machine learning algorithms proves highly effective in monitoring significant drought events. Furthermore, the integration of multiple indices demonstrated a notable enhancement in the accuracy of drought monitoring. Such an evaluation holds significant implications for the effective application of satellite remote sensing SM data in agriculture and other domains.<\/jats:p>","DOI":"10.3390\/rs16071225","type":"journal-article","created":{"date-parts":[[2024,3,31]],"date-time":"2024-03-31T13:28:00Z","timestamp":1711891680000},"page":"1225","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Regional Assessment of Soil Moisture Active Passive Enhanced L3 Soil Moisture Product and Its Application in Agriculture"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9626-8436","authenticated-orcid":false,"given":"Liming","family":"Zhu","sequence":"first","affiliation":[{"name":"College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China"},{"name":"Foundation of Anhui Province Key Laboratory of Physical Geographic Environment, Chuzhou 239099, China"}]},{"given":"Guizhi","family":"Tian","sequence":"additional","affiliation":[{"name":"College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China"}]},{"given":"Huifeng","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China"}]},{"given":"Maohua","family":"Ding","sequence":"additional","affiliation":[{"name":"College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5725-0460","authenticated-orcid":false,"given":"A-Xing","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Geography, Nanjing Normal University, Nanjing 210023, China"},{"name":"Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210046, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210046, China"},{"name":"Department of Geography, University of Wisconsin-Madison, Madison, WI 53706, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6199-9298","authenticated-orcid":false,"given":"Tianwu","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Geography, Nanjing Normal University, Nanjing 210023, China"},{"name":"Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210046, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210046, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6","DOI":"10.2136\/sssaj2013.03.0093","article-title":"State of the Art in Large-Scale Soil Moisture Monitoring","volume":"77","author":"Ochsner","year":"2013","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_2","unstructured":"Mason, P.J., Zillman, J.W., and Simmons, A. (2009, January 7\u201318). Implementation plan for the global observing system for climate in support of the UNFCCC. Proceedings of the Conference of the Parties (COP), Copenhagen, Denmark."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"127610","DOI":"10.1016\/j.jhydrol.2022.127610","article-title":"Responses of spring soil moisture of different land use types to snow cover in Northeast China under climate change background","volume":"608","author":"Li","year":"2022","journal-title":"J. Hydrol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"107450","DOI":"10.1016\/j.agwat.2021.107450","article-title":"Assessing the performance of satellite soil moisture on agricultural drought monitoring in the North China Plain","volume":"263","author":"Cao","year":"2022","journal-title":"Agric. Water Manag."},{"key":"ref_5","first-page":"7852","article-title":"Soil moisture\u2013atmosphere feedback dominates land carbon uptake variability","volume":"592","author":"Vincent","year":"2021","journal-title":"Nature"},{"key":"ref_6","unstructured":"Chen, P., Duan, Y., and Liang, J. (2022, January 16\u201320). Soil Moisture Extraction Based on Time-Frequency Analysis. Proceedings of the International Conference in Communications, Seoul, Republic of Korea."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"112301","DOI":"10.1016\/j.rse.2021.112301","article-title":"Generating surface soil moisture at 30 m spatial resolution using both data fusion and machine learning toward better water resources management at the field scale","volume":"555","author":"Abowarda","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Luo, S. (2022). Dedicated Satellite Remote Sensing Combined with Global Navigation Satellite System Data Used to Remotely Measure the Status of Land Desertification, Yan\u2019an University, School of Physics and Electronics Information.","DOI":"10.1117\/1.JRS.16.015501"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"7039","DOI":"10.1080\/01431161.2022.2155080","article-title":"Fusion level of satellite and UAV image data for soil salinity inversion in the coastal area of the Yellow River Delta","volume":"43","author":"Ma","year":"2022","journal-title":"Int. J. Remote Sens."},{"key":"ref_10","first-page":"474","article-title":"Soil moisture retrieval from remote sensing","volume":"56","author":"Li","year":"2020","journal-title":"J. Beijing Norm. Univ."},{"key":"ref_11","first-page":"1728","article-title":"Progress and development trend of soil moisture microwave remote sensing retrieval method","volume":"23","author":"Qin","year":"2021","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1109\/JSTARS.2021.3124743","article-title":"Validation of soil moisture data products from the NASA SMAP mission","volume":"15","author":"Colliander","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.rse.2016.02.042","article-title":"Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation","volume":"180","author":"Kerr","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1109\/JPROC.2010.2043918","article-title":"The Soil Moisture Active Passive (SMAP) Mission","volume":"98","author":"Entekhabi","year":"2010","journal-title":"Proc. IEEE"},{"key":"ref_15","first-page":"404","article-title":"The advanced scatterometer (ASCAT) on the meteorological operational (MetOp) platform: A follow on for European wind scatterometers","volume":"28","author":"Wilson","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2565","DOI":"10.1109\/TGRS.2017.2763622","article-title":"Passive Microwave Rainfall Error Analysis Using High-Resolution X-Band Dual-Polarization Radar Observations in Complex Terrain","volume":"56","author":"Derin","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","first-page":"477","article-title":"Experimental Study of C Band Passive Microwave Remote Sensing of Soil Moisture","volume":"13","author":"Liu","year":"2013","journal-title":"Appl. Mech. Mater"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1109\/LGRS.2020.2976204","article-title":"Toward P-Band Passive Microwave Sensing of Soil Moisture","volume":"18","author":"Ye","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"112238","DOI":"10.1016\/j.rse.2020.112238","article-title":"SMOS-IC data record of soil moisture and L-VOD: Historical development, applications and perspectives","volume":"254","author":"Wigneron","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"113344","DOI":"10.1016\/j.rse.2022.113344","article-title":"An assessment of L-band surface soil moisture products from SMOS and SMAP in the tropical areas","volume":"284","author":"Ma","year":"2023","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4567","DOI":"10.5194\/hess-25-4567-2021","article-title":"Satellite soil moisture data assimilation for improved operational continental water balance prediction","volume":"25","author":"Tian","year":"2021","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Wen, Y., Zhao, J., Zhu, G., Xu, R., and Yang, J. (2021). Evaluation of the RF-Based Downscaled SMAP and SMOS Products Using Multi-Source Data over an Alpine Mountains Basin, Northwest China. Water, 13.","DOI":"10.3390\/w13202875"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Fernandez-Moran, R., Al-Yaari, A., Mialon, A., Mahmoodi, A., Al Bitar, A., De Lannoy, G., Rodriguez-Fernandez, N., Lopez-Baeza, E., Kerr, Y., and Wigneron, J.P. (2017). SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation Optical Depth Product. Remote Sens, 9.","DOI":"10.20944\/preprints201703.0145.v1"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4994","DOI":"10.1109\/TGRS.2016.2561938","article-title":"Assessment of the SMAP Passive Soil Moisture Product","volume":"54","author":"Chan","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhang, P., Yu, H., Gao, Y., and Zhang, Q. (2023). Evaluation of Remote Sensing and Reanalysis Products for Global Soil Moisture Characteristics. Sustainability, 15.","DOI":"10.3390\/su15119112"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1080\/22797254.2019.1579618","article-title":"Spatial evaluation of L-band satellite-based soil moisture products in the upper Huai River basin of China","volume":"52","author":"Zhu","year":"2019","journal-title":"Eur. J. Remote Sens."},{"key":"ref_27","first-page":"693172","article-title":"A triple collocation-based comparison of three L-band soil moisture datasets, SMAP, SMOS-IC, and SMOS, over varied climates and land covers","volume":"3","author":"Kim","year":"2021","journal-title":"Front. Environ. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Li, C., Lu, H., Yang, K., Han, M., Wright, J.S., Chen, Y., Yu, L., Xu, S., Huang, X., and Gong, W. (2018). The Evaluation of SMAP Enhanced Soil Moisture Products Using High-Resolution Model Simulations and In-Situ Observations on the Tibetan Plateau. Remote Sens., 10.","DOI":"10.3390\/rs10040535"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"11.860","DOI":"10.1002\/2017GL075733","article-title":"Irrigation Signals Detected From SMAP Soil Moisture Retrievals","volume":"44","author":"Lawston","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Zhu, L., and Zhu, A.X. (2021). Extraction of Irrigation Signals by Using SMAP Soil Moisture Data. Remote Sens, 13.","DOI":"10.3390\/rs13112142"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1080\/19475683.2019.1623318","article-title":"Estimation of LST from Multi-Sensor Thermal Remote Sensing Data and Evaluating the Influence of Sensor Characteristics","volume":"25","author":"Dar","year":"2019","journal-title":"Ann. GIS"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"104130","DOI":"10.1016\/j.advwatres.2022.104130","article-title":"Double-scale analysis on the detectability of irrigation signals from remote sensing soil moisture over an area with complex topography in central Italy","volume":"161","author":"Dari","year":"2022","journal-title":"Adv. Water Resour."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"G\u00f3mez, D.G., Ochoa, C.G., Godwin, D., Tomasek, A.A., and Re, M.I.Z. (2022). Soil Moisture and Water Transport through the Vadose Zone and into the Shallow Aquifer: Field Observations in Irrigated and Non-Irrigated Pasture Fields. Land, 11.","DOI":"10.3390\/land11112029"},{"key":"ref_34","first-page":"4500205","article-title":"Indicator of flood-irrigated crops from SMOS and SMAP soil moisture products in southern India","volume":"20","author":"Pascal","year":"2023","journal-title":"IEEE Geosci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"10","DOI":"10.3389\/fdata.2020.00010","article-title":"Agricultural Drought Monitoring via the Assimilation of SMAP Soil Moisture Retrievals into a Global Soil Water Balance Model","volume":"3","author":"Mladenova","year":"2020","journal-title":"Front. Big Data"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"15729","DOI":"10.3390\/rs71115729","article-title":"Evaluation of Satellite and Reanalysis Soil Moisture Products over Southwest China Using Ground-Based Measurements","volume":"7","author":"Peng","year":"2015","journal-title":"Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Lorenz, C., Montzka, C., Jagdhuber, T., Laux, P., and Kunstmann, H. (2018). Long-Term and High-Resolution Global Time Series of Brightness Temperature from Copula-Based Fusion of SMAP Enhanced and SMOS Data. Remote Sens., 10.","DOI":"10.3390\/rs10111842"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"O\u2019Neill, P., Chan, S., Colliander, A., Dunbar, S., Njoku, E., Bindlish, R., Chen, F., Jackson, T., Burgin, M., and Piepmeier, J. (2016, January 10\u201315). Evaluation of the validated Soil Moisture product from the SMAP radiometer. Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China.","DOI":"10.1109\/IGARSS.2016.7729023"},{"key":"ref_39","unstructured":"O\u2019Neill, P., and Chan, E. (2019). SMAP Enhanced L3 Radiometer Global Daily 9 km EASE-Grid Soil Moisture, NASA National Snow and Ice Data Center Distributed Active Archive Center. NASA\/SMAP\/SPL3SMP_E\/005."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Deng, K., Petropoulos, G.P., Bao, Y., Pavlides, A., Chaibou, A.S., and Habtemicheal, B.A. (2022). An Examination of the SMAP Operational Soil Moisture Products Accuracy at the Tibetan Plateau. Remote Sens., 24.","DOI":"10.3390\/rs14246255"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Khare, S., Latifi, H., and Khare, S. (2021). Vegetation Growth Analysis of UNESCO World Heritage Hyrcanian Forests Using Multi-Sensor Optical Remote Sensing Data. Remote Sens, 13.","DOI":"10.3390\/rs13193965"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1175\/2010JHM1223.1","article-title":"Performance metrics for soil moisture retrievals and application requirements","volume":"11","author":"Entekhabi","year":"2010","journal-title":"J. Hydrometeorol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"8955","DOI":"10.1109\/JSTARS.2021.3108432","article-title":"Evaluation of SMAP, SMOS, and AMSR2 soil moisture products based on distributed ground observation network in cold and arid regions of China","volume":"14","author":"Wang","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4463","DOI":"10.5194\/hess-19-4463-2015","article-title":"Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes","volume":"19","author":"Kumar","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"e2021WR030031","DOI":"10.1029\/2021WR030031","article-title":"Estimation of Global Irrigation Water Use by the Integration of Multiple Satellite Observations","volume":"58","author":"Zhang","year":"2022","journal-title":"Water Resour. Res."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Li, X., Xin, X., Jiao, J., Peng, Z., Zhang, H., Shao, S., and Liu, Q. (2017). Estimating Subpixel Surface Heat Fluxes through Applying Temperature-Sharpening Methods to MODIS Data. Remote Sens., 9.","DOI":"10.3390\/rs9080836"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"113272","DOI":"10.1016\/j.rse.2022.113272","article-title":"The first global soil moisture and vegetation optical depth product retrieved from fused SMOS and SMAP L-band observations","volume":"282","author":"Li","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.rse.2017.10.026","article-title":"Global-scale assessment and combination of SMAP with ASCAT (active) and AMSR2 (passive) soil moisture products","volume":"204","author":"Kim","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Nadeem, A.A., Zha, Y., Shi, L., Ran, G., Ali, S., Jahangir, Z., Afzal, M., and Awais, M. (2022). Multi-Scale Assessment of SMAP Level 3 and Level 4 Soil Moisture Products over the Soil Moisture Network within the ShanDian River (SMN-SDR) Basin, China. Remote Sens., 14.","DOI":"10.3390\/rs14040982"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1175\/JHM-D-19-0122.1","article-title":"Effect of Rainfall Events on SMAP Radiometer-Based Soil Moisture Accuracy Using Core Validation Sites","volume":"21","author":"Colliander","year":"2020","journal-title":"J. Hydrometeorol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1080\/19475683.2020.1812716","article-title":"Analysis of Spatiotemporal Variability of Water Productivity in Ethiopian Sugar Estates: Using Open Access Remote Sensing Source","volume":"26","author":"Gemechu","year":"2020","journal-title":"Ann. GIS"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Sawadogo, A., Kouadio, L., Traor\u00e9, F., Zwart, S.J., Hessels, T., and G\u00fcndogdu, K.S. (2020). Spatiotemporal Assessment of Irrigation Performance of the Kou Valley Irrigation Scheme in Burkina Faso Using Satellite Remote Sensing-Derived Indicators. ISPRS Int. J. Geoinf., 9.","DOI":"10.3390\/ijgi9080484"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.jhydrol.2009.12.041","article-title":"Variation of surficial soil hydraulic properties across land uses in the southern Blue Ridge Mountains, North Carolina, USA","volume":"383","author":"Price","year":"2009","journal-title":"J. Hydrol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"54","DOI":"10.3178\/hrl.16.54","article-title":"Impact of changes in the relationship between salinity and soil moisture on remote sensing data usage in northeast Thailand","volume":"16","author":"Masayasu","year":"2022","journal-title":"Hydrol. Res. Lett."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.rse.2015.03.008","article-title":"Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations","volume":"163","author":"Zeng","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Sun, Y., Huang, S., Ma, J., Li, J., Li, X., Wang, H., Chen, S., and Zang, W. (2017). Preliminary Evaluation of the SMAP Radiometer Soil Moisture Product over China Using In Situ Data. Remote Sens., 9.","DOI":"10.3390\/rs9030292"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/7\/1225\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:21:39Z","timestamp":1760106099000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/7\/1225"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,30]]},"references-count":56,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["rs16071225"],"URL":"https:\/\/doi.org\/10.3390\/rs16071225","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,30]]}}}