{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T04:49:14Z","timestamp":1771994954638,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2024,8,17]],"date-time":"2024-08-17T00:00:00Z","timestamp":1723852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"High-Resolution Earth Observation System Major Special Government Comprehensive Governance Application and Scale Industrialization Demonstration Project","award":["89-Y50G31-9001-22\/23-05"],"award-info":[{"award-number":["89-Y50G31-9001-22\/23-05"]}]},{"name":"LIESMARS Special Research Funding","award":["89-Y50G31-9001-22\/23-05"],"award-info":[{"award-number":["89-Y50G31-9001-22\/23-05"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Soil erodibility (K) refers to the inherent ability of soil to withstand erosion. Accurate estimation and spatial prediction of K values are vital for assessing soil erosion and managing land resources. However, as most K-value estimation models are empirical, they suffer from significant extrapolation uncertainty, and traditional studies on spatial prediction focusing on individual empirical K values have neglected to explore the spatial pattern differences between various empirical models. This work proposed a universal framework for selecting an optimal soil-erodibility map using empirical models enhanced by machine learning. Specifically, three empirical models, namely, the erosion-productivity impact calculator model (K_EPIC), the Shirazi model (K_Shirazi), and the Torri model (K_Torri) were used to estimate K values. Random Forest (RF) and Gradient-Boosting Decision Tree (GBDT) algorithms were employed to develop prediction models, which led to the creation of three K-value maps. The spatial distribution of K values and associated environmental covariates were also investigated across varying empirical models. Results showed that RF achieved the highest accuracy, with R2 of K_EPIC, K_Shirazi, and K_Torri increasing by 46%, 34%, and 22%, respectively, compared to GBDT. And distinctions among environmental variables that shape the spatial patterns of empirical models have been identified. The K_EPIC and K_Shirazi are influenced by soil porosity and soil moisture. The K_Torri is more sensitive to soil moisture conditions and terrain location. More importantly, our study has highlighted disparities in the spatial patterns across the three K-value maps. Considering the data distribution, spatial distribution, and measured K values, the K_Torri model outperformed others in estimating soil erodibility in the plateau lake watershed. This study proposed a framework that aimed to create optimal soil-erodibility maps and offered a scientific and accurate K-value estimation method for the assessment of soil erosion.<\/jats:p>","DOI":"10.3390\/rs16163017","type":"journal-article","created":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T05:19:36Z","timestamp":1724044776000},"page":"3017","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Optimal Mapping of Soil Erodibility in a Plateau Lake Watershed: Empirical Models Empowered by Machine Learning"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-2775-6469","authenticated-orcid":false,"given":"Jiaxue","family":"Wang","sequence":"first","affiliation":[{"name":"School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China"},{"name":"Soil Survey and Monitoring Lab of the Wuhan University, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7208-0068","authenticated-orcid":false,"given":"Yujiao","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China"},{"name":"Soil Survey and Monitoring Lab of the Wuhan University, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7847-4703","authenticated-orcid":false,"given":"Zheng","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China"},{"name":"Soil Survey and Monitoring Lab of the Wuhan University, Wuhan 430079, China"}]},{"given":"Shixiang","family":"Gu","sequence":"additional","affiliation":[{"name":"Yunnan Institute of Water and Hydropower Engineering Investigation, Design and Research, Kunming 650021, China"}]},{"given":"Shihan","family":"Bai","sequence":"additional","affiliation":[{"name":"Yunnan Institute of Water and Hydropower Engineering Investigation, Design and Research, Kunming 650021, China"}]},{"given":"Jinming","family":"Chen","sequence":"additional","affiliation":[{"name":"Yunnan Institute of Water and Hydropower Engineering Investigation, Design and Research, Kunming 650021, China"}]},{"given":"Jing","family":"Chen","sequence":"additional","affiliation":[{"name":"Yunnan Institute of Water and Hydropower Engineering Investigation, Design and Research, Kunming 650021, China"}]},{"given":"Yongsheng","family":"Hong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7442-3239","authenticated-orcid":false,"given":"Yiyun","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China"},{"name":"Soil Survey and Monitoring Lab of the Wuhan University, Wuhan 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1016\/S0160-4120(02)00192-7","article-title":"Soil Erosion and the Global Carbon Budget","volume":"29","author":"Lal","year":"2003","journal-title":"Environ. Int."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1261071","DOI":"10.1126\/science.1261071","article-title":"Soil and Human Security in the 21st Century","volume":"348","author":"Amundson","year":"2015","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1126\/science.1145724","article-title":"The Impact of Agricultural Soil Erosion on the Global Carbon Cycle","volume":"318","author":"Quine","year":"2007","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Qian, M., Zhou, W., Wang, S., Li, Y., and Cao, Y. (2022). The Influence of Soil Erodibility and Saturated Hydraulic Conductivity on Soil Nutrients in the Pingshuo Opencast Coalmine, China. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph19084762"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"953","DOI":"10.1016\/j.gsf.2015.10.007","article-title":"Assessment of Soil Erosion by RUSLE Model Using Remote Sensing and GIS\u2014A Case Study of Nethravathi Basin","volume":"7","author":"Ganasri","year":"2016","journal-title":"Geosci. Front."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1007\/s100219900035","article-title":"Ecology of Soil Erosion in Ecosystems","volume":"1","author":"Pimentel","year":"1998","journal-title":"Ecosystems"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"111","DOI":"10.5194\/soil-2-111-2016","article-title":"The Significance of Soils and Soil Science towards Realization of the United Nations Sustainable Development Goals","volume":"2","author":"Keesstra","year":"2016","journal-title":"SOIL"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Kastridis, A., Stathis, D., Sapountzis, M., and Theodosiou, G. (2022). Insect Outbreak and Long-Term Post-Fire Effects on Soil Erosion in Mediterranean Suburban Forest. Land, 11.","DOI":"10.3390\/land11060911"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Baartman, J.E.M., Nunes, J.P., van Delden, H., Vanhout, R., and Fleskens, L. (2022). The Effects of Soil Improving Cropping Systems (SICS) on Soil Erosion and Soil Organic Carbon Stocks across Europe: A Simulation Study. Land, 11.","DOI":"10.5194\/egusphere-egu22-2809"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.biosystemseng.2010.03.006","article-title":"Deducing the USLE Mathematical Structure by Dimensional Analysis and Self-Similarity Theory","volume":"106","author":"Ferro","year":"2010","journal-title":"Biosyst. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"145514","DOI":"10.1016\/j.scitotenv.2021.145514","article-title":"Effects of Vegetation and Climate on the Changes of Soil Erosion in the Loess Plateau of China","volume":"773","author":"Jin","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3255","DOI":"10.1007\/s12665-013-2390-3","article-title":"Application of the Revised Universal Soil Loss Equation Model on Landslide Prevention. An Example from N. Euboea (Evia) Island, Greece","volume":"70","author":"Rozos","year":"2013","journal-title":"Environ. Earth Sci."},{"key":"ref_13","first-page":"421","article-title":"The Erosion-Productivity Impact Calculator (EPIC) Model: A Case History","volume":"329","author":"Williams","year":"1997","journal-title":"Philos. Trans. R. Soc. Lond. B. Biol. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"142","DOI":"10.2136\/sssaj1984.03615995004800010026x","article-title":"A Unifying Quantitative Analysis of Soil Texture","volume":"48","author":"Shirazi","year":"1984","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0341-8162(97)00036-2","article-title":"Predictability and Uncertainty of the Soil Erodibility Factor Using a Global Dataset","volume":"31","author":"Torri","year":"1997","journal-title":"CATENA"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"107271","DOI":"10.1016\/j.catena.2023.107271","article-title":"Mapping Soil Erodibility over India","volume":"230","author":"Raj","year":"2023","journal-title":"CATENA"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.1038\/s41467-017-02142-7","article-title":"An Assessment of the Global Impact of 21st Century Land Use Change on Soil Erosion","volume":"8","author":"Borrelli","year":"2017","journal-title":"Nat. Commun."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1507","DOI":"10.5194\/se-9-1507-2018","article-title":"Soil Erodibility and Its Influencing Factors on the Loess Plateau of China: A Case Study in the Ansai Watershed","volume":"9","author":"Zhao","year":"2018","journal-title":"Solid Earth"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1016\/j.jaridenv.2007.11.018","article-title":"Soil Erodibility and Its Estimation for Agricultural Soils in China","volume":"72","author":"Zhang","year":"2008","journal-title":"J. Arid Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"103359","DOI":"10.1016\/j.earscirev.2020.103359","article-title":"Machine Learning for Digital Soil Mapping: Applications, Challenges and Suggested Solutions","volume":"210","author":"Wadoux","year":"2020","journal-title":"Earth-Sci. Rev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1111\/ejss.12909","article-title":"A Note on Knowledge Discovery and Machine Learning in Digital Soil Mapping","volume":"71","author":"Wadoux","year":"2019","journal-title":"Eur. J. Soil Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1071\/SR13297","article-title":"Deriving RUSLE Cover Factor from Time-Series Fractional Vegetation Cover for Hillslope Erosion Modelling in New South Wales","volume":"52","author":"Yang","year":"2014","journal-title":"Soil Res."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ding, J., Yang, S., Shi, Q., Wei, Y., and Wang, F. (2020). Using Apparent Electrical Conductivity as Indicator for Investigating Potential Spatial Variation of Soil Salinity across Seven Oases along Tarim River in Southern Xinjiang, China. Remote Sens., 12.","DOI":"10.3390\/rs12162601"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"e5714","DOI":"10.7717\/peerj.5714","article-title":"Machine-Learning-Based Quantitative Estimation of Soil Organic Carbon Content by VIS\/NIR Spectroscopy","volume":"6","author":"Ding","year":"2018","journal-title":"PeerJ"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.scitotenv.2014.02.010","article-title":"Soil Erodibility in Europe: A High-Resolution Dataset Based on LUCAS","volume":"479\u2013480","author":"Panagos","year":"2014","journal-title":"Sci. Total Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"116853","DOI":"10.1016\/j.geoderma.2024.116853","article-title":"High-Resolution Digital Mapping of Soil Erodibility in China","volume":"444","author":"Sun","year":"2024","journal-title":"Geoderma"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"106725","DOI":"10.1016\/j.catena.2022.106725","article-title":"High-Resolution Mapping and Driving Factors of Soil Erodibility in Southeastern Tibet","volume":"220","author":"Yu","year":"2023","journal-title":"CATENA"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Wang, S., Nie, X., Ran, F., Liao, W., Yang, C., Xiao, T., Liu, Y., Liu, Y., and Li, Z. (2023). Human Activities Control the Source of Eroded Organic Carbon in Lake Sediments over the Last 100 Years: Evidence from Stable Isotope Fingerprinting. Fundam. Res., 4.","DOI":"10.1016\/j.fmre.2023.04.015"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2218","DOI":"10.1111\/j.1365-2486.2012.02680.x","article-title":"Carbon Cycling in Eroding Landscapes: Geomorphic Controls on Soil Organic C Pool Composition and C Stabilization","volume":"18","author":"Doetterl","year":"2012","journal-title":"Glob. Change Biol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"107788","DOI":"10.1016\/j.envint.2023.107788","article-title":"Sediment Organic Carbon Dynamics Response to Land Use Change in Diverse Watershed Anthropogenic Activities","volume":"172","author":"Xiao","year":"2023","journal-title":"Environ. Int."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"126949","DOI":"10.1016\/j.jhydrol.2021.126949","article-title":"The Applicability of Commonly-Used Tracers in Identifying Eroded Organic Matter Sources","volume":"603","author":"Sun","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.scitotenv.2015.03.058","article-title":"Apportioning Sources of Organic Matter in Streambed Sediments: An Integrated Molecular and Compound-Specific Stable Isotope Approach","volume":"520","author":"Cooper","year":"2015","journal-title":"Sci. Total Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"106703","DOI":"10.1016\/j.catena.2022.106703","article-title":"Spatiotemporal Patterns and Drivers of Soil Erosion in Yunnan, Southwest China: RULSE Assessments for Recent 30 Years and Future Predictions Based on CMIP6","volume":"220","author":"Rao","year":"2023","journal-title":"CATENA"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"106108","DOI":"10.1016\/j.landusepol.2022.106108","article-title":"Positive Impacts of Farmland Fragmentation on Agricultural Production Efficiency in Qilu Lake Watershed: Implications for Appropriate Scale Management","volume":"117","author":"Yu","year":"2022","journal-title":"Land Use Policy"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Chen, J., Yang, X., Dao, H., Gu, H., Chen, G., Mao, C., Bai, S., Gu, S., Zhou, Z., and Yan, Z. (2024). Analyses on Characteristics of Spatial Distribution and Matching of the Human\u2013Land\u2013Water\u2013Heat System on the Yunnan Plateau. Water, 16.","DOI":"10.3390\/w16060867"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wei, Y., Chen, Y., Wang, J., Wang, B., Yu, P., Hong, Y., and Zhu, L. (2024). Unveiling the Explanatory Power of Environmental Variables in Soil Organic Carbon Mapping: A Global-Local Analysis Framework. Geoderma, accepted.","DOI":"10.1016\/j.geoderma.2024.117011"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Sun, Z., Liu, F., Wang, D., Wu, H., and Zhang, G. (2023). Improving 3D Digital Soil Mapping Based on Spatialized Lab Soil Spectral Information. Remote Sens., 15.","DOI":"10.3390\/rs15215228"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2046","DOI":"10.2136\/sssaj2000.6462046x","article-title":"Modeling Soil\u2013Landscape and Ecosystem Properties Using Terrain Attributes","volume":"64","author":"Gessler","year":"2000","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_39","unstructured":"McGarigal, K.S., Cushman, S., Neel, M., and Ene, E. (2002). FRAGSTATS: Spatial Pattern Analysis Program for Categorical Maps, University of Massachusetts."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1007\/s10980-009-9327-y","article-title":"Surface Metrics: An Alternative to Patch Metrics for the Quantification of Landscape Structure","volume":"24","author":"McGarigal","year":"2009","journal-title":"Landsc. Ecol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"105897","DOI":"10.1016\/j.still.2023.105897","article-title":"Assessing Spatial Variations in Soil Organic Carbon and C: N Ratio in Northeast China\u2019s Black Soil Region: Insights from Landsat-9 Satellite and Crop Growth Information","volume":"235","author":"Geng","year":"2024","journal-title":"Soil Tillage Res."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Zhang, X., Xue, J., Chen, S., Wang, N., Xie, T., Xiao, Y., Chen, X., Shi, Z., Huang, Y., and Zhuo, Z. (2023). Fine Resolution Mapping of Soil Organic Carbon in Croplands with Feature Selection and Machine Learning in Northeast Plain China. Remote Sens., 15.","DOI":"10.3390\/rs15205033"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/j.ecolmodel.2007.05.011","article-title":"Random Forests as a Tool for Ecohydrological Distribution Modelling","volume":"207","author":"Peters","year":"2007","journal-title":"Ecol. Model."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1002\/rra.1247","article-title":"Predicting the Natural Flow Regime: Models for Assessing Hydrological Alteration in Streams","volume":"26","author":"Carlisle","year":"2009","journal-title":"River Res. Appl."},{"key":"ref_45","unstructured":"Ke, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W., Ye, Q., and Liu, T.Y. (2017, January 7\u20139). LightGBM: A Highly Efficient Gradient Boosting Decision Tree. Proceedings of the 31st International Conference on Neural Information Processing Systems, Long Beach, CA, USA."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy Function Approximation: A Gradient Boosting Machine","volume":"29","author":"Friedman","year":"2001","journal-title":"Ann. Stat."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"142120","DOI":"10.1016\/j.scitotenv.2020.142120","article-title":"Mapping Farmland Soil Organic Carbon Density in Plains with Combined Cropping System Extracted from NDVI Time-Series Data","volume":"754","author":"Wu","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.still.2016.12.010","article-title":"Assessment of Gravelly Soil Redistribution Caused by a Two-Tooth Harrow in Mountainous Landscapes of the Yunnan-Guizhou Plateau, China","volume":"168","author":"Jia","year":"2017","journal-title":"Soil Tillage Res."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.still.2004.05.006","article-title":"Short and Medium Term Assessment of Tillage Erosion in the Uluguru Mountains, Tanzania","volume":"81","author":"Kimaro","year":"2005","journal-title":"Soil Tillage Res."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.still.2007.06.009","article-title":"Soil Translocation by Weeding on Steep-Slope Swidden Fields in Northern Vietnam","volume":"96","author":"Ziegler","year":"2007","journal-title":"Soil Tillage Res."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.catena.2018.05.032","article-title":"Dynamic Changes of Soil Erosion in a Typical Disturbance Zone of China\u2019s Three Gorges Reservoir","volume":"169","author":"Bao","year":"2018","journal-title":"CATENA"},{"key":"ref_52","unstructured":"Lollino, G., Arattano, M., Rinaldi, M., Giustolisi, O., Marechal, J.C., and Grant, G.E. (2015). Monitoring Program of Reservoir Bank Erosion at Porto Primavera Dam, Parana River, SP\/MS, Brazil. Engineering Geology for Society and Territory, Springer International Publishing."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1139\/l01-018","article-title":"Effects of Simulated Water Level Management on Shore Erosion Rates. Case Study: Baskatong Reservoir, Qu\u00e9bec, Canada","volume":"28","author":"Touileb","year":"2001","journal-title":"Can. J. Civ. Eng."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.catena.2014.01.008","article-title":"Use and Misuse of the K Factor Equation in Soil Erosion Modeling: An Alternative Equation for Determining USLE Nomograph Soil Erodibility Values","volume":"118","author":"Auerswald","year":"2014","journal-title":"CATENA"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.geoderma.2012.05.005","article-title":"Soil Erodibility Mapping and Its Correlation with Soil Properties in Central Chile","volume":"189\u2013190","author":"Bonilla","year":"2012","journal-title":"Geoderma"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1080\/10106049.2015.1073368","article-title":"Spatial Variability of Soil Erodibility and Its Correlation with Soil Properties in Semi-Arid Mountainous Watershed, Saudi Arabia","volume":"31","author":"Mallick","year":"2016","journal-title":"Geocarto Int."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1016\/j.catena.2018.03.002","article-title":"The Importance of Soil Data Availability on Erosion Modeling","volume":"165","author":"Efthimiou","year":"2018","journal-title":"CATENA"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1002\/saj2.20022","article-title":"Nitrogen Fertilization Changes the Molecular Composition of Soil Organic Matter in a Subtropical Plantation Forest","volume":"84","author":"Geng","year":"2020","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1688","DOI":"10.1080\/03650340.2019.1575509","article-title":"Soil Erodibility and Its Prediction in Semi-Arid Regions","volume":"65","author":"Ostovari","year":"2019","journal-title":"Arch. Agron. Soil Sci."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.still.2018.11.001","article-title":"Soil Carbon Stocks under Different Land Uses and the Applicability of the Soil Carbon Saturation Concept","volume":"188","author":"Chen","year":"2019","journal-title":"Soil Tillage Res."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1007\/s10457-007-9044-y","article-title":"Evaluation and Selection of Multipurpose Tree for Improving Soil Hydro-Physical Behaviour under Hilly Eco-System of North East India","volume":"69","author":"Saha","year":"2007","journal-title":"Agrofor. Syst."},{"key":"ref_62","first-page":"185","article-title":"Uncertainty in Prediction of Soil Erodibility K-Factor in Subtropical China","volume":"46","author":"Zhang","year":"2009","journal-title":"Acta Pedol. Sin."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"116996","DOI":"10.1016\/j.geoderma.2024.116996","article-title":"On the Parsimony, Interpretability, and Predictive Capability of a Physically-Based Model in the Optical Domain for Estimating Soil Moisture Content","volume":"49","author":"Zhang","year":"2024","journal-title":"Geoderma"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/16\/3017\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:38:15Z","timestamp":1760110695000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/16\/3017"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,17]]},"references-count":63,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2024,8]]}},"alternative-id":["rs16163017"],"URL":"https:\/\/doi.org\/10.3390\/rs16163017","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,17]]}}}