Filter Set

    Using ISMN data:

  1. Abebrese, David Kwesi and Biney, James Kobina Mensah and Kara, Recep Serdar and Báťková, Kamila and Houška, Jakub and Matula, Svatopluk and Badreldin, Nasem and Truneh, Lemma Adane and Shawula, Tewodros Assefa (2023). Estimating the spatial distribution of soil volumetric water content in an agricultural field employing remote sensing and other auxiliary data under different tillage management practices. Soil Use and Management, 40, 1. 10.1111/sum.12981
  2. Araki, Ryoko, Mu, Ye, McMillan, Hilary (2023). Evaluation of GLDAS soil moisture seasonality in arid climates. Hydrological Sciences Journal, 1-18. 10.1080/02626667.2023.2206032
  3. A, Y. and Jiang, X. and Wang, Y. and Wang, L. and Zhang, Z. and Duan, L. and Fang, Q. (2023). Study on spatio-temporal simulation and prediction of regional deep soil moisture using machine learning. J Contam Hydrol, 258, 104235. 10.1016/j.jconhyd.2023.104235
  4. Batchu, Vishal, Nearing, Grey, Gulshan, Varun (2023). A Deep Learning Data Fusion Model using Sentinel-1/2, SoilGrids, SMAP-USDA, and GLDAS for Soil Moisture Retrieval. Journal of Hydrometeorology. 10.1175/jhm-d-22-0118.1
  5. Berthelin, Romane, Olarinoye, Tunde, Rinderer, Michael, Mudarra, Matías, Demand, Dominic, Scheller, Mirjam, Hartmann, Andreas (2023). Estimating karst groundwater recharge from soil moisture observations – a new method tested at the Swabian Alb, southwest Germany. Hydrology and Earth System Sciences, 27, 385-400. 10.5194/hess-27-385-2023
  6. Brunelli, Benedetta and De Giglio, Michaela and Magnani, Elisa and Dubbini, Marco (2023). Surface soil moisture estimate from Sentinel-1 and Sentinel-2 data in agricultural fields in areas of high vulnerability to climate variations: the Marche region (Italy) case study. Environment, Development and Sustainability, 1-23. 10.1007/s10668-023-03635-w
  7. Burnol, André, Armandine Les Landes, Antoine, Raucoules, Daniel, Foumelis, Michael, Allanic, Cécile, Paquet, Fabien, Maury, Julie, Aochi, Hideo, Guillon, Théophile, Delatre, Mickael, Dominique, Pascal, Bitri, Adnand, Lopez, Simon, Pébaÿ, Philippe P., Bazargan-Sabet, Behrooz (2023). Impacts of Water and Stress Transfers from Ground Surface on the Shallow Earthquake of 11 November 2019 at Le Teil (France). Remote Sensing, 15, 2270. 10.3390/rs15092270
  8. Chen, H. and Chen, P. and Wang, R. and Qiu, L. and Tang, F. and Xiong, M. (2023). Multi-Source Soil Moisture Data Fusion Based on Spherical Cap Harmonic Analysis and Helmert Variance Component Estimation in the Western U.S. Sensors (Basel), 23, 19, 8019. 10.3390/s23198019
  9. Corchia, Timothée and Bonan, Bertrand and Rodríguez-Fernández, Nemesio and Colas, Gabriel and Calvet, Jean-Christophe (2023). Assimilation of ASCAT Radar Backscatter Coefficients over Southwestern France. Remote Sensing, 15, 17, 4258. 10.3390/rs15174258
  10. Dai, Junjie and Zhu, Liujun and Walker, Jeffrey (2023). Machine Learning Methods for 1 km Soil Moisture Retrieval from Sentinel-1: An Evaluation with Limited Training Samples. 2023 IEEE International Radar Conference (RADAR), 1-5. 10.1109/RADAR54928.2023.10371043
  11. Deng, Xiaodong and Zhu, Luyao and Wang, Hongquan and Zhang, XianYun and Tong, Cheng and Li, Sinan and Wang, Ke (2023). Triple Collocation Analysis and In Situ Validation of the CYGNSS Soil Moisture Product. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 1883-1899. 10.1109/jstars.2023.3235111
  12. Ding, Qin and Liang, Yueji and Liang, Xingyong and Ren, Chao and Yan, Hongbo and Liu, Yintao and Zhang, Yan and Lu, Xianjian and Lai, Jianmin and Hu, Xinmiao (2023). Soil Moisture Retrieval Using GNSS-IR Based on Empirical Modal Decomposition and Cross-Correlation Satellite Selection. Remote Sensing, 15, 13, 3218. 10.3390/rs15133218
  13. Donahue, K. and Kimball, J. S. and Du, J. and Bunt, F. and Colliander, A. and Moghaddam, M. and Johnson, J. and Kim, Y. and Rawlins, M. A. (2023). Deep learning estimation of northern hemisphere soil freeze-thaw dynamics using satellite multi-frequency microwave brightness temperature observations. Front Big Data, 6, 1243559. 10.3389/fdata.2023.1243559
  14. Dong, Zhounan, Jin, Shuanggen, Chen, Guodong, Wang, Peng (2023). Enhancing GNSS-R Soil Moisture Accuracy with Vegetation and Roughness Correction. Atmosphere, 14, 509. 10.3390/atmos14030509
  15. Du, Jinyang, Kimball, John S., Chan, Steven K., Chaubell, Mario Julian, Bindlish, Rajat, Dunbar, R. Scott, Colliander, Andreas (2023). Assessment of Surface Fractional Water Impacts on SMAP Soil Moisture Retrieval. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 4871-4881. 10.1109/jstars.2023.3278686
  16. Eylander, John, Bieszczad, Jerry, Ueckermann, Mattheus, Peters, Joffrey, Brooks, Chris, Audette, William, Ekegren, Michael (2023). Geospatial Weather Affected Terrain Conditions and Hazards (GeoWATCH) description and evaluation. Environmental Modelling & Software, 160, 105606. 10.1016/j.envsoft.2022.105606
  17. Graldi, Giulia and Zardi, Dino and Vitti, Alfonso (2023). Retrieving Soil Moisture at the Field Scale from Sentinel-1 Data over a Semi-Arid Mediterranean Agricultural Area. Remote Sensing, 15, 12, 2997. 10.3390/rs15122997
  18. Han, Qianqian and Zeng, Yijian and Zhang, Lijie and Cira, Calimanut-Ionut and Prikaziuk, Egor and Duan, Ting and Wang, Chao and Szabó, Brigitta and Manfreda, Salvatore and Zhuang, Ruodan and Su, Bob (2023). Ensemble of optimised machine learning algorithms for predicting surface soil moisture content at a global scale. Geoscientific Model Development, 16, 20, 5825-5845. 10.5194/gmd-16-5825-2023
  19. Han, Q., Zeng, Y., Zhang, L., Wang, C., Prikaziuk, E., Niu, Z., Su, B. (2023). Global long term daily 1 km surface soil moisture dataset with physics informed machine learning. Sci Data, 10, 101. 10.1038/s41597-023-02011-7
  20. Hegazi, Ehab H., Samak, Abdellateif A., Yang, Lingbo, Huang, Ran, Huang, Jingfeng (2023). Prediction of Soil Moisture Content from Sentinel-2 Images Using Convolutional Neural Network (CNN). Agronomy, 13, 656. 10.3390/agronomy13030656
  21. Heyvaert, Zdenko, Scherrer, Samuel, Bechtold, Michel, Gruber, Alexander, Dorigo, Wouter, Kumar, Sujay, De Lannoy, Gabriëlle (2023). Impact of design factors for ESA CCI satellite soil moisture data assimilation over Europe. Journal of Hydrometeorology. 10.1175/jhm-d-22-0141.1
  22. Huang, Shuzhe, Zhang, Xiang, Wang, Chao, Chen, Nengcheng (2023). Two-step fusion method for generating 1 km seamless multi-layer soil moisture with high accuracy in the Qinghai-Tibet plateau. ISPRS Journal of Photogrammetry and Remote Sensing, 197, 346-363. 10.1016/j.isprsjprs.2023.02.009
  23. Huang, Xinyi and Feng, Shouming and Zhao, Shuaishuai and Fan, Jinlong and Qin, Zhihao and Zhao, Shuhe (2023). Assessment of Different Satellite Image-Derived Drought Indices over the Contiguous United States: A Comparison in Different Climates, Vegetation Cover Types, and Soil Layers. Water, 15, 20, 3634. 10.3390/w15203634
  24. Hulsman, P. and Keune, J. and Koppa, A. and Schellekens, J. and Miralles, D. G. (2023). Incorporating Plant Access to Groundwater in Existing Global, Satellite‐Based Evaporation Estimates. Water Resources Research, 59, 8, e2022WR033731. 10.1029/2022wr033731
  25. Hu, Lu, Zhao, Tianjie, Ju, Weimin, Peng, Zhiqing, Shi, Jiancheng, Rodríguez-Fernández, Nemesio J., Wigneron, Jean-Pierre, Cosh, Michael H., Yang, Kun, Lu, Hui, Yao, Panpan (2023). A twenty-year dataset of soil moisture and vegetation optical depth from AMSR-E/2 measurements using the multi-channel collaborative algorithm. Remote Sensing of Environment, 292, 113595. 10.1016/j.rse.2023.113595
  26. Hu, Yifan and Wang, Guojie and Wei, Xikun and Zhou, Feihong and Kattel, Giri and Amankwah, Solomon Obiri Yeboah and Hagan, Daniel Fiifi Tawia and Duan, Zheng (2023). Reconstructing long-term global satellite-based soil moisture data using deep learning method. Frontiers in Earth Science, 11, 1130853. 10.3389/feart.2023.1130853
  27. Jiang, K. and Pan, Z. and Pan, F. and Teuling, A. J. and Han, G. and An, P. and Chen, X. and Wang, J. and Song, Y. and Cheng, L. and Zhang, Z. and Huang, N. and Ma, S. and Gao, R. and Zhang, Z. and Men, J. and Lv, X. and Dong, Z. (2023). Combined influence of soil moisture and atmospheric humidity on land surface temperature under different climatic background. iScience, 26, 6, 106837. 10.1016/j.isci.2023.106837
  28. Karamvasis, Kleanthis and Karathanassi, Vassilia (2023). Soil moisture estimation from Sentinel-1 interferometric observations over arid regions. Computers & Geosciences, 178, 105410. 10.1016/j.cageo.2023.105410
  29. Lakshmi, Venkataraman, Le, Manh-Hung, Goffin, Benjamin D., Besnier, Jessica, Pham, Hung T., Do, Hong-Xuan, Fang, Bin, Mohammed, Ibrahim, Bolten, John D. (2023). Regional analysis of the 2015–16 Lower Mekong River basin drought using NASA satellite observations. Journal of Hydrology: Regional Studies, 46, 101362. 10.1016/j.ejrh.2023.101362
  30. Li, Ji and Leng, Guoyong and Peng, Jian (2023). The Merit of Estimating High-Resolution Soil Moisture Using Combined Optical, Thermal, and Microwave Data. IEEE Geoscience and Remote Sensing Letters, 20, 1-5. 10.1109/lgrs.2023.3291761
  31. Liu, Jiangtao, Hughes, David, Rahmani, Farshid, Lawson, Kathryn, Shen, Chaopeng (2023). Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats. Geoscientific Model Development, 16, 1553-1567. 10.5194/gmd-16-1553-2023
  32. Liu, Yi and Zhu, Ye and Ren, Liliang and Singh, Vijay P. and Yuan, Shanshui (2023). Flash drought fades away under the effect of accumulated water deficits: the persistence and transition to conventional drought. Environmental Research Letters, 18, 11, 114035. 10.1088/1748-9326/acfccb
  33. Liu, Yonghao and Li, Taohui and Zhang, Wenxiang and Lv, Aifeng (2023). Regionalization of Root Zone Moisture Estimations from Downscaled Surface Moisture and Environmental Data with the Soil Moisture Analytical Relationship Model. Water, 15, 23, 4133. 10.3390/w15234133
  34. Li, Zhenghao and Yuan, Qiangqiang and Zhang, Liangpei (2023). Geo-Intelligent Retrieval Framework Based on Machine Learning in the Cloud Environment: A Case Study of Soil Moisture Retrieval. IEEE Transactions on Geoscience and Remote Sensing, 61, 1-15. 10.1109/tgrs.2023.3280591
  35. Luo, Qidi and Liang, Yueji and Guo, Yue and Liang, Xingyong and Ren, Chao and Yue, Weiting and Zhu, Binglin and Jiang, Xueyu (2023). Enhancing Spatial Resolution of GNSS-R Soil Moisture Retrieval through XGBoost Algorithm-Based Downscaling Approach: A Case Study in the Southern United States. Remote Sensing, 15, 18, 4576. 10.3390/rs15184576
  36. Madelon, Remi, Rodríguez-Fernández, Nemesio J., Bazzi, Hassan, Baghdadi, Nicolas, Albergel, Clement, Dorigo, Wouter, Zribi, Mehrez (2023). Soil moisture estimates at 1 km resolution making a synergistic use of Sentinel data. Hydrology and Earth System Sciences, 27, 1221-1242. 10.5194/hess-27-1221-2023
  37. Ma, Hongliang, Li, Xiaojun, Zeng, Jiangyuan, Zhang, Xiang, Dong, Jianzhi, Chen, Nengcheng, Fan, Lei, Sadeghi, Morteza, Frappart, Frédéric, Liu, Xiangzhuo, Wang, Mengjia, Wang, Huan, Fu, Zheng, Xing, Zanpin, Ciais, Philippe, Wigneron, Jean-Pierre (2023). An assessment of L-band surface soil moisture products from SMOS and SMAP in the tropical areas. Remote Sensing of Environment, 284, 113344. 10.1016/j.rse.2022.113344
  38. Massart, Samuel and Vreugdenhil, Mariette and Bauer-Marschallinger, Bernhard and Navacchi, Claudio and Raml, Bernhard and Dostálová, Alena and Wagner, Wolfgang (2023). Mitigating the impact of dense vegetation on the Sentinel-1 surface soil moisture retrievals over Europe. . 10.1080/22797254.2023.2300985
  39. Mazzariello, A. and Albano, R. and Lacava, T. and Manfreda, S. and Sole, A. (2023). Intercomparison of recent microwave satellite soil moisture products on European ecoregions. Journal of Hydrology, 626, 130311. 10.1016/j.jhydrol.2023.130311
  40. Min, Xiaoxiao, Li, Danlu, Shangguan, YuLin, Tian, Shuo, Shi, Zhou (2023). Characterizing the accuracy of satellite-based products to detect soil moisture at the global scale. Geoderma, 432, 116388. 10.1016/j.geoderma.2023.116388
  41. Mi, Pei, Zheng, Chaolei, Jia, Li, Bai, Yu (2023). Reconstruction of Global Long-Term Gap-Free Daily Surface Soil Moisture from 2002 to 2020 Based on a Pixel-Wise Machine Learning Method. Remote Sensing, 15, 2116. 10.3390/rs15082116
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  43. Mohseni, Farzane and Ahrari, Amirhossein and Haunert, Jan-Henrik and Montzka, Carsten (2023). The synergies of SMAP enhanced and MODIS products in a random forest regression for estimating 1 km soil moisture over Africa using Google Earth Engine. Big Earth Data, 1-25. 10.1080/20964471.2023.2257905
  44. Nabi, M. M. and Senyurek, Volkan and Lei, Fangni and Kurum, Mehmet and Gurbuz, Ali Cafer (2023). Quasi-Global Assessment of Deep Learning-Based CYGNSS Soil Moisture Retrieval. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 5629-5644. 10.1109/jstars.2023.3287591
  45. Nadeem, Adeel Ahmad, Zha, Yuanyuan, Shi, Liangsheng, Ali, Shoaib, Wang, Xi, Zafar, Zeeshan, Afzal, Zeeshan, Tariq, Muhammad Atiq Ur Rehman (2023). Spatial Downscaling and Gap-Filling of SMAP Soil Moisture to High Resolution Using MODIS Surface Variables and Machine Learning Approaches over ShanDian River Basin, China. Remote Sensing, 15, 812. 10.3390/rs15030812
  46. Naz, Bibi S., Sharples, Wendy, Ma, Yueling, Goergen, Klaus, Kollet, Stefan (2023). Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe. Geoscientific Model Development, 16, 1617-1639. 10.5194/gmd-16-1617-2023
  47. Ning, Jing and Yao, Yunjun and Tang, Qingxin and Li, Yufu and Fisher, Joshua B. and Zhang, Xiaotong and Jia, Kun and Xu, Jia and Shang, Ke and Yang, Junming and Yu, Ruiyang and Liu, Lu and Zhang, Xueyi and Xie, Zijing and Fan, Jiahui (2023). Soil moisture at 30 m from multiple satellite datasets fused by random forest. Journal of Hydrology, 625, 130010. 10.1016/j.jhydrol.2023.130010
  48. Pasik, Adam and Gruber, Alexander and Preimesberger, Wolfgang and De Santis, Domenico and Dorigo, Wouter (2023). Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations. Geoscientific Model Development, 16, 17, 4957-4976. 10.5194/gmd-16-4957-2023
  49. Pavur, Gigi, Lakshmi, Venkataraman (2023). Observing the recent floods and drought in the Lake Victoria Basin using Earth observations and hydrological anomalies. Journal of Hydrology: Regional Studies, 46, 101347. 10.1016/j.ejrh.2023.101347
  50. Quast, Raphael and Wagner, Wolfgang and Bauer-Marschallinger, Bernhard and Vreugdenhil, Mariette (2023). Soil moisture retrieval from Sentinel-1 using a first-order radiative transfer model—A case-study over the Po-Valley. Remote Sensing of Environment, 295, 113651. 10.1016/j.rse.2023.113651
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  53. Scherrer, Samuel and De Lannoy, Gabriëlle and Heyvaert, Zdenko and Bechtold, Michel and Albergel, Clement and El-Madany, Tarek S. and Dorigo, Wouter (2023). Bias-blind and bias-aware assimilation of leaf area index into the Noah-MP land surface model over Europe. Hydrology and Earth System Sciences, 27, 22, 4087-4114. 10.5194/hess-27-4087-2023
  54. Shana, S. S., Sreenath, K. R., Sumithra, T. G., Krishnaveny, S. M. S., Joshi, K. K., Nameer, P. O., Gopalakrishnan, A. (2023). A Global-Scale Ecological Niche Modeling of the Emerging Pathogen Serratia marcescens to Aid in its Spatial Ecology. Curr Microbiol, 80, 59. 10.1007/s00284-022-03159-y
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