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A Framework for High-Spatiotemporal-Resolution Soil Moisture Retrieval in China Using Multi-Source Remote Sensing Data
Published 2024-12-01“…This indicates that multi-source data can provide complementary information for SM monitoring. (2) Compared to XGBoost and LSTM, RFR and EL demonstrate superior overall performance and are the preferred models for SM prediction. Their R<sup>2</sup> for the training and test sets exceed 0.969 and 0.743, respectively, and their ubRMSE are below 0.022 and 0.063 m<sup>3</sup>/m<sup>3</sup>, respectively. (3) The SM prediction accuracy is highest for the scenario of optical + SAR + auxiliary data, followed by SAR + auxiliary data, and finally optical + auxiliary data. (4) With an increasing Normalized Difference Vegetation Index (NDVI) and SM values, the trained models exhibit a general decrease in prediction performance and accuracy. (5) In 2021 and 2022, without considering cloud cover, the IF theoretically achieved an SM revisit time of 1–3 days across 95.01% and 96.53% of China’s area, respectively. …”
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Integrated analysis reveals that EGR1 promotes epithelial IL33 production in T2 asthma
Published 2025-02-01Get full text
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Trends, spatial distribution and determinants of maternal home deliveries in Zambia
Published 2025-04-01Get full text
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A 17.1 kb duplication downstream GATA6 is strongly associated with egg weight in chicken
Published 2025-08-01Get full text
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Risk factors for mild cognitive impairment in type 2 diabetes: a systematic review and meta-analysis
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Infrared Monocular Depth Estimation Based on Radiation Field Detail Enhancement
Published 2025-01-01Get full text
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