Research on the Inversion Method of Total Phosphorus Concentration in Water Bodies Based on PSO-Adam-BP Neural Network Model
用PSO-Adam-BP神经网络结合Sentinel-2影像反演白洋淀总磷浓度。
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UAV无人机高光谱图像土壤盐度制图(湿度校正)——MDPI Agronomy
用无人机高光谱结合Stacking集成模型实现湿度干扰下的土壤盐度制图。
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Annual Gridded Anthropogenic CH4 Emissions Estimation in China (2019–2025) Integrating Multisource Data: SHAP-Based Driver Attribution and Spatio-Temporal Patterns
融合多源数据与机器学习构建中国2019-2025年0.1°人为甲烷排放网格，并用SHAP解析驱动机制
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Application of Remote Sensing and Machine Learning in Sustainable Agriculture
综述遥感与机器学习在可持续农业中的应用现状与前景。
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Machine Learning-Based Prediction of Soil Moisture in Sikkim's High-Rainfall Zones Using Multimodal Remote Sensing Data
用多模态遥感与机器学习预测印度锡金高降雨区表层土壤水分。
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Hierarchical spectral ensemble with physics-informed augmentation for global water quality retrieval from hyperspectral remote sensing
提出分层光谱集成模型HSE，从高光谱遥感反射率中全球尺度反演四种水质参数。
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Spatio-temporal characteristics and driving factor identification of precipitation use efficiency: Based on machine learning and SHAP analysis
基于多源遥感与可解释机器学习，揭示东北寒区降水利用效率时空特征及驱动因子。
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Modeling Water Quality Parameters in Laga Dadi Reservoir, Ethiopia: An Integrated Remote Sensing and Machine Learning Approach
Modeling Water Quality Parameters in Laga Dadi Reservoir, Ethiopia: An Integrated Remote Sensing and Machine Learning Approach。Research Square
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MDPI Remote Sensing 18(18):3107 MODIS NDVI与机器学习作物产量预测比较研究
基于印度州级MODIS NDVI与机器学习比较作物产量预测，随机森林优于梯度提升。
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《基于遥感的农作物产量估算综述:机器学习技术及环境、算法和硬件限制》
系统综述遥感估产方法，分类传感器、平台、建模与机器学习，指出深度学习性能最优。
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Crop Yield Estimation with MODIS Derived Normalized Difference Vegetation Index and Comparative Study on Crop Yield Prediction Among Linear Regression, Random Forest and Gradient Boosting as Well as CatBoost
用MODIS NDVI与四种回归模型预测印度各邦作物产量，并做全国尺度验证。
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Spatial modeling of subsurface soil texture in semi-arid regions: Evaluating pure machine learning against hybrid regression kriging using Sentinel-1 and Sentinel-2 data
用Sentinel-1/2多时相数据结合纯机器学习与回归克里金，制图半干旱区30-40cm土壤质地。
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Estimation of Soil Total Nitrogen in Hemerocallis citrina Across Multiple Phenological Stages Using Partitioned Feature Bands
研究利用多传感器模拟光谱和三维指数，结合GA-BPNN，分物候期估算黄花菜土壤全氮，提高精度。
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Hydrochemistry and modeling nitrate concentration in farmland groundwater under different hydrological seasons by integrating hybrid quantum-classical ML, virtual sample generation and AlphaEarth Foundation
提出集成混合量子-经典机器学习、虚拟样本生成和遥感基础模型的框架，预测雄安农田地下水硝酸盐浓度。
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A novel surface reflectance calibration approach to improve the estimation of maize actual evapotranspiration in a semi-arid USA region
提出地表反射率校准方法，结合机器学习与双源像素分解，提高半干旱区玉米蒸散发估算精度。
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Improving Maize Yield Estimation Accuracy by Integrating Satellite Remote Sensing Data and the WOFOST Model Through Data Assimilation
通过数据同化整合卫星遥感与WOFOST模型，提高夏玉米产量估算精度。
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Integrating remote sensing and machine learning for forest fire susceptibility mapping in Peninsular Malaysia: the spatio-temporal sampling tree (STS-T)
提出时空采样树算法STS-T，用于马来西亚半岛森林火灾易发性制图，兼顾精度与可解释性。
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Random Forest-Based Groundwater Potential Zone Mapping in Latur District, Maharashtra, India
利用随机森林结合遥感与GIS绘制印度Latur地区地下水潜力图。
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Estimation of Agricultural Vegetation Water Stress Using Feature-Optimized Remote Sensing and Ensemble Machine Learning
Estimation of Agricultural Vegetation Water Stress Using Feature-Optimized Remote Sensing and Ensemble Machine Learning。Smart Agricultural Technology
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A dictionary-based method for crop yield prediction using satellite remote sensing data
提出基于HYDRA字典方法的机器学习框架，结合物候特征预测玉米产量。
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