MACHINE LEARNING BASED PREDICTION OF HYDROGEOLOGICAL PARAMETERS AND GROUNDWATER POTENTIAL INDEX USING GEOSPATIAL AND BOREHOLE DATA
提出融合地理空间与钻孔数据的机器学习框架，预测水文地质参数与地下水潜力指数。
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机器学习 土壤 遥感
Synergistic Use of Multitemporal SAR and Optical Data with Random Forest Approach for Rice Mapping in Bangladesh
融合Sentinel-1 SAR与Sentinel-2光学影像，用随机森林在GEE上绘制孟加拉国Bo
Spatial Modeling of Topsoil Total Carbon and Texture from Spectral Characteristics of Bare Soil Surface Images of Landsat 5/8 Using Machine Learning
用Landsat 5/8裸土光谱指数识别裸土并机器学习建模表层土壤质地与全碳。
Groundwater Potential Mapping in Northwestern Nigeria: A Comparison of the Analytic Hierarchy Process and Galileo-Enhanced CAT-XGB
对比专家驱动AHP与遥感基础模型增强的CAT-XGB集成，用于尼日利亚西北部地下水潜力制图。
Precision Agriculture in Maize Production Systematic Review 2026·10月9日 · 周五74 分 论文玉米智慧农业 / 农业物联网阅读 2
玉米生产精准农业系统综述：技术、应用与产量优化（2020—2026）
系统综述2020—2026年玉米精准农业技术、应用与产量优化研究。
Evaluation of risk scenarios in Ecuador using Visible Infrared Imaging Radiometer Suite remote sensing, ERA5-Land climate data, and XGBoost
结合VIIRS热异常、ERA5-Land气象数据与XGBoost，构建厄瓜多尔5公里分辨率森林火灾风
Machine-learning modelling of regional landslide susceptibility in eThekwini, South Africa
用随机森林与支持向量机评估南非eThekwini地区滑坡易发性并分析住房风险。
Cross-Regional Digital Soil Mapping of OpenLandMap-Derived USDA Soil Texture Classes Using Remote Sensing and Machine Learning
用Landsat光谱与地形特征结合集成学习，实现马来西亚与巴基斯坦跨区域USDA土壤质地分类。
GIS, Remote Sensing and Machine Learning Applications for Forest Fire Mapping, Susceptibility Assessment and Risk Analysis: A Systematic Review
GIS, Remote Sensing and Machine Learning Applications for Forest Fire Mapping, Susceptibility Assessment and Risk Analysis: A Systematic Review。Research Square
The effect of train-test data splitting ratio on yield prediction from multispectral UAV imagery: effective reduction of training ratio with algorithm selection for single- and multi-date models
研究不同训练-测试数据划分比例对无人机多光谱小麦产量预测的影响，发现可降低训练比例。
Applications of Artificial Intelligence in Soil Characterization and Agriculture: A Systematic Review
系统综述2018-2026年196项AI用于土壤特性与农业的研究。
Impervious Surface Classification Using Artificial Intelligence from Remote Sensing Imagery, Part I: Evaluation of Machine Learning Algorithms
用Landsat与Sentinel-2影像和三种机器学习算法自动分类胡志明市不透水面并监测15年变化
International Journal of Emerging Trends in Engineering and Development·10月2日 · 周五61 分 论文农业AI与大模型农业遥感与作物表型2 个信源同时报道 阅读 2
Comparative Performance of Machine Learning and Deep Learning Algorithms for Agricultural Land Mapping in Anambra State, Nigeria
比较RF、SVM、ANN、CNN在尼日利亚农业用地制图中的表现
A machine learning framework for predicting potential urban cool island locations using Landsat 9 data: a case study of Oued Zenati, Algeria
用遥感与可解释机器学习预测阿尔及利亚半干旱城市潜在城市冷岛位置。
Hyperspectral inversion of soil total nitrogen content using spectral and machine learning
用高光谱与机器学习反演陕北农牧交错带农田土壤全氮含量。
Species identification of crops and weeds in wheat fields using hyperspectral data and machine learning algorithms
利用高光谱数据与随机森林识别哈萨克斯坦东北部麦田作物与杂草，并分析误判的生物学原因。
Journal of Geography Environment and Earth Science International·9月25日 · 周五67 分 论文遥感与农情监测农业遥感与作物表型阅读 4
Spatial Estimation of Carbon Sequestration Using Remote Sensing and Its Application in Carbon-credit Assessment: A Comprehensive Review
综述遥感碳储量估算技术及其在碳信用评估中的应用与挑战。
Rice Cropping Pattern Mapping Using GEE-Based Sentinel-1/2 Time-Series Imagery and Machine Learning
基于GEE融合Sentinel-1/2时序与地形特征，用机器学习高精度制图长三角水稻种植模式。
Understanding Land Use/Land Cover Dynamics and Land Surface Temperature Variations Through Machine Learning and Geospatial Approach: A Case Study of Kullu District, Himachal Pradesh, India
用机器学习与遥感分析印度库鲁区1991-2022年土地利用变化及其对地表温度的影响。
Yield ranking of spring wheat breeding lines absent from model training within two contrasting seasons in northern Kazakhstan
评估春小麦育种品系产量模型在未参与训练品系上的跨季预测能力。
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。
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。
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
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。
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。
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。
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。
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
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。
《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。
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。
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。
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。
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。
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。
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。
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。
International Journal for Research in Applied Science and Engineering Technology·9月3日 · 周四49 分 论文GIS与空间分析农业遥感与作物表型阅读 1
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。
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
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。
Estimation of the Comprehensive High Photosynthetic-Efficiency Phenotypic Index in Winter Wheat Based on UAV Multimodal Remote Sensing Data
基于无人机多模态遥感数据，构建综合高光效表型指数并精准估算，用于小麦育种材料筛选。
International Journal of Environmental and Agriculture Research·8月31日 · 周一74 分 论文农业AI与大模型智慧农业 / 农业物联网阅读 2
Remote Sensing and Machine Learning for Futuristic Horticulture: A Comprehensive Review
综述遥感与机器学习在印度园艺作物精准管理中的应用，涵盖原理、方法、案例与挑战。