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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#机器学习
Pollution-driven surface water quality improvement and expanding population benefits in karst regions of China
用遥感与机器学习评估中国喀斯特地区地表水水质长期变化及受益人口。
An optimized machine learning approach for reliable agronomic parameter prediction in precision farming systems
提出优化机器学习框架，用土壤环境数据预测农艺参数并分类菠菜生长阶段。
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
Optimizing biochar application strategies to improve soil properties and crop productivity in salt-affected croplands: Evidence from a global meta-analysis and machine learning approach
Optimizing biochar application strategies to improve soil properties and crop productivity in salt-affected croplands: Evidence from a global meta-analysis and machine learning approach。Agricultural Systems
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。
MDPI Agriculture 16(17):1932 厄瓜多尔农场级玉米产量模型空间可迁移性研究
评估三种机器学习模型在厄瓜多尔农场级玉米产量预测中的空间可迁移性。
《数字经济参与与农场扩张:来自中国主要粮食产区农地租赁市场进入和经营耕地面积的证据》
基于四省1025户调查，研究农户数字经济参与是否促进农场扩张。
《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。
Comparative evaluation of classical machine learning and deep learning models for early weed detection in precision agriculture
对比经典机器学习与深度学习模型在精准农业早期杂草检测中的性能。
Smart biosensing ecosystems: Integrating nanotechnology, chemometrics, and machine learning for precision analytical applications
综述提出智能生物传感生态系统，融合纳米材料、化学计量学、机器学习与物联网，实现精准分析。
From Farm to Fork: Integrating Smart Farming Data with Isotopic and Spectroscopic Analysis for Food Authentication and Traceability
综述将精准农业采前数据与光谱、同位素分析结合，构建从农场到餐桌的食品溯源与真伪鉴别框架。
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。
Multi-scale drivers of wildfire burn severity in Central Zagros: insights from remote sensing and machine learning
结合遥感与机器学习，量化伊朗扎格罗斯中部野火烧毁严重度的多尺度驱动因素。
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。
Intelligent Prediction of Spray Distribution and Hydraulic Behavior in an Automatic Spraying Machine for Precision Agriculture
用机器学习预测自动喷雾机的流量、喷幅、角度和重叠，实现精准农业。
APPLICATION OF ARTIFICIAL INTELLIGENCE IN SOIL FERTILITY ASSESSMENT AND CROP YIELD PREDICTION IN SOUTHWEST NIGERIA: A STATISTICAL APPROACH
研究AI在尼日利亚西南部土壤肥力评估和作物产量预测中的应用，发现随机森林模型表现最佳。