A review of remote sensing for agricultural drought: technologies, indices, modelling advances and future prospects
系统综述2015-2025年遥感农业干旱监测与预测的传感器、指数、建模及验证进展。
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#机器学习
Comparative analysis of gradient boosting and random forest regressors for nutrient prediction in smart agriculture
比较梯度提升与随机森林回归器，用水培传感器数据预测氮磷钾浓度。
Socio‐Economic Impact of Sustainable Development of Water Resources in the Semi‐Arid Regions of Village Raleras, Maharashtra: A Case Study Using Machine Learning Techniques
用机器学习评估印度半干旱村庄水资源可持续开发对农村生计的社会经济影响。
Predicting water quality in mine-affected environments: A hyperspectral remote sensing study in the Iberian pyrite Belt
用无人机高光谱与机器学习反演矿区酸性废水pH、硫酸盐和铁浓度。
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。
Microbiomes of soils and leafy vegetables in urban agriculture systems reflect crop management and local environmental conditions
研究城市农业中土壤与叶菜微生物组如何受管理措施和局地环境影响。
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
Land Use Change, Flood Exposure, and Vegetation Stress in the Chi River Basin, Northeast Thailand: A Multi-Temporal Remote Sensing and Machine Learning Assessment
用多时相遥感和机器学习评估泰国栖河流域土地利用变化、洪水暴露与植被胁迫的关系。
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
Integrated machine learning and AHP-based framework for spatial delineation of rainwater harvesting potential
结合GIS、AHP与多种机器学习算法，划分印度斋浦尔半干旱区雨水收集适宜性分区。
Machine learning reveals distinct drivers of soil organic carbon across the mountain-oasis-desert system of northwest China
构建基于生态系统的机器学习框架，预测西北荒漠-绿洲-山地系统土壤有机碳并识别各子系统驱动因子。
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。
Integrating multi-sensor optical and SAR data with machine learning ensembles for chickpea area estimation in the Krishna zone of Andhra Pradesh
融合光学与SAR多时相数据，用机器学习集成分类器估算安得拉邦鹰嘴豆种植面积。
Investigating climate-phenology relationships among the most common Italian forest species using Sentinel-2-derived vegetation phenology and productivity products
利用Sentinel-2物候与生产力产品，结合随机森林和SHAP，分析意大利主要森林物种的气候-物候