[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2679":3,"related-2679":120},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":90,"slug":93,"view_count":21,"doi":94,"paper":95,"created_at":119},2679,"Space Science and Technology for Sustainable Development and Climate Resilience in Africa: A Review of Emerging Applications and Challenges","https:\u002F\u002Fdoi.org\u002F10.62292\u002Fnjp.v35(s).2026.731","This study undertakes a systematic review to examine the role of space science and technology in addressing Africa’s pressing challenges in agriculture, water management, disaster resilience, urbanization, and digital inclusion. Evaluating how Earth Observation, satellite navigation, and communication technologies contribute to achieving the Sustainable Development Goals (SDGs) being its main objective. The review draws on secondary sources, including peer‑reviewed journals, space agency reports, and global datasets, with content analysis employed to identify thematic applications and emerging trends. The analysis highlights major themes: precision agriculture, groundwater mapping, urban growth monitoring, disaster early warning systems, climate adaptation, natural resource conservation, and digital inclusion. Case studies from Kenya, Nigeria, Ethiopia, Rwanda, and Mozambique demonstrate measurable benefits, including strengthened food security, improved water resource management, guided infrastructure planning, and enhanced resilience to climate‑induced hazards. Institutional initiatives by the National Space Research and Development Agency (NASRDA) in Nigeria and the African Space Agency further illustrate Africa’s growing commitment to harnessing space technologies for socio‑economic transformation. Despite these advances, more still needs to be done to meet the international standard. Persistent barriers affecting Africa include limited funding, dependence on external datasets, and shortages of technical expertise, which constrain the scalability and sustainability of interventions. Future directions should prioritize investment in indigenous satellite missions, expansion of STEM education, and regional cooperation to build capacity and ensure data sovereignty. Overall, the review underscores that space science offers Africa a strategic pathway to resilience, innovation, and inclusive growth, positioning the continent to accelerate progress toward the SDGs and secure a sustainable future.","本研究开展系统性综述，考察空间科学技术在应对非洲农业、水资源管理、灾害韧性、城市化及数字包容等紧迫挑战中的作用。其主要目标是评估地球观测、卫星导航与通信技术如何助力实现可持续发展目标（SDGs）。本综述基于二手资料，包括同行评审期刊、航天机构报告及全球数据集，并采用内容分析法识别主题性应用与新兴趋势。分析凸显了若干主要主题：精准农业、地下水测绘、城市扩张监测、灾害预警系统、气候适应、自然资源保护及数字包容。来自肯尼亚、尼日利亚、埃塞俄比亚、卢旺达和莫桑比克的案例研究展示了可衡量的效益，包括增强粮食安全、改善水资源管理、指导基础设施规划以及提升对气候诱发灾害的韧性。尼日利亚国家空间研究与发展局（NASRDA）及非洲航天局的机构性举措进一步表明，非洲日益致力于利用空间技术推动社会经济转型。尽管取得了这些进展，但要达到国际标准仍需付出更多努力。影响非洲的持续障碍包括资金有限、依赖外部数据集以及技术专长短缺，这些因素制约了干预措施的可扩展性与可持续性。未来方向应优先投资于本土卫星任务、扩大STEM教育以及区域合作，以建设能力并确保数据主权。总体而言，本综述强调，空间科学为非洲提供了一条通往韧性、创新与包容性增长的战略路径，使该大陆能够加速实现可持续发展目标的进程并确保可持续的未来。",null,"Nigerian Journal of Physics","2026-09-16T00:00:00Z","论文",10,false,78,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":13,"relevant":21,"comment":22},18,20,17,13,1,"系统综述空间科技在非洲农业、水资源与灾害韧性中的应用与瓶颈，含多国案例与机构实践，对农业遥感与数字乡村议题有参考价值，但属域外经验、非国内政策或产业突破。",[24],{"name":10,"url":6},[26,27,28,29,30],"数字乡村","精准农业","非洲农业","遥感","气候韧性",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,52,59,67,74,80,85],{"code":32,"score":45,"supported":46,"title":47,"abstract":49,"tags":51},12,true,[48],"climate resilience",[50],"气候适应",[30],{"code":53,"score":54,"supported":46,"title":55,"abstract":56,"tags":58},"I1",7,[],[27,57],"precision agriculture",[27],{"code":60,"score":61,"supported":46,"title":62,"abstract":63,"tags":66},"A8",6,[],[64,65],"粮食安全","food security",[],{"code":68,"score":61,"supported":46,"title":69,"abstract":70,"tags":73},"H3",[],[71,72],"水资源","water resource",[],{"code":75,"score":76,"supported":46,"title":77,"abstract":78,"tags":79},"J3",4,[],[28],[28],{"code":81,"score":21,"supported":14,"title":82,"abstract":83,"tags":84},"I3",[],[],[29],{"code":86,"score":21,"supported":14,"title":87,"abstract":88,"tags":89},"I6",[],[],[26],[91,92],"数字乡村 气候韧性 精准农业 非洲农业","数字乡村 气候韧性","数字乡村气候韧性精准农业非洲农业-2679","10.62292\u002Fnjp.v35(s).2026.731",{"doi":94,"openalex_id":96,"authors":97,"venue":10,"cited_by_count":110,"oa_url":6,"card":111,"direction":117,"ingested_from":118},"W7213235414",[98,100,102,104,106,108],{"name":99,"orcid":9},"Rufus Oladosu Olakunle",{"name":101,"orcid":9},"Abdulrahman Adegbite",{"name":103,"orcid":9},"Harry Obimba",{"name":105,"orcid":9},"Tosin Awotoye",{"name":107,"orcid":9},"Linda Abegunde",{"name":109,"orcid":9},"Jamiu Taiwo Aileru",0,{"tldr":112,"method":113,"finding":114,"direction":115,"opportunity":116},"系统综述空间科技在非洲农业、水资源、减灾等领域应用及挑战。","系统综述二手文献与机构报告，内容分析提炼主题与案例。","空间科技显著提升非洲粮食安全与水管理，但受资金、数据依赖和人才短缺制约。","农业遥感与作物表型","可研究非洲本土卫星数据主权与低成本遥感在精准农业中的适配机制。","数字乡村与农业信息化","openalex","2026-09-16T23:30:36.955820Z",{"total":61,"page":21,"page_size":61,"items":121},[122,192,284,355,420,489],{"id":123,"title":124,"url":125,"summary":126,"summary_zh":9,"content":9,"source_name":127,"source_url":9,"published_at":128,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":129,"score_detail":130,"sources":135,"tags":137,"primary_topic":141,"secondary_topics":142,"classification":148,"search_phrases":178,"slug":181,"view_count":182,"doi":9,"paper":183,"created_at":191},3121,"Optimization of Farmland Management Zoning in the Black Soil Region: A Climate Adaptability Assessment Considering Crop Growth Response and Topographic Characteristics（黑土区农田管理分区优化：考虑作物生长响应与地形特征的气候适应性评估）","https:\u002F\u002Fwww.mdpi.com\u002F2072-4292\u002F18\u002F18\u002F3260","吉林农业大学 Han Yongqi 等联合中科院东北地理与农业生态研究所、东北农业大学在《Remote Sensing》18(18): 3260 发表论文（2026-09-21 发表）。针对精准农业管理分区对单日期影像依赖难以捕捉年际作物环境变化问题，研究评估 29 个特征组合（融合 Sentinel-2 多光谱、PCA、NDVI 和 DEM 数据）在黑土区友谊农场干旱、湿润和融合场景下的气候适应性。实施异构空间注意力网络（HSAN）和 K-means 聚类，以变异系数（CV）评估稳定性与适应性。结果显示 HSAN 在多源融合下优于 K-means，CV 分别为 11.303-14.774% 与 14.823-16.011%；多期 NDVI 数据是主导因素，相对 CV 减少 34.850-53.701%；DEM 贡献有限；PCA 增强稳定性；多期融合在极端气候年份提升分区生态一致性与适用性。","MDPI Remote Sensing","2026-09-21T00:00:00Z",79,{"impact":131,"substance":132,"depth":17,"authority":133,"freshness":13,"relevant":21,"comment":134},15,22,14,"黑土区精准农业管理分区研究，方法新颖、数据扎实，对农业遥感应用有参考价值。",[136],{"name":127,"url":125},[138,27,139,29,140],"智慧农业","黑土区","管理分区",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[143],{"code":144,"slug":145,"name":146,"path":147,"parent_code":36},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",{"status":39,"locked":14,"version":40,"method":41,"evidence":149},{"candidates":150,"agricultural_evidence":46},[151,156,161,166,171],{"code":32,"score":133,"supported":46,"title":152,"abstract":153,"tags":155},[50],[50,154],"干旱",[],{"code":144,"score":157,"supported":46,"title":158,"abstract":159,"tags":160},8,[145],[],[],{"code":53,"score":162,"supported":46,"title":163,"abstract":164,"tags":165},5,[],[27],[138,27],{"code":81,"score":76,"supported":46,"title":167,"abstract":168,"tags":170},[],[169],"remote sensing",[29],{"code":172,"score":173,"supported":46,"title":174,"abstract":175,"tags":177},"H6",3,[],[176],"农业生态",[],[179,180],"黑土区 管理分区 遥感","Sentinel-2 黑土区 气候适应性","黑土区管理分区遥感-3121",2,{"doi":9,"openalex_id":9,"authors":184,"venue":9,"cited_by_count":110,"oa_url":9,"card":185,"direction":115,"ingested_from":190},[],{"tldr":186,"method":187,"finding":188,"direction":115,"opportunity":189},"评估黑土区多源遥感特征组合在干旱湿润场景下的农田管理分区气候适应性。","融合Sentinel-2多光谱、NDVI、PCA与DEM，用HSAN和K-mea","HSAN优于K-means，多期NDVI主导稳定性提升，DEM贡献有限，PCA增强稳定性。","可探索多期时序特征与深度聚类在极端气候下的跨区域迁移及分区决策落地。","agent","2026-09-22T00:05:38.189091Z",{"id":193,"title":194,"url":195,"summary":196,"summary_zh":197,"content":9,"source_name":198,"source_url":195,"published_at":199,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":200,"score_detail":201,"sources":205,"tags":207,"primary_topic":211,"secondary_topics":212,"classification":223,"search_phrases":261,"slug":264,"view_count":21,"doi":265,"paper":266,"created_at":283},2945,"Assessing spatial suitability and climate resilience of agroforestry systems in the Indian Himalaya of Uttarakhand using remote sensing and artificial neural networks","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44415-026-00113-9","Agroforestry systems are widely recognized for their capacity to enhance ecological sustainability, livelihood security, and climate resilience in mountain environments. However, their spatial suitability and long-term resilience under changing climatic conditions remain poorly quantified in the Indian Himalaya. This study assesses the spatial suitability and climate resilience of agroforestry systems in Uttarakhand using an integrated framework of remote sensing, geographic information systems (GIS), and artificial neural networks (ANNs). Landsat 8 OLI imagery (30 m resolution) was classified using a supervised Gaussian Maximum Likelihood Classifier (MLC), while land-use categories were defined based on a modified Anderson Level I\u002FII classification scheme to represent the heterogeneous Himalayan landscape. Field surveys conducted across representative agroecological zones documented the composition of tree and crop species within prevailing agroforestry systems. A multi-criteria land suitability analysis, guided by FAO (Food and Agriculture Organization of the United Nations) principles, was implemented using key biophysical variables including altitude, slope, aspect, Normalized Difference Vegetation Index (NDVI), soil properties, temperature, and precipitation. Future agroforestry patterns were simulated using an ANN model under RCP 4.5 climate scenarios. The model demonstrated strong predictive performance, indicating reliable simulation of agroforestry distribution. Results show that mid-altitudinal zones offer the highest suitability for agroforestry expansion, whereas small and fragmented systems exhibit reduced climate resilience under future projections. The findings provide a spatially explicit framework to support climate-resilient agroforestry planning and policy formulation in the Himalayan region.","农林复合系统因其在山区环境中提升生态可持续性、生计安全及气候适应能力方面的作用而受到广泛认可。然而，在印度喜马拉雅地区，其空间适宜性及气候变化条件下的长期适应能力仍缺乏充分的量化评估。本研究采用遥感、地理信息系统（GIS）与人工神经网络（ANN）相结合的综合框架，评估了北阿坎德邦农林复合系统的空间适宜性与气候适应能力。利用监督式高斯最大似然分类器（MLC）对Landsat 8 OLI影像（30 m分辨率）进行分类，同时基于改进的Anderson一级\u002F二级分类方案界定土地利用类别，以表征喜马拉雅地区异质性景观。在代表性农业生态区开展实地调查，记录了现有农林复合系统中树种和作物物种的组成。依据联合国粮食及农业组织（FAO）原则，采用多准则土地适宜性分析，纳入海拔、坡度、坡向、归一化植被指数（NDVI）、土壤属性、温度和降水等关键生物物理变量。利用ANN模型在RCP 4.5气候情景下模拟未来农林复合系统格局。模型表现出较强的预测性能，表明对农林复合系统分布的模拟可靠。结果表明，中海拔区域为农林复合系统扩展提供了最高的适宜性，而小型和破碎化系统在未来预测情景下表现出较低的气候适应能力。研究结果为喜马拉雅地区气候适应型农林复合系统规划与政策制定提供了空间明确的框架支持。","Discover Forests","2026-09-18T00:00:00Z",72,{"impact":45,"substance":202,"depth":19,"authority":20,"freshness":203,"relevant":21,"comment":204},21,9,"遥感与人工神经网络结合评估喜马拉雅地区农林复合系统空间适宜性与气候韧性，方法新颖、结论有区域政策参考价值，但属境外区域研究，公共影响有限。",[206],{"name":198,"url":195},[208,29,30,209,210],"农业人工智能","土地适宜性","农林复合经营",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[213,218],{"code":81,"slug":214,"name":215,"path":216,"parent_code":217},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",{"code":219,"slug":220,"name":221,"path":222,"parent_code":217},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis",{"status":39,"locked":14,"version":40,"method":41,"evidence":224},{"candidates":225,"agricultural_evidence":46},[226,231,235,242,247,251,256],{"code":32,"score":17,"supported":46,"title":227,"abstract":228,"tags":230},[48],[229,50,48],"气候变化",[30],{"code":81,"score":131,"supported":46,"title":232,"abstract":233,"tags":234},[169],[29,169],[29],{"code":219,"score":203,"supported":46,"title":236,"abstract":237,"tags":241},[],[238,239,240],"地理信息","GIS","geographic information",[],{"code":144,"score":61,"supported":46,"title":243,"abstract":244,"tags":246},[],[245,145],"土壤",[],{"code":172,"score":173,"supported":46,"title":248,"abstract":249,"tags":250},[],[176],[],{"code":252,"score":21,"supported":14,"title":253,"abstract":254,"tags":255},"H1",[],[],[209],{"code":257,"score":21,"supported":14,"title":258,"abstract":259,"tags":260},"I2",[],[],[208],[262,263],"Uttarakhand 农林复合系统 遥感","印度喜马拉雅 人工神经网络 土地适宜性","Uttarakhand农林复合系统遥感-2945","10.1007\u002Fs44415-026-00113-9",{"doi":265,"openalex_id":267,"authors":268,"venue":198,"cited_by_count":110,"oa_url":195,"card":278,"direction":115,"ingested_from":118},"W7213553408",[269,271,273,276],{"name":270,"orcid":9},"Deepak Kumar Mishra",{"name":272,"orcid":9},"Ujjwal Kumar",{"name":274,"orcid":275},"A. Arunachalam","https:\u002F\u002Forcid.org\u002F0000-0001-6590-4113",{"name":277,"orcid":9},"Ayyanadar Arunachalam",{"tldr":279,"method":280,"finding":281,"direction":115,"opportunity":282},"结合遥感、GIS与人工神经网络评估印度喜马拉雅地区农林复合系统的空间适宜性与气候韧性。","Landsat 8影像监督分类、FAO多准则适宜性分析、ANN在RCP4.5情景","中海拔区最适宜农林复合扩展，小而破碎系统在未来气候下韧性较低。","可将该遥感-ANN框架迁移至中国山区，耦合多情景气候与农户数据优化农林复合布局。","2026-09-19T23:30:33.082917Z",{"id":285,"title":286,"url":287,"summary":288,"summary_zh":289,"content":9,"source_name":290,"source_url":287,"published_at":291,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":292,"score_detail":293,"sources":296,"tags":298,"primary_topic":302,"secondary_topics":303,"classification":304,"search_phrases":336,"slug":339,"view_count":110,"doi":340,"paper":341,"created_at":354},5476,"Digital Transformation of Haryana Agriculture: Strengthening Climate Resilience and Advancing the Sustainable Development Goals","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23491288","Climate change has surfaced as one of the most pivotal challenges confronting the agricultural sector, especially in agrarian regions vulnerable to resource degradation, water scarcity, and climate uncertainties. Haryana, a leading agricultural state in India, has faced significant environmental pressures in recent years, including declining groundwater levels, erratic rainfall patterns, rising temperatures, and soil degradation, necessitating the adoption of climate-resilient agricultural strategies. Against this backdrop, Information and Communication Technology has gained considerable importance as a transformative mechanism for strengthening agricultural sustainability, adaptive capacity, and informed decision-making among farmers. ICT-enabled interventions such as mobile-based advisory services, precision farming technologies, digital marketplaces, weather forecasting systems, remote sensing, and various e-governance platforms have increasingly contributed to improving agricultural efficiency and resilience. The present study aims to evaluate the role of ICT-enabled agricultural practices in Haryana and their contribution to climate resilience and to achieve the Sustainable Development Goals. This study applies a descriptive and analytical approach, drawing on secondary data and narrative review methodology. The study utilizes secondary data from government reports, policy documents, research articles, institutional publications, and international development reports on digital agriculture, climate change, and sustainable development, published between 2016 and 2026. The findings indicate that ICT-based agricultural innovations have substantially enhanced access to climate information, improved resource-use efficiency, increased market connectivity, and enabled adaptive agricultural management practices. Furthermore, ICT interventions have significant potential to support SDG 2: Zero Hunger, SDG 9: Industry, Innovation and Infrastructure, and SDG 13: Climate Action. However, challenges such as digital illiteracy, infrastructural disparities, limited technological accessibility among smallholders, and inadequate institutional support continue to hinder widespread adoption. The study emphasizes the need for inclusive digital policies, strengthened rural ICT infrastructure, farmer-centric skill development, and integrated climate-smart agricultural frameworks to facilitate sustainable, resilient agricultural development in Haryana.","气候变化已成为农业部门面临的最关键挑战之一，在易受资源退化、水资源短缺和气候不确定性影响的农业区域尤为如此。哈里亚纳邦是印度领先的农业邦，近年来面临显著的环境压力，包括地下水位下降、降雨模式不稳定、气温上升和土壤退化，因而亟需采取气候韧性农业策略。在此背景下，信息与通信技术（ICT）作为增强农业可持续性、适应能力以及农民知情决策的变革性机制，其重要性日益凸显。基于ICT的干预措施，如移动端咨询服务、精准农业技术、数字市场、天气预报系统、遥感以及各类电子治理平台，已日益为提升农业效率和韧性作出贡献。本研究旨在评估哈里亚纳邦基于ICT的农业实践所发挥的作用及其对气候韧性和实现可持续发展目标的贡献。本研究采用描述性与分析性方法，依托二手数据和叙述性综述方法。研究使用的二手数据来源于2016年至2026年间发布的政府报告、政策文件、研究论文、机构出版物以及关于数字农业、气候变化和可持续发展的国际发展报告。研究结果表明，基于ICT的农业创新大幅提升了气候信息的获取能力，改善了资源利用效率，增强了市场连通性，并促成了适应性农业管理实践。此外，ICT干预措施在支持可持续发展目标2：零饥饿、目标9：产业、创新和基础设施以及目标13：气候行动方面具有显著潜力。然而，数字文盲、基础设施差距、小农户技术可及性有限以及机构支持不足等挑战仍阻碍其广泛采用。研究强调，需要制定包容性数字政策、加强农村ICT基础设施、开展以农民为中心的技能培养以及构建综合气候智慧型农业框架，以促进哈里亚纳邦可持续且具有韧性的农业发展。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-20T00:00:00Z",70,{"impact":294,"substance":17,"depth":131,"authority":45,"freshness":203,"relevant":21,"comment":295},16,"基于二手数据的综述性研究，系统梳理印度哈里亚纳邦ICT农业与气候韧性、SDGs的关系，结论可靠但方法新颖性一般，对国内智慧农业与气候适应有参考价值。",[297],{"name":290,"url":287},[299,138,300,30,301],"数字农业","可持续发展","农业ICT",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":305},{"candidates":306,"agricultural_evidence":46},[307,312,318,322,326,332],{"code":32,"score":17,"supported":46,"title":308,"abstract":309,"tags":311},[48],[229,310,48],"climate change",[30],{"code":53,"score":313,"supported":46,"title":314,"abstract":315,"tags":317},11,[],[27,299,316],"digital agriculture",[299,138],{"code":144,"score":61,"supported":46,"title":319,"abstract":320,"tags":321},[],[245,145],[],{"code":81,"score":61,"supported":46,"title":323,"abstract":324,"tags":325},[],[29,169],[],{"code":327,"score":173,"supported":46,"title":328,"abstract":329,"tags":331},"G2",[],[330],"小农户",[],{"code":68,"score":173,"supported":46,"title":333,"abstract":334,"tags":335},[],[71],[],[337,338],"Haryana 数字化转型","ICT 气候韧性","Haryana数字化转型-5476","10.5281\u002Fzenodo.23491288",{"doi":340,"openalex_id":342,"authors":343,"venue":290,"cited_by_count":110,"oa_url":287,"card":348,"direction":353,"ingested_from":118},"W7223011965",[344,346],{"name":345,"orcid":9},"Himani Rathi",{"name":347,"orcid":9},"Pardeep Kumar Duhan",{"tldr":349,"method":350,"finding":351,"direction":117,"opportunity":352},"评估印度哈里亚纳邦ICT农业实践对气候韧性与可持续发展目标的贡献。","描述性与分析性方法，基于2016-2026年政府报告等二手数据与叙事综述。","ICT显著提升气候信息获取、资源效率与市场连接，助力SDG 2\u002F9\u002F13，但数字素养与基础设施不足制","可研究小农户数字素养与ICT采纳门槛的实证机制，及包容性数字政策在气候智慧农业中的落地路径。","智慧农业 \u002F 农业物联网","2026-10-21T23:30:08.814085Z",{"id":356,"title":357,"url":358,"summary":359,"summary_zh":360,"content":9,"source_name":361,"source_url":358,"published_at":362,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":363,"score_detail":364,"sources":366,"tags":368,"primary_topic":372,"secondary_topics":376,"classification":378,"search_phrases":396,"slug":399,"view_count":110,"doi":400,"paper":401,"created_at":419},5320,"Machine Learning for Drought Analysis and Forecasting: A Critical Review of Data Fusion, Extreme-Event Sensitivity, Explainability and Generalization","https:\u002F\u002Fdoi.org\u002F10.17485\u002Fijst\u002Fv19i36.1263","Background: Machine learning is increasingly applied to drought monitoring and forecasting, but studies differ widely in how drought is defined, what data are used, and how models are validated, which makes reported performance difficult to compare directly. Objectives: To explain why reported machine-learning drought-model performance varies across definitions, data sources and validation schemes, and to assess whether recent studies adequately address rare severe events and cross-domain transferability. Method: Journal articles published January 2018 to August 2026 were reviewed, starting from a 70-record high-relevance subset of a 359-record discovery export and extended through citation chaining. Publisher and DOI verification produced a final evidence base of 55 articles: 48 primary studies and 7 reviews. Target definition, input data, model family, validation design, metrics, class-imbalance treatment, explainability and external testing were compared across studies. Findings: Reported performance varied with the modelling task rather than with any single algorithm: Random Forest reached 97.7% AUC-ROC for agricultural-drought mapping in Queensland, SVM reached average R²=0.90 for hydrological drought in Algeria, and a CatBoost stacking model reached R²=0.9065 for remote-sensing-based drought monitoring. These scores are not directly comparable because targets, data and validation protocols differ. Recent studies increasingly test cross-product and cross-region transfer, use SHAP\u002FLIME explainability, and adopt extreme-aware losses, yet class-wise reporting of severe and extreme drought, ordinal-aware evaluation, and leakage-resistant temporal validation remain inconsistently applied across the 48 primary studies. Novelty: The review jointly evaluates predictive accuracy alongside rare-event sensitivity, ordinal drought severity, leakage-resistant validation, explainability, uncertainty and cross-domain generalization, criteria largely absent from earlier machine-learning drought reviews. Keywords: Drought Forecasting, Machine Learning, Remote Sensing, Explainable AI, Extreme Drought","背景：机器学习正日益应用于干旱监测与预报，但各研究在干旱定义、所用数据和模型验证方式上差异很大，导致所报告的模型性能难以直接比较。目标：解释为何已报告的机器学习干旱模型性能会因定义、数据来源和验证方案的不同而变化，并评估近期研究是否充分处理了罕见的严重事件和跨域可迁移性问题。方法：综述了2018年1月至2026年8月发表的期刊论文，起始于359条发现导出记录中70条高相关性记录的子集，并通过引文追溯加以扩展。经出版商和DOI核验，最终证据基础为55篇文章：48篇原始研究和7篇综述。比较了各研究的目标定义、输入数据、模型族、验证设计、指标、类别不平衡处理、可解释性和外部测试。发现：所报告的性能随建模任务而非任何单一算法而变化：随机森林在昆士兰农业干旱制图中达到97.7%的AUC-ROC，SVM在阿尔及利亚水文干旱中达到平均R²=0.90，CatBoost堆叠模型在基于遥感的干旱监测中达到R²=0.9065。这些分数不能直接比较，因为目标、数据和验证方案不同。近期研究越来越多地测试跨产品和跨区域迁移，使用SHAP\u002FLIME可解释性，并采用极端事件感知损失函数，然而在48篇原始研究中，严重和极端干旱的分类别报告、序数感知评估以及防泄漏的时间验证仍应用不一致。新颖性：本综述将预测准确性与罕见事件敏感性、序数干旱严重程度、防泄漏验证、可解释性、不确定性和跨域泛化等标准共同评估，这些标准在以往的机器学习干旱综述中大多缺失。关键词：干旱预报，机器学习，遥感，可解释人工智能，极端干旱","Indian Journal of Science and Technology","2026-10-18T00:00:00Z",71,{"impact":45,"substance":202,"depth":19,"authority":45,"freshness":203,"relevant":21,"comment":365},"系统综述机器学习干旱分析与预测，指出评估口径不一、极端事件敏感性与可解释性不足，对农业旱情监测信息化有参考价值，但属学术综述、影响面偏细分领域。",[367],{"name":361,"url":358},[208,369,370,29,371],"可解释AI","极端天气","干旱监测",{"code":257,"slug":373,"name":374,"path":375,"parent_code":217},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",[377],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":379},{"candidates":380,"agricultural_evidence":46},[381,387,392],{"code":257,"score":294,"supported":46,"title":382,"abstract":384,"tags":386},[383],"machine learning",[385,383],"机器学习",[208,369],{"code":32,"score":131,"supported":46,"title":388,"abstract":390,"tags":391},[389],"drought",[154,389],[371],{"code":81,"score":54,"supported":46,"title":393,"abstract":394,"tags":395},[],[29,169],[29],[397,398],"机器学习 干旱预测","遥感 干旱监测","机器学习干旱预测-5320","10.17485\u002Fijst\u002Fv19i36.1263",{"doi":400,"openalex_id":402,"authors":403,"venue":361,"cited_by_count":110,"oa_url":358,"card":413,"direction":115,"ingested_from":118},"W7222882764",[404,407,410],{"name":405,"orcid":406},"Ritik Mallik","https:\u002F\u002Forcid.org\u002F0009-0000-2785-0265",{"name":408,"orcid":409},"Dayal Kumar Behera","https:\u002F\u002Forcid.org\u002F0000-0002-9740-8066",{"name":411,"orcid":412},"Satarupa Mohanty","https:\u002F\u002Forcid.org\u002F0000-0002-1434-7158",{"tldr":414,"method":415,"finding":416,"direction":417,"opportunity":418},"综述55篇文献，比较机器学习干旱监测预报在定义、数据与验证上的差异。","系统综述2018-2026年55篇文献，比较目标定义、数据、模型、验证与可解释性","模型性能差异主要源于任务与验证设计而非算法，极端事件与泄漏防护评估仍不足。","农业人工智能与决策模型","可构建面向极端干旱的序数感知评估与抗泄漏时序验证框架，提升跨区域泛化。","2026-10-19T23:30:22.840943Z",{"id":421,"title":422,"url":423,"summary":424,"summary_zh":425,"content":9,"source_name":426,"source_url":423,"published_at":427,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":428,"score_detail":429,"sources":431,"tags":433,"primary_topic":436,"secondary_topics":441,"classification":448,"search_phrases":470,"slug":473,"view_count":21,"doi":474,"paper":475,"created_at":488},5308,"Geopolitics and food security: A comprehensive review of emerging risks and responses","https:\u002F\u002Fdoi.org\u002F10.51200\u002Fjsffs.v2i2.7666","This review paper examines the relationship between geopolitics and food security through a Systematic Literature Review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework. A total of 15 peer-reviewed journal articles published between 2015 and 2026 were reviewed to identify emerging geopolitical risks and responses affecting global food systems. The study synthesizes literature on armed conflicts, trade restrictions, climate change, supply chain disruptions, energy market instability, and technological transformation in agriculture. The findings identified four major themes. First, geopolitical conflicts and protectionist trade policies significantly disrupt global food supply chains and increase food price volatility. Second, climate-related shock such as droughts, floods, and extreme weather events intensifies food insecurity, particularly in import-dependent and developing economies. Third, weaknesses in global logistics and energy dependence expose food systems to external shocks and market instability. Fourth, technological innovations, including smart farming, precision agriculture, and digital monitoring systems, play an increasingly important role in strengthening agricultural productivity, improving resource efficiency, and enhancing resilience against geopolitical and environmental uncertainties. The policy implications of this study include strengthening regional food reserves, diversifying import sources, investing in climate-resilient agriculture, promoting the adoption of smart farming technologies, and enhancing institutional cooperation between governments and international organizations. The relevance of smart farming is increasingly evident, as precision agriculture, Internet of Things (IoT)-based monitoring systems, and data-driven farming technologies play a critical role in improving productivity, reducing resource inefficiency, and enhancing food system resilience under geopolitical stress. The study contributes to a broader understanding of how geopolitical dynamics shape food security and provides recommendations for building sustainable, resilient, and technology-driven food systems in an increasingly uncertain global environment.","本文通过遵循系统评价与荟萃分析首选报告条目（Preferred Reporting Items for Systematic Reviews and Meta-Analyses）框架的系统文献综述，考察地缘政治与粮食安全之间的关系。共 review 了2015年至2026年间发表的15篇同行评审期刊论文，以识别影响全球粮食系统的新兴地缘政治风险与应对措施。本研究综合了关于武装冲突、贸易限制、气候变化、供应链中断、能源市场不稳定以及农业技术转型的文献。研究结果识别出四大主题。第一，地缘政治冲突和保护主义贸易政策显著扰乱全球粮食供应链并加剧粮食价格波动。第二，干旱、洪水和极端天气事件等气候相关冲击加剧粮食不安全，尤其是在依赖进口的经济体和发展中经济体中。第三，全球物流的薄弱环节和能源依赖使粮食系统暴露于外部冲击和市场不稳定之中。第四，包括智慧农业、精准农业和数字监测系统在内的技术创新，在增强农业生产力、提高资源效率以及增强应对地缘政治和环境不确定性的韧性方面发挥着日益重要的作用。本研究的政策启示包括加强区域粮食储备、多元化进口来源、投资气候韧性农业、促进智慧农业技术的采用，以及加强政府与国际组织之间的制度合作。智慧农业的相关性日益明显，因为精准农业、基于物联网（IoT）的监测系统和数据驱动农业技术在提高生产力、减少资源低效以及增强地缘政治压力下粮食系统韧性方面发挥着关键作用。本研究有助于更广泛地理解地缘政治动态如何塑造粮食安全，并为在日益不确定的全球环境中构建可持续、有韧性且技术驱动的粮食系统提供建议。","Journal of Smart Farming and Food Security","2026-10-19T00:00:00Z",77,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":203,"relevant":21,"comment":430},"系统综述梳理地缘政治与粮食安全风险，并强调智慧农业的韧性价值，具政策与产业参考意义，但属综述性论文，非突破性成果。",[432],{"name":426,"url":423},[138,434,64,27,435],"农业供应链","地缘政治",{"code":60,"slug":437,"name":438,"path":439,"parent_code":440},"yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[442,443],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"code":444,"slug":445,"name":446,"path":447,"parent_code":217},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",{"status":39,"locked":14,"version":40,"method":41,"evidence":449},{"candidates":450,"agricultural_evidence":46},[451,455,459,463],{"code":60,"score":131,"supported":46,"title":452,"abstract":453,"tags":454},[65],[64,65],[64],{"code":53,"score":313,"supported":46,"title":456,"abstract":457,"tags":458},[],[138,27,57],[138,27],{"code":32,"score":203,"supported":46,"title":460,"abstract":461,"tags":462},[],[229,154,310],[],{"code":444,"score":203,"supported":46,"title":464,"abstract":465,"tags":469},[],[466,467,468],"物联网","internet of things","IoT",[],[471,472],"地缘政治 粮食安全","智慧农业 粮食系统韧性","地缘政治粮食安全-5308","10.51200\u002Fjsffs.v2i2.7666",{"doi":474,"openalex_id":476,"authors":477,"venue":426,"cited_by_count":110,"oa_url":423,"card":483,"direction":353,"ingested_from":118},"W7222902031",[478,480],{"name":479,"orcid":9},"Parameswaran Mahendran",{"name":481,"orcid":482},"Wong Sing Yun","https:\u002F\u002Forcid.org\u002F0000-0001-5776-8852",{"tldr":484,"method":485,"finding":486,"direction":353,"opportunity":487},"系统综述地缘政治风险对粮食安全的影响及应对，强调智慧农业的韧性作用。","按PRISMA框架系统综述2015-2026年15篇同行评议文献。","冲突、贸易限制、气候与能源冲击威胁粮食安全，智慧农业可提升韧性与效率。","可量化研究物联网与精准农业在地缘政治冲击下对粮食系统韧性的实证贡献。","2026-10-19T23:30:07.850994Z",{"id":490,"title":491,"url":492,"summary":493,"summary_zh":494,"content":9,"source_name":495,"source_url":492,"published_at":496,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":497,"score_detail":498,"sources":500,"tags":502,"primary_topic":505,"secondary_topics":506,"classification":507,"search_phrases":545,"slug":548,"view_count":110,"doi":549,"paper":550,"created_at":562},5195,"Nanoagricultural revolution under global warming: optimizing growth and nutrient use efficiency","https:\u002F\u002Fdoi.org\u002F10.1080\u002F01904167.2026.2742923","Global food security faces growing threats from climate change, population growth, and environmental degradation, which reduce crop yield and quality. Innovative solutions are needed beyond conventional farming. This review examines nanotechnology’s potential to transform agriculture under climate stress, focusing on metallic, carbon-based, biogenic, and polymeric nanomaterials. These materials act as nanofertilizers, nanopesticides, nanosensors, and soil amendments. They enhance seed germination, photosynthetic efficiency, hormone regulation, gene expression, and antioxidant defenses. They also mitigate drought and salinity by improving water uptake, ion balance, osmolyte accumulation, and stress-gene regulation. Nanofertilizers enable controlled nutrient release, reducing emissions and fertilizer waste, while nanopesticides provide targeted pest control. Nanosensors support precision agriculture through real-time monitoring. Overall, nanotechnology improves soil quality, carbon sequestration, and crop resilience. However, safe application requires optimizing concentrations and methods to avoid toxicity. Future work should address molecular mechanisms, ecological impacts, cost-effective production, and regulatory frameworks. When integrated sustainably, nanotechnology offers a transformative path toward global food security under climate uncertainty.","全球粮食安全正面临气候变化、人口增长和环境退化日益加剧的威胁，这些因素导致作物产量和品质下降。需要超越传统农业的创新解决方案。本综述探讨了纳米技术在气候胁迫下变革农业的潜力，重点关注金属基、碳基、生物源和聚合物纳米材料。这些材料可作为纳米肥料、纳米农药、纳米传感器和土壤改良剂。它们增强种子萌发、光合效率、激素调节、基因表达和抗氧化防御。它们还通过改善水分吸收、离子平衡、渗透调节物质积累和胁迫基因调控来缓解干旱和盐胁迫。纳米肥料可实现养分的控释，减少排放和肥料浪费，而纳米农药则提供靶向病虫害防治。纳米传感器通过实时监测支持精准农业。总体而言，纳米技术改善土壤质量、碳固存和作物抗逆性。然而，安全应用需要优化浓度和方法以避免毒性。未来工作应关注分子机制、生态影响、经济高效的生产和监管框架。在可持续整合的前提下，纳米技术为气候不确定性下的全球粮食安全提供了一条变革性路径。","Journal of Plant Nutrition","2026-10-15T00:00:00Z",76,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":157,"relevant":21,"comment":499},"系统综述纳米材料在气候胁迫下提升作物生长与养分利用效率的机制与应用前景，信息增量与专业深度较好，但属综述类论文、非突破性成果，适合进入主题聚合而非头条精选。",[501],{"name":495,"url":492},[138,27,229,503,504],"纳米农业","纳米肥料",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":508},{"candidates":509,"agricultural_evidence":46},[510,514,518,522,529,533,539],{"code":32,"score":13,"supported":46,"title":511,"abstract":512,"tags":513},[],[229,154,310,389],[229],{"code":53,"score":157,"supported":46,"title":515,"abstract":516,"tags":517},[],[27,57],[138,27],{"code":60,"score":61,"supported":46,"title":519,"abstract":520,"tags":521},[],[64,65],[],{"code":523,"score":61,"supported":46,"title":524,"abstract":525,"tags":528},"F3",[],[526,527],"肥料","fertilizer",[],{"code":144,"score":61,"supported":46,"title":530,"abstract":531,"tags":532},[],[245,145],[],{"code":534,"score":173,"supported":46,"title":535,"abstract":536,"tags":538},"F4",[],[537],"农药",[],{"code":540,"score":173,"supported":46,"title":541,"abstract":542,"tags":544},"H4",[],[543],"carbon sequestration",[],[546,547],"纳米肥料 养分利用效率","纳米传感器 精准农业","纳米肥料养分利用效率-5195","10.1080\u002F01904167.2026.2742923",{"doi":549,"openalex_id":551,"authors":552,"venue":495,"cited_by_count":110,"oa_url":9,"card":556,"direction":560,"ingested_from":118},"W7222281865",[553],{"name":554,"orcid":555},"Azam Ranjbar","https:\u002F\u002Forcid.org\u002F0000-0001-8650-7395",{"tldr":557,"method":558,"finding":559,"direction":560,"opportunity":561},"综述纳米材料在气候胁迫下提升作物生长与养分利用效率的潜力与风险。","综述金属、碳基、生物源及聚合物纳米材料作为纳米肥料、农药和传感器的作用。","纳米材料可增强抗逆性、控释养分并支持精准农业，但需优化浓度以避免毒性。","农业绿色发展与碳","可研究纳米材料在田间尺度下的分子机制、生态风险与低成本规模化生产及监管标准。","2026-10-17T23:31:02.249682Z"]