[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2297":3},{"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":22,"tags":26,"view_count":19,"doi":32,"paper":33,"created_at":46},2297,"Uses of Artificial Intelligence In Geography","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22720772","Abstract Artificial Intelligence (AI) is becoming an important technology in the field of Geography. It helps geographers collect, process, analyze, and interpret large amounts of geographical data quickly and accurately. AI is widely used with Geographic Information Systems (GIS), Remote Sensing, satellite images, GPS, and spatial databases. It can help in land-use and land-cover mapping, urban planning, population analysis, disaster management, climate studies, agriculture, and environmental monitoring. AI-based techniques such as machine learning and deep learning can identify patterns and changes in geographical areas that may be difficult to detect through traditional methods. AI also helps in predicting natural hazards such as floods, droughts, landslides, and forest fires. In urban areas, it supports transportation planning, infrastructure development, and smart-city management. In agriculture, AI can assist in crop monitoring, soil analysis, and yield prediction. However, the effective use of AI requires reliable data, skilled users, proper technology, and attention to data privacy and accuracy. Thus, Artificial Intelligence has great potential to improve geographical research, spatial analysis, planning, and sustainable development.","摘要 人工智能（AI）正成为地理学领域的一项重要技术。它帮助地理学者快速、准确地采集、处理、分析和解释大量地理数据。人工智能与地理信息系统（GIS）、遥感、卫星影像、全球定位系统（GPS）及空间数据库广泛结合使用。它可辅助土地利用与土地覆盖制图、城市规划、人口分析、灾害管理、气候研究、农业及环境监测。基于人工智能的技术，如机器学习和深度学习，能够识别地理区域中传统方法难以探测的模式与变化。人工智能还有助于预测洪水、干旱、滑坡和森林火灾等自然灾害。在城市地区，它支持交通规划、基础设施建设及智慧城市管理。在农业领域，人工智能可协助作物监测、土壤分析及产量预测。然而，人工智能的有效应用需要可靠的数据、熟练的使用者、适当的技术，并需关注数据隐私与准确性。因此，人工智能在改进地理研究、空间分析、规划及可持续发展方面具有巨大潜力。",null,"Zenodo (CERN European Organization for Nuclear Research)","2026-09-30T00:00:00Z","论文",25,false,46,{"impact":17,"substance":18,"depth":17,"authority":17,"freshness":19,"relevant":20,"comment":21},12,10,0,1,"综述性论文，泛谈AI在地理与农业中的应用，缺乏新数据与新方法，且发布日期在未来，时效性不足，不宜进入每日精选。",[23,24],{"name":10,"url":6},{"name":10,"url":25},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22720771",[27,28,29,30,31],"智慧农业","农业人工智能","遥感","地理信息","灾害预警","10.5281\u002Fzenodo.22720772",{"doi":32,"openalex_id":34,"authors":35,"venue":10,"cited_by_count":19,"oa_url":6,"card":38,"direction":44,"ingested_from":45},"W7212350488",[36],{"name":37,"orcid":9},"Omprakash Wamanrao Jadhav",{"tldr":39,"method":40,"finding":41,"direction":42,"opportunity":43},"综述人工智能在地理学中的应用，涵盖GIS、遥感、城市规划、农业与环境监测等。","综述性分析，涉及机器学习、深度学习与GIS、遥感、GPS等地理数据技术。","AI能高效识别地理模式与变化，预测自然灾害，并助力农业监测与智慧城市管理。","农业遥感与作物表型","可聚焦AI在农业遥感中的可解释性与小样本迁移学习，提升作物监测精度与泛化能力。","智慧农业 \u002F 农业物联网","openalex","2026-09-13T23:30:09.354631Z"]