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品质电商","数商兴农农产品出村进城-4618","2026-10-11T00:09:35.998753Z",{"id":67,"title":68,"url":69,"summary":70,"summary_zh":19,"content":71,"source_name":72,"source_url":19,"published_at":73,"category":74,"cover_url":19,"hotness":23,"is_selected":24,"score":75,"score_detail":76,"sources":79,"tags":81,"primary_topic":87,"secondary_topics":93,"classification":94,"search_phrases":112,"slug":115,"view_count":116,"doi":19,"paper":19,"created_at":117},4623,"专家解读|提升乡村建设信息化水平,助力数字乡村高质量发展新征程","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694591827630653987\u002F","中央网信办、农业农村部、工信部联合印发的《数字乡村高质量发展行动计划(2026—2030年)》明确十五五乡村建设信息化任务。截至2025年底,全国行政村5G通达率达95%,农村宽带用户2.04亿户,农村网民3.14亿人,农村互联网普及率69.5%,较十三五末提升13.6个百分点;远程医疗网络覆盖全国所有市县,农村中小学校(含教学点)互联网接入率达100%。","“十五五”时期是网络强国建设夯实基础、全面发力的关键时期，也是基本实现农业农村现代化的关键时期。近日，中央网信办、农业农村部、工业和信息化部印发《数字乡村高质量发展行动计划（2026—2030年）》（以下简称《行动计划》），以强农惠农富农为目标，对“十五五”时期数字乡村发展重点任务作出系统部署。乡村建设信息化是数字乡村建设的重点领域和关键环节，是直接关乎农民群众获得感、幸福感、安全感的基础性工程，对推进农村基本具备现代生活条件，激发乡村发展内生动力具有重要作用。\n\n一、把握当前数字乡村发展的新机遇新挑战\n\n近年来，我国数字乡村建设取得显著成效，特别是乡村建设信息化水平大幅提升，乡村基础设施和信息服务加快从“用得上”到“用得起”“用得好”转变，让广大农民群众在信息化发展中有更多获得感、幸福感、安全感。截至2025年底，全国行政村5G通达率已达95%，农村宽带用户总数达2.04亿户；农村网民规模达3.14亿人，农村地区互联网普及率达69.5%，较“十三五”末期提升13.6个百分点；远程医疗服务网络已覆盖全国所有市县，农村中小学校（含教学点）互联网接入率达100%。但对照数字乡村高质量发展的目标，还存在一些短板弱项，距离农民群众对美好生活期待还存在差距，需要加快推进乡村建设信息化，推动数字乡村发展迈上新台阶。\n\n一方面，乡村信息服务的供需适配性还有待提升。农村以及偏远地区的诊疗服务和教育资源分布不平衡、供给不充分现象还较为明显。“一老一小”、残疾人等重点人群的适老化、无障碍数字服务能力不足，乡村数字文化内容形式还较为单一，针对小农户等农业主体的轻量化数字金融产品供给有限，农村生态环境、农村污染源、土地利用的信息化监测水平不高，农村群众和基层干部的数字素养与技能水平还有待提升。另一方面，人工智能快速迭代发展为乡村建设带来宝贵机遇。当前我国大模型产品性能位居全球前列，人形机器人等规模化量产持续加速，智能体应用数量快速增长，推动乡村基础设施和信息服务数字化智能化升级，为乡村建设信息化提供了新动能。\n\n二、充分认识推进乡村建设信息化的重要意义\n\n习近平总书记指出，全面建设社会主义现代化国家，最艰巨最繁重的任务仍在农村。乡村建设信息化关系着数字乡村发展的成效和“底色”，是实现强农惠农富农目标的必由之路，通过充分运用人工智能、大数据、区块链等新一代信息技术，赋能乡村公共服务发展和生态人居环境改善，不断满足农民群众美好生活新期待的重要途径，对于加快数字乡村高质量发展具有重要意义和时代价值。\n\n一是缩小城乡公共服务差距。通过优化和完善信息服务，推动教育、医疗等优质资源下沉覆盖，推动打破城乡资源共享和双向流动壁垒，让农村群众在家门口就能够享受到便利普惠的公共服务，不断提升城乡基本公共服务均等化水平。\n\n二是推进乡村精神文明建设。通过推动乡村数字文化发展，激发乡村本土文化创作人才热情，丰富乡村优秀网络文化作品供给，推动培育文明乡风、良好家风、淳朴民风，满足农村群众对高质量精神文化生活的追求和期盼。同时，数智技术为农耕文化、非遗民俗、古村落遗产等乡村文化资源打造了永久保存与全域传播载体，促进中华优秀农耕文明创造性转化、创新性发展，为乡村文化守住根脉，为故土记忆留住“乡愁”。\n\n三是改善乡村生态人居环境。通过建设完善生态环境监测网络体系，系统部署物联网传感器、遥感监测等设备和智能分析系统，实现对农村生活环境及空气质量等重要指标的实时监测与智能预警，探索农村人居环境管理新模式，推动乡村生态环境治理从“被动响应”向“主动预防”转变。\n\n三、聚焦重点方向推进乡村建设信息化\n\n《行动计划》明确，“十五五”时期要聚焦乡村数字教育、乡村数字健康、重点人群信息服务保障、乡村普惠金融、乡村数字文化、智慧美丽乡村等重点方向，构建深度覆盖、普惠便捷、协同高效的乡村建设信息化体系，加速补齐系统性短板，释放数字惠民效能。\n\n一是提升乡村数字教育水平。农村和偏远地区的义务教育水平还存在薄弱环节，教育资源面临着供给不足的局面。要通过充分利用国家中小学智慧教育平台等平台资源，持续扩大优质教育资源的覆盖范围，推动优质课程向农村、偏远地区延伸。要合理利用人工智能等技术赋能乡村课堂教学，支持有条件的乡村学校部署智能教育终端、教育智能体等。要实施数字化赋能教师发展行动，常态化开展农村教师数字素养与技能培训，全面提升农村教师数字化教学能力。\n\n二是提升乡村数字健康服务水平。我国大量优质医疗资源还集中在县级以上行政区域，乡村医疗资源面临着人才、设备、运营、能力等结构性短板。同时，随着我国农村人口老龄化加剧，对长期慢病管理、康复护理、老年健康服务需求快速增长。要推进紧密型县域医共体信息化建设，打通县、乡、村三级医疗机构数据壁垒，提升医疗资源联动共享水平。要推广人工智能在乡村医疗服务中的应用，完善远程会诊、慢病管理线上服务网络，优化农村医保智能终端配置，促进医疗资源加速下沉。\n\n三是提升重点人群信息服务水平。我国农村还存在大量老年人和留守儿童，在数字接入服务、使用习惯等方面需求差异较大，需要乡村信息服务具备更强的包容性。要充分运用信息技术强化这些重点人群主动发现和精准救助能力，更好打通民政、医保、残联、养老等数据渠道，深入推进政务、医疗、金融、文化等各类数字服务的适老化、无障碍改造，建设更有温度的乡村信息服务体系。\n\n四是提升乡村数字普惠金融服务水平。小农户、新型农业经营主体等乡村经济“毛细血管”普遍面临融资难、融资贵、风控弱等问题，传统金融服务在覆盖广度和响应速度上难以满足其灵活、小额、高频的需求。要积极开展政银企农融资对接，引导金融机构立足农业生产周期、农户经营规模创新数字信贷、保险等产品，开发特色农业保险、农产品价格保险等适配农村经济活动特征和居民需求的产品，推动数字技术在农业保险全流程中的应用，提升农村普惠金融服务覆盖和使用水平。\n\n五是提升乡村数字文化发展水平。当前，乡村数字文化内容和渠道还较为缺乏，乡村文化活力还有待释放。要积极扶持“三农”题材的优秀网络文化作品创作，加快培育乡村本土文化创作人才队伍，激发网络文化作品创作活力。要提升乡村文化场所数字化应用水平，发挥县级融媒体中心等作用，打造乡村数字传播矩阵，拓宽乡土文化线上传播和优质文化资源下沉渠道。要开展农村文物资源、非遗传承人等数字化建档，推动非遗资源与数字文旅、乡村旅游深度融合，以数字技术传承和创新利用乡土文化资源。\n\n六是提升智慧美丽乡村建设水平。当前，一些地区乡村人居环境治理还存在监测手段粗放、管理响应滞后、运维机制不健全等问题，难以满足宜居宜业和美乡村建设要求。要推动构建“天空地海”一体化生态环境监测网络体系，强化农村污染源监测评估，支撑自然资源开发利用和生态保护修复工作，推动解决农村生态环境污染问题。要健全人居环境问题在线受理与响应机制，优化供水水质监测体系，推进生活污水设施数字化改造升级，梳理农房相关信息数据，持续改善农村人居环境。\n\n当前，我国数字乡村加快迈向高质量发展阶段。要立足乡村实际、坚持因地制宜、分类施策，提升乡村建设信息化水平，充分发挥以人工智能为代表的新一代信息技术作用，更好赋能乡村生产、生活和治理方式转型升级，推动农村基本具备现代生活条件，不断满足农民群众对美好生活的新期待，奋力书写数字乡村高质量发展新篇章，为全面推进乡村振兴、加快农业农村现代化注入持久数字力量。\n\n作者：王 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覆盖华东、华中、西南","https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002F2026-10\u002F09\u002Fcontent_593119.html","上海市农业科学院林木果树研究所桃全产业链技术创新团队数十年深耕种质创新,成功选育锦绣、锦冠、锦春、锦园、锦香、锦花等梯次成熟的锦系列黄桃矩阵。锦冠2026年获国家植物新品种权,成熟期比锦绣提早20天,填补7月中旬至8月初优质黄桃市场空白。锦系列黄桃全国推广超百万亩,湖南炎陵带动6万余人从业、近4万桃农人均年增收1.2万元,福建建宁、上海奉贤、贵州玉屏等实现上海育种、全国种植、梯次上市格局。","研究表明，上海是优质桃的重要起源地，世界95%以上的优质栽培桃可追溯到“上海水蜜”，其甘甜多汁、香味浓郁、品质优良，衍生出的众多后代成为现代桃育种的骨干亲本。然而，手握得天独厚的种源家底，上海桃产业却一度受困于品种同质化、育种周期长等多重瓶颈。破解产业难题，关键在于种质资源自主可控。上海农科院桃团队数十年深耕种质创新，实现从资源保存到分子育种的系统性突破。\n\n团队系统收集保存“上海水蜜”、山桃、光核桃等特异种质资源，依托新技术将桃的香气、黄酮等拆解至分子层面，建成涵盖成熟期、抗病性、上百种风味物质的表型与基因型数据库，彻底告别传统“凭经验选苗”的粗放育种模式。针对果树育种周期长、筛选效率低的痛点，该团队融合全基因组分子标记辅助选择育种与传统杂交育种，大幅缩短优良单株筛选周期，成功选育出梯次成熟的“锦”系列黄桃矩阵。1973年，上海农科院科研人员选育出“锦绣”。2022年，“锦冠”通过上海市林木品种审定，并于2026年获得国家植物新品种权。\n\n上海农科院桃团队原负责人、研究员叶正文介绍，“锦冠”以“锦绣”为母本、“玉露蟠桃”为父本杂交培育而成，脆软双吃、纤维少。其成熟期比传统晚熟“锦绣”提早20天，精准填补7月中旬至8月初优质黄桃市场空白，成为种质创新落地的最新标志性成果。\n\n新品种进入产业，不能只靠品种本身。上海桃园普遍面临用工多、机械化程度不高、从业者老龄化显著等问题。上海农科院桃团队结合上海高温多雨、土壤黏重、果园作业难度大的实际情况，创新推广起垄栽培、暗排技术，破解桃园排水难与机械化作业的矛盾。团队还筛选适合本地作业的打药、割草、物料运输、精准施肥等方面的果园机械，集成宜机化建园、省力化修剪等配套技术，推动桃园机械化作业。\n\n在奉贤区黄桃采后保鲜方面，团队形成保鲜技术规程，有效延长了“锦绣”黄桃贮藏期，降低了鲜果物流损失率。团队研发的桃果实采后贮运保鲜技术，还助推山东“蒙阴蜜桃”走出国门，远销新加坡、阿联酋、俄罗斯等国。“对产业主体而言，采后技术带来的不仅是少损耗，更是长销售期、大市场和更稳定的商品价值。”上海农科院桃团队负责人李雄伟说。","科技日报 2026-10-09",88,{"impact":127,"substance":128,"depth":29,"authority":129,"freshness":77,"relevant":31,"comment":130},26,22,14,"上海农科院锦系列黄桃全国推广超百万亩，涵盖种质创新、分子育种与宜机化栽培，产业级突破且信息增量充足，值得入选每日精选。",[132],{"name":124,"url":121},[134,135,136,137,138],"种业振兴","种质资源","黄桃","分子育种","宜机化果园",{"code":140,"slug":141,"name":142,"path":143,"parent_code":144},"F1","seed-industry","种业与品种管理","\u002Ftopic\u002Finputs-equipment\u002Fseed-industry","F",[],{"status":49,"locked":50,"version":51,"method":52,"evidence":147},{"candidates":148,"agricultural_evidence":24},[149,154,161],{"code":140,"score":56,"supported":24,"title":150,"abstract":151,"tags":153},[],[152],"新品种权",[134,135],{"code":155,"score":156,"supported":24,"title":157,"abstract":158,"tags":160},"B2",4,[],[159],"果树",[136],{"code":162,"score":31,"supported":50,"title":163,"abstract":164,"tags":165},"F2",[],[],[137],[167,168],"上海农科院 锦系列 黄桃","锦冠 黄桃 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2026-10-10",{"impact":127,"substance":128,"depth":180,"authority":129,"freshness":181,"relevant":31,"comment":182},17,9,"六部门联合印发乡村振兴投入机制实施方案，含具体信贷条款与多地金融机构创新案例，政策层级高、信息增量足，值得进入每日精选。",[184],{"name":178,"url":175},[186,187,188,189,190],"乡村振兴","农村金融","信贷支农","农村信用体系","农业产业链金融",{"code":192,"slug":193,"name":194,"path":195,"parent_code":19},"G","rural-services","农业服务与乡村发展","\u002Ftopic\u002Frural-services",[],{"status":198,"locked":50,"version":51,"method":52,"evidence":199},"partial",{"candidates":200,"agricultural_evidence":24},[201,205],{"code":192,"score":98,"supported":24,"title":202,"abstract":203,"tags":204},[186],[186],[186],{"code":103,"score":31,"supported":50,"title":206,"abstract":207,"tags":208},[],[],[187],[210,211],"六部门 乡村振兴投入机制","邮担快贷 邮储银行 四川","六部门乡村振兴投入机制-4622","2026-10-11T00:09:36.350801Z",{"id":215,"title":216,"url":217,"summary":218,"summary_zh":19,"content":219,"source_name":220,"source_url":19,"published_at":73,"category":74,"cover_url":19,"hotness":23,"is_selected":24,"score":221,"score_detail":222,"sources":225,"tags":227,"primary_topic":232,"secondary_topics":236,"classification":237,"search_phrases":250,"slug":253,"view_count":116,"doi":19,"paper":19,"created_at":254},4619,"央视《新闻联播》关注成都彭州农产品物流网建设:3分钟排出一套配送方案","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694590220515279394","10月7日,央视《新闻联播》一线调研以《从物畅其流到产销联动》为题深度报道成都彭州农产品物流网建设。彭州四川国际农产品交易中心连接31省区市、340座城市,日交易果蔬超1.5万吨;新打造的数字化供应链平台3分钟即可排出一套配送方案,装载率提升至95%以上,日均损耗由5%降至0.5%;20万斤猕猴桃尚未采摘便已提前排定采收和发货计划,获国家发改委、交通运输部关注并官网宣传。","[](https:\u002F\u002Fwww.toutiao.com\u002F)\n\n*   关注 \n*   推荐 \n*   北京   \n*   视频 \n*   财经 \n*   科技 \n*   热点 \n*   国际 \n*   更多 \n\n    *   军事 \n    *   体育 \n    *   娱乐 \n    *   历史 \n    *   美食 \n    *   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2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002F32c3b78dfed0404eafbd9f9036facd42~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792282212&x-signature=q2JLBBQAe5lnjmix2GZK1wWjzyg%3D)\n\n物畅其流\n\n●新打造的农产品数字化供应链平台，补齐订单组织、仓储配送等服务环节，最快3分钟即可排出一套配送方案，装载率提升至95%以上，日均损耗由原来的5%降低到0.5%\n\n产销联动\n\n●平台在全国设有多个中心仓，各地行情汇成一张“需求地图”。“货沿着网卖出去，信息沿着网传回来。”20万斤猕猴桃尚未采摘便已提前排定采收和发货计划\n\n2026年10月7日，央视《新闻联播》“一线调研”栏目以《从物畅其流到产销联动》为题，用4分钟篇幅深度报道了成都彭州农产品物流网建设的创新实践，相关内容获国家发展改革委、交通运输部关注并在官网宣传。作为成都市物流网建设的典型案例，彭州农产品供应链实践登上国家级媒体平台，获得国家层面关注与肯定，是成都推进物流网建设，加快补短板、畅联通、提能级的生动缩影。\n\n**一线调研**\n\n**一张物流网如何“成链成网”**\n\n四川国际农产品交易中心位于成都彭州，是成都市建设商贸服务型国家物流枢纽的核心承载区。\n\n央视记者的镜头之下，这个西南地区最大的农产品集散枢纽连接起31个省区市、340座城市，每天交易果蔬超1.5万吨。最近的一辆车可能只开几十公里，最远的来自新疆喀什，3400多公里，经过戈壁、高原，再进入四川盆地。\n\n市场上的“四季鲜”首先得益于路网建设的不断完善，但货到了市场还只是第一步。大量鲜果蔬菜抵达之后，怎样快速流转？\n\n有时几箱菜、十几件水果，单独叫一辆车不划算，等着凑满一车，又耽误不起新鲜度。小批量货物如何能被有效地组织起来？\n\n央视记者在市场一街之隔，找到了另一个正在发生的变化。新打造的农产品数字化供应链平台，该平台补齐订单组织、仓储配送等服务环节，将不同去向的货物重新组合，车辆、线路、装载率交由系统计算，最快3分钟即可排出一套配送方案，装载率提升至95%以上，日均损耗由原来的5%降低到0.5%。\n\n报道说，配送统一了，信息也连成了网。平台在全国设有多个中心仓，各地行情汇成一张“需求地图”。“货沿着网卖出去，信息沿着网传回来。”20万斤猕猴桃尚未采摘便已提前排定采收和发货计划。\n\n这一“产销联动”“硬建设和软联通并重”的新模式，有效破解了传统农产品流通中“小批量货物难以有效组织”“流通损耗高”等痛点，切实降低物流成本，推动物流网从“通道保障”向“产业赋能”跃升。报道称，今年8月印发的《物流网建设实施方案》，推动物流基础设施从“布点畅线”转向“成链成网”。这个市场的变化正是物流网建设的缩影。过去，看一个枢纽建没建、一条线路通没通；现在，看枢纽和通道能不能高效衔接，物流服务能不能连上产业和市场。\n\n**平台集聚**\n\n**成都正高位推动物流网建设**\n\n此次央视聚焦成都案例并非偶然。\n\n近年来，在国家大力支持下，成都“国字号”平台集聚赋能，是全国少有的“四型”国家物流枢纽承载城市，全国重要的国际航空枢纽，先后获批国家骨干冷链物流基地、国家综合货运枢纽补链强链首批支持城市、全球性国际邮政快递枢纽承载城市、综合型现代流通战略支点城市、物流数据开放互联试点城市等。\n\n2025年成都航空旅客吞吐量、货邮吞吐量分别居全国第3、第5位，铁路运营里程1011公里、居全国第5位，国际班列通达境外133个城市，高速公路网通车里程1347公里，为物流网建设奠定了坚实基础。\n\n在构建现代物流体系的过程中，成都市大胆探索、改革创新，前期已有成都国际铁路港国际陆路运输“单一窗口”等新模式、新举措被国家关注点赞，为全国物流网建设提供系列样本。\n\n当前，按照国家部署，成都市正统筹推进“六张网”建设，高位推动物流网建设，组建全市物流网规划建设工作专班，发展改革、交通、商务、口岸物流等11个部门协同推进、形成合力，多次组织开展物流网建设专题培训。\n\n川藏铁路引入线、成乐高速公路扩容、中欧班列集结中心、“一带一路”进出口商品集散中心等一大批重大工程加快建设、年度计划投资超200亿元。同时，聚焦国家方案明确的重点方向、重点任务，围绕国家物流枢纽等重要枢纽能级提升和功能性组网、骨干物流通道建设提升、物流设施设备数智化绿色化转型等领域，储备物流网项目110个、总投资近3000亿元。\n\n来源：成都日报\n\n举报\n\n评论 0\n\n请先 登录 后发表评论～\n\n今日头条推荐引擎有 9 条更新\n\n[上海新华医院接诊多例“汞超标”患儿，集中在1-3岁，专家提示→](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694992484623745576\u002F)\n*   [![Image 3: 上海新华医院接诊多例“汞超标”患儿，集中在1-3岁，专家提示→-图1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fbf4675ea301a377716482e21061a7bf6~tplv-tt-cs0:1024:603.jpg?_iz=31826&bid=10&from=article.headline&gid=7694992484623745576&lk3s=06827d14&x-expires=1794269416&x-signature=%2FtC9WQhjGaWFbUi4hIEy1R5qkFU%3D)](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694992484623745576\u002F) \n*   [![Image 4: 上海新华医院接诊多例“汞超标”患儿，集中在1-3岁，专家提示→-图2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Ff8404cce1f14acdca4c3e3a5811f648d~tplv-tt-cs0:1064:1067.jpg?_iz=31826&bid=10&from=article.headline&gid=7694992484623745576&lk3s=06827d14&x-expires=1794269416&x-signature=0CvMep5NyRHzmwhlI%2Blw1R%2Ftsrk%3D)](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694992484623745576\u002F) \n*   [![Image 5: 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12](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Fuser-avatar\u002F8180f1a45a7f9c40606e87991579ce15~300x300.image?_iz=112761&from=tt_user.headline_wtt&lk3s=06827d14&x-expires=1792368000&x-signature=cjo0WRwmHFrRM8UE%2FljL6ZuI028%3D)澎湃新闻](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAApOspM7AnWqplD9FIBGnhJRfUjFT_msD1KZMfNPBZa-c\u002F?source=tuwen_detail \"澎湃新闻\")\n\n30分钟前\n\n·\n\n澎湃新闻官方账号\n\n关注\n\n[卸任CEO后，苹果董事长库克再度到访中国 苹果公司董事长蒂姆·库克在卸任公司CEO后首次访华。 10月10日，库克现身广州，探班iPhone 18 Pro咏春短片拍摄。在充满岭南风情的园林实景中，他探班了青年导演古天鸡与咏春拳传承人戴子龙的拍摄现场。 库克还表达了对中国传统文化的深厚兴趣与喜爱，并表示：“很高兴再次来到中国！在广州第一次通过iPhone 18 Pro镜头感受咏春的魅力，真是一次难忘的体验。” 今年9月1日，苹果正式完成权力交接。硬件工程高级副总裁约翰·特努斯接替库克，出任苹果新一任CEO。库克转任执行董事长，协助处理公司部分事务，包括与全球政策制定者沟通。 澎湃新闻记者 周玲 (本文来自澎湃新闻，更多原创资讯请下载“澎湃新闻”APP)](https:\u002F\u002Fwww.toutiao.com\u002Fw\u002F1878708036645891\u002F)\n\n分享\n\n*   转发到头条 \n*   复制链接 \n*   微信  微信扫码分享  \n*   新浪微博 \n*   QQ空间 \n\n[1](https:\u002F\u002Fwww.toutiao.com\u002Fw\u002F1878708036645891\u002F#comment)\n\n赞\n\n[昨夜今晨丨曝梅艳芳骨灰被盗丨女子仅退款“薅走”盒马399件商品丨葫芦娃爷爷最新告示丨商家回应“厨师疑用漱口水洗锅”](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7695180296303510054\u002F)\n\n[津云](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAktkeq7OyyK2iPn23EKaDhc0v3o1fI97WlY_8d5EPRh0\u002F?source=tuwen_detail)\n\n50分钟前\n\n[![Image 13](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002F1698e5698bf7d71373272c8cebc25b6b~tplv-tt-cs0:768:554.jpg?_iz=31826&bid=10&from=article.headline&gid=7695149526050538038&lk3s=06827d14&x-expires=1794269416&x-signature=yrRIYZiIOy%2BWQlmXIITaaq5Qdrk%3D)](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7695149526050538038\u002F \"“蛟龙”入海\")\n\n[“蛟龙”入海](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7695149526050538038\u002F)\n\n[光明网](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAA9Lz0MeLdJDmqpU26Xi9O_M-cYI9z530wjM7eDKvzZTw\u002F?source=tuwen_detail)\n\n[1评论](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7695149526050538038\u002F)\n\n2小时前\n\n[政策“组合拳”集中落地后首个国庆假期：现房销售重构房企打法，重点25城新房日均成交面积同比增长33.8%](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694271501981237760\u002F)\n*   [![Image 14: 政策“组合拳”集中落地后首个国庆假期：现房销售重构房企打法，重点25城新房日均成交面积同比增长33.8%-图1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002F15a1031ffdbfbcddd2a69bbd5f87b31b~tplv-tt-cs0:1706:1279.jpg?_iz=31826&bid=10&from=article.headline&gid=7694271501981237760&lk3s=06827d14&x-expires=1794269416&x-signature=oMdBt5GN0I69XyhAqIu%2F7FHA3sE%3D)](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694271501981237760\u002F) \n*   [![Image 15: 政策“组合拳”集中落地后首个国庆假期：现房销售重构房企打法，重点25城新房日均成交面积同比增长33.8%-图2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fa6e1ea2bbd273924111bc877871a2b44~tplv-tt-cs0:1030:445.jpg?_iz=31826&bid=10&from=article.headline&gid=7694271501981237760&lk3s=06827d14&x-expires=1794269416&x-signature=V1%2F3xSbc0%2BUTgJxwoITq6romrBg%3D)](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694271501981237760\u002F) \n*   [![Image 16: 政策“组合拳”集中落地后首个国庆假期：现房销售重构房企打法，重点25城新房日均成交面积同比增长33.8%-图3](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002F039980200b8c2e64efee6ed84e131771~tplv-tt-cs0:697:731.jpg?_iz=31826&bid=10&from=article.headline&gid=7694271501981237760&lk3s=06827d14&x-expires=1794269416&x-signature=pSgyrtUM%2F0aKq28xIBjcO1tC4C8%3D)](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694271501981237760\u002F) \n*   [![Image 17: 政策“组合拳”集中落地后首个国庆假期：现房销售重构房企打法，重点25城新房日均成交面积同比增长33.8%-图4](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fbd3b9cd426aeb3bf51a7d7fae37d42a2~tplv-tt-cs0:1019:520.jpg?_iz=31826&bid=10&from=article.headline&gid=7694271501981237760&lk3s=06827d14&x-expires=1794269416&x-signature=osdAqj8qqZoBw09ey%2BkzWTl%2FDXA%3D)](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694271501981237760\u002F) \n\n[每日经济新闻](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAA56eGL40AT6T7eLJ7ir3rhX74Fa6LtzNWkfcq2jcXAek\u002F?source=tuwen_detail)\n\n[1评论](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694271501981237760\u002F#comment)\n\n3天前\n\n[![Image 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21](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-e874c6\u002FoIOjEGr9DGmGdjAEAOLBBzVACifAfEubIXei2I~tplv-tt-cs0-jzss2:960:540.jpg?_iz=31127&bid=16&from=ttvideo.headline&gid=7689461431258858010&lk3s=06827d14&x-expires=1792282216&x-signature=9gA40qir8tjLqw9IAgrOr%2B%2BFAgA%3D)](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7689461431258858010\u002F \"每天一个历史故事，今天讲唐朝。\")30:34   [每天一个历史故事，今天讲唐朝。](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7689461431258858010\u002F \"每天一个历史故事，今天讲唐朝。\")[浪迹天涯](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAPoz2XAQMlWlULClJxxdhcIHXndTahluI_Ht43DvCMnEtI6hFbeE-muxIflyNS8FK\u002F?source=tuwen_detail) [10评论](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7689461431258858010\u002F) 09月26日        \n\n[![Image 22](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-ezhpy3drpa\u002F499d93dc89854bcaa6f19865ecfbf4c0~tplv-tt-post:400:400.jpeg?_iz=97245&bid=15&from=post.headline&gid=1878704901735433&lk3s=06827d14&x-expires=1799452800&x-signature=RjFtnq21Zc930%2FiwgxKLX31HQCg%3D)](https:\u002F\u002Fwww.toutiao.com\u002Fw\u002F1878704901735433\u002F)\n\n3 图\n\n[![Image 23](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Fuser-avatar\u002F4fb008b546b95a8d373990d8c01e6250~300x300.image?_iz=112761&from=tt_user.headline_wtt&lk3s=06827d14&x-expires=1792368000&x-signature=0pZhAJFsLVXdgmfnbScwyd55oCo%3D)梅姐说法](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAkZLhR98Y6zmYv8JlU0ZbJFBsJj8KEc-c1Ra7QQMW48zzxcDci3D0UWWLMUQK0cQt\u002F?source=tuwen_detail \"梅姐说法\")\n\n1小时前\n\n·\n\n优质社会领域创作者\n\n关注\n\n[海南海口，9岁自闭症男孩独自下楼买饮料，乘坐电梯返程时，被男人一脚猛踹出电梯。男孩也不会表达，回到家只是悄悄躲起来，家长还是从邻居口中知晓此事。上门要男人理论，却被他拿刀威胁。家长害怕被男人打击报复，也不敢再追究此事了。 来源：温州都市报 10月8日男孩独自下楼买饮料，他也不敢跑远了，就在楼下买个饮料就坐电梯回家了。 男孩要下电梯时，竟然被电梯的男人一脚猛踹出去。旁边的老奶奶都惊呆了，显然不知道男人为什么这么做。 孩子那么小，重重一脚踹到身体肯定很疼，同乘电梯的人都认为男人做法太过分。 男孩回到家后，感觉到很害怕，找了个地方悄悄躲起来，想要远离这个世界。 家长察觉到孩子异常，询问他到底怎么了，可是男孩说不出来，他不能表达自己受到的伤害。 男孩的情绪很不好，一个人躲着不敢见人，也不愿意出来。家长尽量安抚他，可是无济于事。 直到邻居过来和他们说了这件事，他们才知道儿子受到了什么样的惊吓。 检查了儿子的身体，幸好没有造成太大的伤害。他们又去调取了监控，证实了邻居的说法。 看到儿子被狠狠一脚踹出电梯，家长生气极了，立马去找男人理论。 男人压根不觉得自己有问题，说都是因为男孩在电梯里碰到了他，而且还踢他。 可是监控中显示，男孩和他根本没有接触。男孩身体不好，平时不和陌生人交流，不会说故意去碰别人。 家长拿出证据和男人理论，但是男人不听这些，态度特别嚣张，就是说都是男孩的错。 双方理论后，男人居然拿刀出来，一边骂骂咧咧，一边举着刀威胁。 男人不道歉，还警告家长，不要再找他麻烦，否则就别怪他不客气。 面对这么不讲理的人，男孩家长不再继续争辩，主要是看他拿出刀来，确实是害怕。 家长害怕被男人打击报复，也怕家里的老人担心，决定不再追究此事。 目前男人已经被行政拘留，家长怕他出来后会找麻烦，已经联系了房主要求男人搬离该小区。 很多网友都认为家长不应该这么怂，要以其人之道还治其人之身，毕竟受伤害的是自己的孩子，而且孩子本身有病，受到的心理伤害会更加严重。 家长为了怕被打击报复，选择息事宁人，忍气吞声。可是这种退一步的行为，真的会换来和平吗？ 男人明显欺软怕硬，对一个孩子都下手这么狠，本身就是不讲理的人。 要是继续忍让，可能一家人都会受到骚扰。虽然联系房东让男人搬家，可是男人会不会走还是个问题。 根据《治安管理处罚法》43条，殴打他人的，或者故意伤害他人身体的，处五日以上十日以下拘留，并处二百元以上五百元以下罚款；情节较轻的，处五日以下拘留或者五百元以下罚款。有下列情形之一的，处十日以上十五日以下拘留，并处五百元以上一千元以下罚款：（二）殴打、伤害残疾人、孕妇、不满十四周岁的人或者六十周岁以上的人的； 男孩只有9岁，身体状况还不好，就遭遇男人殴打，幸好没有受伤，否则就不是行政拘留这么简单了。在家长上门理论后，男人还拿刀威胁，属于罪加一等。 男人拒不认罪，态度恶劣，对未成年人都能下手，情节严重。虽然说男人说男孩碰到了自己，但是监控没有显示。即便说男孩真的碰到了他，身为大人也不应该和一个孩子计较。 该事件中男人的行为令人发指，单看视频都觉得那一脚踹的太狠了。家长对男人还是太仁慈了，就应该对抗到底，才算是真正保护自己的儿子。](https:\u002F\u002Fwww.toutiao.com\u002Fw\u002F1878704901735433\u002F)\n\n分享\n\n*   转发到头条 \n*   复制链接 \n*   微信  微信扫码分享  \n*   新浪微博 \n*   QQ空间 \n\n[5](https:\u002F\u002Fwww.toutiao.com\u002Fw\u002F1878704901735433\u002F#comment)\n\n9\n\n热门：\n*   [2026.10](https:\u002F\u002Fm.ixigua.com\u002Fdx\u002F7694473893855555830 \"2026.10.09周五早龙教健身舞直播回放完整版减肥操 #龙教健身舞 #龙教健身舞直播回放 #龙教健身操 #龙教健身 \")\n*   [只有打赢战争，](https:\u002F\u002Fm.ixigua.com\u002Fdx\u002F7694473755480902975 \"只有打赢战争，才能存活下来 #志愿军#长长长假电影时间  #国庆档观影repo\")\n*   [#牛肉出锅了](https:\u002F\u002Fm.ixigua.com\u002Fdx\u002F7694473749920355003 \"#牛肉出锅了\")\n*   [#山乡苗寨 #](https:\u002F\u002Fm.ixigua.com\u002Fdx\u002F7694473751044104886 \"#山乡苗寨 #宝藏山村 #农村女生#农村牵线\")\n*   [心心念念海绵宝](https:\u002F\u002Fm.ixigua.com\u002Fdx\u002F7694473608717946131 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While climatic factors influencing vegetation sensitivity are well recognized, the role of phenological shifts remains poorly understood. Using multiple satellite-derived vegetation proxies (NDVI, LAI, SIF, and VOD) during 2001–2021, we show that earlier green-up dates (GUD) exacerbate vegetation sensitivity to flash droughts across 61.2–84.1% of the Northern Hemisphere (>23.5°N). Earlier GUDs enhance pre-drought vegetation growth, especially during the early growing season. Such amplified vegetation growth exacerbates sensitivity by accelerating soil moisture depletion and respiration cost, outweighing the benefit of increased subsequent net carbon assimilation. The contribution of GUD to vegetation sensitivity is comparable to that of major climatic factors. Ignoring phenological changes may lead to underestimation of long-term trends in vegetation sensitivity. These findings underscore the necessity of incorporating the interactions between phenology and flash droughts into projections of ecosystem resistance and resilience. Flash droughts can rapidly reduce vegetation growth, but the role of spring phenology is unclear. The authors show that earlier green-up increases vegetation sensitivity to flash drought across much of the Northern Hemisphere ecosystems.","闪旱导致的植被活动与冠层功能相对下降，即植被敏感性，是衡量干旱影响的关键指标。尽管影响植被敏感性的气候因素已被广泛认识，但物候偏移的作用仍知之甚少。利用2001—2021年多颗卫星衍生的植被代用指标（NDVI、LAI、SIF和VOD），我们发现，在北半球（>23.5°N）61.2%—84.1%的区域，提前的返青期（GUD）加剧了植被对闪旱的敏感性。较早的GUD增强了干旱前的植被生长，尤其是在生长季早期。这种放大的植被生长通过加速土壤水分消耗和呼吸成本加剧了敏感性，其效应超过了随后净碳同化增加带来的益处。GUD对植被敏感性的贡献与主要气候因子相当。忽视物候变化可能导致对植被敏感性长期趋势的低估。这些发现强调了将物候与闪旱之间的相互作用纳入生态系统抵抗力和恢复力预估的必要性。闪旱可迅速降低植被生长，但春季物候的作用尚不清楚。作者表明，在北半球大部分生态系统中，较早的返青增加了植被对闪旱的敏感性。","Nature Communications","2026-10-08T00:00:00Z","论文",86,{"impact":128,"substance":28,"depth":266,"authority":30,"freshness":223,"relevant":31,"comment":267},19,"基于多源卫星遥感揭示春季提前返青加剧北半球植被对骤发干旱的敏感性，方法扎实、结论新颖，对农业干旱监测预警有参考价值。",[269],{"name":261,"url":258},[271,272,273,274,275],"气候变化","遥感监测","植被物候","干旱预警","生态遥感",[],{"status":278,"locked":50,"version":51,"method":52,"evidence":279},"needs_review",{"candidates":280,"agricultural_evidence":50,"reason":302},[281,289,297],{"code":282,"score":283,"supported":24,"title":284,"abstract":286,"tags":288},"H7",16,[285],"drought",[287,285],"干旱",[274,271],{"code":290,"score":291,"supported":24,"title":292,"abstract":293,"tags":296},"H2",6,[],[294,295],"土壤","soil",[],{"code":298,"score":170,"supported":50,"title":299,"abstract":300,"tags":301},"I3",[],[],[275,272],"农业相关性需要复核",[304,305],"北半球 植被 干旱 敏感性","NDVI LAI SIF VOD 遥感","北半球植被干旱敏感性-4590","10.1038\u002Fs41467-026-78296-0",{"doi":307,"openalex_id":309,"authors":310,"venue":261,"cited_by_count":116,"oa_url":334,"card":335,"direction":339,"ingested_from":341},"W7115172292",[311,314,317,320,323,326,328,331],{"name":312,"orcid":313},"Wenrui Bai","https:\u002F\u002Forcid.org\u002F0009-0009-4885-3348",{"name":315,"orcid":316},"Quansheng Ge","https:\u002F\u002Forcid.org\u002F0000-0001-8712-8565",{"name":318,"orcid":319},"Constantin M. Zohner","https:\u002F\u002Forcid.org\u002F0000-0002-8302-4854",{"name":321,"orcid":322},"Jun Wang","https:\u002F\u002Forcid.org\u002F0009-0005-5869-832X",{"name":324,"orcid":325},"Shaozhi Lin","https:\u002F\u002Forcid.org\u002F0000-0002-8975-281X",{"name":327,"orcid":19},"Yani Liang",{"name":329,"orcid":330},"Yongshuo H. 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食品安全抽检","农业产业链可信数据空间-4644","10.12133\u002Fj.smartag.sa202605005",{"doi":471,"openalex_id":19,"authors":473,"venue":19,"cited_by_count":116,"oa_url":19,"card":474,"direction":478,"ingested_from":480},[],{"tldr":475,"method":476,"finding":477,"direction":478,"opportunity":479},"构建农业产业链可信数据空间框架，并在某市食品安全场景验证数据可信流转闭环。","基于可信数据空间标准，融合语义互操作、连接器、隐私计算与区块链，用约12万条抽检","框架可实现农业产业链数据可信流转闭环，但仅单场景验证，跨域推广效果待评估。","数字乡村与农业信息化","可研究跨域、多产业链场景下的可信数据空间推广机制与互操作标准适配问题。","agent","2026-10-11T00:09:47.452615Z",{"id":483,"title":484,"url":485,"summary":486,"summary_zh":19,"content":487,"source_name":488,"source_url":19,"published_at":73,"category":74,"cover_url":19,"hotness":23,"is_selected":50,"score":433,"score_detail":489,"sources":491,"tags":493,"primary_topic":498,"secondary_topics":504,"classification":505,"search_phrases":521,"slug":524,"view_count":116,"doi":19,"paper":19,"created_at":525},4613,"重庆445万块耕地实现赋码管理:45项信息一图统揽、一码查地","https:\u002F\u002Fnyncw.cq.gov.cn\u002Fzwxx_161\u002Fzwdt\u002F202610\u002Ft20261009_16204300.html","重庆市依托巴渝良田应用系统,整合农业农村、自然资源、水利、林业等部门123个图层数据,将全市445万块耕地纳入农地一张图,每块地赋唯一编码、关联地类、质量、坡度、权属、高标准农田建设情况等45项信息。AI识别+无人机巡查可半小时巡完上千亩耕地、秒级预警隐蔽问题;建设资金专户管理与预算一体化平台互联互通,实现资金流、项目流、业务流三流贯通全程可追溯。","本报讯  10月8日，记者从市农业农村委获悉，我市依托“巴渝良田”应用系统，全市445万块耕地实现“赋码管理”，通过整合123个图层数据，构建起“农地一张图”，实现地类、质量、坡度等45项信息“一图统揽、一码查地”。\n\n10月8日，在垫江县桂东街道龙田村，种粮大户李伦明站在田埂上，掏出手机对着高标准农田建设项目标识牌上的二维码轻轻一扫，屏幕上立刻弹出地块信息：面积326亩，坡度小于15度，土壤类型为紫色土，属于2025年高标准农田改造提升项目区，施工单位、监理单位、建设工期清清楚楚。“有了这个‘电子身份证’，哪块地什么情况，一目了然。”李伦明说。\n\n李伦明口中的“电子身份证”，正是我市全面启动的“巴渝良田”应用系统。该系统通过整合农业农村、自然资源、水利、林业等部门的123个图层数据，将全市445万块耕地纳入“农地一张图”，每块地都被赋予唯一编码，关联地类、质量、坡度、权属、高标准农田建设情况等45项信息。管理人员和群众扫码即可查地，彻底告别了过去翻图纸、跑现场、层层问询的传统模式。\n\n垫江县农业农村委工作人员王强打开“巴渝良田”系统，轻点鼠标，一架无人机沿着预设航线对在建的高标准农田项目进行空中巡查。高清画面实时回传，AI很快识别出某处沟渠铺设厚度不达标。系统立即生成整改工单，同步推送给施工方、监理方和项目负责人。“以前发现这种隐蔽问题，得靠人下到田里一处处量，现在‘空中慧眼’半小时就能巡完上千亩耕地，问题秒级预警、闭环整改。”王强说。\n\n除了“管地”，数字监管还“管钱”。我市将所有高标准农田项目建设资金纳入专户管理，依托“巴渝良田”系统与预算管理一体化平台互联互通，让资金流、项目流、业务流“三流贯通”，每一笔资金拥有唯一“身份证号”，实现全程可追溯、可核验。","重庆市农业农村委员会 2026-10-09",{"impact":128,"substance":128,"depth":180,"authority":98,"freshness":77,"relevant":31,"comment":490},"省级耕地数字化管理落地案例，445万块耕地赋码、123图层整合与AI无人机巡查等细节扎实，具备主题聚合与检索价值。",[492],{"name":488,"url":485},[82,494,495,272,496,497],"高标准农田","耕地保护","农地一张图","赋码管理",{"code":499,"slug":500,"name":501,"path":502,"parent_code":503},"H1","farmland","耕地保护与高标准农田","\u002Ftopic\u002Fenvironment\u002Ffarmland","H",[],{"status":49,"locked":50,"version":51,"method":52,"evidence":506},{"candidates":507,"agricultural_evidence":24},[508,513,517],{"code":499,"score":77,"supported":24,"title":509,"abstract":510,"tags":512},[],[494,511],"农田建设",[495,494],{"code":298,"score":31,"supported":50,"title":514,"abstract":515,"tags":516},[],[],[272],{"code":88,"score":31,"supported":50,"title":518,"abstract":519,"tags":520},[],[],[82],[522,523],"重庆 巴渝良田 赋码管理","重庆 高标准农田 一码查地","重庆巴渝良田赋码管理-4613","2026-10-11T00:09:35.623381Z",{"id":527,"title":528,"url":529,"summary":530,"summary_zh":531,"content":19,"source_name":532,"source_url":529,"published_at":73,"category":263,"cover_url":19,"hotness":23,"is_selected":50,"score":433,"score_detail":533,"sources":535,"tags":537,"primary_topic":541,"secondary_topics":545,"classification":546,"search_phrases":565,"slug":568,"view_count":170,"doi":569,"paper":570,"created_at":586},4588,"Integrating terrestrial and marine remote sensing indicators to estimate subnational economic output","https:\u002F\u002Fdoi.org\u002F10.1080\u002F01431161.2026.2743115","Subnational economic data remain scarce across much of the Global South, particularly in fragmented island and coastal geographies, thereby constraining the capacity of researchers and policymakers to monitor local economic conditions. This study proposes and empirically evaluates a four-proxy remote sensing framework for subnational gross domestic product (GDP) estimation. The framework extends the established Night-time Lights (NTL)–Normalised Difference Vegetation Index (NDVI)–Forest Loss (FL) approach by incorporating sea surface Chlorophyll-a (CHLA) as a marine fisheries proxy. This achieves full proxy coverage across the non-agriculture, forestry, and fisheries sector through NTL, agriculture through NDVI, forestry through FL, and marine fisheries through CHLA. The empirical analysis employs Multiscale Geographically Weighted Regression (MGWR) and pooled ordinary least squares (OLS) across 102 regencies and cities in Sulawesi and Maluku, eastern Indonesia, over 2015–2024, with a province-level panel extending to 2002–2024. The stepwise MGWR R2 rises from 0.468 (NTL only) to 0.543 (NTL, NDVI, and FL) to 0.561 (full model), with a pooled Pearson correlation of 0.760. CHLA is positive and significant at both spatial scales after conditioning on all terrestrial proxies, confirmed by OLS coefficients of 0.029 at the regency\u002Fcity level and 0.148 at the province level, significant at the 0.1% and 1% levels respectively. All proxy relationships replicate in direction and significance across scales and over the 23-year panel. The framework provides a freely replicable tool for subnational economic monitoring in data-scarce coastal and island settings, with direct applicability to marine-dependent primary sector economies globally.","在全球南方的大部分地区，尤其是碎片化的岛屿和沿海地理区域，地方经济数据仍然稀缺，从而制约了研究者和政策制定者监测地方经济状况的能力。本研究提出并实证评估了一个用于地方国内生产总值（GDP）估算的四代理变量遥感框架。该框架在已有的夜间灯光（NTL）—归一化植被指数（NDVI）—森林损失（FL）方法基础上，引入海表叶绿素a（CHLA）作为海洋渔业代理变量。由此实现了对非农、林业和渔业部门的代理变量全覆盖：NTL对应非农部门，NDVI对应农业，FL对应林业，CHLA对应海洋渔业。实证分析采用多尺度地理加权回归（MGWR）和混合普通最小二乘法（OLS），覆盖印度尼西亚东部苏拉威西和马鲁古的102个县和市，时间范围为2015—2024年，并辅以延伸至2002—2024年的省级面板数据。逐步MGWR的R²从0.468（仅NTL）升至0.543（NTL、NDVI和FL）再升至0.561（全模型），混合皮尔逊相关系数为0.760。在控制所有陆地代理变量后，CHLA在两个空间尺度上均为正向且显著，OLS系数在县\u002F市级为0.029、省级为0.148，分别在0.1%和1%水平上显著。所有代理变量关系在不同尺度和23年面板期间在方向和显著性上均得到重复验证。该框架为数据稀缺的沿海和岛屿地区的地方经济监测提供了一个可自由复制的工具，并可直接适用于全球依赖海洋的初级产业经济体。","International Journal of Remote Sensing",{"impact":29,"substance":128,"depth":29,"authority":129,"freshness":181,"relevant":31,"comment":534},"将叶绿素a纳入遥感代理框架估算次国家级GDP，方法新颖、数据扎实，对数据稀缺沿海岛屿地区的农业与渔业经济监测有直接参考价值。",[536],{"name":532,"url":529},[82,538,272,539,540],"农业遥感","渔业经济","GDP估算",{"code":298,"slug":542,"name":543,"path":544,"parent_code":92},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",[],{"status":49,"locked":50,"version":51,"method":52,"evidence":547},{"candidates":548,"agricultural_evidence":24},[549,555,561],{"code":298,"score":283,"supported":24,"title":550,"abstract":552,"tags":554},[551],"remote sensing",[553,551],"遥感",[538,272],{"code":556,"score":241,"supported":24,"title":557,"abstract":558,"tags":560},"D",[],[559],"渔业",[],{"code":88,"score":31,"supported":50,"title":562,"abstract":563,"tags":564},[],[],[82],[566,567],"苏拉威西 马鲁古 遥感 GDP","叶绿素a 海洋渔业 遥感","苏拉威西马鲁古遥感GDP-4588","10.1080\u002F01431161.2026.2743115",{"doi":569,"openalex_id":571,"authors":572,"venue":532,"cited_by_count":116,"oa_url":19,"card":581,"direction":339,"ingested_from":341},"W7221189467",[573,576,578],{"name":574,"orcid":575},"Laurenz Thiele","https:\u002F\u002Forcid.org\u002F0009-0009-9294-1337",{"name":577,"orcid":19},"Amanus Khalifafilardy Yunus",{"name":579,"orcid":580},"Rahmatia","https:\u002F\u002Forcid.org\u002F0009-0009-7550-9243",{"tldr":582,"method":583,"finding":584,"direction":339,"opportunity":585},"提出融合陆地与海洋遥感指标的四代理框架，估算印尼东部次国家级GDP。","用夜间灯光、NDVI、森林损失与叶绿素a，结合MGWR和OLS分析102个县市。","加入叶绿素a后模型R²从0.543升至0.561，海洋渔业代理显著提升经济估算精度。","可将海洋遥感代理拓展至其他沿海地区，并耦合渔业产量与贸易数据验证经济监测普适性。","2026-10-10T23:30:28.117529Z",{"id":588,"title":589,"url":590,"summary":591,"summary_zh":592,"content":19,"source_name":593,"source_url":590,"published_at":262,"category":263,"cover_url":19,"hotness":23,"is_selected":50,"score":433,"score_detail":594,"sources":596,"tags":598,"primary_topic":602,"secondary_topics":603,"classification":612,"search_phrases":655,"slug":658,"view_count":170,"doi":659,"paper":660,"created_at":679},4575,"A review of remote sensing for agricultural drought: technologies, indices, modelling advances and future prospects","https:\u002F\u002Fdoi.org\u002F10.1080\u002F15481603.2026.2738981","Agricultural drought is a complex hazard that jeopardises food security and progress toward the Sustainable Development Goals. We systematically reviewed peer-reviewed English-language literature published between 2015 and 2025, focusing on Remote Sensing (RS)-driven agricultural drought monitoring and prediction. Eligible studies were identified from the Web of Science and Scopus databases (last searched in August 2025); review articles, duplicates, and irrelevant studies were excluded, resulting in 181 articles. This review critically examined the evolution of sensors, drought indices, modelling approaches, and emerging technologies used to assess agricultural drought across diverse agro-ecological regions. Specifically, we (1) systematically evaluated the use of optical, thermal, and microwave RS platforms, along with satellite-based, model-based, and reanalysis products for agricultural drought monitoring; (2) reviewed widely used RS-based drought indices, including single indices grouped into nine categories, as well as composite indices; (3) reviewed software or programming languages applied; (4) assessed the progression of modelling approaches from traditional statistical and time-series methods to machine learning (ML) and deep learning (DL) frameworks; and (5) examined validation strategies applied to agricultural drought assessment. The analysis reveals a growing research interest in this topic, with a strong geographic concentration in Asia, particularly China. Optical and thermal platforms (e.g. MODIS and Landsat) dominate the literature (~54%) due to their accessibility, followed by satellite-derived precipitation products (17%), while microwave soil-moisture missions remain underutilized (~7%). Regarding RS-based indices, most studies employed more than one index: 44% analysed multiple individual indices, 51% used composite indices (either alone or in combination with individual indices), and only 5% relied on a single index. Vegetation indices, such as NDVI, remain workhorses; however, their sensitivity to soil background effects and canopy saturation has driven increased adoption of thermal composites (e.g. VHI), as well as adaptive weighting schemes and principal component analysis-based approaches. Moreover, computational tools used in drought research can be broadly grouped into geospatial and RS platforms for large-scale data processing and analysis (e.g. QGIS, GEE), and general-purpose programming languages (e.g. R, Python) for model development and advanced analytics. Regarding the methodology, statistical and time-series approaches account for 64% of the reviewed studies, followed by ML models (20%) and DL methods (15%), while explainable artificial intelligence (XAI) remains nascent. Techniques, such as random forests, support vector machines, and CNN and LSTM architectures, generally outperform traditional models but require large training datasets and raise concerns related to interpretability and ethics. In terms of validation, hydro-climatic indices such as SPI and SPEI are most commonly used (32%), followed by crop yield and yield anomaly data (19%). This review further identifies key research gaps across sensors, indices, and modelling approaches and proposes a roadmap for developing equitable, interpretable, and resilient agricultural drought monitoring systems. Emerging opportunities include context-aware and interpretable AI, multi-sensor and multi-scale data fusion across optical, thermal, and microwave domains, integration of physiologically meaningful indicators such as sun-induced chlorophyll fluorescence (SIF), robust uncertainty quantification, and the development of hybrid and physics-informed modelling frameworks.","农业干旱是一种复杂的灾害，威胁粮食安全和可持续发展目标的实现。我们系统综述了2015年至2025年间发表的同行评议英文文献，聚焦于遥感（RS）驱动的农业干旱监测与预测。符合条件的研究通过Web of Science和Scopus数据库检索确定（最后检索时间为2025年8月）；综述文章、重复文献及不相关研究被排除，最终纳入181篇文献。本综述批判性地审视了用于评估不同农业生态区农业干旱的传感器、干旱指数、建模方法及新兴技术的演变。具体而言，我们（1）系统评估了光学、热红外和微波遥感平台，以及基于卫星、基于模型和再分析产品在农业干旱监测中的应用；（2）综述了广泛使用的基于遥感的干旱指数，包括归为九类的单一指数以及复合指数；（3）综述了所应用的软件或编程语言；（4）评估了建模方法从传统统计和时间序列方法向机器学习（ML）和深度学习（DL）框架的演进；（5）考察了应用于农业干旱评估的验证策略。分析显示，该主题的研究兴趣日益增长，地理上高度集中于亚洲，尤其是中国。光学和热红外平台（如MODIS和Landsat）因其可获取性在文献中占主导地位（约54%），其次是卫星降水产品（17%），而微波土壤水分任务仍未得到充分利用（约7%）。在基于遥感的指数方面，大多数研究采用了不止一种指数：44%分析了多个单一指数，51%使用了复合指数（单独使用或与单一指数结合使用），仅5%依赖单一指数。植被指数（如NDVI）仍是主力工具；然而，其对土壤背景效应和冠层饱和的敏感性推动了热红外复合指数（如VHI）以及自适应权重方案和基于主成分分析的方法得到更多采用。此外，干旱研究中使用的计算工具可大致分为用于大规模数据处理和分析的地理空间与遥感平台（如QGIS、GEE），以及用于模型开发的通用编程语言（如R、Python）。","GIScience & Remote Sensing",{"impact":29,"substance":128,"depth":266,"authority":129,"freshness":77,"relevant":31,"comment":595},"系统综述181篇文献，梳理遥感干旱监测的传感器、指数与建模进展，方法学价值高，但属学术综述，产业落地影响有限。",[597],{"name":593,"url":590},[439,599,600,272,601],"粮食安全","机器学习","农业干旱",{"code":298,"slug":542,"name":543,"path":544,"parent_code":92},[604,608],{"code":282,"slug":605,"name":606,"path":607,"parent_code":503},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate",{"code":108,"slug":609,"name":610,"path":611,"parent_code":92},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",{"status":49,"locked":50,"version":51,"method":52,"evidence":613},{"candidates":614,"agricultural_evidence":24},[615,619,623,631,636,640,645,651],{"code":298,"score":30,"supported":24,"title":616,"abstract":617,"tags":618},[551],[553,551],[272],{"code":282,"score":129,"supported":24,"title":620,"abstract":621,"tags":622},[285],[287,285],[],{"code":108,"score":23,"supported":24,"title":624,"abstract":625,"tags":630},[],[626,600,627,628,629],"深度学习","machine learning","deep learning","artificial intelligence",[600],{"code":375,"score":223,"supported":24,"title":632,"abstract":633,"tags":635},[],[599,634],"food security",[599],{"code":290,"score":291,"supported":24,"title":637,"abstract":638,"tags":639},[],[294,295],[],{"code":556,"score":241,"supported":24,"title":641,"abstract":642,"tags":644},[],[643],"水产",[],{"code":646,"score":241,"supported":24,"title":647,"abstract":648,"tags":650},"H6",[],[649],"农业生态",[],{"code":459,"score":31,"supported":50,"title":652,"abstract":653,"tags":654},[],[],[439],[656,657],"遥感 农业干旱 监测","GIScience Remote Sensing 干旱指数","遥感农业干旱监测-4575","10.1080\u002F15481603.2026.2738981",{"doi":659,"openalex_id":661,"authors":662,"venue":593,"cited_by_count":116,"oa_url":672,"card":673,"direction":678,"ingested_from":341},"W7221081979",[663,666,669],{"name":664,"orcid":665},"Fatemeh Saba","https:\u002F\u002Forcid.org\u002F0000-0001-6171-155X",{"name":667,"orcid":668},"Nima Ahmadian","https:\u002F\u002Forcid.org\u002F0000-0003-3676-1840",{"name":670,"orcid":671},"Olena Dubovyk","https:\u002F\u002Forcid.org\u002F0000-0002-7338-3167","https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Fpdf\u002F10.1080\u002F15481603.2026.2738981?needAccess=true",{"tldr":674,"method":675,"finding":676,"direction":339,"opportunity":677},"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。","基于Web of Science与Scopus的181篇文献系统综述，涵盖光学\u002F","光学热红外平台占主导，微波土壤水分利用不足；复合指数与机器学习建模成为趋势。","微波土壤水分数据融合与深度学习干旱预测模型在数据稀缺区验证是潜在研究空白。","智慧农业 \u002F 农业物联网","2026-10-10T23:30:14.933078Z",{"id":681,"title":682,"url":683,"summary":684,"summary_zh":685,"content":19,"source_name":686,"source_url":683,"published_at":73,"category":263,"cover_url":19,"hotness":687,"is_selected":50,"score":433,"score_detail":688,"sources":692,"tags":697,"primary_topic":702,"secondary_topics":703,"classification":714,"search_phrases":756,"slug":759,"view_count":31,"doi":760,"paper":761,"created_at":771},4573,"APPLICATION OF ARTIFICIAL INTELLIGENCE AND AUTOMATION TECHNOLOGIES IN MODERN AGRICULTURAL MACHINERY","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23255982","The rapid development of artificial intelligence (AI), robotics, computer vision, Internet of Things (IoT), satellite navigation, remote sensing, and autonomous control systems is transforming the design and operation of modern agricultural machinery. Agricultural machinery is increasingly evolving from conventional mechanical equipment into intelligent cyber-physical systems capable of sensing field conditions, processing large volumes of data, making operational decisions, and executing agricultural tasks with limited human intervention. This article examines the application of artificial intelligence and automation technologies in tractors, harvesters, sprayers, robotic platforms, unmanned aerial vehicles, and other agricultural machinery. The study is based on a systematic analysis of scientific publications, international institutional reports, and documented agricultural technology adoption data. Particular attention is given to autonomous navigation, machine vision, precision spraying, variable-rate application, crop monitoring, yield prediction, robotic weeding, harvesting, and safety systems. Evidence from the United States demonstrates substantial growth in precision-agriculture adoption: automated guidance systems were used on more than half of the acreage planted to several major crops, while in 2023 guidance autosteering was used by 52 percent of midsize farms and 70 percent of large-scale crop-producing farms. Scientific literature also demonstrates the growing role of machine learning in yield estimation, nitrogen management, disease detection, and robotic perception. However, high acquisition costs, inadequate rural connectivity, data governance issues, cybersecurity, technical complexity, and safety risks remain significant barriers. The study concludes that AI-enabled agricultural machinery can contribute to higher operational efficiency, more precise input application, reduced operator fatigue, improved resource management, and greater agricultural sustainability, provided that technological development is accompanied by appropriate infrastructure, human-capacity development, interoperability standards, and safety regulation.","人工智能（AI）、机器人技术、计算机视觉、物联网（IoT）、卫星导航、遥感及自主控制系统的快速发展，正在深刻改变现代农业机械的设计与运行方式。农业机械正日益从传统机械设备演变为智能信息物理系统，能够感知田间条件、处理海量数据、做出作业决策，并在有限人工干预下执行农业任务。本文探讨了人工智能与自动化技术在拖拉机、联合收割机、喷雾机、机器人平台、无人机及其他农业机械中的应用。研究基于对科学文献、国际机构报告及已记录的农业技术采用数据的系统分析。重点关注自主导航、机器视觉、精准喷雾、变量施用、作物监测、产量预测、机器人除草、收获及安全系统。来自美国的证据表明，精准农业的采用率大幅增长：自动导航系统已应用于多种主要作物一半以上的种植面积，而2023年，52%的中型农场和70%的大型作物生产农场使用了导航自动转向技术。科学文献也表明，机器学习在产量估算、氮素管理、病害检测和机器人感知中的作用日益增强。然而，高昂的购置成本、农村网络连接不足、数据治理问题、网络安全、技术复杂性及安全风险仍是重要障碍。研究结论认为，在技术发展的同时配套适当的基础设施、人力能力建设、互操作性标准和安全监管，人工智能赋能的农业机械能够有助于提高作业效率、实现更精准的投入施用、减轻操作人员疲劳、改善资源管理并增强农业可持续性。","Zenodo (CERN European Organization for Nuclear Research)",25,{"impact":128,"substance":689,"depth":29,"authority":690,"freshness":77,"relevant":31,"comment":691},20,13,"系统梳理AI与自动化在农机领域应用的综述性论文，含美国精准农业采纳率等实证数据，对智慧农业主题聚合有较高参考价值。",[693,694],{"name":686,"url":683},{"name":695,"url":696},"International Bulletin of Engineering and Technology","https:\u002F\u002Finternationalbulletins.com\u002Fintjour\u002Findex.php\u002Fibet\u002Farticle\u002Fview\u002F2468",[439,83,698,699,700,701],"农业机器人","农业物联网","精准农业","自动驾驶农机",{"code":108,"slug":609,"name":610,"path":611,"parent_code":92},[704,709],{"code":705,"slug":706,"name":707,"path":708,"parent_code":144},"F5","machinery","农机装备与机械化","\u002Ftopic\u002Finputs-equipment\u002Fmachinery",{"code":710,"slug":711,"name":712,"path":713,"parent_code":92},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",{"status":49,"locked":50,"version":51,"method":52,"evidence":715},{"candidates":716,"agricultural_evidence":24},[717,723,730,737,741,745,751],{"code":108,"score":29,"supported":24,"title":718,"abstract":719,"tags":722},[629],[600,720,627,629,721],"计算机视觉","computer vision",[83],{"code":705,"score":180,"supported":24,"title":724,"abstract":726,"tags":729},[725],"agricultural machinery",[727,728,725],"农业机械","收割机",[],{"code":710,"score":23,"supported":24,"title":731,"abstract":732,"tags":736},[],[733,734,735],"物联网","internet of things","IoT",[699],{"code":298,"score":291,"supported":24,"title":738,"abstract":739,"tags":740},[],[553,551],[],{"code":459,"score":56,"supported":24,"title":742,"abstract":743,"tags":744},[],[700],[439,700],{"code":746,"score":241,"supported":24,"title":747,"abstract":748,"tags":750},"F4",[],[749],"除草",[],{"code":752,"score":31,"supported":50,"title":753,"abstract":754,"tags":755},"F6",[],[],[698],[757,758],"农业机械 人工智能 自动化","精准农业 自动驾驶 农机","农业机械人工智能自动化-4573","10.5281\u002Fzenodo.23255982",{"doi":760,"openalex_id":762,"authors":763,"venue":686,"cited_by_count":116,"oa_url":683,"card":766,"direction":678,"ingested_from":341},"W7221138004",[764],{"name":765,"orcid":19},"Rahimjonov Shoxrux Shuhratjon o'g'li",{"tldr":767,"method":768,"finding":769,"direction":678,"opportunity":770},"系统综述AI与自动化技术在现代农机中的应用现状、效益与障碍。","系统分析科学文献、国际机构报告及美国精准农业采用数据。","AI农机可提升效率与可持续性，但成本、连接性、数据治理与安全仍是主要障碍。","可研究低成本AI农机方案、农村连接与数据治理标准，及人机协同安全监管框架。","2026-10-10T23:30:13.826410Z",{"id":773,"title":774,"url":775,"summary":776,"summary_zh":777,"content":19,"source_name":778,"source_url":775,"published_at":73,"category":263,"cover_url":19,"hotness":23,"is_selected":50,"score":433,"score_detail":779,"sources":781,"tags":783,"primary_topic":789,"secondary_topics":794,"classification":795,"search_phrases":859,"slug":862,"view_count":170,"doi":863,"paper":864,"created_at":878},4557,"The impact of agricultural socialized services on grain farmers’ agricultural eco‑economic efficiency","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1880279","Developing agricultural socialized services (ASS) while promoting green and low-carbon grain production is an important component of agricultural modernization in China. Although previous studies have examined the effects of ASS on agricultural productivity, farm income, and individual input use, it remains unclear whether ASS improve household-level agricultural eco-economic efficiency (AEE), which jointly accounts for economic output, resource use, and environmental costs. Evidence is also limited regarding the factor-allocation channels and production conditions underlying this relationship. Using survey data from 5,992 grain-producing households across 14 provinces in China, this study examines household-level AEE and examines its relationship with ASS adoption using OLS and an instrumental-variable two-stage least squares specification. The results indicate that: (1) ASS adoption is positively associated with grain farmers’ AEE; (2) the estimated relationship varies across farm sizes and crop types, with a more pronounced positive estimate among farmers operating at least 2 ha, but a negative estimate among wheat-growing households; and (3) ASS adoption is associated with a lower share of fertilizer and pesticide expenditure in total variable production costs, whereas no statistically significant labor-reallocation channel is identified. These findings suggest that ASS policies should improve service quality, reduce smallholders’ barriers to service access, develop crop- and production-stage-specific service packages, and promote more precise management of agricultural inputs.","发展农业社会化服务（agricultural socialized services，ASS）并推动粮食绿色低碳生产，是中国农业现代化的重要组成部分。尽管已有研究考察了ASS对农业生产力、农户收入及单项投入品使用的影响，但ASS是否能够提升农户层面的农业生态经济效率（agricultural eco-economic efficiency，AEE）——该效率综合考量经济产出、资源利用与环境成本——仍不明确。关于这一关系背后的要素配置渠道和生产条件，现有证据也较为有限。本研究利用中国14个省份5 992户粮食种植户的调查数据，测度农户层面的AEE，并采用OLS和工具变量两阶段最小二乘（IV-2SLS）方法考察其与ASS采纳的关系。结果表明：（1）ASS采纳与粮农AEE呈正相关；（2）这一估计关系因经营规模和作物类型而异，在经营面积不低于2公顷的农户中正向估计更为显著，但在小麦种植户中呈负向估计；（3）ASS采纳与肥料和农药支出在总可变生产成本中占比下降相关，而未发现统计上显著的劳动力再配置渠道。上述发现表明，ASS政策应提升服务质量，降低小农户获取服务的门槛，开发针对特定作物和生产环节的服务包，并推动农业投入品更为精准的管理。","Frontiers in Sustainable Food Systems",{"impact":29,"substance":128,"depth":29,"authority":129,"freshness":181,"relevant":31,"comment":780},"基于14省5992户粮农调查的实证研究，方法规范、数据扎实，结论对农业社会化服务政策有参考价值，但属学术论文，公共传播性有限。",[782],{"name":778,"url":775},[784,785,786,787,788],"农业绿色发展","农业社会化服务","农户调查","粮食生产","生态经济效率",{"code":790,"slug":791,"name":792,"path":793,"parent_code":192},"G2","farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services",[],{"status":49,"locked":50,"version":51,"method":52,"evidence":796},{"candidates":797,"agricultural_evidence":24},[798,804,811,818,824,831,837,841,845,849,854],{"code":790,"score":77,"supported":24,"title":799,"abstract":800,"tags":803},[],[801,802],"社会化服务","小农户",[785,786],{"code":805,"score":291,"supported":24,"title":806,"abstract":807,"tags":810},"A2",[],[808,809],"小麦","wheat",[],{"code":812,"score":291,"supported":24,"title":813,"abstract":814,"tags":817},"F3",[],[815,816],"肥料","fertilizer",[],{"code":746,"score":291,"supported":24,"title":819,"abstract":820,"tags":823},[],[821,822],"农药","pesticide",[],{"code":825,"score":291,"supported":24,"title":826,"abstract":827,"tags":830},"J2",[],[828,829],"农业现代化","agricultural 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