[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4579":3,"related-4579":115},{"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":24,"tags":26,"primary_topic":9,"secondary_topics":32,"classification":33,"search_phrases":68,"slug":71,"view_count":22,"doi":72,"paper":73,"created_at":114},4579,"Drought responses of a Norway spruce forest on drained peat soil: combining sap-flow sensors, eddy-covariance, meteorological, soil and UAV data","https:\u002F\u002Fdoi.org\u002F10.5194\u002Fbg-23-7091-2026","Abstract. The summer of 2021 brought a severe drought to southern Finland. We explored how a drained boreal peatland forest responds to drought by combining a wide range of in situ monitoring and Unmanned Aerial Vehicle (UAV) remote sensing. A dataset combining eddy-covariance (EC) fluxes, sap-flow sensors, UAV mapping, soil and weather data was collected. Spruce stand reaction to drought is examined at sub-daily to seasonal time scales, and its temporal and spatial features are identified separately for a recently thinned Continuous Cover Forestry (CCF) block and a control block. Sap flow data showed that the CCF-harvested block shows greater tree resilience to high vapour pressure deficit (VPD) than the control block, likely due to the higher soil water availability during the rainless and hot period. At the same time, both the control and CCF harvest blocks had notably reduced net ecosystem exchange (NEE) and increased Bowen ratio, particularly on high VPD days. The UAV surveys indicated that trees in the CCF block tend to have higher canopy temperatures and lower Normalized Difference Vegetation Index (NDVI) than in the control block, implying their possible susceptibility to more extreme drought.","摘要：2021年夏季，芬兰南部遭遇严重干旱。我们结合多种原位监测与无人机（UAV）遥感手段，探讨了排水泥炭地森林对干旱的响应。研究收集了涡度协方差（EC）通量、液流传感器、无人机测绘、土壤及气象数据。我们在亚日到季节尺度上考察了云杉林分对干旱的响应，并分别针对近期疏伐的连续覆盖林业（CCF）样地和对照样地识别其时间和空间特征。液流数据显示，CCF采伐样地中的树木对高饱和水汽压差（VPD）的恢复力强于对照样地，这可能归因于无雨高温期间较高的土壤水分有效性。同时，对照样地和CCF采伐样地的净生态系统交换（NEE）均显著降低，波文比升高，尤其在高VPD日更为明显。无人机调查表明，CCF样地中的树木冠层温度较高，归一化植被指数（NDVI）较低，暗示其可能更易受到更极端干旱的影响。",null,"Biogeosciences","2026-10-09T00:00:00Z","论文",10,false,74,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,22,18,14,8,1,"多源遥感与地面通量观测结合的干旱响应研究，方法新颖、数据扎实，对林业碳汇与智慧林业监测有参考价值。",[25],{"name":10,"url":6},[27,28,29,30,31],"气候变化","无人机遥感","遥感监测","土壤水分","森林碳汇",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":37},"needs_review","2026-10-22.2","rules",{"candidates":38,"agricultural_evidence":14,"reason":67},[39,48,55,62],{"code":40,"score":41,"supported":42,"title":43,"abstract":45,"tags":47},"H2",15,true,[44],"soil",[46,44],"土壤",[30],{"code":49,"score":41,"supported":42,"title":50,"abstract":52,"tags":54},"H7",[51],"drought",[53,51],"干旱",[27],{"code":56,"score":21,"supported":42,"title":57,"abstract":58,"tags":61},"I3",[],[59,60],"遥感","remote sensing",[28,29],{"code":63,"score":22,"supported":14,"title":64,"abstract":65,"tags":66},"H4",[],[],[31],"农业相关性需要复核",[69,70],"挪威云杉 泥炭地 干旱","UAV 涡度相关 云杉","挪威云杉泥炭地干旱-4579","10.5194\u002Fbg-23-7091-2026",{"doi":72,"openalex_id":74,"authors":75,"venue":10,"cited_by_count":106,"oa_url":6,"card":107,"direction":111,"ingested_from":113},"W7127903348",[76,79,82,85,88,91,93,96,98,101,103],{"name":77,"orcid":78},"Pavel Alekseychik","https:\u002F\u002Forcid.org\u002F0000-0002-4081-3917",{"name":80,"orcid":81},"Mikko Peltoniemi","https:\u002F\u002Forcid.org\u002F0000-0003-2028-6969",{"name":83,"orcid":84},"Raisa Mäkipää","https:\u002F\u002Forcid.org\u002F0000-0003-3146-4425",{"name":86,"orcid":87},"Ville Tuominen","https:\u002F\u002Forcid.org\u002F0000-0002-0612-128X",{"name":89,"orcid":90},"Tuomas Laurila","https:\u002F\u002Forcid.org\u002F0000-0002-1967-0624",{"name":92,"orcid":9},"Hamlyn G. Jones",{"name":94,"orcid":95},"Mitro Müller","https:\u002F\u002Forcid.org\u002F0000-0003-0456-9432",{"name":97,"orcid":9},"Evgeny Lopatin",{"name":99,"orcid":100},"Helena Rautakoski","https:\u002F\u002Forcid.org\u002F0000-0002-5297-286X",{"name":102,"orcid":9},"Timo Vesala",{"name":104,"orcid":105},"Samuli Launiainen","https:\u002F\u002Forcid.org\u002F0000-0001-6611-6573",0,{"tldr":108,"method":109,"finding":110,"direction":111,"opportunity":112},"结合液流、涡度协方差与无人机数据，研究芬兰排水泥炭云杉林对2021年干旱的响应。","液流传感器、涡度协方差、气象土壤及无人机多源数据，对比间伐与对照样地。","间伐样地树木对高VPD更具恢复力，但冠层温度更高、NDVI更低，可能更易受极端干旱影响。","农业遥感与作物表型","可探究间伐后水分可利用性改善与冠层胁迫信号矛盾背后的机制，并融合多源遥感构建干旱脆弱性预警指标。","openalex","2026-10-10T23:30:20.055428Z",{"total":116,"page":22,"page_size":116,"items":117},6,[118,199,247,364,425,474],{"id":119,"title":120,"url":121,"summary":122,"summary_zh":123,"content":9,"source_name":124,"source_url":121,"published_at":125,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":126,"score_detail":127,"sources":130,"tags":132,"primary_topic":9,"secondary_topics":135,"classification":136,"search_phrases":161,"slug":164,"view_count":22,"doi":165,"paper":166,"created_at":198},4595,"Nationwide deadwood mapping reveals rising mountain forests vulnerability","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.isprsjprs.2026.09.041","Forest mortality is increasing globally under climate change, making detailed, large-scale monitoring essential for understanding ecosystem responses and guiding adaptive forest management. Here, we present a spatio-temporal assessment of standing deadwood in Switzerland from 2018 to 2023, derived from centimeter-scale high-resolution aerial imagery. We reveal a consistent upslope concentration of standing deadwood, with highest shares occurring around mid to high elevations (∼1,500 m), despite declining forest cover, and relative increases of up to 43% in overlapping survey areas following the 2018 drought. Maximum temperature anomalies and conifer dominance were the strongest predictors of standing deadwood. The consistent accumulation of standing deadwood at higher elevations suggests increasing vulnerability of mountain forests, with implications for carbon storage, biodiversity, and disturbance susceptibility under ongoing climate change. These patterns highlight the need to address rising forest mortality as a key component of climate-adaptive forest management. Furthermore, our results demonstrate the potential of high-resolution remote sensing for large-scale forest mortality monitoring. Our methods offer a reproducible and transferable framework for identifying vulnerability hotspots and supporting climate-adapted forest management.","在气候变化背景下，全球森林死亡率不断上升，因此开展详细、大规模监测对于理解生态系统响应和指导适应性森林管理至关重要。本文基于厘米级高分辨率航空影像，对2018年至2023年瑞士的立枯木进行了时空评估。我们揭示了立枯木沿海拔向上集中分布的一致规律，尽管森林覆盖度下降，其占比仍在中高海拔（约1，500 m）附近最高，且在2018年干旱后的重叠调查区域中相对增幅可达43%。最高温度异常和针叶树优势度是立枯木最强的预测因子。立枯木在高海拔地区持续累积，表明山地森林脆弱性日益增加，这对碳储存、生物多样性以及持续气候变化下的干扰易感性具有重要意义。这些格局凸显了将不断上升的森林死亡率作为气候适应性森林管理关键组成部分加以应对的必要性。此外，我们的结果证明了高分辨率遥感在大规模森林死亡率监测方面的潜力。我们的方法为识别脆弱性热点和支持气候适应性森林管理提供了一个可重复、可迁移的框架。","ISPRS Journal of Photogrammetry and Remote Sensing","2026-10-08T00:00:00Z",79,{"impact":19,"substance":18,"depth":128,"authority":20,"freshness":116,"relevant":22,"comment":129},19,"基于厘米级航空影像的全国尺度立枯木制图，方法可迁移，对山地森林脆弱性与气候适应性经营有实质参考价值。",[131],{"name":124,"url":121},[27,29,31,133,134],"林业信息化","高分影像",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":137},{"candidates":138,"agricultural_evidence":14,"reason":67},[139,145,150,157],{"code":49,"score":13,"supported":42,"title":140,"abstract":141,"tags":144},[],[27,142,53,143,51],"气候适应","climate change",[27],{"code":56,"score":146,"supported":42,"title":147,"abstract":148,"tags":149},7,[],[59,60],[29],{"code":151,"score":116,"supported":42,"title":152,"abstract":153,"tags":156},"H6",[],[154,155],"生物多样性","biodiversity",[],{"code":63,"score":22,"supported":14,"title":158,"abstract":159,"tags":160},[],[],[31],[162,163],"瑞士 立枯木 遥感监测","森林死亡 高分辨率航空影像","瑞士立枯木遥感监测-4595","10.1016\u002Fj.isprsjprs.2026.09.041",{"doi":165,"openalex_id":167,"authors":168,"venue":124,"cited_by_count":106,"oa_url":192,"card":193,"direction":111,"ingested_from":113},"W7220997028",[169,172,175,178,181,184,187,190],{"name":170,"orcid":171},"Luca Ferrari","https:\u002F\u002Forcid.org\u002F0000-0002-8957-4830",{"name":173,"orcid":174},"Lars T. Waser‬","https:\u002F\u002Forcid.org\u002F0000-0002-2609-9147",{"name":176,"orcid":177},"Achilleas Psomas","https:\u002F\u002Forcid.org\u002F0009-0008-9966-4988",{"name":179,"orcid":180},"Clemens Mosig","https:\u002F\u002Forcid.org\u002F0009-0003-8662-7698",{"name":182,"orcid":183},"Teja Kattenborn","https:\u002F\u002Forcid.org\u002F0000-0001-7381-3828",{"name":185,"orcid":186},"Christian Ginzler","https:\u002F\u002Forcid.org\u002F0000-0001-6365-2151",{"name":188,"orcid":189},"Verena C. Griess","https:\u002F\u002Forcid.org\u002F0000-0002-3856-3736",{"name":191,"orcid":9},"Mirela Beloiu","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0924271626004892\u002Fpdf",{"tldr":194,"method":195,"finding":196,"direction":111,"opportunity":197},"基于厘米级航空影像绘制瑞士2018-2023年枯立木分布图，揭示山区森林脆弱性上升。","厘米级高分辨率航空影像，时空分析与预测因子建模。","枯立木集中在中高海拔约1500米，2018年干旱后增加达43%，高温异常和针叶树优势是主因。","可迁移该高分辨率遥感框架至其他山区，结合多源数据监测森林死亡动态与碳汇变化。","2026-10-10T23:30:29.803110Z",{"id":200,"title":201,"url":202,"summary":203,"summary_zh":204,"content":9,"source_name":205,"source_url":202,"published_at":206,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":106,"score_detail":207,"sources":209,"tags":211,"primary_topic":9,"secondary_topics":214,"classification":215,"search_phrases":226,"slug":229,"view_count":106,"doi":230,"paper":231,"created_at":246},5560,"How do weather, topography and fuel condition drive the extreme behavior of a Mediterranean megafire? A case study of the 2025 Jarilla wildfire (western Spain)","https:\u002F\u002Fdoi.org\u002F10.3389\u002Fffgc.2026.1953360","The 2025 wildfire season was the most destructive on record in the European Union, with more than 1 million hectares burned, and the Iberian Peninsula was the hardest-hit region, accounting for 43% of that area. The Jarilla wildfire (Cáceres, Spain; 17,317 ha, august 2025) exemplifies how meteorology, topography, and fuel condition jointly controlled the behavior of these Iberian megafires. Our aim was to analyze the role of these three factors in the fire’s behavior and to evaluate their interpretation against the post-fire severity footprint, within a reproducible workflow relying entirely on open-access data. We combined ERA5 hourly reanalysis, the fire weather index (FWI), Sentinel-2 spectral indices (NDVI, NDII, dNBR), VIIRS active-fire detections, and the 5 m PNOA digital elevation model. During the active phase (august 12–17), the atmosphere was extremely desiccating—vapor pressure deficit peaking at 5.9 kPa, minimum relative humidity near 15%, and FWI in the “extreme” class—acting on a dense but already water-stressed fuel cover (mean NDVI 0.53, mean NDII 0.05). The wind regime was bimodal: a frequent but weak nocturnal north-easterly flow and a diurnal south–south-westerly (SSW) flow that drove the observed SW–NE progression. Fire spread corridors—steep, wind-aligned, fuel-laden terrain delineated with the SSW driving wind—covered 13.7% of the burned area and showed higher mean severity (dNBR 665) than their surroundings (525); however, 84% of the high-severity area lay outside them. These results indicate that, in such “hot-drought” megafires, severity is driven primarily by extreme atmospheric drying acting on continuous, dry fuel, whereas topography and wind spatially organize its peaks rather than determining them. Beyond reconstructing a single event, the study provides a transferable, open-data framework for diagnosing megafire drivers and suggests that fuel- and weather-based prevention, more than topographic targeting, is key to mitigating Mediterranean megafires.","2025年野火季是欧盟有记录以来破坏性最强的一个野火季，过火面积超过100万公顷，其中伊比利亚半岛是受灾最严重的地区，占该面积的43%。Jarilla野火（西班牙卡塞雷斯，17,317公顷，2025年8月）体现了气象、地形和可燃物条件如何共同控制这些伊比利亚特大火灾的行为。我们的目标是分析这三个因素在火灾行为中的作用，并在完全依赖开放获取数据的可重复工作流程中，评估它们与火后严重程度足迹的对应解释。我们结合了ERA5逐小时再分析数据、火险天气指数（FWI）、Sentinel-2光谱指数（NDVI、NDII、dNBR）、VIIRS活跃火点检测以及5米PNOA数字高程模型。在活跃阶段（8月12日至17日），大气极度干燥——饱和水汽压差峰值达5.9 kPa，最低相对湿度接近15%，FWI处于“极端”等级——作用于密集但已受水分胁迫的可燃物覆盖层（平均NDVI为0.53，平均NDII为0.05）。风况呈双峰分布：夜间频繁但微弱的东北气流，以及白天驱动观测到的西南—东北方向蔓延的南—西南（SSW）气流。火势蔓延走廊——陡峭、与风向一致、可燃物载量高的地形，以SSW驱动风 delineated——覆盖了过火面积的13.7%，并显示出比周围区域更高的平均严重程度（dNBR 665对525）；然而，84%的高严重程度区域位于这些走廊之外。这些结果表明，在此类“高温—干旱”特大火灾中，严重程度主要由极端大气干燥作用于连续、干燥的可燃物所驱动，而地形和风在空间上组织其峰值而非决定峰值。除重建单一事件外，该研究提供了一个可迁移的开放数据框架，用于诊断特大火灾驱动因素，并表明基于可燃物和天气的预防，而非地形靶向，是缓解地中海特大火灾的关键。","Frontiers in Forests and Global Change","2026-10-20T00:00:00Z",{"impact":106,"substance":106,"depth":106,"authority":106,"freshness":106,"relevant":106,"comment":208},"该研究聚焦西班牙地中海野火的气象与地形驱动机制，属于林火生态与遥感应用，与三农、农业信息化、智慧农业主题无直接关联，不建议进入每日精选。",[210],{"name":205,"url":202},[27,29,212,213],"野火研究","西班牙",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":216},{"candidates":217,"agricultural_evidence":14,"reason":67},[218,222],{"code":49,"score":146,"supported":42,"title":219,"abstract":220,"tags":221},[],[53,51],[27],{"code":56,"score":22,"supported":14,"title":223,"abstract":224,"tags":225},[],[],[29],[227,228],"气候变化 遥感监测 野火研究 西班牙","气候变化 遥感监测","气候变化遥感监测野火研究西班牙-5560","10.3389\u002Fffgc.2026.1953360",{"doi":230,"openalex_id":232,"authors":233,"venue":205,"cited_by_count":106,"oa_url":239,"card":240,"direction":245,"ingested_from":113},"W7223002169",[234,236],{"name":235,"orcid":9},"Luis Hernández-Sánchez",{"name":237,"orcid":238},"Marcos Francos","https:\u002F\u002Forcid.org\u002F0000-0002-3311-5686","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fforests-and-global-change\u002Farticles\u002F10.3389\u002Fffgc.2026.1953360\u002Fpdf",{"tldr":241,"method":242,"finding":243,"direction":111,"opportunity":244},"分析2025年西班牙Jarilla特大火灾，揭示气象、地形与燃料条件如何共同驱动火行为。","融合ERA5再分析、FWI、Sentinel-2指数、VIIRS火点和5米DEM","极端大气干燥叠加连续干旱燃料主导火强度，地形与风仅空间组织高严重度峰值而非决定其分布。","可延伸至多源遥感融合的野火驱动因子归因与火险预警，并检验该开源框架在其他地中海火区的可迁移性。","智慧农业 \u002F 农业物联网","2026-10-22T11:20:20.437834Z",{"id":248,"title":249,"url":250,"summary":251,"summary_zh":252,"content":9,"source_name":253,"source_url":250,"published_at":206,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":254,"score_detail":255,"sources":258,"tags":260,"primary_topic":264,"secondary_topics":269,"classification":278,"search_phrases":335,"slug":338,"view_count":106,"doi":339,"paper":340,"created_at":363},5483,"Soil Salinity under Climate Change in Pakistan: Emerging Challenges and Sustainable Management Approaches for Agriculture","https:\u002F\u002Fdoi.org\u002F10.71317\u002Fkjard.2.10.2026.883","Soil salinity is a major constraint to agricultural productivity, soil health, and food security in Pakistan, particularly under changing climatic conditions. Rising temperatures, increased evapotranspiration, irregular precipitation, droughts, flooding, and sea-level rise can intensify salt accumulation and alter soil–water interactions. This review examines the emerging challenges associated with climate change and soil salinity in Pakistan, focusing on their impacts on soil properties, crop physiology, agricultural production, and rural livelihoods. It discusses the mechanisms of soil salinity and sodicity, their spatial distribution, and the interactions among climate variability, irrigation practices, groundwater quality, and secondary salinization. Furthermore, sustainable management approaches are evaluated, including gypsum application, organic amendments, integrated nutrient management, efficient irrigation, drainage improvement, and appropriate leaching strategies. Climate-resilient approaches, such as conventional crop breeding, modern biotechnology, halophyte utilization, plant growth-promoting microorganisms, and mycorrhizal associations, are also explored. The review highlights the potential of remote sensing, geographic information systems, precision agriculture, and predictive modelling to support salinity monitoring and site-specific management. Despite these opportunities, important challenges remain, including insufficient long-term monitoring, limited region-specific data, economic constraints, and gaps in farmer awareness and institutional coordination. Addressing these challenges requires integrated research, effective agricultural policies, improved extension services, and collaboration among researchers, policymakers, and farming communities. Prioritizing locally adapted, economically feasible, and environmentally sustainable interventions can strengthen agricultural resilience, restore salt-affected soils, and protect freshwater resources. Overall, integrating climate adaptation with sustainable soil and water management is essential for maintaining agricultural productivity and improving long-term food security in Pakistan.","土壤盐渍化是制约巴基斯坦农业生产力、土壤健康和粮食安全的主要因素，在气候变化条件下尤为突出。气温升高、蒸散加剧、降水不规律、干旱、洪水以及海平面上升可能加剧盐分积累并改变土壤—水相互作用。本文综述了巴基斯坦气候变化与土壤盐渍化相关的新兴挑战，重点关注其对土壤性质、作物生理、农业生产和农村生计的影响。文章讨论了土壤盐渍化和钠质化的机制、其空间分布，以及气候变率、灌溉实践、地下水质量和次生盐渍化之间的相互作用。此外，评估了可持续管理途径，包括施用石膏、有机改良、综合养分管理、高效灌溉、排水改良和适宜的淋洗策略。还探讨了气候韧性方法，如常规作物育种、现代生物技术、盐生植物利用、植物促生微生物和菌根共生。本文强调了遥感、地理信息系统、精准农业和预测建模在支持盐渍化监测和因地制宜管理方面的潜力。尽管存在这些机遇，重要挑战依然存在，包括长期监测不足、区域特定数据有限、经济制约以及农民意识和制度协调方面的差距。应对这些挑战需要综合研究、有效的农业政策、改进的推广服务以及研究人员、政策制定者和农业社区之间的协作。优先采取适应当地、经济可行且环境可持续的干预措施，可增强农业韧性、修复盐渍化土壤并保护淡水资源。总体而言，将气候适应与可持续水土管理相结合，对于维持巴基斯坦农业生产力和改善长期粮食安全至关重要。","Kashmir Journal of Academic Research and Development",66,{"impact":256,"substance":19,"depth":41,"authority":17,"freshness":21,"relevant":22,"comment":257},13,"综述性论文，系统梳理气候变化下巴基斯坦土壤盐渍化成因与可持续治理路径，兼具遥感与精准农业视角，对盐碱地治理议题有参考价值，但属区域性综述、非突破性成果。",[259],{"name":253,"url":250},[27,261,29,262,263],"盐碱地治理","智慧灌溉","土壤盐渍化",{"code":49,"slug":265,"name":266,"path":267,"parent_code":268},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[270,273],{"code":40,"slug":44,"name":271,"path":272,"parent_code":268},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",{"code":274,"slug":275,"name":276,"path":277,"parent_code":268},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",{"status":279,"locked":14,"version":35,"method":36,"evidence":280},"classified",{"candidates":281,"agricultural_evidence":42},[282,286,290,297,301,308,315,322,329],{"code":49,"score":19,"supported":42,"title":283,"abstract":284,"tags":285},[143],[27,142,53,143],[27],{"code":40,"score":41,"supported":42,"title":287,"abstract":288,"tags":289},[44],[46,44],[261],{"code":274,"score":13,"supported":42,"title":291,"abstract":292,"tags":296},[],[293,294,275,295],"灌溉","水资源","evapotranspiration",[262],{"code":56,"score":146,"supported":42,"title":298,"abstract":299,"tags":300},[],[59,60],[29],{"code":302,"score":116,"supported":42,"title":303,"abstract":304,"tags":307},"A8",[],[305,306],"粮食安全","food security",[],{"code":309,"score":116,"supported":42,"title":310,"abstract":311,"tags":314},"I1",[],[312,313],"精准农业","precision agriculture",[],{"code":316,"score":116,"supported":42,"title":317,"abstract":318,"tags":321},"I4",[],[319,320],"地理信息","geographic information",[],{"code":323,"score":324,"supported":42,"title":325,"abstract":326,"tags":328},"F3",3,[],[327],"养分管理",[],{"code":330,"score":324,"supported":42,"title":331,"abstract":332,"tags":334},"J1",[],[333],"农业政策",[],[336,337],"巴基斯坦 土壤盐渍化","盐碱地 遥感监测","巴基斯坦土壤盐渍化-5483","10.71317\u002Fkjard.2.10.2026.883",{"doi":339,"openalex_id":341,"authors":342,"venue":253,"cited_by_count":106,"oa_url":250,"card":358,"direction":111,"ingested_from":113},"W7222999158",[343,345,347,349,351,353,356],{"name":344,"orcid":9},"Asifa Naz",{"name":346,"orcid":9},"Muhammad Abu Baker Siddiq",{"name":348,"orcid":9},"Syed Asghar Hussain Shah",{"name":350,"orcid":9},"Shahrish Nawaz",{"name":352,"orcid":9},"Muhmmad Irfan",{"name":354,"orcid":355},"Rizwana Kausar","https:\u002F\u002Forcid.org\u002F0000-0002-1339-3312",{"name":357,"orcid":9},"Muhammad Nouman Khalid",{"tldr":359,"method":360,"finding":361,"direction":111,"opportunity":362},"综述气候变化下巴基斯坦土壤盐渍化的挑战与可持续管理途径。","文献综述，整合盐渍化机制、空间分布及遥感GIS与预测模型应用。","需将气候适应与水土管理结合，优先本地化、经济可行的干预措施。","可填补长期盐渍化监测与区域数据空白，发展遥感+预测模型的精准分区治理。","2026-10-21T23:30:23.059448Z",{"id":365,"title":366,"url":367,"summary":368,"summary_zh":369,"content":9,"source_name":370,"source_url":367,"published_at":371,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":372,"sources":374,"tags":376,"primary_topic":380,"secondary_topics":381,"classification":382,"search_phrases":397,"slug":400,"view_count":106,"doi":401,"paper":402,"created_at":424},5172,"Forest green-up in the Pearl River Basin: trends, driving factors, and relationships with net primary productivity","https:\u002F\u002Fdoi.org\u002F10.1080\u002F17538947.2026.2738487","The spring green-up date (GUD), a critical indicator of ecosystem response to climate change, profoundly influences terrestrial productivity. However, the complex drivers of GUD remain elusive, while the contentious relationship between GUD and net primary productivity (NPP) challenges the universal validity of the hypothesis that earlier green-up enhances productivity. Using MODIS NDVI data (2000-2020), we quantified forest GUD dynamics in the Pearl River Basin and combined random forest, SHAP, and structural equation modelling to identify drivers and assess GUD-NPP relationships. GUD was advanced by approximately 5 days, with 81.8% of forestland pixels advancing and 18.2% delaying. Only 5.39% of advances showed significant trends, whereas 30.45% of delays were concentrated near croplands and developed areas. The random forest model explained 58.2% of GUD variation. Elevation, precipitation, and soil potassium and phosphorus were dominant; elevation-induced thermal gradients outweighed ambient temperature effects, with elevations above 1,200 m exhibiting markedly delayed GUD. Spatially, GUD had a positive correlation with NPP, indicating that later GUD was associated with higher forest NPP, possibly because of early-spring cold snaps and frost. Temporally, areas with stronger GUD delays tended to show greater NPP increases. This study identified key controls on subtropical forest phenology and revealed a GUD-NPP trade-off.","春季返青期（GUD）是生态系统响应气候变化的关键指标，深刻影响陆地生产力。然而，GUD的复杂驱动机制仍不明确，且GUD与净初级生产力（NPP）之间存在争议性关系，挑战了“提前返青提高生产力”这一假说的普适性。本研究利用MODIS NDVI数据（2000—2020年），量化了珠江流域森林GUD动态，并结合随机森林、SHAP和结构方程模型识别驱动因子并评估GUD-NPP关系。GUD整体提前约5天，其中81.8%的林地像元提前、18.2%推迟。仅5.39%的提前像元呈显著趋势，而30.45%的推迟像元集中在农田和建成区附近。随机森林模型解释了58.2%的GUD变异。海拔、降水以及土壤钾和磷为主导因子；海拔引起的热梯度效应超过环境温度的影响，海拔1200 m以上区域GUD显著推迟。空间上，GUD与NPP呈正相关，表明GUD越晚森林NPP越高，这可能与早春寒潮和霜冻有关。时间上，GUD推迟越强的区域往往表现为NPP增加越大。本研究识别了亚热带森林物候的关键控制因子，揭示了GUD-NPP之间的权衡关系。","International Journal of Digital Earth","2026-10-15T00:00:00Z",{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":373},"基于MODIS长时序数据的区域森林物候研究，方法组合新颖、结论有增量，但属区域基础研究，产业与政策影响有限，可作专业补充而非每日精选头条。",[375],{"name":370,"url":367},[27,29,377,378,379],"植被生产力","森林物候","珠江流域",{"code":49,"slug":265,"name":266,"path":267,"parent_code":268},[],{"status":279,"locked":14,"version":35,"method":36,"evidence":383},{"candidates":384,"agricultural_evidence":42},[385,389,393],{"code":49,"score":146,"supported":42,"title":386,"abstract":387,"tags":388},[],[27,143],[27],{"code":40,"score":116,"supported":42,"title":390,"abstract":391,"tags":392},[],[46,44],[],{"code":56,"score":22,"supported":14,"title":394,"abstract":395,"tags":396},[],[],[29],[398,399],"珠江流域 森林 返青期","MODIS NDVI 植被生产力","珠江流域森林返青期-5172","10.1080\u002F17538947.2026.2738487",{"doi":401,"openalex_id":403,"authors":404,"venue":370,"cited_by_count":106,"oa_url":418,"card":419,"direction":111,"ingested_from":113},"W7221897424",[405,408,410,412,414,416],{"name":406,"orcid":407},"Shijie Yang","https:\u002F\u002Forcid.org\u002F0009-0001-7573-5509",{"name":409,"orcid":9},"Zhaoju Zheng",{"name":411,"orcid":9},"Xueming Zhao",{"name":413,"orcid":9},"Zhipeng Zhang",{"name":415,"orcid":9},"Xiaohui Cui",{"name":417,"orcid":9},"Yuan Zeng","https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Fpdf\u002F10.1080\u002F17538947.2026.2738487?needAccess=true",{"tldr":420,"method":421,"finding":422,"direction":111,"opportunity":423},"基于MODIS NDVI量化珠江流域森林返青期动态，并解析其驱动因子及与NPP的关系。","MODIS NDVI（2000-2020）、随机森林、SHAP与结构方程模型。","返青期整体提前约5天，但延迟区NPP更高，揭示返青期与NPP的权衡关系。","可探究早春寒潮霜冻对返青-NPP权衡的调控机制，并拓展至其他亚热带流域验证普适性。","2026-10-17T23:30:29.750744Z",{"id":426,"title":427,"url":428,"summary":429,"summary_zh":430,"content":9,"source_name":431,"source_url":428,"published_at":432,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":433,"score_detail":434,"sources":438,"tags":440,"primary_topic":9,"secondary_topics":444,"classification":445,"search_phrases":454,"slug":457,"view_count":106,"doi":458,"paper":459,"created_at":473},5100,"Scale‐space image analysis for mapping spotted knapweed in grassland ecosystems","https:\u002F\u002Fdoi.org\u002F10.1002\u002Faps3.70086","Abstract Premise This study investigates the value of scale‐space representations of spatial features for the identification and mapping of invasive plants using high‐resolution multispectral imagery. Scale‐space representations combine the two‐dimensional spatial domain with a third dimension representing spatial scale, such that features can be represented across both space and image spatial resolution. Methods Gaussian pyramids were constructed to create representations of the features across five image resolution levels (between 3 and 46 cm) within the scale space. A case study was employed to evaluate the importance of features across the scale space for the identification and mapping of spotted knapweed in a grassland ecosystem using multispectral imagery acquired using a remotely piloted aircraft system (RPAS). Classification was performed using a random forest classifier that was constructed using a process that included feature and hyperparameter optimization. Results The results of this case study show that classifiers constructed with only high spatial resolution features were associated with better classification performance than those constructed with only lower spatial resolution features; however, the best classification is achieved by leveraging features from throughout the feature scale spaces. Discussion These findings suggest that optimization of the spatial scale at which features are computed can substantially improve remote sensing image analysis and potentially inform RPAS flight planning to improve mission efficiency.","摘要 前提 本研究探讨了空间特征的尺度空间表示在高分辨率多光谱影像中用于入侵植物识别与制图的价值。尺度空间表示将二维空间域与表示空间尺度的第三维相结合，从而使特征能够在空间和影像空间分辨率两个维度上得到表示。方法 构建高斯金字塔，以在尺度空间内生成跨越五个影像分辨率层级（3至46厘米）的特征表示。通过一个案例研究，评估尺度空间中的特征在使用由遥控驾驶航空器系统（RPAS）获取的多光谱影像对草地生态系统中斑点矢车菊进行识别与制图时的重要性。分类使用随机森林分类器完成，该分类器通过包含特征优化和超参数优化的流程构建。结果 本案例研究的结果表明，仅使用高空间分辨率特征构建的分类器，其分类性能优于仅使用较低空间分辨率特征构建的分类器；然而，最佳分类效果是通过综合利用整个特征尺度空间中的特征实现的。讨论 这些发现表明，优化特征计算所采用的空间尺度可以显著改进遥感影像分析，并有可能为RPAS飞行规划提供依据，以提高任务效率。","Applications in Plant Sciences","2026-10-14T00:00:00Z",71,{"impact":17,"substance":435,"depth":436,"authority":256,"freshness":21,"relevant":22,"comment":437},21,17,"方法新颖、结论可靠，但属细分领域基础研究，产业影响有限，适合作为技术前沿收录而非头条精选。",[439],{"name":431,"url":428},[28,29,441,442,443],"多光谱影像","入侵植物","草地生态",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":446},{"candidates":447,"agricultural_evidence":14,"reason":67},[448],{"code":56,"score":449,"supported":42,"title":450,"abstract":451,"tags":453},11,[],[59,60,452],"multispectral",[28,29],[455,456],"斑点矢车菊 无人机 遥感","尺度空间 多光谱 草地","斑点矢车菊无人机遥感-5100","10.1002\u002Faps3.70086",{"doi":458,"openalex_id":460,"authors":461,"venue":431,"cited_by_count":106,"oa_url":467,"card":468,"direction":111,"ingested_from":113},"W7222056923",[462,464],{"name":463,"orcid":9},"Shohreh Sahebi",{"name":465,"orcid":466},"David Hill","https:\u002F\u002Forcid.org\u002F0000-0002-4530-3131","https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002Fpdfdirect\u002F10.1002\u002Faps3.70086",{"tldr":469,"method":470,"finding":471,"direction":111,"opportunity":472},"利用尺度空间表示多光谱影像特征，结合随机森林分类器，实现草地生态系统中斑点矢车菊的识别与制图。","构建高斯金字塔生成5个分辨率层级（3-46cm）的尺度空间特征，用随机森林分类并","仅用高分辨率特征的分类器优于仅用低分辨率特征，但融合整个尺度空间特征时分类效果最佳。","可探索尺度空间特征优化在入侵植物早期监测中的应用，并指导无人机飞行规划以提升效率。","2026-10-16T23:30:31.287501Z",{"id":475,"title":476,"url":477,"summary":478,"summary_zh":479,"content":9,"source_name":480,"source_url":477,"published_at":371,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":481,"score_detail":482,"sources":486,"tags":488,"primary_topic":492,"secondary_topics":498,"classification":500,"search_phrases":541,"slug":544,"view_count":22,"doi":545,"paper":546,"created_at":557},5086,"Artificial Intelligence for Environmental Sustainability and Climate Change Mitigation: Recent Advances, Challenges, and Future Perspectives","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23399627","Abstract Climate change and environmental degradation have emerged as two of the most pressing global challenges of the twenty-first century, threatening ecosystems, biodiversity, human health, and sustainable development. Artificial Intelligence (AI) has transformed environmental research and management by enabling advanced data analytics, real-time monitoring, predictive modeling, and intelligent decision-support systems. This review critically examines the applications of AI in addressing environmental and climate-related challenges, including climate forecasting, air and water quality monitoring, biodiversity conservation, precision agriculture, renewable energy optimization, carbon emission assessment, waste management, and disaster risk reduction. Furthermore, The review also identifies current research gaps and highlights future opportunities for developing transparent, energy-efficient, and explainable AI systems that support evidence-based environmental decisionmaking. It concludes that AI has become a transformative tool for accelerating progress toward climate change mitigation, environmental sustainability, and the achievement of the United Nations Sustainable Development Goals (SDGs). Strengthening interdisciplinary collaboration, responsible AI governance, and policy support will be essential to maximize the environmental benefits of AI while minimizing its ecological footprint. Keywords: Artificial Intelligence; Climate Change; Environmental Sustainability; Machine Learning; Deep Learning; Remote Sensing; Internet of Things; Renewable Energy; Biodiversity Conservation; Sustainable Development Goals.","摘要 气候变化和环境退化已成为二十一世纪最紧迫的全球性挑战之一，威胁着生态系统、生物多样性、人类健康和可持续发展。人工智能（AI）通过实现先进的数据分析、实时监测、预测建模和智能决策支持系统，改变了环境研究与管理的方式。本文综述批判性地考察了AI在应对环境和气候相关挑战中的应用，包括气候预测、空气和水质监测、生物多样性保护、精准农业、可再生能源优化、碳排放评估、废物管理和灾害风险降低。此外，本综述还指出了当前的研究空白，并强调了未来开发透明、节能且可解释的AI系统的机遇，以支持基于证据的环境决策。文章得出结论，AI已成为加速气候变化减缓、环境可持续发展以及实现联合国可持续发展目标（SDGs）的变革性工具。加强跨学科合作、负责任的AI治理和政策支持，对于最大化AI的环境效益并同时最小化其生态足迹至关重要。关键词：人工智能；气候变化；环境可持续性；机器学习；深度学习；遥感；物联网；可再生能源；生物多样性保护；可持续发展目标。","Zenodo (CERN European Organization for Nuclear Research)",70,{"impact":19,"substance":483,"depth":41,"authority":17,"freshness":484,"relevant":22,"comment":485},16,9,"综述性论文，覆盖AI在气候预测、精准农业、遥感监测等方向的应用，与农业信息化相关但偏宏观综述，增量有限。",[487],{"name":480,"url":477},[489,490,491,27,29],"智慧农业","农业人工智能","可持续发展",{"code":493,"slug":494,"name":495,"path":496,"parent_code":497},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[499],{"code":49,"slug":265,"name":266,"path":267,"parent_code":268},{"status":279,"locked":14,"version":35,"method":36,"evidence":501},{"candidates":502,"agricultural_evidence":42},[503,512,516,520,524,530,534],{"code":493,"score":19,"supported":42,"title":504,"abstract":506,"tags":511},[505],"artificial intelligence",[507,508,509,510,505],"深度学习","机器学习","machine learning","deep learning",[490],{"code":49,"score":41,"supported":42,"title":513,"abstract":514,"tags":515},[143],[27,143],[27],{"code":309,"score":146,"supported":42,"title":517,"abstract":518,"tags":519},[],[312,313],[489],{"code":56,"score":146,"supported":42,"title":521,"abstract":522,"tags":523},[],[59,60],[29],{"code":63,"score":116,"supported":42,"title":525,"abstract":526,"tags":529},[],[527,528],"碳排放","carbon emission",[],{"code":151,"score":116,"supported":42,"title":531,"abstract":532,"tags":533},[],[154,155],[],{"code":535,"score":116,"supported":42,"title":536,"abstract":537,"tags":540},"I5",[],[538,539],"物联网","internet of things",[],[542,543],"AI 气候变化","人工智能 环境可持续","AI气候变化-5086","10.5281\u002Fzenodo.23399627",{"doi":545,"openalex_id":547,"authors":548,"venue":480,"cited_by_count":106,"oa_url":477,"card":551,"direction":245,"ingested_from":113},"W7222092855",[549],{"name":550,"orcid":9},"Deepmala Suryavanshi",{"tldr":552,"method":553,"finding":554,"direction":555,"opportunity":556},"综述AI在气候变化缓解与环境可持续领域的应用进展、挑战与未来方向。","文献综述，涵盖机器学习、深度学习、遥感、物联网等技术应用。","AI已成为推动气候减缓与可持续发展目标实现的变革性工具。","农业绿色发展与碳","可聚焦可解释、低能耗AI在农业碳减排与精准环境决策中的落地研究。","2026-10-16T23:30:15.059867Z"]