[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4682":3,"related-4682":74},{"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":18,"tags":20,"primary_topic":9,"secondary_topics":25,"classification":26,"search_phrases":48,"slug":51,"view_count":15,"doi":52,"paper":53,"created_at":73},4682,"Disentangling distance decay from vegetation-ground effects on traffic noise attenuation in highway-adjacent urban parks","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-72076-y","Quantifying how vegetation and ground surfaces independently contribute to traffic noise attenuation, over and above geometric spreading, is a critical gap in urban green space planning. This study explicitly separates baseline geometric spreading from excess attenuation (additional noise reduction beyond distance decay) to quantify how vegetation and ground surfaces uniquely affect sound propagation. We measured equivalent continuous sound levels along transects extending 60 m from the highway edge in six road-aligned parks. A mixed-effects model showed that noise decreased by 8.48 dB per natural log unit increase in distance (β = − 8.48, p \u003C 0.001; marginal R 2 = 0.61, conditional R 2 = 0.73). Residual excess attenuation (observed minus distance-predicted noise) was then modeled against vegetation structure and ground surface characteristics (adjusted R 2 = 0.53). Vegetation height (β = − 0.38, p \u003C 0.001), canopy density (β = − 0.041, p \u003C 0.001), NDVI (β = − 3.21, p \u003C 0.001), and shrub density (β = − 0.19, p \u003C 0.001) were associated with greater noise reduction, whereas higher open soil proportion (β = 0.052, p \u003C 0.001) and ground hardness (β = 0.87, p = 0.003) were associated with higher residual noise levels (i.e., less attenuation). Scenario simulations indicated that increasing vegetation height by 8 m, canopy density by 60%, shrub density by 7 stems per 10 m 2 , and reducing open soil proportion by 40% could achieve up to 10.13 dBA of additional noise reduction beyond distance decay. These findings quantify the independent contributions of vegetation and ground surfaces to excess attenuation, supporting dense, vertically complex planting designs for noise mitigation in highway-adjacent urban green spaces.","量化植被与地表在几何扩散之外对交通噪声衰减的独立贡献，是城市绿地规划中的一个关键空白。本研究明确将基线几何扩散与超额衰减（超出距离衰减的额外降噪量）分离，以量化植被和地表对声音传播的独特影响。我们在六个沿路公园中，沿从公路边缘向外延伸60米的样线测量了等效连续声级。混合效应模型显示，距离每增加一个自然对数单位，噪声降低8.48分贝（β = − 8.48，p \u003C 0.001；边际R² = 0.61，条件R² = 0.73）。随后，将残差超额衰减（观测噪声减去距离预测噪声）对植被结构和地表特征进行建模（调整R² = 0.53）。植被高度（β = − 0.38，p \u003C 0.001）、冠层密度（β = − 0.041，p \u003C 0.001）、归一化植被指数（NDVI）（β = − 3.21，p \u003C 0.001）和灌木密度（β = − 0.19，p \u003C 0.001）与更大的降噪量相关，而较高的裸露土壤比例（β = 0.052，p \u003C 0.001）和地表硬度（β = 0.87，p = 0.003）与较高的残差噪声水平（即较少的衰减）相关。情景模拟表明，将植被高度增加8米、冠层密度增加60%、灌木密度增加每10平方米7株，并将裸露土壤比例减少40%，可在距离衰减之外额外实现高达10.13 dBA的降噪量。这些发现量化了植被和地表对超额衰减的独立贡献，支持在公路邻近的城市绿地中采用密集、垂直结构复杂的种植设计以缓解噪声。",null,"Scientific Reports","2026-10-09T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"研究城市公园植被与地面如何削减交通噪声，属城市声环境与绿地规划范畴，与三农、农业信息化、智慧农业无直接关联，不建议进入每日精选。",[19],{"name":10,"url":6},[21,22,23,24],"NDVI","城市绿地","交通噪声","植被降噪",[],{"status":27,"locked":14,"version":28,"method":29,"evidence":30},"needs_review","2026-10-22.2","rules",{"candidates":31,"agricultural_evidence":14,"reason":47},[32,41],{"code":33,"score":34,"supported":35,"title":36,"abstract":37,"tags":40},"H2",6,true,[],[38,39],"土壤","soil",[],{"code":42,"score":43,"supported":14,"title":44,"abstract":45,"tags":46},"I3",1,[],[],[21],"农业相关性需要复核",[49,50],"高速公路 城市公园 交通噪声 衰减","交通噪声 城市绿地 植被降噪 NDVI","高速公路城市公园交通噪声衰减-4682","10.1038\u002Fs41598-026-72076-y",{"doi":52,"openalex_id":54,"authors":55,"venue":10,"cited_by_count":15,"oa_url":64,"card":65,"direction":71,"ingested_from":72},"W7221106861",[56,59,62],{"name":57,"orcid":58},"Sarmad Mahdi Kadhum Alghanimi","https:\u002F\u002Forcid.org\u002F0000-0001-7518-4789",{"name":60,"orcid":61},"Atefeh Chamani","https:\u002F\u002Forcid.org\u002F0000-0002-9463-8579",{"name":63,"orcid":9},"Sawsan Samir Hadi","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-026-72076-y_reference.pdf",{"tldr":66,"method":67,"finding":68,"direction":69,"opportunity":70},"量化城市公园中植被与地面独立于距离衰减的交通噪声削减贡献。","六公园60米样带实测声级，混合效应模型分离距离与超额衰减。","植被高度、冠层密度、NDVI和灌木密度提升降噪，裸土与硬地面降低降噪。","农业绿色发展与碳","可探索不同植被配置与地面材质组合的降噪优化，并耦合碳汇与声景服务。","农业遥感与作物表型","openalex","2026-10-11T23:30:31.548961Z",{"total":34,"page":43,"page_size":34,"items":75},[76,153,220,281,329,377],{"id":77,"title":78,"url":79,"summary":80,"summary_zh":81,"content":9,"source_name":82,"source_url":79,"published_at":83,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":84,"score_detail":85,"sources":92,"tags":94,"primary_topic":99,"secondary_topics":105,"classification":106,"search_phrases":132,"slug":135,"view_count":15,"doi":136,"paper":137,"created_at":152},5575,"Wetland vegetation dynamics and its linkage with climatic, hydrological, and land-use\u002F land cover changes in the Foket floodplain of the Fetam River Watershed, Northwestern Ethiopia","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44274-026-01136-x","Timely monitoring of wetland changes is vital for effective conservation and management of the landscape. This study, therefore, examines vegetation dynamics and their climatic, hydrological, and land-use drivers in the Foket floodplain wetland, Upper Blue Nile basin, Ethiopia. The LULC analysis was employed based on 1985, 2002, and 2020 cloud-free Landsat images. The maximum likelihood classification algorithm was applied to classify the images into eight LULC classes. The spatial and temporal dynamics of the floodplain’s surface water were further analyzed using the Global Surface Water Explorer (1984–2020), focusing on water occurrence, seasonality, transitions, and changes in surface-water dynamics. The Normalized Difference Vegetation Index (NDVI) was used to assess the temporal dynamics of wetland vegetation, while annual rainfall, temperature, and evapotranspiration data were used to examine the climatic context of vegetation change. The results reveal that the area coverage of water body and wetland decreased by 63.2% and 29%, respectively, over the study period. In contrast, cultivated land, settlement, and eucalyptus plantation had expanded by 39.8%, 280.6%, and 380%, respectively, at the expense of wetland, woodland, and shrubland. Surface-water dynamics showed a substantial decline in seasonally inundated areas and changes in the spatial distribution and persistence of surface water. This indicates the reduction of the floodplain’s hydrological connectivity. The NDVI analysis also revealed a significant increasing of wetland vegetation over 1985–2020\u002F21. Vegetation growth was very fast during 1985–2000, slowed down between 2001 and 2012, and dropped slightly from 2013 to 2020\u002F21. Analysis of climatic variables showed no major change in annual rainfall or evapotranspiration, whereas temperature exhibited a significant upward trend. The overall findings revealed the association of the floodplain vegetation dynamics with land-use land cover, hydrological, and climatic changes. This indicates that land-use land cover, hydrological, and climatic changes have contributed to the degradation of the floodplain vegetation, highlighting the urgent need for integrated management interventions that regulate agricultural expansion, grazing, and water diversion while maintaining hydrological connectivity and wetland vegetation. Clinical trial number Not applicable (NA).","及时监测湿地变化对于景观的有效保护和管理至关重要。因此，本研究考察了埃塞俄比亚上青尼罗河流域福凯特洪泛平原湿地的植被动态及其气候、水文和土地利用驱动因素。基于1985年、2002年和2020年无云Landsat影像进行土地利用\u002F土地覆盖（LULC）分析，采用最大似然分类算法将影像分为八个LULC类别。进一步利用全球地表水探索器（1984—2020年）分析洪泛平原地表水的时空动态，重点关注水的出现频率、季节性、转换及地表水动态变化。采用归一化差异植被指数（NDVI）评估湿地植被的时间动态，同时利用年降水量、气温和蒸散发数据考察植被变化的气候背景。结果表明，研究期间水体和湿地的面积覆盖率分别下降了63.2%和29%。相比之下，耕地、居民点和桉树种植园分别扩张了39.8%、280.6%和380%，侵占了湿地、林地和灌丛。地表水动态显示季节性淹没区域大幅减少，地表水的空间分布和持续性发生变化，表明洪泛平原水文连通性降低。NDVI分析还揭示1985—2020\u002F21年间湿地植被显著增加。植被生长在1985—2000年间非常迅速，2001—2012年间放缓，2013—2020\u002F21年间略有下降。气候变量分析显示年降水量或蒸散发无重大变化，而气温呈显著上升趋势。总体研究结果揭示了洪泛平原植被动态与土地利用\u002F土地覆盖、水文和气候变化的关联。这表明土地利用\u002F土地覆盖、水文和气候变化共同导致了洪泛平原植被退化，凸显了迫切需要综合管理干预措施，以调控农业扩张、放牧和引水，同时维持水文连通性和湿地植被。临床试验编号：不适用（NA）。","Discover Environment","2026-10-20T00:00:00Z",65,{"impact":86,"substance":87,"depth":88,"authority":89,"freshness":90,"relevant":43,"comment":91},8,20,16,12,9,"基于Landsat与NDVI的湿地植被动态实证研究，数据扎实但属区域案例，国际参考价值有限，不宜进入每日精选。",[93],{"name":82,"url":79},[21,95,96,97,98],"埃塞俄比亚","土地利用变化","湿地遥感","水文连通性",{"code":100,"slug":101,"name":102,"path":103,"parent_code":104},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",[],{"status":107,"locked":14,"version":28,"method":29,"evidence":108},"classified",{"candidates":109,"agricultural_evidence":35},[110,116,123,128],{"code":100,"score":34,"supported":35,"title":111,"abstract":112,"tags":115},[],[113,114],"蒸散发","evapotranspiration",[],{"code":117,"score":118,"supported":35,"title":119,"abstract":120,"tags":122},"H7",3,[],[121],"气候变化",[],{"code":124,"score":43,"supported":14,"title":125,"abstract":126,"tags":127},"H6",[],[],[96],{"code":42,"score":43,"supported":14,"title":129,"abstract":130,"tags":131},[],[],[21],[133,134],"土地利用变化 埃塞俄比亚 水文连通性 湿地遥感","土地利用变化 埃塞俄比亚","土地利用变化埃塞俄比亚水文连通性湿地遥感-5575","10.1007\u002Fs44274-026-01136-x",{"doi":136,"openalex_id":138,"authors":139,"venue":82,"cited_by_count":15,"oa_url":146,"card":147,"direction":71,"ingested_from":72},"W7223064056",[140,143],{"name":141,"orcid":142},"Workiyie Worie Assefa","https:\u002F\u002Forcid.org\u002F0000-0002-4029-9022",{"name":144,"orcid":145},"Belachew Getnet Eneyew","https:\u002F\u002Forcid.org\u002F0000-0003-1196-9004","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs44274-026-01136-x.pdf",{"tldr":148,"method":149,"finding":150,"direction":71,"opportunity":151},"分析埃塞俄比亚Foket洪泛湿地植被动态及其气候、水文与土地利用驱动因素。","用Landsat影像做最大似然分类，结合全球地表水数据与NDVI及气候数据分析。","水体与湿地面积大幅减少，耕地、居民点和桉树种植扩张，温度显著上升。","可结合多源遥感与水文连通性指标，量化湿地退化对农业灌溉与乡村生态服务的影响。","2026-10-22T11:20:42.476484Z",{"id":154,"title":155,"url":156,"summary":157,"summary_zh":158,"content":9,"source_name":159,"source_url":156,"published_at":160,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":161,"score_detail":162,"sources":166,"tags":168,"primary_topic":9,"secondary_topics":173,"classification":174,"search_phrases":198,"slug":201,"view_count":15,"doi":202,"paper":203,"created_at":219},5481,"Comparison of Satellite-Based Drought Monitoring Indicators (NDVI, NDMI, and LST): The Case of the Northern Aegean Drainage Basin","https:\u002F\u002Fdoi.org\u002F10.30910\u002Fturkjans.2010067","Thanks to advancements in technology, satellite remote sensing provides a valuable means of monitoring the spatial and temporal responses of vegetation, surface moisture conditions, and land surface temperature to drought. Its capacity to monitor large areas with high temporal continuity significantly eliminates the spatial limitations of ground observations. This allows for the simultaneous and comparable analysis of key variables such as vegetation dynamics, soil moisture, and land surface temperature. Indicators such as the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), and Land Surface Temperature (LST) provide complementary information on vegetation condition, surface moisture, and thermal stress, thereby supporting drought monitoring. This integrated monitoring framework supports the sustainable management of water resources while strengthening the scientific basis of decision-making processes, significantly contributing to disaster risk reduction. This study comparatively evaluates NDVI, NDMI, and LST values derived from Landsat 8 data obtained in March, April, and May between 2019 and 2022, and examines the relationships between these variables across the Northern Aegean Drainage Basin (NADB). The results show increasingly strong negative relationships between LST and the spectral indices from March to May, with the strongest correlations observed in May for NDMI–LST (r = −0.78) and NDVI–LST (r = −0.74). The NDMI-LST relationship can be said to be slightly better than the NDVI-LST relationship. The correlation coefficient between NDMI and NDVI was calculated to be lowest in March at r=0.54 and highest in May at r=0.90. It was determined that areas with high LST values had lower NDVI and NDMI values. Drought monitoring using remote sensing methods is important in terms of time and accuracy, but it is not sufficient on its own. In addition to problems arising from satellite imagery, land surfaces are affected by short-term climatic factors. Therefore, the indices obtained from satellite images must be evaluated together with meteorological and terrestrial data. However, it is thought that satellite-based drought monitoring will produce more reliable results under current technological and methodological conditions.","得益于技术进步，卫星遥感为监测植被、地表水分状况和地表温度对干旱的时空响应提供了重要手段。其大范围、高时间连续性的监测能力显著消除了地面观测的空间局限性，使得植被动态、土壤水分和地表温度等关键变量能够被同步、可比地分析。归一化差异植被指数（NDVI）、归一化差异水分指数（NDMI）和地表温度（LST）等指标提供了关于植被状况、地表水分和热胁迫的互补信息，从而支持干旱监测。这一综合监测框架既支持水资源的可持续管理，又增强了决策过程的科学基础，对减少灾害风险具有重要贡献。本研究对2019年至2022年3月、4月和5月获取的Landsat 8数据所衍生的NDVI、NDMI和LST值进行了比较评估，并考察了北爱琴海流域（NADB）内这些变量之间的关系。结果表明，从3月到5月，LST与光谱指数之间的负相关关系日益增强，5月观测到最强相关性，NDMI–LST（r = −0.78）和NDVI–LST（r = −0.74）。可以认为NDMI-LST关系略优于NDVI-LST关系。NDMI与NDVI之间的相关系数在3月最低（r=0.54），5月最高（r=0.90）。研究确定，LST值较高的区域其NDVI和NDMI值较低。利用遥感方法进行干旱监测在时间和精度方面具有重要意义，但仅靠其自身并不充分。除卫星影像带来的问题外，地表还受到短期气候因素的影响。因此，从卫星影像获得的指数必须与气象和地面数据结合评估。然而，可以认为在当前技术和方法条件下，基于卫星的干旱监测将产生更可靠的结果。","Türk Tarım ve Doğa Bilimleri Dergisi","2026-10-19T00:00:00Z",61,{"impact":86,"substance":163,"depth":164,"authority":89,"freshness":86,"relevant":43,"comment":165},18,15,"方法对比扎实、结论明确，但属区域案例研究，公共影响有限，适合作为遥感干旱监测主题的补充素材而非头条精选。",[167],{"name":159,"url":156},[21,169,170,171,172],"遥感监测","干旱监测","NDMI","LST",[],{"status":27,"locked":14,"version":28,"method":29,"evidence":175},{"candidates":176,"agricultural_evidence":14,"reason":47},[177,183,189,193],{"code":117,"score":164,"supported":35,"title":178,"abstract":180,"tags":182},[179],"drought",[181,179],"干旱",[170],{"code":42,"score":86,"supported":35,"title":184,"abstract":185,"tags":188},[],[186,187],"遥感","remote sensing",[21,169],{"code":33,"score":34,"supported":35,"title":190,"abstract":191,"tags":192},[],[38,39],[],{"code":100,"score":118,"supported":35,"title":194,"abstract":195,"tags":197},[],[196],"水资源",[],[199,200],"北爱琴海流域 干旱监测","干旱监测 遥感监测 NDMI NDVI","北爱琴海流域干旱监测-5481","10.30910\u002Fturkjans.2010067",{"doi":202,"openalex_id":204,"authors":205,"venue":159,"cited_by_count":15,"oa_url":212,"card":213,"direction":218,"ingested_from":72},"W7222954725",[206,209],{"name":207,"orcid":208},"Arman Monshizadeh Karimi","https:\u002F\u002Forcid.org\u002F0000-0002-2945-5346",{"name":210,"orcid":211},"İ̇smail Taş","https:\u002F\u002Forcid.org\u002F0000-0003-0872-2529","https:\u002F\u002Fdergipark.org.tr\u002Fen\u002Fdownload\u002Farticle-file\u002F6296754",{"tldr":214,"method":215,"finding":216,"direction":71,"opportunity":217},"比较Landsat 8的NDVI、NDMI与LST三种遥感干旱指标在北爱琴海流域的相关性。","用2019-2022年3-5月Landsat 8数据计算NDVI、NDMI、LS","LST与NDMI、NDVI负相关随春季增强，5月最强（r=-0.78、-0.74），NDMI略优。","可融合气象与地面数据构建多源干旱指数，并验证NDMI-LST关系在其他气候区的普适性。","智慧农业 \u002F 农业物联网","2026-10-21T23:30:10.758669Z",{"id":221,"title":222,"url":223,"summary":224,"summary_zh":225,"content":9,"source_name":226,"source_url":223,"published_at":227,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":228,"score_detail":229,"sources":233,"tags":235,"primary_topic":9,"secondary_topics":238,"classification":239,"search_phrases":250,"slug":253,"view_count":43,"doi":254,"paper":255,"created_at":280},5246,"Spatial divergence of climate–vegetation relationships in Florida: A 43-year multi-method analysis (1982–2024)","https:\u002F\u002Fdoi.org\u002F10.1088\u002F2515-7620\u002Faeb5af","Abstract Attributing long-term vegetation change to climate is difficult in subtropical ecosystems, where temperature and precipitation act simultaneously, are confounded by abrupt disturbances, and where statewide averages can conceal offsetting associations. Here we apply a multi-method convergence-of-evidence framework to a sensor-harmonized 43-year record (1982–2024) of NOAA CDR NDVI, temperature, and precipitation across Florida, which spans cool temperate forests to warm subtropical wetlands. Modified Mann–Kendall tests with false-discovery-rate correction detected monotonic trends; pixel-level correlation, spatial-error regression, and lagged cross-correlation evaluated association strength, direction, and timing; Empirical Orthogonal Function decomposition of deseasonalized anomalies separated persistent climatic signals from episodic disturbance, with the leading mode (58.4% of variance) tracking latitudinal warming and a lower-order mode (PC3) tracking hurricane impacts. Florida warmed by +0.033 °C yr⁻¹, significant in 99.6% of land pixels, while precipitation showed no field-significant trend. The temperature–greenness association was positive across essentially the entire state, marginally stronger in the south; localized negative responses were confined to specific southern wetland and urban-fringe pixels rather than forming a systematic north–south reversal. The state-mean precipitation–NDVI correlation was negative at zero lag and reversed from r = −0.263 to r = +0.102 when incoming shortwave radiation was partialed out, consistent with cloud-associated light suppression rather than water limitation—a phenomenon we term the Water Paradox. SPI\u002FSPEI–NDVI correlations were near zero, and Everglades water levels were largely decoupled from wetland greenness (r = 0.08, n.s.), indicating that inundation acts as a localized threshold modifier rather than a dominant suppressor. Climate–vegetation models for comparable high-rainfall subtropical systems may therefore need to account for spatially divergent temperature sensitivities and treat precipitation as an energy constraint rather than a uniform benefit.","摘要 在亚热带生态系统中，将长期植被变化归因于气候十分困难，因为温度和降水同时起作用，又受到突发干扰的混杂影响，而且全州尺度的平均值可能掩盖相互抵消的关联。本文采用多方法证据汇聚框架，对佛罗里达州1982—2024年共43年经传感器协调的NOAA CDR NDVI、温度和降水记录进行分析，该区域涵盖从冷温带森林到暖亚热带湿地。采用经错误发现率校正的改进Mann–Kendall检验检测单调趋势；通过像元级相关、空间误差回归和滞后互相关评估关联强度、方向和时间；对去季节化异常进行经验正交函数分解，以区分持续性气候信号与偶发干扰，其中主导模态（占总方差58.4%）追踪纬度变暖，低阶模态（PC3）追踪飓风影响。佛罗里达州以+0.033 °C yr⁻¹的速率变暖，在99.6%的陆地像元上显著，而降水未显示出区域显著趋势。温度—绿度关联在全州几乎均为正，南部略强；局地负响应仅限于特定的南部湿地和城市边缘像元，而非形成系统的南北反转。州平均降水—NDVI相关在零滞后时为负，当偏除入射短波辐射后由r = −0.263反转为r = +0.102，这与云相关的光抑制而非水分限制相一致——我们将这一现象称为“水悖论”。SPI\u002FSPEI—NDVI相关接近零，大沼泽地水位与湿地绿度基本解耦（r = 0.08，不显著），表明淹水作为局地阈值调节因子而非主导抑制因子起作用。因此，针对可比的高降雨亚热带系统的气候—植被模型可能需要考虑空间分异的温度敏感性，并将降水视为能量约束而非均一益处。","Environmental Research Communications","2026-10-16T00:00:00Z",70,{"impact":86,"substance":230,"depth":163,"authority":231,"freshness":90,"relevant":43,"comment":232},22,13,"基于43年NDVI遥感记录的多方法气候-植被关系研究，方法扎实、结论新颖，但属区域基础研究，对国内三农信息化仅有方法借鉴价值。",[234],{"name":226,"url":223},[121,186,21,236,237],"植被监测","佛罗里达",[],{"status":27,"locked":14,"version":28,"method":29,"evidence":240},{"candidates":241,"agricultural_evidence":14,"reason":47},[242,246],{"code":42,"score":118,"supported":14,"title":243,"abstract":244,"tags":245},[],[],[21,236,186],{"code":117,"score":43,"supported":14,"title":247,"abstract":248,"tags":249},[],[],[121],[251,252],"Florida NDVI 气候变化","佛罗里达 植被 遥感","FloridaNDVI气候变化-5246","10.1088\u002F2515-7620\u002Faeb5af",{"doi":254,"openalex_id":256,"authors":257,"venue":226,"cited_by_count":15,"oa_url":274,"card":275,"direction":71,"ingested_from":72},"W7222444517",[258,261,264,267,270,272],{"name":259,"orcid":260},"A. Mandal","https:\u002F\u002Forcid.org\u002F0009-0004-0192-7497",{"name":262,"orcid":263},"Aman Kumar Thapa","https:\u002F\u002Forcid.org\u002F0009-0003-8956-6632",{"name":265,"orcid":266},"Madan Thapa Chhetri","https:\u002F\u002Forcid.org\u002F0009-0002-3567-7591",{"name":268,"orcid":269},"Hongbo Su","https:\u002F\u002Forcid.org\u002F0000-0002-2147-3646",{"name":271,"orcid":9},"Yan Yong",{"name":273,"orcid":9},"Fred Bloetscher","https:\u002F\u002Fiopscience.iop.org\u002Farticle\u002F10.1088\u002F2515-7620\u002Faeb5af\u002Fpdf",{"tldr":276,"method":277,"finding":278,"direction":71,"opportunity":279},"用多方法分析佛罗里达43年气候与植被关系，揭示空间分异。","NOAA CDR NDVI与气候数据，结合趋势检验、回归、EOF分解。","全州变暖显著，温度与绿度正相关；降水因云量抑制光照呈负相关。","高降雨亚热带区需将降水视为能量约束，并关注温度敏感性的空间分异。","2026-10-18T23:30:31.356484Z",{"id":282,"title":283,"url":284,"summary":285,"summary_zh":9,"content":9,"source_name":286,"source_url":284,"published_at":227,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":287,"score_detail":288,"sources":291,"tags":293,"primary_topic":9,"secondary_topics":297,"classification":298,"search_phrases":310,"slug":313,"view_count":15,"doi":314,"paper":315,"created_at":328},5241,"Assessing Nutritional Status in Super-High-Density Olive Orchards: Integrating Diagnostic Models and NDVI-Based Remote Sensing","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-11156833\u002Fv1","Assessing Nutritional Status in Super-High-Density Olive Orchards: Integrating Diagnostic Models and NDVI-Based Remote Sensing。Research Square","Research Square",72,{"impact":88,"substance":163,"depth":289,"authority":89,"freshness":90,"relevant":43,"comment":290},17,"该研究将诊断模型与NDVI遥感结合用于超密植油橄榄园营养评估，方法有创新、对智慧果园管理有参考价值，但属预印本且应用面偏窄，可入精选但非头条。",[292],{"name":286,"url":284},[294,186,21,295,296],"智慧农业","果园管理","油橄榄",[],{"status":27,"locked":14,"version":28,"method":29,"evidence":299},{"candidates":300,"agricultural_evidence":14,"reason":47},[301,305],{"code":42,"score":231,"supported":35,"title":302,"abstract":303,"tags":304},[187],[187],[21,186],{"code":306,"score":43,"supported":14,"title":307,"abstract":308,"tags":309},"I1",[],[],[294],[311,312],"超密植 油橄榄 营养诊断","NDVI 遥感 果园","超密植油橄榄营养诊断-5241","10.21203\u002Frs.3.rs-11156833\u002Fv1",{"doi":314,"openalex_id":316,"authors":317,"venue":286,"cited_by_count":15,"oa_url":327,"card":9,"direction":218,"ingested_from":72},"W7222710807",[318,321,324],{"name":319,"orcid":320},"Mahrokh Sharifmand","https:\u002F\u002Forcid.org\u002F0009-0006-8010-5348",{"name":322,"orcid":323},"Mehdi Taheri","https:\u002F\u002Forcid.org\u002F0000-0002-9228-763X",{"name":325,"orcid":326},"Ebrahim Sepehr","https:\u002F\u002Forcid.org\u002F0000-0001-5843-0669","https:\u002F\u002Fwww.researchsquare.com\u002Farticle\u002Frs-11156833\u002Flatest.pdf","2026-10-18T23:30:11.167282Z",{"id":330,"title":331,"url":332,"summary":333,"summary_zh":334,"content":9,"source_name":335,"source_url":332,"published_at":336,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":337,"score_detail":338,"sources":340,"tags":342,"primary_topic":9,"secondary_topics":346,"classification":347,"search_phrases":360,"slug":363,"view_count":15,"doi":364,"paper":365,"created_at":376},5182,"Land Use Land Cover (LULC) Change Detection in Delhi NCT Using Multi-Sensor Satellite Data and Google Earth Engine","https:\u002F\u002Fdoi.org\u002F10.21275\u002Fsr26903183702","Land Use Land Cover (LULC) change detection is essential for understanding the dynamics of human modified landscapes and for supporting effective land management and urban planning. This study analyses LULC change across the Delhi National Capital Territory over a fifteen-year period, from 2010 to 2025, to assess urban sprawl and its environmental impact in one of India's fastest growing metropolitan regions. Multi temporal Landsat imagery was used as the primary data source, processed on Google Earth Engine, the cloud-based platform that enabled efficient handling and visualisation of large geospatial datasets. Five classes, built up area, agricultural land, vegetation, water, and barren land, were mapped and monitored, and classification accuracy was assessed for both dates. The Normalised Difference Vegetation Index was additionally employed to track vegetation vigour and ecological change. Results reveal a marked expansion of built-up areas alongside a substantial decline in agricultural and vegetated land, driven by peri urban growth along the northwestern and southwestern fringe. NDVI analysis shows rising greenness across the outer belt, reflecting more intensive cultivation on land that remains under crops, a pattern that complements rather than contradicts the measured loss of vegetated area. Combining classification based and an index-based approach provides a robust, scalable framework for LULC monitoring. By revealing where and how urban growth is reshaping the landscape, the study offers a transferable basis for environmental assessment, resource management, and sustainable urban planning in rapidly urbanising regions worldwide.","土地利用\u002F土地覆盖（LULC）变化检测对于理解人类改造景观的动态以及支撑有效的土地管理和城市规划至关重要。本研究分析了德里国家首都辖区在2010年至2025年十五年间的土地利用\u002F土地覆盖变化，以评估印度增长最快的大都市区之一的城市蔓延及其环境影响。研究以多时相Landsat影像作为主要数据源，在Google Earth Engine这一基于云的平台上进行处理，该平台能够高效处理和可视化大型地理空间数据集。研究对建成区、农业用地、植被、水体与裸地五个类别进行了制图和监测，并对两个时相的分类精度进行了评估。此外，研究采用归一化植被指数（NDVI）追踪植被长势与生态变化。结果表明，建成区显著扩张，农业用地和植被用地大幅减少，这一变化主要由西北部和西南部边缘的近郊增长所驱动。NDVI分析显示外围地带的绿度上升，反映出仍处于耕作状态的土地上集约化种植程度提高，这一格局与所测得的植被面积损失相辅相成而非相互矛盾。将基于分类的方法与基于指数的方法相结合，为土地利用\u002F土地覆盖监测提供了一个稳健且可扩展的框架。通过揭示城市增长在何处以及如何重塑景观，本研究为全球快速城市化地区的环境评估、资源管理和可持续城市规划提供了可迁移的基础。","International Journal of Science and Research (IJSR)","2026-10-15T00:00:00Z",62,{"impact":89,"substance":163,"depth":164,"authority":86,"freshness":90,"relevant":43,"comment":339},"方法可迁移的遥感LULC变化检测研究，对快速城市化地区土地管理有参考价值，但属区域案例、非三农核心议题。",[341],{"name":335,"url":332},[21,169,343,344,345],"土地利用","Google Earth Engine","城市化",[],{"status":348,"locked":14,"version":28,"method":29,"evidence":349},"unclassified",{"candidates":350,"agricultural_evidence":35,"reason":359},[351,355],{"code":42,"score":118,"supported":14,"title":352,"abstract":353,"tags":354},[],[],[344,21,169],{"code":124,"score":43,"supported":14,"title":356,"abstract":357,"tags":358},[],[],[343],"缺少足够的主题证据",[361,362],"德里 土地利用 遥感","Google Earth Engine 城市扩张","德里土地利用遥感-5182","10.21275\u002Fsr26903183702",{"doi":364,"openalex_id":366,"authors":367,"venue":335,"cited_by_count":15,"oa_url":370,"card":371,"direction":71,"ingested_from":72},"W7222341300",[368],{"name":369,"orcid":9},"Neil Rohatgi","https:\u002F\u002Fwww.ijsr.net\u002Farchive\u002Fv15i10\u002FSR26903183702.pdf",{"tldr":372,"method":373,"finding":374,"direction":71,"opportunity":375},"基于多时相Landsat与GEE分析德里国家首都辖区2010-2025年土地利用变化。","多时相Landsat影像、Google Earth Engine平台、五类分类与","建设用地显著扩张，农业与植被用地大幅减少，城郊西北和西南边缘增长驱动。","可结合分类与指数方法构建可迁移框架，拓展至城乡交错带耕地保护与可持续规划研究。","2026-10-17T23:30:31.767409Z",{"id":378,"title":379,"url":380,"summary":381,"summary_zh":382,"content":9,"source_name":10,"source_url":380,"published_at":336,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":383,"score_detail":384,"sources":387,"tags":389,"primary_topic":9,"secondary_topics":392,"classification":393,"search_phrases":409,"slug":412,"view_count":43,"doi":413,"paper":414,"created_at":440},5177,"Long-term associations between land-surface indicators and dust-storm occurrence along the margins of the Taklimakan Desert","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-75251-3","Land-surface change and atmospheric variability jointly shape dust activity in arid regions. We examined land-cover transitions, station dust-storm records, a Sentinel-1 backscatter index, meteorological variables from the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) and dust diagnostics from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) along the margins of the Taklimakan Desert. Within the mapped domain, grassland increased from 9.45% in 1990 to 10.59% in 2023, while barren land decreased from 86.45% to 82.30%. Annual dust-storm-day trends were negative at 21 of 30 stations over available 1990–2024 records, and Sentinel-1 index trends were positive at 22 stations during 2015–2024. Mixed-effects path analysis of 3,804 station-month observations showed that the Sentinel-1 index was negatively associated with modelled dust emission (standardized coefficient = − 0.191; 95% confidence interval: −0.289 to − 0.043). The normalized difference vegetation index (NDVI) and friction velocity had the highest training-set feature importance in the random forest analysis.","地表变化与大气变率共同塑造了干旱地区的沙尘活动。我们沿塔克拉玛干沙漠边缘，研究了土地覆盖转变、台站沙尘暴记录、Sentinel-1后向散射指数、来自欧洲中期天气预报中心第五代再分析资料（ERA5）的气象变量，以及来自现代研究与应用回顾分析第2版（MERRA-2）的沙尘诊断量。在制图范围内，草地面积从1990年的9.45%增加到2023年的10.59%，而裸地面积从86.45%减少到82.30%。在1990—2024年现有记录中，30个台站中有21个台站的年沙尘暴日数呈下降趋势；2015—2024年间，22个台站的Sentinel-1指数呈上升趋势。对3804个台站—月观测值的混合效应路径分析表明，Sentinel-1指数与模拟沙尘排放呈负相关（标准化系数=−0.191；95%置信区间：−0.289至−0.043）。在随机森林分析中，归一化植被指数（NDVI）和摩擦速度在训练集中的特征重要性最高。",78,{"impact":88,"substance":230,"depth":163,"authority":385,"freshness":86,"relevant":43,"comment":386},14,"基于多源遥感与30站长期记录，量化地表指标与沙尘暴关联，方法扎实、数据规模可观，对干旱区生态监测有参考价值。",[388],{"name":10,"url":380},[21,390,169,343,391],"荒漠化","沙尘暴",[],{"status":27,"locked":14,"version":28,"method":29,"evidence":394},{"candidates":395,"agricultural_evidence":14,"reason":47},[396,400,405],{"code":117,"score":118,"supported":35,"title":397,"abstract":398,"tags":399},[],[181],[],{"code":124,"score":401,"supported":14,"title":402,"abstract":403,"tags":404},2,[],[],[343,390],{"code":42,"score":401,"supported":14,"title":406,"abstract":407,"tags":408},[],[],[21,169],[410,411],"塔克拉玛干沙漠 沙尘暴 遥感","Sentinel-1 土地覆盖 沙尘","塔克拉玛干沙漠沙尘暴遥感-5177","10.1038\u002Fs41598-026-75251-3",{"doi":413,"openalex_id":415,"authors":416,"venue":10,"cited_by_count":15,"oa_url":434,"card":435,"direction":71,"ingested_from":72},"W7222086957",[417,419,422,425,427,429,431],{"name":418,"orcid":9},"Yifei Wang",{"name":420,"orcid":421},"Wen Huo","https:\u002F\u002Forcid.org\u002F0000-0002-7861-2424",{"name":423,"orcid":424},"Mayibaier Maihamuti","https:\u002F\u002Forcid.org\u002F0009-0007-4084-5891",{"name":426,"orcid":9},"Fan Yang",{"name":428,"orcid":9},"Chenglong Zhou",{"name":430,"orcid":9},"Xinghua Yang",{"name":432,"orcid":433},"Ali Mamtimin","https:\u002F\u002Forcid.org\u002F0000-0001-7335-801X","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-026-75251-3_reference.pdf",{"tldr":436,"method":437,"finding":438,"direction":71,"opportunity":439},"分析塔克拉玛干沙漠边缘地表指标与沙尘暴发生的长期关联。","结合土地覆盖、站点沙尘记录、Sentinel-1后向散射、ERA5与MERRA-","站点沙尘日数多呈下降趋势，Sentinel-1指数与模拟沙尘排放显著负相关。","可引入多源遥感与机器学习量化地表变化对沙尘的因果贡献，并拓展至绿洲农业防护。","2026-10-17T23:30:30.235613Z"]