[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1833":3,"related-1833":57},{"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":22,"classification":23,"search_phrases":38,"slug":39,"view_count":15,"doi":40,"paper":41,"created_at":56},1833,"Exploring the Role of Urban Green Spaces in Building Climate-Resilient Cities: The Case of Nairobi City","https:\u002F\u002Fdoi.org\u002F10.21275\u002Fsr23123133454","Urbanization alters urban microclimates by replacing vegetated and permeable surfaces with impervious surfaces that absorb and retain solar radiation, contributing to urban heat island (UHI) effects. This study examined the role of urban green spaces in mitigating urban heat and supporting climate resilience in Nairobi City. A geospatial approach using Landsat imagery from 1986, 2002, 2010, and 2020 was applied to assess land use and land cover (LULC), land surface temperature (LST), and vegetation abundance using the Normalized Difference Vegetation Index (NDVI). The results showed substantial expansion of built-up areas, from 46.7 km2 in 1986 to 203.6 km2 in 2020, while mean LST increased from 24.52°C to 27.70°C. Forest and other vegetated areas generally recorded lower LST values than built-up and bare or transitional areas. Regression analysis further indicated a predominantly inverse relationship between LST and NDVI, demonstrating the cooling influence of vegetation. These findings highlight the importance of protecting, restoring, and appropriately configuring urban green spaces as part of heat-mitigation and climate-resilient urban planning in Nairobi.","城市化通过以吸收并保留太阳辐射的不透水表面取代植被覆盖和可渗透表面，改变了城市微气候，从而加剧了城市热岛效应。本研究探讨了城市绿地在缓解城市热力及增强内罗毕市气候韧性方面的作用。采用地理空间方法，利用1986年、2002年、2010年和2020年的Landsat影像，评估了土地利用与土地覆盖、地表温度以及基于归一化差异植被指数的植被丰度。结果显示，建成区面积大幅扩张，从1986年的46.7平方公里增至2020年的203.6平方公里，而平均地表温度从24.52°C升至27.70°C。森林及其他植被区域的地表温度普遍低于建成区及裸地或过渡区域。回归分析进一步表明，地表温度与归一化差异植被指数之间主要呈反比关系，证实了植被的降温作用。这些发现凸显了在内罗毕的热缓解及气候韧性城市规划中，保护、恢复并合理配置城市绿地的重要性。",null,"International Journal of Science and Research (IJSR)","2026-09-05T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"主题为城市热岛与绿地，非三农或农业信息化领域，不进入精选。",[19],{"name":10,"url":6},[21],"城市绿地",[],{"status":24,"locked":14,"version":25,"method":26,"evidence":27},"needs_review","2026-10-22.2","rules",{"candidates":28,"agricultural_evidence":14,"reason":37},[29],{"code":30,"score":31,"supported":32,"title":33,"abstract":34,"tags":36},"H7",3,true,[],[35],"climate resilience",[],"农业相关性需要复核",[],"ExploringtheRoleofUrbanGreenSpacesinBuil-1833","10.21275\u002Fsr23123133454",{"doi":40,"openalex_id":42,"authors":43,"venue":10,"cited_by_count":15,"oa_url":48,"card":49,"direction":53,"ingested_from":55},"W7208838460",[44,46],{"name":45,"orcid":9},"Esther Barbara Njiru",{"name":47,"orcid":9},"Antony Abilla","https:\u002F\u002Fwww.ijsr.net\u002Farchive\u002Fv15i9\u002FSR23123133454.pdf",{"tldr":50,"method":51,"finding":52,"direction":53,"opportunity":54},"研究内罗毕城市绿地缓解热岛效应和增强气候韧性的作用。","利用Landsat影像分析LULC、LST和NDVI，并进行回归分析。","建成区扩张导致地表温度升高，植被与温度呈负相关，绿地有降温作用。","农业遥感与作物表型","可延伸研究城市绿地空间配置优化对降温效果的影响，结合高分辨率遥感与实地监测。","openalex","2026-09-07T23:30:24.548274Z",{"total":58,"page":59,"page_size":58,"items":60},2,1,[61,118],{"id":62,"title":63,"url":64,"summary":65,"summary_zh":66,"content":9,"source_name":67,"source_url":64,"published_at":68,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":69,"sources":71,"tags":73,"primary_topic":9,"secondary_topics":77,"classification":78,"search_phrases":94,"slug":97,"view_count":15,"doi":98,"paper":99,"created_at":117},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。","Scientific Reports","2026-10-09T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":70},"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。",[72],{"name":67,"url":64},[74,21,75,76],"NDVI","交通噪声","植被降噪",[],{"status":24,"locked":14,"version":25,"method":26,"evidence":79},{"candidates":80,"agricultural_evidence":14,"reason":37},[81,89],{"code":82,"score":83,"supported":32,"title":84,"abstract":85,"tags":88},"H2",6,[],[86,87],"土壤","soil",[],{"code":90,"score":59,"supported":14,"title":91,"abstract":92,"tags":93},"I3",[],[],[74],[95,96],"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":98,"openalex_id":100,"authors":101,"venue":67,"cited_by_count":15,"oa_url":110,"card":111,"direction":53,"ingested_from":55},"W7221106861",[102,105,108],{"name":103,"orcid":104},"Sarmad Mahdi Kadhum Alghanimi","https:\u002F\u002Forcid.org\u002F0000-0001-7518-4789",{"name":106,"orcid":107},"Atefeh Chamani","https:\u002F\u002Forcid.org\u002F0000-0002-9463-8579",{"name":109,"orcid":9},"Sawsan Samir Hadi","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-026-72076-y_reference.pdf",{"tldr":112,"method":113,"finding":114,"direction":115,"opportunity":116},"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。","2026-10-11T23:30:31.548961Z",{"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":132,"tags":134,"primary_topic":9,"secondary_topics":139,"classification":140,"search_phrases":164,"slug":167,"view_count":58,"doi":168,"paper":169,"created_at":187},1729,"CAFF-Net for coupled eco-health prediction of urban green space and water body with multi-source remote sensing","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asej.2026.104404","Aiming at three bottlenecks of multi-source remote sensing eco-health inversion: cross-modal feature redundancy, decoupled single-task modeling, and detail distortion of fragmented urban land covers, this paper proposes CAFF-Net for coupled eco-health prediction of urban green spaces and water bodies using Sentinel-1 SAR and Sentinel-2 optical data. A dual-branch Swin-Transformer separately extracts heterogeneous features, and serial CBAM realizes adaptive feature filtering to suppress redundant information. An improved multi-task UNet synchronously predicts green space, water body and coupled ecological health indices with joint loss to model aquatic-terrestrial ecological linkages. Experiments show CAFF-Net achieves an 𝑅 2 of 0.928, 3.3% higher than SOTA, with strong robustness under heavy cloud interference, supporting sponge city and watershed governance.","针对多源遥感生态健康反演中存在的三大瓶颈——跨模态特征冗余、单任务解耦建模以及城市破碎化地物细节失真问题，本文提出CAFF-Net，利用Sentinel-1 SAR与Sentinel-2光学数据实现城市绿地和水体耦合生态健康预测。双分支Swin-Transformer分别提取异质特征，串联CBAM实现自适应特征过滤以抑制冗余信息。改进的多任务UNet通过联合损失同步预测绿地、水体及耦合生态健康指数，以建模水陆生态关联。实验表明，CAFF-Net的R²达到0.928，较SOTA提升3.3%，且在强云干扰下具有较强鲁棒性，可为海绵城市和流域治理提供支撑。","Ain Shams Engineering Journal","2026-09-03T00:00:00Z",65,{"impact":128,"substance":129,"depth":130,"authority":128,"freshness":31,"relevant":59,"comment":131},12,20,18,"提出CAFF-Net模型，耦合预测城市绿地与水体生态健康，方法新颖，数据可靠，对智慧城市生态管理有参考价值。",[133],{"name":124,"url":121},[135,136,137,138,21],"智慧农业","农业人工智能","遥感","生态监测",[],{"status":24,"locked":14,"version":25,"method":26,"evidence":141},{"candidates":142,"agricultural_evidence":14,"reason":37},[143,149,154,159],{"code":90,"score":144,"supported":32,"title":145,"abstract":147,"tags":148},15,[146],"remote sensing",[137,146],[137],{"code":150,"score":59,"supported":14,"title":151,"abstract":152,"tags":153},"H6",[],[],[138],{"code":155,"score":59,"supported":14,"title":156,"abstract":157,"tags":158},"I1",[],[],[135],{"code":160,"score":59,"supported":14,"title":161,"abstract":162,"tags":163},"I2",[],[],[136],[165,166],"农业人工智能 城市绿地 智慧农业 生态监测","农业人工智能 城市绿地","农业人工智能城市绿地智慧农业生态监测-1729","10.1016\u002Fj.asej.2026.104404",{"doi":168,"openalex_id":170,"authors":171,"venue":124,"cited_by_count":15,"oa_url":180,"card":181,"direction":186,"ingested_from":55},"W7207862972",[172,175,177],{"name":173,"orcid":174},"Yifeng Shen","https:\u002F\u002Forcid.org\u002F0009-0009-3887-4938",{"name":176,"orcid":9},"Y. F. Ye",{"name":178,"orcid":179},"Shulai Wang","https:\u002F\u002Forcid.org\u002F0009-0007-7101-3449","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS2090447926004351\u002Fpdf",{"tldr":182,"method":183,"finding":184,"direction":53,"opportunity":185},"提出CAFF-Net，用多源遥感数据耦合预测城市绿地和水体生态健康。","双分支Swin-Transformer提取特征，CBAM过滤冗余，改进多任务UN","R²达0.928，比SOTA高3.3%，抗云干扰强，支持海绵城市治理。","可延伸至农业生态系统，耦合预测农田植被与水体健康，探索多任务联合损失在农业遥感中的应用。","智慧农业 \u002F 农业物联网","2026-09-05T23:30:13.221496Z"]