[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4229":3,"related-4229":90},{"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":23,"tags":25,"primary_topic":9,"secondary_topics":31,"classification":32,"search_phrases":55,"slug":58,"view_count":59,"doi":60,"paper":61,"created_at":89},4229,"Spatiotemporal characteristics of vegetation responses to compound drought and heatwave events in Central Asia","https:\u002F\u002Fdoi.org\u002F10.1080\u002F15481603.2026.2741443","With climate warming intensifying, compound drought and heatwave (CDHW) events have become more frequent and intense in arid Central Asia, severely affecting vegetation growth. However, systematic quantitative assessments of vegetation responses and their drivers under such compound extremes remain limited. Using meteorological and remote sensing data, we identified growing-season CDHW events across Central Asia from 1982 to 2023. Integrating the Kernel normalized difference vegetation index (KNDVI) and the long-term continuous SIF-informed photosynthesis proxy (LCSPP), we established a vegetation response indicator system including total loss (LOSStot), maximum decline (DECmax), and time to decline (TIMEdec) to characterize vegetation damage. We further applied the XGBoost model and SHAP analysis to quantify the environmental driving effects and interactions. The results indicate that CDHW events increased significantly during 1982–2023, with heatwave frequency rising at 0.38 days yr−1 and an abrupt shift around 1996. High-frequency CDHW events were primarily concentrated in north-central Kazakhstan and northern Xinjiang, China, while their frequency and duration generally increased with latitude, indicating a pronounced northward enhancement pattern. CDHW caused larger vegetation losses than individual drought or heatwave events. Event duration was the most important environmental variable of LOSStot, with the highest mean SHAP value (0.140), while precipitation anomalies during events showed a strong association with rapid vegetation decline, with a direct path coefficient of 0.333 for DECmax. This study clarifies vegetation loss characteristics and key contributing factors under compound extremes in Central Asia, providing a scientific basis for ecological risk assessment and climate adaptation in arid regions.","随着气候变暖加剧，中亚干旱区复合干旱与热浪（CDHW）事件日趋频繁和强烈，严重影响了植被生长。然而，针对此类复合极端事件下植被响应及其驱动因素的系统性定量评估仍较为有限。本研究利用气象和遥感数据，识别了1982—2023年中亚生长季CDHW事件。通过整合核归一化植被指数（KNDVI）和长期连续SIF光合代理指标（LCSPP），构建了包含总损失（LOSStot）、最大下降幅度（DECmax）和下降时间（TIMEdec）的植被响应指标体系，以表征植被受损程度。进一步应用XGBoost模型和SHAP分析，量化了环境驱动效应及其交互作用。结果表明，1982—2023年间CDHW事件显著增加，热浪频率以0.38天\u002F年的速率上升，并在1996年前后发生突变。高频CDHW事件主要集中在哈萨克斯坦中北部和中国新疆北部，其频率和持续时间总体随纬度增加而增大，呈现出明显的向北增强格局。CDHW造成的植被损失大于单一干旱或热浪事件。事件持续时间是LOSStot最重要的环境变量，其平均SHAP值最高（0.140），而事件期间的降水异常与植被快速下降密切相关，其对DECmax的直接路径系数为0.333。本研究阐明了中亚复合极端事件下植被损失特征及关键影响因素，为干旱区生态风险评估和气候适应提供了科学依据。",null,"GIScience & Remote Sensing","2026-10-04T00:00:00Z","论文",10,false,80,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,14,8,1,"基于1982—2023年遥感与气象数据量化中亚复合干旱热浪对植被的影响，方法新颖、结论可靠，对干旱区生态风险评估有参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"气候适应","遥感监测","中亚农业","干旱热浪","植被响应",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":36},"needs_review","2026-10-22.2","rules",{"candidates":37,"agricultural_evidence":14,"reason":54},[38,46],{"code":39,"score":17,"supported":40,"title":41,"abstract":43,"tags":45},"H7",true,[42],"drought",[26,44,42],"干旱",[26],{"code":47,"score":48,"supported":40,"title":49,"abstract":50,"tags":53},"I3",7,[],[51,52],"遥感","remote sensing",[27],"农业相关性需要复核",[56,57],"中亚 复合干旱热浪 植被","KNDVI 植被损失 遥感","中亚复合干旱热浪植被-4229",2,"10.1080\u002F15481603.2026.2741443",{"doi":60,"openalex_id":62,"authors":63,"venue":10,"cited_by_count":80,"oa_url":81,"card":82,"direction":86,"ingested_from":88},"W7219762973",[64,66,69,71,73,75,77],{"name":65,"orcid":9},"Manfeng Ding",{"name":67,"orcid":68},"Renping Zhang","https:\u002F\u002Forcid.org\u002F0009-0003-6271-2775",{"name":70,"orcid":9},"Jing Guo",{"name":72,"orcid":9},"Li Li",{"name":74,"orcid":9},"Feifei Niu",{"name":76,"orcid":9},"Yansong Li",{"name":78,"orcid":79},"Jinlong Gao","https:\u002F\u002Forcid.org\u002F0000-0003-1188-8271",0,"https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Fpdf\u002F10.1080\u002F15481603.2026.2741443?needAccess=true",{"tldr":83,"method":84,"finding":85,"direction":86,"opportunity":87},"量化中亚1982-2023年复合干旱热浪对植被的时空影响及驱动因素。","用KNDVI与SIF代理构建响应指标，结合XGBoost和SHAP分析。","复合事件致植被损失大于单一事件，事件时长最关键，降水异常驱动快速衰退。","农业遥感与作物表型","可拓展至不同干旱区作物类型，构建复合极端事件植被风险预警模型。","openalex","2026-10-05T23:30:24.935545Z",{"total":91,"page":21,"page_size":91,"items":92},6,[93,156,223,297,362,450],{"id":94,"title":95,"url":96,"summary":97,"summary_zh":98,"content":9,"source_name":99,"source_url":96,"published_at":100,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":101,"score_detail":102,"sources":105,"tags":107,"primary_topic":9,"secondary_topics":110,"classification":111,"search_phrases":130,"slug":133,"view_count":21,"doi":134,"paper":135,"created_at":155},3852,"Rainfall–Surface Temperature Coupling and Compound Dry-Hot Persistence Across Northwestern Bangladesh: A 25-Year Multi-Sensor Earth Observation Analysis","https:\u002F\u002Fdoi.org\u002F10.11648\u002Fj.ajrs.20261402.17","Understanding how rainfall variability regulates land-surface thermal conditions is essential for climate-sensitive regions where water availability, vegetation dynamics, and heat stress interact. However, the temporal persistence and spatial heterogeneity of rainfall–surface temperature relationships remain insufficiently characterized in northwestern Bangladesh. This study integrates 25 years (2001–2025) of multi-source Earth observation data, including Terra MODIS land-surface temperature (MOD11A2), MODIS vegetation index (MOD13A2), and CHIRPS precipitation, to quantify pre-monsoon hydrothermal coupling across 16 districts of the Rajshahi and Rangpur divisions. A total of 275 quality-controlled 8-day March–May composites were analyzed using Mann–Kendall trend tests, Sen's slope estimation, fixed-effects distributed lag models, and a locally standardized compound dry-hot persistence indicator. Mean daytime land-surface temperature ranged from 27.93°C in Kurigram to 31.38°C in Chapai Nawabganj. No district exhibited a significant daytime land-surface temperature trend after false-discovery-rate correction, whereas NDVI increased significantly across all districts. The distributed-lag model showed that 10 mm of concurrent rainfall was associated with a 0.164°C lower daytime land-surface temperature (95% CI: −0.224 to −0.103°C), while rainfall during the preceding 8–16 days was associated with a weaker effect (−0.093°C per 10 mm). The 16–24-day rainfall effect was not significant. Rainfall sensitivity varied considerably among districts, ranging from −0.538°C per 10 mm in Rajshahi to −0.123°C per 10 mm in Lalmonirhat. These findings demonstrate that satellite-derived hydrothermal responses are spatially heterogeneous and highlight the value of multi-sensor Earth observation frameworks for identifying location-specific climate adaptation priorities.","理解降雨变率如何调控地表热状况，对于水资源可利用性、植被动态与热胁迫相互作用的气候敏感区至关重要。然而，在孟加拉国西北部，降雨—地表温度关系的时间持续性与空间异质性仍缺乏充分刻画。本研究整合了25年（2001—2025年）的多源地球观测数据，包括Terra MODIS地表温度（MOD11A2）、MODIS植被指数（MOD13A2）和CHIRPS降水数据，以量化拉杰沙希和朗布尔专区16个地区的季风前水热耦合关系。研究分析了275幅经质量控制、时间分辨率为8天的3—5月合成影像，采用Mann–Kendall趋势检验、Sen's斜率估计、固定效应分布滞后模型以及局部标准化的复合干热持续性指标。白天平均地表温度范围为库里格拉姆的27.93°C至杰拉伊纳瓦布甘杰的31.38°C。经错误发现率校正后，没有任何地区表现出显著的白天地表温度趋势，而所有地区的NDVI均显著增加。分布滞后模型显示，同期10 mm降雨与白天地表温度降低0.164°C相关（95% CI：−0.224至−0.103°C），而前8—16天的降雨效应较弱（每10 mm降低0.093°C）。16—24天的降雨效应不显著。降雨敏感性在各地区间差异显著，从拉杰沙希的每10 mm降低0.538°C到拉尔莫尼哈德的每10 mm降低0.123°C不等。这些发现表明，卫星反演的水热响应具有空间异质性，并凸显了多传感器地球观测框架在识别特定地点气候适应优先事项方面的价值。","American Journal of Remote Sensing","2026-09-28T00:00:00Z",69,{"impact":20,"substance":18,"depth":17,"authority":103,"freshness":20,"relevant":21,"comment":104},13,"基于25年多源遥感数据揭示孟加拉国西北部降水—地表温度耦合与干热复合持续性，方法扎实、结论具体，但属区域气候研究，对国内三农领域参考价值有限。",[106],{"name":99,"url":96},[108,26,27,29,109],"农业气象","作物植被",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":112},{"candidates":113,"agricultural_evidence":14,"reason":54},[114,119,126],{"code":39,"score":115,"supported":40,"title":116,"abstract":117,"tags":118},5,[],[26],[108,26],{"code":120,"score":121,"supported":40,"title":122,"abstract":123,"tags":125},"H3",3,[],[124],"水资源",[],{"code":47,"score":21,"supported":14,"title":127,"abstract":128,"tags":129},[],[],[27],[131,132],"孟加拉国 西北部 遥感 干旱","MODIS CHIRPS 地表温度 降水","孟加拉国西北部遥感干旱-3852","10.11648\u002Fj.ajrs.20261402.17",{"doi":134,"openalex_id":136,"authors":137,"venue":99,"cited_by_count":80,"oa_url":149,"card":150,"direction":86,"ingested_from":88},"W7214647936",[138,140,143,146],{"name":139,"orcid":9},"Nafia Muntakim",{"name":141,"orcid":142},"Md. Imran Hossain","https:\u002F\u002Forcid.org\u002F0009-0004-6856-9276",{"name":144,"orcid":145},"Zihad Ahmed","https:\u002F\u002Forcid.org\u002F0000-0002-5657-6258",{"name":147,"orcid":148},"Md. Mizanoor Rahman","https:\u002F\u002Forcid.org\u002F0000-0002-2049-9246","http:\u002F\u002Farticle.sciencepg.com\u002Fpdf\u002Fj.ajrs.20261402.17",{"tldr":151,"method":152,"finding":153,"direction":86,"opportunity":154},"基于25年多源遥感数据，量化孟加拉国西北部季风前降雨与地表温度的耦合及干热复合持续性。","MODIS地表温度与植被指数、CHIRPS降水，结合趋势检验、分布滞后模型和复合","降雨与地表温度呈负相关且空间异质，无显著升温趋势但NDVI普遍增加，干热复合持续存在。","可结合作物物候与灌溉数据，探究降雨-温度耦合对农业干旱风险的滞后影响及适应策略。","2026-09-30T23:30:32.426070Z",{"id":157,"title":158,"url":159,"summary":160,"summary_zh":161,"content":9,"source_name":162,"source_url":159,"published_at":163,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":164,"score_detail":165,"sources":169,"tags":171,"primary_topic":175,"secondary_topics":180,"classification":181,"search_phrases":202,"slug":205,"view_count":59,"doi":206,"paper":207,"created_at":222},4593,"Climate Resilience and the Hydro-Vegetal Paradox in El Bayadh Province (Algeria, 1984-2023)","https:\u002F\u002Fdoi.org\u002F10.56093\u002Faaz.v65i3.177509","The decade 2010 to 2020 was the warmest ever recorded in the Mediterranean basin (+1.5°C), exceeding the global average. North Africa, identified as a vulnerability hotspot by the IPCC AR6, experiences intensified droughts and ecosystem degradation. This study presents the first quantitative assessment of climate resilience in El Bayadh Province (Algeria), revealing an unexpected hydro-vegetal paradox. A comparative multi-index methodology (restricted climate index vs. global index integrating 7 variables) was applied to 22 municipalities over the period of 1984 to 2023. The results showed a universal degradation of water balance (-8.2 to -21.4 mm yr-1) and widespread warming (+0.8 to +2.1°C decade-1). Paradoxically, 73 to 77% of municipalities showed improvement in vegetation indices (NDVI, SAVI), suggesting ecological adaptation. Principal component analysis (PCA-99%) variance explained) identified water stress as the main differentiating factor, and clustering distinguishes 5 territorial profiles (silhouette = 0.521). The global index proves more discriminant than the restricted index for capturing the complexity of socio-ecological dynamics. This study highlights the need for differentiated adaptation policies addressing challenges related to water, food security, and migration.","2010年至2020年是有记录以来地中海盆地最暖的十年（升温+1.5°C），超过了全球平均水平。北非被IPCC第六次评估报告（AR6）确定为脆弱性热点地区，正经历着加剧的干旱和生态系统退化。本研究首次对阿尔及利亚埃尔贝伊德省（El Bayadh Province）的气候韧性进行了定量评估，揭示了一个意想不到的水文-植被悖论。研究采用比较多指标方法（限制性气候指数与整合7个变量的全局指数），对22个市镇在1984年至2023年期间进行了分析。结果表明，水平衡普遍退化（-8.2至-21.4 mm yr⁻¹），且普遍升温（+0.8至+2.1°C decade⁻¹）。悖论的是，73%至77%的市镇植被指数（NDVI、SAVI）有所改善，表明存在生态适应。主成分分析（PCA，方差解释率达99%）确定水分胁迫为主要区分因子，聚类分析区分出5种地域类型（轮廓系数=0.521）。在捕捉社会-生态动态复杂性方面，全局指数比限制性指数更具判别力。本研究强调了制定差异化适应政策的必要性，以应对与水、粮食安全和移民相关的挑战。","Annals of Arid Zone","2026-10-08T00:00:00Z",74,{"impact":166,"substance":18,"depth":17,"authority":103,"freshness":167,"relevant":21,"comment":168},12,9,"基于22个市镇40年多指标遥感数据的干旱区气候韧性定量研究，方法新颖、结论有反差价值，但属区域案例研究，公共影响层级有限。",[170],{"name":162,"url":159},[172,26,27,173,174],"NDVI","干旱区农业","水资源安全",{"code":39,"slug":176,"name":177,"path":178,"parent_code":179},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":182,"locked":14,"version":34,"method":35,"evidence":183},"classified",{"candidates":184,"agricultural_evidence":40},[185,191,198],{"code":39,"score":186,"supported":40,"title":187,"abstract":189,"tags":190},16,[188],"climate resilience",[44,188],[173,26],{"code":192,"score":91,"supported":40,"title":193,"abstract":194,"tags":197},"A8",[],[195,196],"粮食安全","food security",[],{"code":47,"score":59,"supported":14,"title":199,"abstract":200,"tags":201},[],[],[172,27],[203,204],"El Bayadh 阿尔及利亚 气候韧性","NDVI 植被指数 干旱区","ElBayadh阿尔及利亚气候韧性-4593","10.56093\u002Faaz.v65i3.177509",{"doi":206,"openalex_id":208,"authors":209,"venue":162,"cited_by_count":80,"oa_url":216,"card":217,"direction":86,"ingested_from":88},"W7220949140",[210,213],{"name":211,"orcid":212},"Lakhdar Guérine","https:\u002F\u002Forcid.org\u002F0000-0003-0836-2703",{"name":214,"orcid":215},"Naîmi Bendouina","https:\u002F\u002Forcid.org\u002F0000-0002-9776-1660","http:\u002F\u002Fepubs.icar.org.in\u002Findex.php\u002FAAZ\u002Farticle\u002Fdownload\u002F177509\u002F68050",{"tldr":218,"method":219,"finding":220,"direction":86,"opportunity":221},"首次量化阿尔及利亚El Bayadh省1984-2023年气候韧性，揭示水-植被悖论。","多指标对比法（限制性气候指数与7变量全球指数），对22个市镇做PCA和聚类。","水均衡普遍恶化、升温显著，但73-77%市镇植被指数改善，呈生态适应悖论。","可探究干旱区NDVI改善的驱动机制（灌溉、物种更替或遥感尺度效应），并耦合社会经济数据。","2026-10-10T23:30:29.597640Z",{"id":224,"title":225,"url":226,"summary":227,"summary_zh":228,"content":9,"source_name":229,"source_url":226,"published_at":230,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":231,"score_detail":232,"sources":235,"tags":237,"primary_topic":241,"secondary_topics":242,"classification":243,"search_phrases":273,"slug":276,"view_count":21,"doi":277,"paper":278,"created_at":296},4560,"Assessment of Flood Impacts, Losses and Adaptation Practices in Bhajani Municipality, Kailali District, Nepal","https:\u002F\u002Fdoi.org\u002F10.3126\u002Futjliast.v2i3.101085","Floods are the most frequent and damaging hydro-meteorological hazard in the Terai region of Nepal, yet municipal-scale evidence that links hazard mapping, community perception, historical losses and local adaptation remains scarce. This study assesses flood impacts, losses, and adaptation practices in Bhajani Municipality, Kailali District, Sudurpashchim Province, a low-lying municipality with nine wards (176.25 km²) and crossed by the Mohana, Kandra, Kanda (Kadha), and Patharaiya rivers. A mixed-methods design combined a questionnaire survey of 156 respondents (Slovin’s formula, e = 8%), focus group discussions, in-depth interviews, field observation and desk review of the Local Disaster and Climate Resilience Plan (LDCRP). The Relative Importance Index (RII) was used to rank 16 flood-related problems, their causes and effects, and 12 adaptation measures rated on a five-point Likert scale; 64 Chi-square tests of independence examined whether perceptions differ by gender, age, occupation and education, and a GIS-based Weighted Multi-Criteria Decision Analysis (WMCDA) using distance from rivers (30%), Topographic Wetness Index (25%), slope (25%) and Height Above Nearest Drainage (20%) produced a flood hazard map. Wards 3, 5, 7 and 8 were classified as very high flood-risk areas, wards 6 and 9 as high, wards 1 and 2 as moderate and ward 4 as low–moderate; 85 settlements and hamlets are potentially exposed. Sixteen flood events recorded in municipal and community records affected 5,140 households, displaced 598 households, destroyed 188 houses, damaged about 1,695 bighas of cultivable land, caused an estimated loss of NPR 702.4 million and claimed 10 lives. Agriculture damage (RII = 0.863) and livestock damage (0.846) ranked as the most important problems. Non-compliance with flood-resistant building standards (0.914), waterlogging from slow runoff (0.891), insufficient investment in early warning systems (0.854) and weak institutional capacity (0.854) were the leading perceived causes, while displacement of local communities (0.905) and high livestock mortality (0.862) were leading effects. Perceptions were largely homogeneous: 62 of 64 tests (96.9%) showed no demographic association, with age linked only to views on public awareness and physical infrastructure. Strengthening river management and flood-control infrastructure (0.803) was the highest-rated adaptation measure, followed by climate-smart agriculture (0.760). A case study contrasts the slow-onset, long-duration Kandra floods with the rapid, short-warning Kadha flash floods. Flood risk in Bhajani is multidimensional, combining physical exposure, socio-economic vulnerability, infrastructure deficiencies, institutional weaknesses and climatic variability. Ward-prioritized embankment and drainage works, community-based early warning, enforcement of flood-resilient construction, climate-smart agriculture and ecosystem-based watershed management are recommended.","洪水是尼泊尔特莱地区最频繁且破坏性最强的水文气象灾害，然而，将灾害制图、社区感知、历史损失与地方适应相联系的市镇尺度证据仍然匮乏。本研究评估了苏杜尔帕希姆省凯拉利县巴贾尼市的洪水影响、损失与适应实践。该市地势低洼，下辖9个区（176.25平方公里），莫哈纳河、坎德拉河、坎达河（卡达河）和帕塔拉伊亚河穿境而过。研究采用混合方法设计，结合了156名受访者的问卷调查（Slovin公式，e = 8%）、焦点小组讨论、深度访谈、实地观察以及对《地方灾害与气候韧性计划》（LDCRP）的案头审查。采用相对重要性指数（RII）对16项洪水相关问题及其成因与影响、以及12项适应措施进行排序，评分采用五点李克特量表；通过64项卡方独立性检验考察感知是否因性别、年龄、职业和教育程度而异；并运用基于GIS的加权多准则决策分析（WMCDA），以距河流距离（30%）、地形湿度指数（25%）、坡度（25%）和距最近排水沟高度（20%）为因子，生成了洪水灾害图。第3、5、7和8区被划为极高洪水风险区，第6和9区为高风险区，第1和2区为中等风险区，第4区为低至中等风险区；85个居民点和村落可能受到影响。市镇和社区记录中记载的16次洪水事件共影响5，140户家庭，使598户家庭流离失所，摧毁188栋房屋，损坏约1，695比加耕地，造成约7.024亿尼泊尔卢比的估计损失，并导致10人丧生。农业损失（RII = 0.863）和牲畜损失（0.846）被列为最重要的问题。不遵守抗洪建筑标准（0.914）、径流缓慢导致的内涝（0.891）、预警系统投资不足（0.854）和机构能力薄弱（0.854）是主要的感知成因，而当地社区流离失所（0.905）和高牲畜死亡率（0.862）是主要影响。感知在很大程度上具有同质性：64项检验中有62项（96.9%）未显示人口统计学关联，年龄仅与对公众意识和物质基础设施的看法相关。加强河流管理和防洪基础设施（0.803）是评分最高的适应措施，其次是气候智慧型农业（0.760）。一项案例研究对比了缓发性","Universal Technical Journal of Lumbini International Academy of Science and Technology","2026-10-09T00:00:00Z",61,{"impact":20,"substance":18,"depth":233,"authority":91,"freshness":20,"relevant":21,"comment":234},17,"尼泊尔市级洪水风险与农业损失实证研究，方法扎实数据翔实，但属境外地方案例，对国内三农信息化参考价值有限。",[236],{"name":229,"url":226},[26,27,238,239,240],"洪水风险","尼泊尔","农业减灾",{"code":39,"slug":176,"name":177,"path":178,"parent_code":179},[],{"status":182,"locked":14,"version":34,"method":35,"evidence":244},{"candidates":245,"agricultural_evidence":40},[246,251,257,263,269],{"code":39,"score":20,"supported":40,"title":247,"abstract":248,"tags":250},[],[188,249],"waterlogging",[26,238],{"code":252,"score":121,"supported":40,"title":253,"abstract":254,"tags":256},"C",[],[255],"livestock",[],{"code":258,"score":121,"supported":40,"title":259,"abstract":260,"tags":262},"I1",[],[261],"smart agriculture",[],{"code":264,"score":121,"supported":40,"title":265,"abstract":266,"tags":268},"I4",[],[267],"GIS",[],{"code":47,"score":21,"supported":14,"title":270,"abstract":271,"tags":272},[],[],[27],[274,275],"Bhajani Municipality 洪水风险","Kailali 农业损失 适应","BhajaniMunicipality洪水风险-4560","10.3126\u002Futjliast.v2i3.101085",{"doi":277,"openalex_id":279,"authors":280,"venue":229,"cited_by_count":80,"oa_url":226,"card":289,"direction":295,"ingested_from":88},"W7221076000",[281,283,285,287],{"name":282,"orcid":9},"Anesh Shrestha",{"name":284,"orcid":9},"Khet Raj Dahal",{"name":286,"orcid":9},"Sujeet Dhakal",{"name":288,"orcid":9},"Sagar Sedhain",{"tldr":290,"method":291,"finding":292,"direction":293,"opportunity":294},"评估尼泊尔Bhajani市洪水影响、损失与适应实践，并绘制洪水风险图。","混合方法：156份问卷、RII排序、卡方检验与GIS加权多准则决策分析。","第3、5、7、8区为极高风险；农业与牲畜损失最重，河流管理是最受认可的适应措施。","农业绿色发展与碳","可延伸至社区感知与GIS风险图耦合的适应策略优化，及气候智慧型农业的落地评估。","智慧农业 \u002F 农业物联网","2026-10-10T23:30:07.730161Z",{"id":298,"title":299,"url":300,"summary":301,"summary_zh":302,"content":9,"source_name":303,"source_url":300,"published_at":304,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":305,"score_detail":306,"sources":309,"tags":311,"primary_topic":9,"secondary_topics":315,"classification":316,"search_phrases":333,"slug":336,"view_count":21,"doi":337,"paper":338,"created_at":361},4240,"Quantifying the Relationship Between Satellite-Derived Mangrove Canopy Cover and In Situ Air Temperature in Wonorejo Mangrove Ecotourism","https:\u002F\u002Fdoi.org\u002F10.48084\u002Fetasr.19268","Mangrove canopy contributes to local thermal regulation, but field-based evidence linking satellite-derived canopy cover to in situ air temperature remains limited in tropical urban coastal environments. This study quantified the relationship between Normalized Difference Vegetation Index (NDVI)-based canopy values and in situ air temperature at Wonorejo Mangrove Ecotourism by integrating Landsat 8\u002F9-based canopy mapping with field temperature observations. In situ air temperature was measured at 25 observation points across mangrove and non-mangrove settings from November 2024 to January 2025 using an environmental thermometer positioned 1.3 m above the ground. The mapped mangrove area covered 13.14 ha and was dominated by rare to moderate canopy cover, with 11.34 ha classified as rare and 1.80 ha as moderate. Point-based NDVI values ranged from -0.0051 to 0.42428, while mean in situ air temperature ranged from 31.4 °C to 39.4 °C. Lower air temperatures were generally recorded at mangrove points than at adjacent non-mangrove points. Simple linear regression showed a significant negative correlation between NDVI-based canopy values and average in situ air temperature ( = -0.648, = 0.420, \u003C 0.001), suggesting that higher NDVI values related to the canopy are linked with lower local air temperatures. These findings provide site-specific, seasonally bounded evidence of an inverse relationship between NDVI-derived canopy condition and near-surface air temperature in Wonorejo. The empirical trend may support local mangrove management and climate-adaptation planning, but broader application beyond the study site requires additional temporal monitoring and independent validation.","红树林冠层有助于局部热调节，但在热带城市海岸环境中，将卫星衍生的冠层覆盖度与原位气温相联系的实地证据仍然有限。本研究通过整合基于Landsat 8\u002F9的冠层制图与实地温度观测，量化了Wonorejo红树林生态旅游区基于归一化植被指数（NDVI）的冠层值与原地气温之间的关系。2024年11月至2025年1月期间，使用置于地面上方1.3米处的环境温度计，在红树林和非红树林环境中的25个观测点测量了原地气温。制图所得红树林面积为13.14公顷，以稀疏至中等冠层覆盖为主，其中11.34公顷被归类为稀疏，1.80公顷为中等。基于点位的NDVI值范围为-0.0051至0.42428，而原地平均气温范围为31.4 °C至39.4 °C。红树林点位的 recorded 气温通常低于相邻的非红树林点位。简单线性回归显示，基于NDVI的冠层值与原地平均气温之间存在显著的负相关（ = -0.648， = 0.420， \u003C 0.001），表明与冠层相关的较高NDVI值与较低的局部气温有关。这些发现提供了Wonorejo地区NDVI衍生的冠层状况与近地表气温之间反比关系的特定地点、季节性有限的证据。这一经验趋势可能支持当地红树林管理和气候适应规划，但超出研究地点的更广泛应用需要额外的时间监测和独立验证。","Engineering Technology & Applied Science Research","2026-10-02T00:00:00Z",66,{"impact":20,"substance":307,"depth":186,"authority":103,"freshness":167,"relevant":21,"comment":308},20,"以Landsat NDVI与实地气温观测量化红树林降温效应，方法清晰、数据具体，但属单点单季案例，应用范围有限。",[310],{"name":303,"url":300},[26,27,312,313,314],"红树林","城市热环境","生态旅游",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":317},{"candidates":318,"agricultural_evidence":14,"reason":54},[319,324,329],{"code":39,"score":320,"supported":40,"title":321,"abstract":322,"tags":323},4,[],[26],[26],{"code":325,"score":21,"supported":14,"title":326,"abstract":327,"tags":328},"H6",[],[],[312],{"code":47,"score":21,"supported":14,"title":330,"abstract":331,"tags":332},[],[],[27],[334,335],"Wonorejo 红树林 NDVI 气温","红树林 冠层覆盖 遥感 气温","Wonorejo红树林NDVI气温-4240","10.48084\u002Fetasr.19268",{"doi":337,"openalex_id":339,"authors":340,"venue":303,"cited_by_count":80,"oa_url":355,"card":356,"direction":86,"ingested_from":88},"W7219808713",[341,343,346,349,352],{"name":342,"orcid":9},"Mohammad Agung Wahyudi Prasetyo",{"name":344,"orcid":345},"Muhammad Naufal Eka Putra","https:\u002F\u002Forcid.org\u002F0009-0001-8821-6070",{"name":347,"orcid":348},"Aulia Lanudia Fathah","https:\u002F\u002Forcid.org\u002F0009-0005-0443-5241",{"name":350,"orcid":351},"Berlania Mahardika Putri","https:\u002F\u002Forcid.org\u002F0009-0006-9898-3085",{"name":353,"orcid":354},"Andik Isdianto","https:\u002F\u002Forcid.org\u002F0000-0002-4808-7868","https:\u002F\u002Fwww.etasr.com\u002Findex.php\u002FETASR\u002Farticle\u002Fdownload\u002F19268\u002F7117",{"tldr":357,"method":358,"finding":359,"direction":86,"opportunity":360},"该研究量化了红树林卫星冠层覆盖与实地气温的关系，发现NDVI越高气温越低。","整合Landsat 8\u002F9冠层制图与25个点实地气温观测，用线性回归分析。","NDVI与实地气温显著负相关（r=-0.648），红树林点气温低于非红树林点。","可扩展至多时相、多区域验证，并耦合微气候模型探究红树林降温机制与规划应用。","2026-10-05T23:30:28.120699Z",{"id":363,"title":364,"url":365,"summary":366,"summary_zh":367,"content":9,"source_name":368,"source_url":365,"published_at":369,"category":12,"cover_url":9,"hotness":13,"is_selected":40,"score":370,"score_detail":371,"sources":374,"tags":376,"primary_topic":379,"secondary_topics":380,"classification":381,"search_phrases":409,"slug":412,"view_count":48,"doi":413,"paper":414,"created_at":449},3919,"Meteorological to agricultural drought propagation and vegetation response across China","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejrh.2026.104022","Study region This study covers mainland China, spanning the Eastern Monsoon Region, the Northwest Arid and Semi-Arid Region, and the Qinghai-Tibet Alpine Region. Study focus Meteorological drought does not translate linearly into agricultural drought, and lagged vegetation responses remain poorly constrained. We combined Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI), satellite solar-induced chlorophyll fluorescence (SIF), and drought diagnostics based on the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Soil Moisture Index (SSMI) to quantify meteorological-to-agricultural drought propagation, drought duration and severity, and vegetation response memory across China. We examined long-term trends and propagation lags, evaluated cumulative and delayed vegetation responses using correlation and wavelet coherence analyses, and used machine-learning attribution to identify the dominant controls on vegetation variability. New hydrological insights for the region Agricultural drought lasts longer and is more severe than the meteorological drought that triggers it, with a duration approximately one month longer, reflecting the drought amplification effect within the soil-vegetation system. Drought propagation time varies significantly across China, with a median lag of 3–5 months, and the longest lags occur in inland semi-arid regions. Vegetation exhibits a pronounced drought memory effect: NDVI and SIF responses lag approximately 5 months behind drought onset. Compared with NDVI, SIF is more sensitive to short-term water stress. In most parts of China, temperature and evapotranspiration dominate vegetation dynamics, while hydrological factors exert a stronger influence in the humid southeastern regions.","研究区域 本研究涵盖中国大陆，横跨东部季风区、西北干旱半干旱区以及青藏高寒区。研究重点 气象干旱并非线性转化为农业干旱，植被的滞后响应仍缺乏充分约束。我们结合中分辨率成像光谱仪（MODIS）归一化植被指数（NDVI）、卫星太阳诱导叶绿素荧光（SIF），以及基于标准化降水蒸散指数（SPEI）和标准化土壤湿度指数（SSMI）的干旱诊断，量化了中国气象干旱向农业干旱的传播过程、干旱历时与严重程度，以及植被响应记忆。我们检验了长期趋势与传播滞后，利用相关分析和小波相干分析评估了植被的累积响应与延迟响应，并采用机器学习归因方法识别植被变异的主导控制因子。该区域的新水文学认识 农业干旱比触发它的气象干旱持续时间更长、程度更严重，历时约长一个月，反映了土壤—植被系统内的干旱放大效应。干旱传播时间在中国各地差异显著，中位滞后为3—5个月，最长滞后出现在内陆半干旱区。植被表现出显著的干旱记忆效应：NDVI和SIF的响应滞后于干旱发生约5个月。与NDVI相比，SIF对短期水分胁迫更为敏感。在中国大部分地区，温度和蒸散主导植被动态，而在湿润的东南部地区，水文因素的影响更强。","Journal of Hydrology Regional Studies","2026-09-29T00:00:00Z",85,{"impact":18,"substance":372,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":373},23,"基于多源遥感与机器学习量化全国气象到农业干旱传导及植被滞后响应，方法新颖、结论可靠，对农业旱情监测预警有直接参考价值。",[375],{"name":368,"url":365},[377,108,27,378,30],"机器学习","干旱预警",{"code":39,"slug":176,"name":177,"path":178,"parent_code":179},[],{"status":182,"locked":14,"version":34,"method":35,"evidence":382},{"candidates":383,"agricultural_evidence":40},[384,388,395,400,405],{"code":39,"score":186,"supported":40,"title":385,"abstract":386,"tags":387},[42],[44,42],[108,378],{"code":389,"score":91,"supported":40,"title":390,"abstract":391,"tags":394},"H2",[],[392,393],"土壤","soil",[],{"code":396,"score":320,"supported":40,"title":397,"abstract":398,"tags":399},"I2",[],[377],[377],{"code":120,"score":121,"supported":40,"title":401,"abstract":402,"tags":404},[],[403],"evapotranspiration",[],{"code":47,"score":21,"supported":14,"title":406,"abstract":407,"tags":408},[],[],[27],[410,411],"MODIS NDVI SIF 干旱","SPEI SSMI 农业干旱","MODISNDVISIF干旱-3919","10.1016\u002Fj.ejrh.2026.104022",{"doi":413,"openalex_id":415,"authors":416,"venue":368,"cited_by_count":80,"oa_url":365,"card":443,"direction":448,"ingested_from":88},"W7214733729",[417,420,423,425,428,431,433,435,437,439,441],{"name":418,"orcid":419},"Dong Liu","https:\u002F\u002Forcid.org\u002F0000-0001-6924-0748",{"name":421,"orcid":422},"Zihan Ma","https:\u002F\u002Forcid.org\u002F0009-0009-2854-2622",{"name":424,"orcid":9},"Liangliang Zhang",{"name":426,"orcid":427},"Nan Sun","https:\u002F\u002Forcid.org\u002F0009-0008-4472-3573",{"name":429,"orcid":430},"Muhammad Abrar Faiz","https:\u002F\u002Forcid.org\u002F0000-0003-0626-0308",{"name":432,"orcid":9},"Mo Li",{"name":434,"orcid":9},"Xiaochen Qi",{"name":436,"orcid":9},"Tianxiao Li",{"name":438,"orcid":9},"Song Cui",{"name":440,"orcid":9},"Zhaoqiang Zhou",{"name":442,"orcid":9},"Muhammad Imran Khan",{"tldr":444,"method":445,"finding":446,"direction":86,"opportunity":447},"量化中国气象干旱向农业干旱的传播及植被滞后响应。","用MODIS NDVI、SIF、SPEI、SSMI及机器学习归因分析。","农业干旱比气象干旱长约1个月，植被响应滞后约5个月，SIF更敏感。","可探索不同气候区干旱传播阈值与SIF早期预警指标，构建区域化干旱记忆模型。","农业人工智能与决策模型","2026-10-01T23:30:55.666679Z",{"id":451,"title":452,"url":453,"summary":454,"summary_zh":455,"content":9,"source_name":456,"source_url":453,"published_at":100,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":80,"score_detail":457,"sources":459,"tags":461,"primary_topic":9,"secondary_topics":464,"classification":465,"search_phrases":482,"slug":485,"view_count":59,"doi":486,"paper":487,"created_at":508},3832,"Applications of Earth Observation for Monitoring and Management of Natural Hazards and Emergency Situations in Central Asia","https:\u002F\u002Fdoi.org\u002F10.64599\u002Fmwdj4371","Central Asia is highly vulnerable to a wide range of natural hazards due to its complex mountainous terrain, glacierized catchments, and highly variable climate. Hazards such as glacial lake outburst floods (GLOFs), mudflows, snow avalanches, river floods, and droughts pose significant risks to communities, infrastructure, and water resources across the region. Many of these hazards originate in the high mountain systems of the Tien Shan and Pamir ranges, where climate change is accelerating glacier retreat, altering hydrological regimes, and increasing the likelihood of extreme events. Effective monitoring and management of these hazards require timely and spatially comprehensive information, which is often limited by sparse ground-based observations in remote mountain environments. Earth Observation (EO) technologies provide powerful tools for monitoring environmental conditions and supporting disaster risk management in such regions. Satellite remote sensing enables the detection of glacial lake expansion, monitoring of snow and ice dynamics, mapping of flood and mudflow events, and assessment of drought conditions over large areas. Radar and optical satellite data allow near-real-time hazard detection and provide critical information for early warning and emergency response. This short commentary article reviews the applications of EO technologies for monitoring major natural hazards in Central Asia and highlights their role in improving disaster preparedness and response. The study also discusses operational satellite platforms and emerging technologies that can support hazard assessment and risk reduction across the region.","中亚地区因其复杂的山地地形、冰川流域和高度多变的气候，极易受到多种自然灾害的影响。冰川湖溃决洪水（GLOFs）、泥石流、雪崩、河流洪水和干旱等灾害对该地区的社区、基础设施和水资源构成了重大风险。其中许多灾害源于天山和帕米尔山脉的高山系统，气候变化正在加速冰川退缩、改变水文情势并增加极端事件的发生概率。对这些灾害进行有效监测和管理需要及时且空间上全面的信息，而偏远山区稀疏的地面观测往往限制了信息的获取。地球观测（EO）技术为监测此类地区的环境状况和支持灾害风险管理提供了强有力的工具。卫星遥感能够探测冰川湖扩张、监测冰雪动态、绘制洪水和泥石流事件分布图，以及评估大范围区域的干旱状况。雷达和光学卫星数据可实现近实时的灾害探测，并为预警和应急响应提供关键信息。这篇简短的评论文章综述了地球观测技术在中亚主要自然灾害监测中的应用，并强调了其在改善灾害防备和响应方面的作用。该研究还讨论了可支持该地区灾害评估和风险减轻的业务化卫星平台及新兴技术。","International Journal of Sustainability and Risk Control",{"impact":80,"substance":80,"depth":80,"authority":80,"freshness":80,"relevant":80,"comment":458},"主题为地球观测与灾害管理，与三农及农业信息化关联弱，不建议进入每日精选。",[460],{"name":456,"url":453},[462,27,463,28],"气候变化","灾害预警",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":466},{"candidates":467,"agricultural_evidence":14,"reason":54},[468,474,478],{"code":39,"score":469,"supported":40,"title":470,"abstract":471,"tags":473},11,[],[462,44,472,42],"climate change",[462,463],{"code":47,"score":48,"supported":40,"title":475,"abstract":476,"tags":477},[],[51,52],[27],{"code":120,"score":121,"supported":40,"title":479,"abstract":480,"tags":481},[],[124],[],[483,484],"中亚 地球观测 自然灾害","天山 冰川湖 洪水 遥感","中亚地球观测自然灾害-3832","10.64599\u002Fmwdj4371",{"doi":486,"openalex_id":488,"authors":489,"venue":456,"cited_by_count":80,"oa_url":502,"card":503,"direction":295,"ingested_from":88},"W7214586653",[490,493,495,497,500],{"name":491,"orcid":492},"Ben Jarihani","https:\u002F\u002Forcid.org\u002F0000-0002-1728-0008",{"name":494,"orcid":9},"Behzod Pulatov",{"name":496,"orcid":9},"Vasila Sulaymonova",{"name":498,"orcid":499},"Aliyev Vugar","https:\u002F\u002Forcid.org\u002F0009-0008-9984-8349",{"name":501,"orcid":9},"Álvaro Salazar","https:\u002F\u002Fijsrc.com\u002Findex.php\u002Fijsrc\u002Farticle\u002Fdownload\u002F80\u002F56",{"tldr":504,"method":505,"finding":506,"direction":86,"opportunity":507},"综述地球观测技术在中亚自然灾害监测与应急管理中的应用。","综述卫星遥感（雷达与光学）用于冰川湖、洪水、泥石流、干旱监测。","地球观测可弥补地面观测不足，支持近实时预警与应急响应。","可探索多源遥感融合与AI方法，提升中亚跨境灾害预警的时效与精度。","2026-09-30T23:30:16.535343Z"]