[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4756":3,"related-4756":88},{"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":31,"secondary_topics":37,"classification":38,"search_phrases":64,"slug":67,"view_count":21,"doi":68,"paper":69,"created_at":87},4756,"ديناميكيات وحساسية المناخ والغطاء النباتي في العراق باستخدام بيانات رصد الأرض طويلة الأمد","https:\u002F\u002Fdoi.org\u002F10.66026\u002Fy7543b35","تؤدي تغيرات المناخ إلى تكثيف الإجهاد الحراري والمائي عبر المناطق الجافة، مما يزيد من الحاجة إلى رصد متسق مكانياً وطويل الأمد لاستجابات الغطاء النباتي. العراق معرض بشكل خاص لهذه التغيرات لأن التدرجات المناخية القوية، والجفاف المتكرر، ومحدودية توافر المياه تتزامن مع مساحات شاسعة من الأراضي المطرية والمروية. قامت هذه الدراسة بتقييم ديناميكيات المناخ والغطاء النباتي في العراق من عام 2001 إلى 2025 باستخدام مؤشر الاختلاف الغطائي النباتي الطبيعي (MODIS NDVI)، وبيانات هطول الأمطار (CHIRPS)، وبيانات درجة حرارة الهواء على ارتفاع مترين (ERA5-Land). تم تحليل متوسط هطول الأمطار للفترة من أكتوبر إلى مايو، واتجاهات مؤشر (NDVI) للفترة من يناير إلى مايو، وارتباطات المناخ مع مؤشر (NDVI) بعد إزالة الاتجاه (detrended) على شبكة مشتركة بدقة 0.1 درجة.تم بعد ذلك تصنيف البكسلات النباتية على أنها: حساسة لهطول الأمطار، أو حساسة للحرارة، أو حساسة لكليهما، أو لا تظهر علاقة متوقعة قوية، أو تظهر اتجاهاً قوياً آخر. أظهر هطول الأمطار في الموسم الرطب تدرجاً واضحاً من إجماليات عالية جداً في شمال وشمال شرق العراق إلى إجماليات منخفضة ومنخفضة جداً عبر الغرب والجنوب الغربي والجنوب. كان الاخضرار ذو الدلالة الإحصائية أكثر انتشاراً بشكل ملحوظ من الاسمرار، حيث تركزت أقوى اتجاهات مؤشر (NDVI) الإيجابية في المناطق الزراعية في الشمال والشمال الشرقي والوسط. بعد إزالة الاتجاهات الخطية، كانت ارتباطات هطول الأمطار مع مؤشر (NDVI) إيجابية في الغالب وواسعة النطاق مكانياً، في حين كانت ارتباطات درجة الحرارة مع مؤشر (NDVI) ذات دلالة سلبية بشكل رئيسي ومركّزة في شمال وشرق وجنوب شرق العراق. هيمنت حساسية هطول الأمطار على التصنيف المتكامل، بينما شكلت الحساسية المزدوجة لهطول الأمطار والحرارة مجموعات متميزة في شمال-وسط وجنوب شرق البلاد. توفر هذه النتائج خط أساس مكانياً وطنياً لتحديد مناطق الغطاء النباتي المرتبطة بتقلبات المياه والحرارة بين السنوات. وتمثل فئات الحساسية ارتباطات إحصائية وليست عزوًا سببيًا.","气候变化正在加剧干旱地区的高温与水分胁迫，从而增加了对植被响应进行空间一致、长期监测的需求。伊拉克尤其容易受到这些变化的影响，因为强烈的气候梯度、频繁的干旱以及有限的水资源可用性，与大片雨养和灌溉土地并存。本研究利用MODIS归一化植被指数（NDVI）、降雨数据（CHIRPS）以及2米高度气温数据（ERA5-Land），评估了2001年至2025年伊拉克的气候与植被动态。研究在0.1度分辨率的统一网格上，分析了10月至5月的平均降雨量、1月至5月的NDVI趋势，以及去趋势（detrended）后气候与NDVI的相关性。随后将植被像元分类为：对降雨敏感、对温度敏感、对两者均敏感、未表现出强预期关系，或表现出其他强趋势。湿季降雨呈现出从伊拉克北部和东北部极高总量向西、西南和南部低及极低总量的明显梯度。具有统计显著性的绿化现象明显比褐化更为广泛，其中最强的NDVI正趋势集中在北部、东北部和中部的农业区。去除线性趋势后，降雨与NDVI的相关性大多为正且在空间上广泛分布，而温度与NDVI的相关性主要为显著负相关，集中在伊拉克北部、东部和东南部。降雨敏感性在综合分类中占主导地位，而降雨与温度的双重敏感性在该国中北部和东南部形成了独特的集群。这些结果为识别与年际水热波动相关的植被区域提供了全国尺度的空间基线。敏感性类别代表统计关联，而非因果归因。",null,"Journal Of Babylon Center for Humanities Studies","2026-10-09T00:00:00Z","论文",10,false,70,{"impact":17,"substance":18,"depth":19,"authority":17,"freshness":20,"relevant":21,"comment":22},12,22,18,6,1,"基于MODIS、CHIRPS与ERA5-Land长时序数据评估伊拉克气候与植被敏感性，方法规范、结论有区域参考价值，但属境外基础研究，公共影响有限。",[24],{"name":10,"url":6},[26,27,28,29,30],"气候变化","NDVI","遥感监测","干旱区农业","植被覆盖",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,51,58],{"code":32,"score":45,"supported":46,"title":47,"abstract":48,"tags":50},8,true,[],[26,49],"干旱",[29,26],{"code":52,"score":20,"supported":46,"title":53,"abstract":54,"tags":57},"H3",[],[55,56],"灌溉","水资源",[],{"code":59,"score":60,"supported":14,"title":61,"abstract":62,"tags":63},"I3",3,[],[],[27,30,28],[65,66],"伊拉克 NDVI 植被动态","MODIS CHIRPS ERA5-Land 遥感","伊拉克NDVI植被动态-4756","10.66026\u002Fy7543b35",{"doi":68,"openalex_id":70,"authors":71,"venue":10,"cited_by_count":78,"oa_url":79,"card":80,"direction":84,"ingested_from":86},"W7221306668",[72,74,76],{"name":73,"orcid":9},"خولة‌ حمه‌رشید عمر",{"name":75,"orcid":9},"سایە دلاوەر محمد",{"name":77,"orcid":9},"Daban Kadhim Omar",0,"https:\u002F\u002Fbcchj.uobabylon.edu.iq\u002Findex.php\u002Fbcchj\u002Farticle\u002Fdownload\u002F4819\u002F4866",{"tldr":81,"method":82,"finding":83,"direction":84,"opportunity":85},"基于2001–2025年MODIS NDVI、CHIRPS降水与ERA5-Land温度数据，评估伊拉","MODIS NDVI、CHIRPS降水、ERA5-Land温度，0.1°网格去趋","植被绿化趋势多于褐化，降水敏感性主导，温度负相关集中于北部、东部和东南部。","农业遥感与作物表型","可结合灌溉与土地覆盖数据，区分雨养与灌溉区植被对水热胁迫的差异化响应机制。","openalex","2026-10-12T23:30:27.995466Z",{"total":20,"page":21,"page_size":20,"items":89},[90,152,265,327,413,489],{"id":91,"title":92,"url":93,"summary":94,"summary_zh":95,"content":9,"source_name":96,"source_url":93,"published_at":97,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":98,"score_detail":99,"sources":103,"tags":105,"primary_topic":108,"secondary_topics":109,"classification":110,"search_phrases":131,"slug":134,"view_count":127,"doi":135,"paper":136,"created_at":151},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":17,"substance":18,"depth":19,"authority":100,"freshness":101,"relevant":21,"comment":102},13,9,"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。",[104],{"name":96,"url":93},[27,106,28,29,107],"气候适应","水资源安全",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":111},{"candidates":112,"agricultural_evidence":46},[113,119,126],{"code":32,"score":114,"supported":46,"title":115,"abstract":117,"tags":118},16,[116],"climate resilience",[49,116],[29,106],{"code":120,"score":20,"supported":46,"title":121,"abstract":122,"tags":125},"A8",[],[123,124],"粮食安全","food security",[],{"code":59,"score":127,"supported":14,"title":128,"abstract":129,"tags":130},2,[],[],[27,28],[132,133],"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":135,"openalex_id":137,"authors":138,"venue":96,"cited_by_count":78,"oa_url":145,"card":146,"direction":84,"ingested_from":86},"W7220949140",[139,142],{"name":140,"orcid":141},"Lakhdar Guérine","https:\u002F\u002Forcid.org\u002F0000-0003-0836-2703",{"name":143,"orcid":144},"Naîmi Bendouina","https:\u002F\u002Forcid.org\u002F0000-0002-9776-1660","http:\u002F\u002Fepubs.icar.org.in\u002Findex.php\u002FAAZ\u002Farticle\u002Fdownload\u002F177509\u002F68050",{"tldr":147,"method":148,"finding":149,"direction":84,"opportunity":150},"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":153,"title":154,"url":155,"summary":156,"summary_zh":157,"content":9,"source_name":158,"source_url":155,"published_at":159,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":160,"score_detail":161,"sources":164,"tags":166,"primary_topic":170,"secondary_topics":171,"classification":181,"search_phrases":236,"slug":239,"view_count":78,"doi":240,"paper":241,"created_at":264},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","2026-10-20T00:00:00Z",66,{"impact":100,"substance":19,"depth":162,"authority":17,"freshness":45,"relevant":21,"comment":163},15,"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。",[165],{"name":158,"url":155},[26,167,28,168,169],"盐碱地治理","智慧灌溉","土壤盐渍化",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[172,177],{"code":173,"slug":174,"name":175,"path":176,"parent_code":36},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",{"code":52,"slug":178,"name":179,"path":180,"parent_code":36},"irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",{"status":39,"locked":14,"version":40,"method":41,"evidence":182},{"candidates":183,"agricultural_evidence":46},[184,189,194,199,206,210,217,224,230],{"code":32,"score":19,"supported":46,"title":185,"abstract":187,"tags":188},[186],"climate change",[26,106,49,186],[26],{"code":173,"score":162,"supported":46,"title":190,"abstract":191,"tags":193},[174],[192,174],"土壤",[167],{"code":52,"score":13,"supported":46,"title":195,"abstract":196,"tags":198},[],[55,56,178,197],"evapotranspiration",[168],{"code":59,"score":200,"supported":46,"title":201,"abstract":202,"tags":205},7,[],[203,204],"遥感","remote sensing",[28],{"code":120,"score":20,"supported":46,"title":207,"abstract":208,"tags":209},[],[123,124],[],{"code":211,"score":20,"supported":46,"title":212,"abstract":213,"tags":216},"I1",[],[214,215],"精准农业","precision agriculture",[],{"code":218,"score":20,"supported":46,"title":219,"abstract":220,"tags":223},"I4",[],[221,222],"地理信息","geographic information",[],{"code":225,"score":60,"supported":46,"title":226,"abstract":227,"tags":229},"F3",[],[228],"养分管理",[],{"code":231,"score":60,"supported":46,"title":232,"abstract":233,"tags":235},"J1",[],[234],"农业政策",[],[237,238],"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":240,"openalex_id":242,"authors":243,"venue":158,"cited_by_count":78,"oa_url":155,"card":259,"direction":84,"ingested_from":86},"W7222999158",[244,246,248,250,252,254,257],{"name":245,"orcid":9},"Asifa Naz",{"name":247,"orcid":9},"Muhammad Abu Baker Siddiq",{"name":249,"orcid":9},"Syed Asghar Hussain Shah",{"name":251,"orcid":9},"Shahrish Nawaz",{"name":253,"orcid":9},"Muhmmad Irfan",{"name":255,"orcid":256},"Rizwana Kausar","https:\u002F\u002Forcid.org\u002F0000-0002-1339-3312",{"name":258,"orcid":9},"Muhammad Nouman Khalid",{"tldr":260,"method":261,"finding":262,"direction":84,"opportunity":263},"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":266,"title":267,"url":268,"summary":269,"summary_zh":270,"content":9,"source_name":271,"source_url":268,"published_at":272,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":98,"score_detail":273,"sources":276,"tags":278,"primary_topic":282,"secondary_topics":283,"classification":284,"search_phrases":299,"slug":302,"view_count":78,"doi":303,"paper":304,"created_at":326},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":274,"freshness":45,"relevant":21,"comment":275},14,"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。",[277],{"name":271,"url":268},[26,28,279,280,281],"植被生产力","森林物候","珠江流域",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":285},{"candidates":286,"agricultural_evidence":46},[287,291,295],{"code":32,"score":200,"supported":46,"title":288,"abstract":289,"tags":290},[],[26,186],[26],{"code":173,"score":20,"supported":46,"title":292,"abstract":293,"tags":294},[],[192,174],[],{"code":59,"score":21,"supported":14,"title":296,"abstract":297,"tags":298},[],[],[28],[300,301],"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":303,"openalex_id":305,"authors":306,"venue":271,"cited_by_count":78,"oa_url":320,"card":321,"direction":84,"ingested_from":86},"W7221897424",[307,310,312,314,316,318],{"name":308,"orcid":309},"Shijie Yang","https:\u002F\u002Forcid.org\u002F0009-0001-7573-5509",{"name":311,"orcid":9},"Zhaoju Zheng",{"name":313,"orcid":9},"Xueming Zhao",{"name":315,"orcid":9},"Zhipeng Zhang",{"name":317,"orcid":9},"Xiaohui Cui",{"name":319,"orcid":9},"Yuan Zeng","https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Fpdf\u002F10.1080\u002F17538947.2026.2738487?needAccess=true",{"tldr":322,"method":323,"finding":324,"direction":84,"opportunity":325},"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":328,"title":329,"url":330,"summary":331,"summary_zh":332,"content":9,"source_name":333,"source_url":330,"published_at":272,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":334,"sources":336,"tags":338,"primary_topic":342,"secondary_topics":348,"classification":350,"search_phrases":395,"slug":398,"view_count":21,"doi":399,"paper":400,"created_at":412},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)",{"impact":19,"substance":114,"depth":162,"authority":17,"freshness":101,"relevant":21,"comment":335},"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。",[337],{"name":333,"url":330},[339,340,341,26,28],"智慧农业","农业人工智能","可持续发展",{"code":343,"slug":344,"name":345,"path":346,"parent_code":347},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[349],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":351},{"candidates":352,"agricultural_evidence":46},[353,362,366,370,374,381,388],{"code":343,"score":19,"supported":46,"title":354,"abstract":356,"tags":361},[355],"artificial intelligence",[357,358,359,360,355],"深度学习","机器学习","machine learning","deep learning",[340],{"code":32,"score":162,"supported":46,"title":363,"abstract":364,"tags":365},[186],[26,186],[26],{"code":211,"score":200,"supported":46,"title":367,"abstract":368,"tags":369},[],[214,215],[339],{"code":59,"score":200,"supported":46,"title":371,"abstract":372,"tags":373},[],[203,204],[28],{"code":375,"score":20,"supported":46,"title":376,"abstract":377,"tags":380},"H4",[],[378,379],"碳排放","carbon emission",[],{"code":382,"score":20,"supported":46,"title":383,"abstract":384,"tags":387},"H6",[],[385,386],"生物多样性","biodiversity",[],{"code":389,"score":20,"supported":46,"title":390,"abstract":391,"tags":394},"I5",[],[392,393],"物联网","internet of things",[],[396,397],"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":399,"openalex_id":401,"authors":402,"venue":333,"cited_by_count":78,"oa_url":330,"card":405,"direction":411,"ingested_from":86},"W7222092855",[403],{"name":404,"orcid":9},"Deepmala Suryavanshi",{"tldr":406,"method":407,"finding":408,"direction":409,"opportunity":410},"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。","智慧农业 \u002F 农业物联网","2026-10-16T23:30:15.059867Z",{"id":414,"title":415,"url":416,"summary":417,"summary_zh":418,"content":9,"source_name":419,"source_url":416,"published_at":420,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":421,"score_detail":422,"sources":424,"tags":426,"primary_topic":429,"secondary_topics":430,"classification":433,"search_phrases":456,"slug":459,"view_count":127,"doi":460,"paper":461,"created_at":488},4172,"Machine learning reveals distinct drivers of soil organic carbon across the mountain-oasis-desert system of northwest China","https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs13021-026-00522-5","The mountain-oasis-desert system (MODS) is a distinctive landscape pattern shaped by interactions between geomorphological configurations and hydrological processes in arid regions. However, most soil organic carbon (SOC) mapping studies treat arid landscapes as homogeneous units, leaving limited quantitative evidence on how SOC patterns and environmental associations differ among MODS subsystems. As a critical ecosystem highly sensitive to climate change and human activities, understanding these responses is essential for regional soil carbon management and ecological restoration. In this study, we developed an ecosystem-based modeling framework in the Hexi Region (HXR) to construct separate SOC prediction models for different subsystems, aiming to investigate the spatiotemporal dynamics of SOC stocks and identify their key driving factors across MODS. The results show that incorporating remote sensing (RS) variables significantly improved model performance, increasing the mean R 2 from 0.51 to 0.58. Among the tested models, XGBoost achieved the best performance, providing an effective tool for SOC mapping in arid regions. Shapley additive explanations (SHAP) analysis of the best-performing XGBoost models identified distinct leading predictors across the MODS, including surface shortwave radiation (SRAD) in mountain and desert ecosystems and the difference vegetation index (DVI) in oasis ecosystems. Furthermore, the partial least squares path model (PLS-PM) revealed contrasting influences of climate change and human activities across ecological subsystems. Climatic factors exerted the strongest influence in the mountainous subsystem, whereas in the oasis subsystem intensive human management became the dominant driver of soil carbon cycling. From 2001 to 2023, SOC stocks in oasis regions increased significantly at a rate of 0.17 t C ha⁻ 1 year⁻ 1 , potentially associated with land-use change and agricultural management. Approximately 19.3% of the study area experienced significant SOC stocks declines. By resolving subsystem-specific SOC patterns and environmental associations, this study advances ecosystem-aware SOC assessment in arid regions. The resulting framework also provides a basis for differentiated carbon management across MODS.","山地-绿洲-荒漠系统（MODS）是干旱区地貌格局与水文过程相互作用形成的独特景观格局。然而，大多数土壤有机碳（SOC）制图研究将干旱区景观视为均质单元，关于MODS各子系统间SOC格局及其环境关联差异的定量证据仍然有限。作为对气候变化和人类活动高度敏感的关键生态系统，理解这些响应对于区域土壤碳管理和生态恢复至关重要。本研究在河西地区（HXR）构建了基于生态系统的建模框架，针对不同子系统分别建立SOC预测模型，旨在探究MODS中SOC储量的时空动态并识别其关键驱动因子。结果表明，引入遥感（RS）变量显著提升了模型性能，平均R²从0.51提高至0.58。在测试的模型中，XGBoost表现最佳，为干旱区SOC制图提供了有效工具。对最优XGBoost模型的SHAP（Shapley加法解释）分析识别出MODS各子系统的不同主导预测因子，其中山地和荒漠生态系统为地表短波辐射（SRAD），绿洲生态系统为差值植被指数（DVI）。此外，偏最小二乘路径模型（PLS-PM）揭示了气候变化和人类活动在各生态子系统中的差异化影响。气候因子在山地子系统中影响最强，而在绿洲子系统中，集约化人类管理成为土壤碳循环的主导驱动因素。2001年至2023年，绿洲区域SOC储量以0.17 t C ha⁻¹ year⁻¹的速率显著增加，这可能与土地利用变化和农业管理有关。约19.3%的研究区域经历了SOC储量的显著下降。通过解析子系统特定的SOC格局及其环境关联，本研究推进了干旱区生态系统感知型SOC评估，所构建的框架也为MODS差异化碳管理提供了依据。","Carbon Balance and Management","2026-10-03T00:00:00Z",79,{"impact":114,"substance":18,"depth":19,"authority":274,"freshness":101,"relevant":21,"comment":423},"基于XGBoost与SHAP的干旱区SOC分异驱动研究，方法新颖、数据翔实，对区域碳管理与生态修复有参考价值。",[425],{"name":419,"url":416},[358,427,428,28,29],"土壤有机碳","生态修复",{"code":173,"slug":174,"name":175,"path":176,"parent_code":36},[431,432],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"code":343,"slug":344,"name":345,"path":346,"parent_code":347},{"status":39,"locked":14,"version":40,"method":41,"evidence":434},{"candidates":435,"agricultural_evidence":46},[436,440,444,448,452],{"code":173,"score":162,"supported":46,"title":437,"abstract":438,"tags":439},[174],[192,174],[427],{"code":32,"score":13,"supported":46,"title":441,"abstract":442,"tags":443},[],[26,49,186],[29],{"code":343,"score":101,"supported":46,"title":445,"abstract":446,"tags":447},[359],[],[358],{"code":59,"score":200,"supported":46,"title":449,"abstract":450,"tags":451},[],[203,204],[28],{"code":382,"score":21,"supported":14,"title":453,"abstract":454,"tags":455},[],[],[428],[457,458],"河西地区 土壤有机碳 机器学习","山地-绿洲-荒漠 遥感 碳储量","河西地区土壤有机碳机器学习-4172","10.1186\u002Fs13021-026-00522-5",{"doi":460,"openalex_id":462,"authors":463,"venue":419,"cited_by_count":78,"oa_url":416,"card":483,"direction":84,"ingested_from":86},"W7219075005",[464,466,469,471,474,476,479,481],{"name":465,"orcid":9},"Y. Chen",{"name":467,"orcid":468},"Haiyang Xi","https:\u002F\u002Forcid.org\u002F0000-0003-3158-8161",{"name":470,"orcid":9},"Meng Zhu",{"name":472,"orcid":473},"Wenju Cheng","https:\u002F\u002Forcid.org\u002F0000-0002-1822-5668",{"name":475,"orcid":9},"Yulian Hao",{"name":477,"orcid":478},"Linbo Qu","https:\u002F\u002Forcid.org\u002F0009-0007-4669-8407",{"name":480,"orcid":9},"Zhehui Wang",{"name":482,"orcid":9},"Bin Wang",{"tldr":484,"method":485,"finding":486,"direction":84,"opportunity":487},"构建基于生态系统的机器学习框架，预测西北荒漠-绿洲-山地系统土壤有机碳并识别各子系统驱动因子。","XGBoost、SHAP、PLS-PM，结合遥感变量与2001-2023年多源数","遥感变量提升模型R²至0.58；山地和沙漠由辐射主导，绿洲由人类管理主导，绿洲碳储量年增0.17 t","可延伸研究绿洲农业管理措施对土壤碳的长期影响，并开发子系统自适应的碳监测与决策模型。","2026-10-04T23:30:24.631460Z",{"id":490,"title":491,"url":492,"summary":493,"summary_zh":494,"content":9,"source_name":495,"source_url":492,"published_at":496,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":497,"score_detail":498,"sources":500,"tags":502,"primary_topic":505,"secondary_topics":506,"classification":511,"search_phrases":535,"slug":538,"view_count":21,"doi":539,"paper":540,"created_at":553},3903,"An Analysis of Land Use and Land Cover Change Detection Using Geospatial Technology-A Case Study of Phalsoond Tehsil in Jaisalmer District, Rajasthan, India","https:\u002F\u002Fdoi.org\u002F10.22214\u002Fijraset.2026.84983","Analysis of Land Use and Land Cover (LULC) change is significant indicators of environmental changes, resource utilization and sustainable development, especially in arid regions where land and water resources are very fragile. The present study has investigated the spatio-temporal analysis of LULC changes in Phascoond Tehsil of Jaisalmer District of Rajasthan, India from the year 2017 to 2024 using Remote sensing and Geographic Information System (GIS) techniques. To classify the study area, multi-temporal Sentinel-2 data with 10 m spatial resolution were provided by the Esri Sentinel-2 Land Cover Explorer, which was used to separate the area into five categories i.e. water bodies, agriculture land, built-up areas, bare ground and wasteland. LULC changes were quantified in terms of magnitude and direction using post-classification comparison and GIS-based change detection techniques. The findings show significant change in landscape over the year 2017 to 2024. Wasteland remained the dominant land-cover category but declined from 779.07 km² (78.28%) in 2017 to 726.86 km² (71.41%) in 2024. Agricultural area grew by 86.62 km² (+19.48% to 280.52 km²), adding 94.76 km² of wasteland. Gradual settlement and infrastructure development also resulted in an increase in built-up area from 3.89 km2 to 7.73 km2 . The water bodies were small in spatial extent and slight shifts happened between bare ground and other land-cover classes. The results clearly show that the Sentinel-2 data and GIS-based analysis is useful in monitoring LULC dynamics in data-sparse arid regions. The present extent of agriculture and development has occurred at a time when there is a need to manage the land and groundwater resources sustainably, monitor environment, and plan land use with climate change in Phalsoond tehsil of Jaisalmer District in western Rajasthan.","土地利用与土地覆盖（LULC）变化分析是环境变化、资源利用和可持续发展的重要指标，在土地与水资源极为脆弱的干旱地区尤为如此。本研究利用遥感与地理信息系统（GIS）技术，对印度拉贾斯坦邦杰伊瑟尔梅尔县Phascoond乡2017年至2024年间的LULC变化进行了时空分析。为对研究区进行分类，采用了Esri Sentinel-2土地覆盖浏览器提供的10 m空间分辨率多时相Sentinel-2数据，将区域划分为五个类别，即水体、农用地、建设用地、裸地和荒地。通过分类后比较和基于GIS的变化检测技术，从幅度和方向两方面对LULC变化进行了量化。研究结果表明，2017年至2024年间景观发生了显著变化。荒地仍为优势土地覆盖类型，但从2017年的779.07 km²（78.28%）下降至2024年的726.86 km²（71.41%）。农业面积增加了86.62 km²（增幅19.48%，达到280.52 km²），占用了94.76 km²的荒地。逐步的聚落与基础设施建设也导致建设用地从3.89 km²增加至7.73 km²。水体空间范围较小，裸地与其他土地覆盖类别之间发生了轻微转换。结果清楚表明，Sentinel-2数据与基于GIS的分析对于监测数据稀缺干旱地区的LULC动态具有实用价值。当前农业与开发的程度出现在这样一个时期：拉贾斯坦邦西部杰伊瑟尔梅尔县Phalsoond乡亟需可持续管理土地与地下水资源、监测环境，并在气候变化背景下进行土地利用规划。","International Journal for Research in Applied Science and Engineering Technology","2026-09-30T00:00:00Z",52,{"impact":20,"substance":19,"depth":274,"authority":20,"freshness":45,"relevant":21,"comment":499},"基于Sentinel-2与GIS的印度干旱区土地利用变化研究，方法规范但属区域性案例，对国内三农信息化参考价值有限。",[501],{"name":495,"url":492},[28,503,29,504],"土地利用","GIS应用",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[507],{"code":218,"slug":508,"name":509,"path":510,"parent_code":347},"gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis",{"status":39,"locked":14,"version":40,"method":41,"evidence":512},{"candidates":513,"agricultural_evidence":46},[514,518,523,527,531],{"code":32,"score":13,"supported":46,"title":515,"abstract":516,"tags":517},[],[26,49,186],[29],{"code":218,"score":101,"supported":46,"title":519,"abstract":520,"tags":522},[],[221,521,222],"GIS",[],{"code":59,"score":200,"supported":46,"title":524,"abstract":525,"tags":526},[],[203,204],[28],{"code":52,"score":60,"supported":46,"title":528,"abstract":529,"tags":530},[],[56],[],{"code":382,"score":21,"supported":14,"title":532,"abstract":533,"tags":534},[],[],[503],[536,537],"Jaisalmer 土地利用变化","Sentinel-2 遥感 干旱区","Jaisalmer土地利用变化-3903","10.22214\u002Fijraset.2026.84983",{"doi":539,"openalex_id":541,"authors":542,"venue":495,"cited_by_count":78,"oa_url":492,"card":548,"direction":84,"ingested_from":86},"W7214996325",[543,545],{"name":544,"orcid":9},"Deendayal .",{"name":546,"orcid":547},"Om Prakash","https:\u002F\u002Forcid.org\u002F0000-0003-1239-445X",{"tldr":549,"method":550,"finding":551,"direction":84,"opportunity":552},"基于Sentinel-2和GIS分析印度拉贾斯坦邦干旱区2017-2024年土地利用\u002F覆盖变化。","Sentinel-2 10m影像与GIS分类，采用分类后比较法检测LULC变化。","荒地减少52.21 km²，农业增加86.62 km²，建设用地翻倍，水资源面积小。","可结合多源遥感与机器学习，在数据稀疏干旱区开展高精度LULC动态监测与驱动机制研究。","2026-10-01T23:30:29.277138Z"]