[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1638":3,"related-1638":80},{"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":30,"classification":31,"search_phrases":54,"slug":57,"view_count":58,"doi":59,"paper":60,"created_at":79},1638,"Forest fire burned area extraction and evaluation of post-fire ecological restoration based on remote sensing technology","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffenvs.2026.1882685","Forest fires are a major threat to the ecosystem stability in the face of a growing global climate change; however, long-term post-fire recovery quantitative assessment is methodologically limited in mountainous terrain. In this study, OTSU-optimized differenced Normalized Burn Ratio (dNBR) thresholds were integrated with multi-temporal Remote Sensing Ecological Index (RSEI) model to systematically investigate the extent of burned area, classification of burn severity and spatiotemporal patterns of post-fire ecological recovery for the representative wildfire event, the 3.30 Lushan fire (March 2020) in Xichang City, China. Results indicated that there were 28.26 km 2 of burned area, and the OTSU-derived dNBR classification thresholds of 0.18\u002F0.30\u002F0.42 effectively discriminated low, moderate and high-severity burn areas in the Lushan fire. The RSEI dropped from 0.69 (pre-fire) to 0.33 (post-fire) for an overall decrease in ecological quality of 52.2%. The recovery trajectory unfolded in three phases: rapid recovery in the initial phase with the mean RSEI reaching 0.47 in 2021; decelerated recovery in the second phase, where the RSEI slightly decreased to 0.45 in 2022; and the third phase of accelerated recovery to 0.56 in 2023, and then stabilized at 0.55 in 2024. The Good and Excellent grades recovered to just 37.2% (11.26 km 2 ) by 2024, suggesting that ecological restoration is not yet complete. There were significant differences in the post-fire ecological recovery rates in different burn severity areas. Specifically, increasing burn severity promotes the rate of ecological recovery. These findings show that ecological restoration in highly complex mountainous environments requires longer than the four-year observation period to achieve full restoration, especially in the high severity burn areas. This study confirms the applicability of the integrated dNBR–RSEI assessment framework, and offers a scientific basis and theoretical support for post-fire ecological restoration planning in mountainous Southwestern China.","森林火灾在全球气候变化日益加剧的背景下，对生态系统稳定性构成重大威胁；然而，在地形复杂的山区，火灾后长期恢复的定量评估在方法上仍存在局限。本研究将OTSU优化的差分归一化燃烧指数（dNBR）阈值与多时相遥感生态指数（RSEI）模型相结合，系统研究了代表性野火事件——中国西昌市“3·30”泸山火灾（2020年3月）的过火面积、燃烧严重程度分级及火灾后生态恢复的时空格局。结果表明：过火面积为28.26 km²，基于OTSU的dNBR分级阈值0.18\u002F0.30\u002F0.42能有效区分泸山火灾中的轻度、中度和重度燃烧区域。RSEI从火灾前的0.69降至火灾后的0.33，生态质量总体下降52.2%。恢复轨迹呈现三个阶段：初期快速恢复阶段，2021年平均RSEI达到0.47；第二阶段恢复减速，2022年RSEI略微下降至0.45；第三阶段恢复加速，2023年升至0.56，随后在2024年稳定于0.55。截至2024年，良和优等级面积仅恢复到37.2%（11.26 km²），表明生态恢复尚未完成。不同燃烧严重程度区域的火灾后生态恢复速率存在显著差异。具体而言，燃烧严重程度的增加促进了生态恢复速率。这些发现表明，在高度复杂的山地环境中，生态恢复需要超过四年的观测期才能实现完全恢复，尤其是在重度燃烧区域。本研究证实了dNBR–RSEI综合评估框架的适用性，并为中国西南山区火灾后生态恢复规划提供了科学依据和理论支持。",null,"Frontiers in Environmental Science","2026-09-03T00:00:00Z","论文",10,false,69,{"impact":17,"substance":18,"depth":19,"authority":17,"freshness":20,"relevant":21,"comment":22},12,20,18,7,1,"研究提出集成dNBR与RSEI的评估框架，为山地森林火灾后生态恢复提供科学依据，对农业生态遥感有参考价值。",[24],{"name":10,"url":6},[26,27,28,29],"农业遥感","遥感监测","森林火灾","生态恢复",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":35},"needs_review","2026-10-22.2","rules",{"candidates":36,"agricultural_evidence":14,"reason":53},[37,46],{"code":38,"score":39,"supported":40,"title":41,"abstract":43,"tags":45},"I3",16,true,[42],"remote sensing",[44,42],"遥感",[26,27],{"code":47,"score":20,"supported":40,"title":48,"abstract":49,"tags":52},"H7",[],[50,51],"气候变化","climate change",[28],"农业相关性需要复核",[55,56],"农业遥感 森林火灾 生态恢复 遥感监测","农业遥感 森林火灾","农业遥感森林火灾生态恢复遥感监测-1638",2,"10.3389\u002Ffenvs.2026.1882685",{"doi":59,"openalex_id":61,"authors":62,"venue":10,"cited_by_count":70,"oa_url":71,"card":72,"direction":76,"ingested_from":78},"W7207710349",[63,65,67],{"name":64,"orcid":9},"Chuan Luo",{"name":66,"orcid":9},"Xin Su",{"name":68,"orcid":69},"Haitao Li","https:\u002F\u002Forcid.org\u002F0000-0001-5322-5375",0,"https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fenvironmental-science\u002Farticles\u002F10.3389\u002Ffenvs.2026.1882685\u002Fpdf",{"tldr":73,"method":74,"finding":75,"direction":76,"opportunity":77},"结合dNBR与RSEI评估森林火灾过火面积及恢复动态，发现四年未完全恢复。","OTSU优化的dNBR阈值与多时相RSEI模型结合，分析火灾前后生态质量。","过火面积28.26km²，生态质量下降52.2%，恢复分三阶段，高烈度区恢复更快但四年未完全恢复。","农业遥感与作物表型","可延伸研究不同植被类型和地形下的长期恢复阈值，以及气候因子对恢复速率的影响，建立预测模型。","openalex","2026-09-04T23:30:32.157199Z",{"total":81,"page":21,"page_size":81,"items":82},6,[83,157,218,282,351,405],{"id":84,"title":85,"url":86,"summary":87,"summary_zh":88,"content":9,"source_name":89,"source_url":86,"published_at":90,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":91,"score_detail":92,"sources":98,"tags":100,"primary_topic":9,"secondary_topics":104,"classification":105,"search_phrases":127,"slug":130,"view_count":21,"doi":131,"paper":132,"created_at":156},5012,"Evaluating Multi-Index Remote Sensing Frameworks for Drought Monitoring in Seasonally Dry Dipterocarp Deciduous Forests: A Case Study of Yok Don National Park, Vietnam","https:\u002F\u002Fdoi.org\u002F10.5755\u002Fj01.erem.82.3.44241","This study examined the effectiveness of the normalized difference vegetation index (NDVI), land surface temperature (LST), and their integrated indices in capturing dry-season drought dynamics in the dipterocarp deciduous forest ecosystems of Yok Don National Park from 2014 to 2024. Results indicate that individual remote-sensing indices captured drought processes but reflected different dimensions of drought conditions, with NDVI indicating canopy greenness and LST detecting early thermal stress. Integrated indices partially mitigated the limitations of single indicators during confirmed drought years by showing stronger correlations with reference data. The effectiveness of the integrated indices varied significantly depending on the integration framework. The spatial-normalization–based integration of NDVI and LST showed consistently strong correlations with surface evapotranspiration (ET), with correlation coefficients of approximately 0.8 across years, and was less sensitive to land-cover heterogeneity. In contrast, the triangular NDVI–LST space integration exhibited variable relationships with ET due to its sensitivity to edge definition and phenological shifts in dipterocarp deciduous forests. Phase-dependent behavior was observed, with integrated indices maintaining more stable relationships with ET during drying periods, while NDVI showed greater sensitivity under wetter conditions. The results also indicate that VHI demonstrated a more robust and stable performance than TVDI, suggesting its suitability as a primary indicator in heterogeneous forest environments. These findings provide practical guidance for drought monitoring in heterogeneous forest landscapes by identifying adaptive integration strategies tailored to different hydroclimatic conditions.","本研究考察了归一化差异植被指数（NDVI）、地表温度（LST）及其综合指数在捕捉2014至2024年 Yok Don 国家公园龙脑香落叶林生态系统旱季干旱动态方面的有效性。结果表明，单一遥感指数能够捕捉干旱过程，但反映的是干旱状况的不同维度，其中NDVI指示冠层绿度，LST探测早期热胁迫。综合指数在已确认的干旱年份中通过与参考数据表现出更强的相关性，部分缓解了单一指标的局限性。综合指数的有效性因集成框架的不同而差异显著。基于空间标准化的NDVI与LST集成与地表蒸散发（ET）表现出持续较强的相关性，各年份相关系数约为0.8，且对土地覆盖异质性较不敏感。相比之下，三角NDVI–LST空间集成与ET的关系多变，这是由于其边缘定义及龙脑香落叶林物候变化较为敏感。研究观察到相位依赖行为，综合指数在干旱期与ET保持更稳定的关系，而NDVI在较湿润条件下表现出更高的敏感性。结果还表明，VHI比TVDI表现出更稳健和稳定的性能，表明其适合作为异质森林环境中的主要指标。这些发现通过识别适应不同水文气候条件的自适应集成策略，为异质森林景观的干旱监测提供了实践指导。","Environmental Research Engineering and Management","2026-10-13T00:00:00Z",67,{"impact":93,"substance":18,"depth":94,"authority":95,"freshness":96,"relevant":21,"comment":97},8,17,13,9,"越南干旱区遥感监测方法学研究，方法新颖数据扎实，对农业遥感干旱监测有参考价值，但属区域性案例，公共影响有限。",[99],{"name":89,"url":86},[26,101,27,102,103],"NDVI","干旱监测","森林生态",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":106},{"candidates":107,"agricultural_evidence":14,"reason":53},[108,115,120],{"code":47,"score":109,"supported":40,"title":110,"abstract":112,"tags":114},15,[111],"drought",[113,111],"干旱",[102],{"code":38,"score":116,"supported":40,"title":117,"abstract":118,"tags":119},14,[42],[44],[101,26,27],{"code":121,"score":81,"supported":40,"title":122,"abstract":123,"tags":126},"H3",[],[124,125],"蒸散发","evapotranspiration",[],[128,129],"Yok Don 国家公园 遥感 干旱","NDVI LST 干旱监测 森林","YokDon国家公园遥感干旱-5012","10.5755\u002Fj01.erem.82.3.44241",{"doi":131,"openalex_id":133,"authors":134,"venue":89,"cited_by_count":70,"oa_url":150,"card":151,"direction":76,"ingested_from":78},"W7221717828",[135,138,141,143,145,147],{"name":136,"orcid":137},"Mai Son Le","https:\u002F\u002Forcid.org\u002F0000-0002-5360-7119",{"name":139,"orcid":140},"Ha Thu Nguyen","https:\u002F\u002Forcid.org\u002F0000-0002-4490-308X",{"name":142,"orcid":9},"Hung Manh Nguyen",{"name":144,"orcid":9},"Huy Xuan Chu",{"name":146,"orcid":9},"Hoa Thanh Nguyen",{"name":148,"orcid":149},"Duy-Toan Dao","https:\u002F\u002Forcid.org\u002F0009-0003-6057-4436","https:\u002F\u002Ferem.ktu.lt\u002Findex.php\u002Ferem\u002Farticle\u002Fdownload\u002F44241\u002F23724",{"tldr":152,"method":153,"finding":154,"direction":76,"opportunity":155},"评估NDVI、LST及其集成指数在越南干旱季风落叶林干旱监测中的效果。","利用2014-2024年NDVI、LST遥感数据，构建空间归一化和三角空间集成指","空间归一化集成指数与ET相关性稳定（约0.8），VHI比TVDI更稳健，集成效果依赖框架。","可探索自适应集成框架在不同水热条件和异质景观下的干旱监测普适性。","2026-10-15T23:30:32.336137Z",{"id":158,"title":159,"url":160,"summary":161,"summary_zh":162,"content":9,"source_name":163,"source_url":160,"published_at":164,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":165,"score_detail":166,"sources":169,"tags":171,"primary_topic":9,"secondary_topics":175,"classification":176,"search_phrases":194,"slug":197,"view_count":70,"doi":198,"paper":199,"created_at":217},4823,"Comparing Sentinel-2 Spectral Indices for Mapping Forest Fire Damage in Pollino National Park, Italy","https:\u002F\u002Fdoi.org\u002F10.5194\u002Fisprs-archives-xlviii-m-13-2026-1-2026","In recent years, climate change has significantly increased the severity and frequency of wildfires across Europe, with the 2025 season marking an unprecedented peak of one million hectares burned. Rapid and cost-effective mapping of these damaged areas is crucial for environmental recovery, making satellite remote sensing an indispensable tool. This study evaluates and compares the performance of four Sentinel-2 spectral burn indices for mapping forest fire damage within the Pollino National Park (Italy) occurred in September 2025, an area severely affected by the devastating summer fires of 2025. The analyzed indices include the Normalized Burn Ratio (NBR), Normalized Burn Ratio Plus (NBR+), Normalized Burn Ratio Short Wave Infrared (NBR-SWIR), and Normalized Difference Short Wave Infrared (ND-SWIR). An image differencing technique was applied to pre-fire (June 7, 2025) and post-fire (November 14, 2025) datasets, followed by a supervised Maximum Likelihood classification to map burned and unburned classes. Accuracy assessment via confusion matrices showed that NBR and NBR+ delivered the highest performance, achieving an Overall Accuracy (OA) of 0.976 and 0.974, respectively. ND-SWIR performed closely at 0.966, whereas NBR-SWIR yielded a lower OA of 0.873 due to the misclassification of bare soil transitions as burned areas. These findings highlight the critical role of specific SWIR-band combinations in optimizing automated wildfire monitoring systems.","近年来，气候变化显著加剧了欧洲野火的严重程度和发生频率，2025年火灾季烧毁面积达到一百万公顷，创下历史新高。快速且经济高效地绘制这些受损区域对于环境恢复至关重要，使卫星遥感成为不可或缺的工具。本研究评估并比较了四种哨兵2号（Sentinel-2）光谱燃烧指数在绘制2025年9月发生于意大利波利诺国家公园（Pollino National Park）的森林火灾损害中的表现，该地区受2025年夏季毁灭性火灾的严重影响。所分析的指数包括归一化燃烧比率（NBR）、归一化燃烧比率增强版（NBR+）、归一化燃烧比率短波红外（NBR-SWIR）以及归一化差值短波红外（ND-SWIR）。研究对火灾前（2025年6月7日）和火灾后（2025年11月14日）数据集应用了图像差值技术，随后采用监督最大似然分类法绘制燃烧与未燃烧类别。通过混淆矩阵进行的精度评估表明，NBR和NBR+表现最佳，总体精度（OA）分别达到0.976和0.974。ND-SWIR紧随其后，为0.966，而NBR-SWIR由于将裸土转变误分类为燃烧区域，总体精度较低，为0.873。这些发现凸显了特定短波红外波段组合在优化自动化野火监测系统中的关键作用。","˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences\u002FInternational archives of the photogrammetry, remote sensing and spatial information sciences","2026-10-12T00:00:00Z",74,{"impact":17,"substance":167,"depth":19,"authority":95,"freshness":96,"relevant":21,"comment":168},22,"方法对比扎实、结论明确，但属区域案例研究，对农业信息化有间接参考价值，可入精选但非必选。",[170],{"name":163,"url":160},[172,27,173,28,174],"Sentinel-2","灾害评估","植被指数",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":177},{"candidates":178,"agricultural_evidence":14,"reason":53},[179,183,187],{"code":38,"score":96,"supported":40,"title":180,"abstract":181,"tags":182},[],[44,42],[172,174,27],{"code":47,"score":93,"supported":40,"title":184,"abstract":185,"tags":186},[],[50,51],[28,173],{"code":188,"score":189,"supported":40,"title":190,"abstract":191,"tags":193},"H2",3,[],[192],"soil",[],[195,196],"Sentinel-2 森林火灾 遥感","Pollino 国家公园 火烧迹地","Sentinel-2森林火灾遥感-4823","10.5194\u002Fisprs-archives-xlviii-m-13-2026-1-2026",{"doi":198,"openalex_id":200,"authors":201,"venue":163,"cited_by_count":70,"oa_url":211,"card":212,"direction":76,"ingested_from":78},"W7221528348",[202,204,206,209],{"name":203,"orcid":9},"Giuseppina Costanzo",{"name":205,"orcid":9},"Gianluigi Ferrara",{"name":207,"orcid":208},"Claudio Parente","https:\u002F\u002Forcid.org\u002F0000-0002-8328-9764",{"name":210,"orcid":9},"Vincenzo Verde","https:\u002F\u002Fisprs-archives.copernicus.org\u002Farticles\u002FXLVIII-M-13-2026\u002F1\u002F2026\u002Fisprs-archives-XLVIII-M-13-2026-1-2026.pdf",{"tldr":213,"method":214,"finding":215,"direction":76,"opportunity":216},"比较四种 Sentinel-2 光谱指数在意大利 Pollino 国家公园 2025 年林火损伤制图","Sentinel-2 火前火后影像差值 + 最大似然监督分类，用混淆矩阵评估四种","NBR 与 NBR+ 精度最高（OA 0.976、0.974），NBR-SWIR 因裸土误判仅 0.","可探索多指数融合与机器学习分类器，提升复杂地表下火烧迹地自动制图鲁棒性。","2026-10-13T23:30:23.838067Z",{"id":219,"title":220,"url":221,"summary":222,"summary_zh":223,"content":9,"source_name":224,"source_url":221,"published_at":225,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":226,"score_detail":227,"sources":229,"tags":231,"primary_topic":235,"secondary_topics":240,"classification":241,"search_phrases":260,"slug":263,"view_count":58,"doi":264,"paper":265,"created_at":281},4588,"Integrating terrestrial and marine remote sensing indicators to estimate subnational economic output","https:\u002F\u002Fdoi.org\u002F10.1080\u002F01431161.2026.2743115","Subnational economic data remain scarce across much of the Global South, particularly in fragmented island and coastal geographies, thereby constraining the capacity of researchers and policymakers to monitor local economic conditions. This study proposes and empirically evaluates a four-proxy remote sensing framework for subnational gross domestic product (GDP) estimation. The framework extends the established Night-time Lights (NTL)–Normalised Difference Vegetation Index (NDVI)–Forest Loss (FL) approach by incorporating sea surface Chlorophyll-a (CHLA) as a marine fisheries proxy. This achieves full proxy coverage across the non-agriculture, forestry, and fisheries sector through NTL, agriculture through NDVI, forestry through FL, and marine fisheries through CHLA. The empirical analysis employs Multiscale Geographically Weighted Regression (MGWR) and pooled ordinary least squares (OLS) across 102 regencies and cities in Sulawesi and Maluku, eastern Indonesia, over 2015–2024, with a province-level panel extending to 2002–2024. The stepwise MGWR R2 rises from 0.468 (NTL only) to 0.543 (NTL, NDVI, and FL) to 0.561 (full model), with a pooled Pearson correlation of 0.760. CHLA is positive and significant at both spatial scales after conditioning on all terrestrial proxies, confirmed by OLS coefficients of 0.029 at the regency\u002Fcity level and 0.148 at the province level, significant at the 0.1% and 1% levels respectively. All proxy relationships replicate in direction and significance across scales and over the 23-year panel. The framework provides a freely replicable tool for subnational economic monitoring in data-scarce coastal and island settings, with direct applicability to marine-dependent primary sector economies globally.","在全球南方的大部分地区，尤其是碎片化的岛屿和沿海地理区域，地方经济数据仍然稀缺，从而制约了研究者和政策制定者监测地方经济状况的能力。本研究提出并实证评估了一个用于地方国内生产总值（GDP）估算的四代理变量遥感框架。该框架在已有的夜间灯光（NTL）—归一化植被指数（NDVI）—森林损失（FL）方法基础上，引入海表叶绿素a（CHLA）作为海洋渔业代理变量。由此实现了对非农、林业和渔业部门的代理变量全覆盖：NTL对应非农部门，NDVI对应农业，FL对应林业，CHLA对应海洋渔业。实证分析采用多尺度地理加权回归（MGWR）和混合普通最小二乘法（OLS），覆盖印度尼西亚东部苏拉威西和马鲁古的102个县和市，时间范围为2015—2024年，并辅以延伸至2002—2024年的省级面板数据。逐步MGWR的R²从0.468（仅NTL）升至0.543（NTL、NDVI和FL）再升至0.561（全模型），混合皮尔逊相关系数为0.760。在控制所有陆地代理变量后，CHLA在两个空间尺度上均为正向且显著，OLS系数在县\u002F市级为0.029、省级为0.148，分别在0.1%和1%水平上显著。所有代理变量关系在不同尺度和23年面板期间在方向和显著性上均得到重复验证。该框架为数据稀缺的沿海和岛屿地区的地方经济监测提供了一个可自由复制的工具，并可直接适用于全球依赖海洋的初级产业经济体。","International Journal of Remote Sensing","2026-10-09T00:00:00Z",81,{"impact":19,"substance":167,"depth":19,"authority":116,"freshness":96,"relevant":21,"comment":228},"将叶绿素a纳入遥感代理框架估算次国家级GDP，方法新颖、数据扎实，对数据稀缺沿海岛屿地区的农业与渔业经济监测有直接参考价值。",[230],{"name":224,"url":221},[232,26,27,233,234],"数字乡村","渔业经济","GDP估算",{"code":38,"slug":236,"name":237,"path":238,"parent_code":239},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[],{"status":242,"locked":14,"version":33,"method":34,"evidence":243},"classified",{"candidates":244,"agricultural_evidence":40},[245,249,255],{"code":38,"score":39,"supported":40,"title":246,"abstract":247,"tags":248},[42],[44,42],[26,27],{"code":250,"score":189,"supported":40,"title":251,"abstract":252,"tags":254},"D",[],[253],"渔业",[],{"code":256,"score":21,"supported":14,"title":257,"abstract":258,"tags":259},"I6",[],[],[232],[261,262],"苏拉威西 马鲁古 遥感 GDP","叶绿素a 海洋渔业 遥感","苏拉威西马鲁古遥感GDP-4588","10.1080\u002F01431161.2026.2743115",{"doi":264,"openalex_id":266,"authors":267,"venue":224,"cited_by_count":70,"oa_url":9,"card":276,"direction":76,"ingested_from":78},"W7221189467",[268,271,273],{"name":269,"orcid":270},"Laurenz Thiele","https:\u002F\u002Forcid.org\u002F0009-0009-9294-1337",{"name":272,"orcid":9},"Amanus Khalifafilardy Yunus",{"name":274,"orcid":275},"Rahmatia","https:\u002F\u002Forcid.org\u002F0009-0009-7550-9243",{"tldr":277,"method":278,"finding":279,"direction":76,"opportunity":280},"提出融合陆地与海洋遥感指标的四代理框架，估算印尼东部次国家级GDP。","用夜间灯光、NDVI、森林损失与叶绿素a，结合MGWR和OLS分析102个县市。","加入叶绿素a后模型R²从0.543升至0.561，海洋渔业代理显著提升经济估算精度。","可将海洋遥感代理拓展至其他沿海地区，并耦合渔业产量与贸易数据验证经济监测普适性。","2026-10-10T23:30:28.117529Z",{"id":283,"title":284,"url":285,"summary":286,"summary_zh":287,"content":9,"source_name":288,"source_url":285,"published_at":225,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":289,"score_detail":290,"sources":292,"tags":294,"primary_topic":9,"secondary_topics":298,"classification":299,"search_phrases":329,"slug":332,"view_count":70,"doi":333,"paper":334,"created_at":350},4584,"Farmland Transformation Reshapes Ecosystem Services Through Multi-Level Landscape Reconfiguration: Evidence from China’s Songnen Plain","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fagriculture16202188","Global agricultural expansion has profoundly reshaped terrestrial landscapes, yet the ecological consequences of farmland transformation across multiple spatial scales remain insufficiently understood. This study investigates how farmland dynamics influence ecosystem service (ES) provision in China’s Songnen Plain by integrating long-term land-use trajectories, remote sensing data, and landscape ecological analysis. Using annual 30 m land-use\u002Fland-cover datasets from 2000 to 2020, we identified diverse farmland transformation pathways, including stable cultivation, reclamation, abandonment, fallow, afforestation, and urban encroachment. The InVEST model was applied to quantify three key ecosystem services: food supply, soil conservation, and carbon storage, while grid-level Partial Least Squares Regression (PLSR) was employed to identify their major drivers. Results revealed substantial spatial and temporal heterogeneity in ecosystem services. Food supply and soil conservation generally increased during the study period, whereas carbon storage exhibited a declining trend. Landscape-level characteristics, particularly Shannon diversity index (SHDI), aggregation index (AI), and patch density (PD), were identified as dominant factors regulating ecosystem service variation. Class-level indicators, including farmland area (FA) and mean patch area (MPA), also showed significant but comparatively weaker effects. This study provides new insights into the ecological consequences of intensive farmland transformation and highlights the importance of optimizing multi-scale landscape configurations to balance agricultural production and ecosystem sustainability.","全球农业扩张深刻重塑了陆地景观格局，但农田转型在多个空间尺度上的生态效应仍缺乏充分认识。本研究通过整合长期土地利用轨迹、遥感数据和景观生态分析，探讨了农田动态如何影响中国松嫩平原的生态系统服务（ES）供给。基于2000—2020年逐年30 m土地利用\u002F土地覆盖数据集，我们识别了多种农田转型路径，包括稳定耕作、开垦、撂荒、休耕、退耕还林和城市侵占。应用InVEST模型量化了粮食供给、土壤保持和碳储量三项关键生态系统服务，并采用格网级偏最小二乘回归（PLSR）识别其主要驱动因子。结果表明，生态系统服务存在显著的空间和时间异质性。粮食供给和土壤保持总体上在研究期间呈增加趋势，而碳储量则表现出下降趋势。景观尺度特征，特别是香农多样性指数（SHDI）、聚集度指数（AI）和斑块密度（PD），被识别为调控生态系统服务变化的主导因子。类型尺度指标，包括农田面积（FA）和平均斑块面积（MPA），也表现出显著但相对较弱的影响。本研究为集约化农田转型的生态后果提供了新见解，并强调了优化多尺度景观格局以平衡农业生产与生态系统可持续性的重要性。","Agriculture",79,{"impact":19,"substance":167,"depth":19,"authority":95,"freshness":93,"relevant":21,"comment":291},"基于2000—2020年30米土地利用数据与InVEST模型，揭示松嫩平原农田转型对生态系统服务的多尺度影响，方法与数据扎实，对黑土地保护与农业可持续布局有参考价值。",[293],{"name":288,"url":285},[26,295,27,296,297],"黑土地保护","土地利用","生态系统服务",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":300},{"candidates":301,"agricultural_evidence":40,"reason":328},[302,308,312,317,323],{"code":303,"score":93,"supported":40,"title":304,"abstract":305,"tags":307},"H6",[],[297,306],"ecosystem service",[296,297],{"code":38,"score":93,"supported":40,"title":309,"abstract":310,"tags":311},[],[44,42],[26,27],{"code":188,"score":81,"supported":40,"title":313,"abstract":314,"tags":316},[],[315,192],"土壤",[],{"code":318,"score":189,"supported":40,"title":319,"abstract":320,"tags":322},"J3",[],[321],"全球农业",[],{"code":324,"score":21,"supported":14,"title":325,"abstract":326,"tags":327},"H1",[],[],[295],"多个产业证据相当，需要确认主归属",[330,331],"松嫩平原 农田转型 生态系统服务","InVEST模型 碳储量 土壤保持","松嫩平原农田转型生态系统服务-4584","10.3390\u002Fagriculture16202188",{"doi":333,"openalex_id":335,"authors":336,"venue":288,"cited_by_count":70,"oa_url":285,"card":344,"direction":76,"ingested_from":78},"W7221099965",[337,339,342],{"name":338,"orcid":9},"Ruhao Xue",{"name":340,"orcid":341},"Bonoua Faye","https:\u002F\u002Forcid.org\u002F0000-0003-4465-6792",{"name":343,"orcid":9},"Hu Xie",{"tldr":345,"method":346,"finding":347,"direction":348,"opportunity":349},"基于松嫩平原2000-2020年土地利用数据，揭示耕地转型通过多尺度景观格局重塑生态系统服务。","30米土地利用数据、InVEST模型与网格级偏最小二乘回归（PLSR）。","食物供给与土壤保持增加而碳储量下降，景观格局指数是主导驱动因子。","农业绿色发展与碳","可探究不同耕地转型路径对碳储量的非线性影响及多尺度景观优化配置阈值。","2026-10-10T23:30:27.812095Z",{"id":352,"title":353,"url":354,"summary":355,"summary_zh":356,"content":9,"source_name":357,"source_url":354,"published_at":358,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":359,"score_detail":360,"sources":362,"tags":364,"primary_topic":9,"secondary_topics":367,"classification":368,"search_phrases":381,"slug":384,"view_count":58,"doi":385,"paper":386,"created_at":404},4368,"Dinâmica de supressão e recuperação florestal por meio do índice NDVI: um estudo de caso em Realeza – PR (2016 - 2026)","https:\u002F\u002Fdoi.org\u002F10.4025\u002Fbolgeogr.v44.a2026.e83759","O constante avanço agropecuário sobre o bioma da Mata Atlântica exige um monitoramento contínuo da integridade ecológica dos remanescentes florestais locais. Este estudo avaliou a dinâmica espaço-temporal da cobertura florestal no município de Realeza-PR, entre os anos de 2016 e 2026, quantificando as taxas de supressão e ganho florestal analisando a influência do relevo e da fragmentação na paisagem. A metodologia aplicada baseou-se em séries temporais orbitais do sensor Sentinel-2 (MSI), com a calibração de limiares locais do índice NDVI ( e ) para diferenciar a floresta nativa estável da agricultura sazonal. A declividade foi extraída a partir do Modelo Digital de Elevação ALOS PALSAR, submetido à compatibilização matricial via software GDAL e ao cálculo subsequente de métricas de paisagem, realizados em ambiente R. Os resultados obtidos apontaram um ganho líquido total de 775,81 hectares na cobertura florestal durante a década analisada. Apesar do saldo quantitativo positivo, as métricas estruturais registraram um aumento de 8,79% no Número de Manchas (NP) e uma queda de 1,14 pontos percentuais no Índice de Agregação (AI). Desse modo, conclui-se que o ganho absoluto de área florestal mascarou um processo contínuo de retalhamento e fragmentação dos corredores ecológicos, comprometendo a qualidade e a resiliência ecológica da paisagem a longo prazo.","农业活动对马塔大西洋森林生物群落的持续扩张，要求对当地森林残余的生态完整性进行持续监测。本研究评估了雷阿莱扎市（巴拉那州）2016年至2026年间森林覆盖的时空动态，量化了森林抑制与增益速率，并分析了地形和破碎化对景观的影响。所采用的方法基于Sentinel-2（MSI）传感器的轨道时间序列，通过校准NDVI指数的局部阈值（和）以区分稳定原生林与季节性农业。坡度数据提取自ALOS PALSAR数字高程模型，经GDAL软件进行矩阵兼容化处理，随后在R环境中计算景观指标。结果表明，在分析的十年间，森林覆盖净增总面积达775.81公顷。尽管数量上呈正平衡，但结构指标显示斑块数量（NP）增加了8.79%，聚集度指数（AI）下降了1.14个百分点。因此，结论是森林面积的绝对增益掩盖了生态廊道持续被切割和破碎化的过程，损害了景观的长期质量和生态韧性。","Boletim de Geografia","2026-10-04T00:00:00Z",66,{"impact":93,"substance":18,"depth":94,"authority":17,"freshness":96,"relevant":21,"comment":361},"基于Sentinel-2与NDVI的十年森林动态监测案例，方法扎实、数据具体，但属地方性研究，公共影响有限。",[363],{"name":357,"url":354},[26,101,365,27,366],"生态保护","森林覆盖",[],{"status":369,"locked":14,"version":33,"method":34,"evidence":370},"unclassified",{"candidates":371,"agricultural_evidence":40,"reason":380},[372,376],{"code":38,"score":189,"supported":14,"title":373,"abstract":374,"tags":375},[],[],[101,26,27],{"code":303,"score":21,"supported":14,"title":377,"abstract":378,"tags":379},[],[],[365],"缺少足够的主题证据",[382,383],"Realeza PR NDVI 森林","Sentinel-2 森林覆盖 监测","RealezaPRNDVI森林-4368","10.4025\u002Fbolgeogr.v44.a2026.e83759",{"doi":385,"openalex_id":387,"authors":388,"venue":357,"cited_by_count":70,"oa_url":398,"card":399,"direction":76,"ingested_from":78},"W7220453253",[389,392,395],{"name":390,"orcid":391},"Marcos Henrique Tomazini Mikoanski","https:\u002F\u002Forcid.org\u002F0000-0003-0715-0581",{"name":393,"orcid":394},"Francieli Alves Teixeira","https:\u002F\u002Forcid.org\u002F0009-0000-0055-9718",{"name":396,"orcid":397},"Fernando César Manosso","https:\u002F\u002Forcid.org\u002F0000-0003-2568-7403","https:\u002F\u002Fperiodicos.uem.br\u002Fojs\u002Findex.php\u002FBolGeogr\u002Farticle\u002Fdownload\u002F83759\u002F751375163932",{"tldr":400,"method":401,"finding":402,"direction":76,"opportunity":403},"基于Sentinel-2 NDVI时序评估2016-2026年Realeza-PR森林消长与破碎化动","Sentinel-2 NDVI阈值校准、ALOS PALSAR坡度、R景观指标分","森林净增775.81公顷，但斑块数增8.79%、聚集度降1.14%，破碎化加剧。","可结合多源遥感与景观连通性模型，探究农业扩张下森林恢复的生态质量与廊道功能。","2026-10-07T23:30:30.363166Z",{"id":406,"title":407,"url":408,"summary":409,"summary_zh":410,"content":9,"source_name":411,"source_url":408,"published_at":412,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":226,"score_detail":413,"sources":415,"tags":417,"primary_topic":421,"secondary_topics":427,"classification":428,"search_phrases":450,"slug":453,"view_count":189,"doi":454,"paper":455,"created_at":475},3987,"Spatio-temporal diagnosis of land fragmentation in the Yellow River Basin: providing a basis for comprehensive land improvement","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agsy.2026.104971","CONTEXT Land fragmentation (LF) poses a major challenge to sustainable land management, land consolidation, and agricultural productivity, especially in ecologically sensitive and strategically important regions such as the Yellow River Basin (YRB) in China. This area faces prominent issues such as LF and land degradation during land-resource utilization, underscoring the need for spatially adaptive governance and targeted land consolidation strategies. OBJECTIVE This study aims to systematically examine the spatiotemporal evolution of LF in the YRB from 2000 to 2022, with the goal of identifying regional differentiation patterns and influencing factors. It further seeks to propose tailored land consolidation strategies based on fine-grained spatial assessment and functional zoning, in order to support sustainable land use and national food security. METHODS Landscape pattern indices and profile line analysis were used across five time periods to capture LF dynamics. A composite land fragmentation index (LFI) is developed from six landscape metrics, weighted by the entropy method, enabling high-resolution spatial evaluation at the grid scale. Additionally, a Four-Quadrant Model was applied to classify functional zones for land consolidation, incorporating factors such as elevation, temperature, and GDP. RESULTS AND CONCLUSIONS LF in the YRB exhibits significant regional variation, with lower fragmentation in the upper reaches and higher fragmentation in eastern regions—especially in Shanxi and Shandong provinces. Over 60% of the basin remained stable, and LF was strongly associated with elevation, temperature, and economic activity. Based on these patterns, four functional zones were delineated: dynamic reconstruction, optimization and enhancement, steady-state restoration, and collaborative demonstration areas. Comprehensive policy suggestions are provided for integrated land consolidation aligned with LF characteristics and zonal planning. SIGNIFICANCE This study innovatively developed a scientific and systematic LF evaluation framework from a raster-based perspective. Using this framework, we conducted a precise quantitative analysis of the dynamic LF process and explored the mechanisms and impacts of various factors such as policy direction, natural environmental conditions, and socioeconomic factors on LF. Based on the LF findings, this study proposes a comprehensive and feasible land consolidation plan, providing solid, reliable data support for the plan's rationale and scientific foundation. The results are of significant theoretical and practical value for optimizing land resource allocation, enhancing land use efficiency, and promoting regional sustainable development.","背景 土地细碎化（LF）是可持续土地管理、土地整治和农业生产率面临的重大挑战，尤其是在黄河 basin（YRB）等生态敏感且具有战略重要性的地区。该区域在土地资源利用过程中面临土地细碎化和土地退化等突出问题，凸显了空间适应性治理和针对性土地整治策略的必要性。 目标 本研究旨在系统考察2000年至2022年黄河流域土地细碎化的时空演变，以识别区域分异格局及其影响因素。研究进一步寻求基于精细化空间评估和功能分区提出有针对性的土地整治策略，以支持可持续土地利用和国家粮食安全。 方法 采用景观格局指数和剖面线分析，涵盖五个时期，以刻画土地细碎化动态。基于六个景观指标构建综合土地细碎化指数（LFI），并采用熵权法赋权，从而实现网格尺度上的高分辨率空间评估。此外，应用四象限模型对土地整治功能区进行分类，纳入海拔、气温和GDP等因素。 结果与结论 黄河流域土地细碎化表现出显著的区域差异，上游细碎化程度较低，东部地区细碎化程度较高，尤其是山西和山东两省。超过60%的流域保持稳定，土地细碎化与海拔、气温和经济活动密切相关。基于这些格局，划定了四类功能区：动态重构区、优化提升区、稳态修复区和协同示范区。并提出了与土地细碎化特征和分区规划相一致的综合土地整治政策建议。 意义 本研究创新性地从栅格视角构建了科学、系统的土地细碎化评价框架。利用该框架，我们对土地细碎化动态过程进行了精确的定量分析，并探讨了政策导向、自然环境条件和社会经济因素等多种因素对土地细碎化的作用机制及影响。基于土地细碎化研究结果，本研究提出了综合且可行的土地整治方案，为","Agricultural Systems","2026-10-01T00:00:00Z",{"impact":19,"substance":167,"depth":19,"authority":116,"freshness":96,"relevant":21,"comment":414},"基于栅格尺度构建土地细碎化指数并划分整治功能分区，方法新颖、数据扎实，对黄河流域耕地保护与土地整治有直接参考价值。",[416],{"name":411,"url":408},[26,418,419,27,420],"耕地保护","黄河流域","土地整治",{"code":422,"slug":423,"name":424,"path":425,"parent_code":426},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[],{"status":242,"locked":14,"version":33,"method":34,"evidence":429},{"candidates":430,"agricultural_evidence":40},[431,437,441,445],{"code":422,"score":81,"supported":40,"title":432,"abstract":433,"tags":436},[],[434,435],"粮食安全","food security",[],{"code":324,"score":58,"supported":14,"title":438,"abstract":439,"tags":440},[],[],[420,418],{"code":38,"score":58,"supported":14,"title":442,"abstract":443,"tags":444},[],[],[26,27],{"code":446,"score":21,"supported":14,"title":447,"abstract":448,"tags":449},"G2",[],[],[420],[451,452],"黄河流域 土地细碎化","土地细碎化指数 土地整治","黄河流域土地细碎化-3987","10.1016\u002Fj.agsy.2026.104971",{"doi":454,"openalex_id":456,"authors":457,"venue":411,"cited_by_count":70,"oa_url":408,"card":470,"direction":76,"ingested_from":78},"W7215038160",[458,460,463,465,468],{"name":459,"orcid":9},"Xiaoxu Wei",{"name":461,"orcid":462},"Qiaolin Shu","https:\u002F\u002Forcid.org\u002F0009-0009-9478-6625",{"name":464,"orcid":9},"Wei Wei",{"name":466,"orcid":467},"Binbin Xie","https:\u002F\u002Forcid.org\u002F0000-0003-0224-5485",{"name":469,"orcid":9},"Junju Zhou",{"tldr":471,"method":472,"finding":473,"direction":76,"opportunity":474},"构建栅格尺度土地破碎化指数，诊断黄河流域2000-2022年时空演变并划分整治功能区。","景观格局指数、剖面线分析、熵权法综合指数与四象限模型，结合高程、气温、GDP数据","上游破碎化低、东部山西山东高，超60%区域稳定，破碎化与高程、气温和经济活动强相关。","可将栅格破碎化指数与遥感作物分类、地块边界提取耦合，发展面向智慧农业的田块尺度整治与种植决策模型。","2026-10-02T23:30:06.999389Z"]