[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3894":3,"related-3894":109},{"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":88,"slug":91,"view_count":92,"doi":93,"paper":94,"created_at":108},3894,"Assessment of Spatio-temporal Dynamics of the Remote Sensing Ecological Index (RSEI) based on Landsat 8 Data: A Case Study of Kherson Region, Ukraine (2013–2025)","https:\u002F\u002Fdoi.org\u002F10.36023\u002Fujrs.2026.13.3.310","This scientific paper presents a comprehensive assessment of the spatio-temporal dynamics of the ecological state of the Kherson region from 2013 to 2025, with a particular focus on the consequences of the full-scale military aggression by the Russian Federation. Amidst intensive hostilities, the destruction of critical infrastructure, and global climate challenges, objective geospatial monitoring of the natural environment is a crucial task for documenting damages and forecasting the region's future development.The study is based on the use of modern geographic information systems and remote sensing data. Using the Google Earth Engine cloud computing platform and an archive of multispectral satellite imagery from Landsat 8 OLI\u002FTIRS, the Remote Sensing Ecological Index (RSEI) was calculated. This index comprehensively integrates four key biophysical indicators: greenness (based on the Normalized Difference Vegetation Index, NDVI), wetness (Wet), dryness (based on the Normalized Difference Build-up and Soil Index, NDBSI), and land surface temperature (LST). The application of Principal Component Analysis (PCA) allowed these indicators to be mathematically combined into a single standardized index, where the first principal component (PC1) explains the highest proportion of the total spatial data variance. This indicates that the first principal component (PC1) successfully captures the vast majority of the variance among the four input indicators, which is a basic premise of the RSEI methodology.The results of the cartographic and statistical analyses revealed a sharp, unprecedented deterioration in the ecosystem health of the study region in 2025 compared to retrospective data from previous years. A critical drop in the average RSEI value was established – from 0.381 in the relatively stable year of 2021 to 0.205 in 2025. The spatial assessment demonstrated that the area of territories classified as being in a state of ecological crisis (the «Terrible» category, with an index ranking from 0 to 0.2) more than doubled: from 26% of the region's total area in 2021 to a critical 60% in 2025.The sharp drop in RSEI spatially aligns with the large-scale hydrological transformations caused by the destruction of the Kakhovka Dam; however, this indicator also reflects the synergistic impact of intense hostilities, fires, the cessation of irrigation, and climate anomalies. Kakhovka Dam destruction led to the catastrophic destruction of the hydrographic network, the disappearance of water supply sources for vital agricultural lands, and the disruption of life-support systems in urbanized areas. The only exception against the general backdrop of the ecological catastrophe is the recorded local natural restoration of the old Dnipro riverbed ecosystem, which is gradually returning to its historical state that preceded massive anthropogenic intervention and river regulation in the 1950s.In conclusion, the synergistic impact of continuous large-scale hostilities, the destruction of established ecosystem links, and the exacerbation of global climate change shape an extremely bleak forecast. Further degradation of the soil and vegetation cover and the depletion of water resources create a high risk of transforming a significant part of the Kherson region into a territory unfit for safe living, agriculture, and socio-economic functioning. Disclosure of AI use. In the process of conducting research and preparing the manuscript, the author used the large language model Google Gemini 3 Pro. The tool acted as a technical assistant and consultant at the stages:1. Software development: assistance in writing, debugging and optimizing JavaScript scripts for the Google Earth Engine environment, in particular the implementation of the PCA algorithm.2. Text preparation: providing recommendations on structuring the work, describing the methodology and improving the academic style of presentation.The author carried out a full check of the generated code and text, verified the results obtained and bears sole responsibility for the content of this publication. Data availability and integrity. The JavaScript code for Google Earth Engine developed for this study has been deposited in the Zenodo repository with a reserved DOI to ensure long-term accessibility and reproducibility of the results. The code will be publicly available upon acceptance of the manuscript for publication. The data can be provided by the author upon reasonable request. Conflicts of Interest. The author declares that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements. The author is grateful to the reviewers and editors for their valuable comments, recommendations, and attention to the work.","本文对2013年至2025年赫尔松地区生态状况的时空动态进行了综合评估，尤其关注俄罗斯联邦全面军事侵略所造成的后果。在激烈的敌对行动、关键基础设施的破坏以及全球气候挑战的背景下，对自然环境进行客观的地理空间监测是记录损害和预测该地区未来发展的关键任务。本研究基于现代地理信息系统和遥感数据的应用。利用Google Earth Engine云计算平台和Landsat 8 OLI\u002FTIRS多光谱卫星影像档案，计算了遥感生态指数（RSEI）。该指数综合集成了四个关键生物物理指标：绿度（基于归一化差异植被指数，NDVI）、湿度（Wet）、干度（基于归一化差异建筑与土壤指数，NDBSI）以及地表温度（LST）。主成分分析（PCA）的应用使这些指标能够在数学上组合为一个标准化的单一指数，其中第一主成分（PC1）解释了总空间数据方差的最大比例。这表明第一主成分（PC1）成功捕捉了四个输入指标之间的绝大部分方差，这是RSEI方法论的基本前提。制图与统计分析的结果揭示，与往年回顾性数据相比，2025年研究区域的生态系统健康出现了急剧且前所未有的恶化。研究确定了平均RSEI值的临界下降——从相对稳定的2021年的0.381降至2025年的0.205。空间评估表明，被归类为生态危机状态的领土面积（“极差”类别，指数排名从0到0.2）增加了一倍以上：从2021年占该地区总面积的26%增至2025年临界水平的60%。RSEI的急剧下降在空间上与卡霍夫卡大坝被毁所引发的大规模水文变化相吻合；然而，该指标也反映了激烈敌对行动、火灾、灌溉停止以及气候异常的协同影响。卡霍夫卡大坝被毁导致水文网络的灾难性破坏，",null,"Ukrainian journal of remote sensing","2026-09-30T00:00:00Z","论文",10,false,73,{"impact":17,"substance":18,"depth":19,"authority":17,"freshness":20,"relevant":21,"comment":22},12,22,18,9,1,"基于Landsat 8与Google Earth Engine的RSEI时空动态研究，方法规范、数据翔实，对战争与气候双重压力下的农业生态退化具有实证价值，但属区域案例、与国内三农信息化关联偏弱。",[24],{"name":10,"url":6},[26,27,28,29,30],"NDVI","遥感监测","生态遥感","Landsat 8","乌克兰农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,53,61,68,75,82],{"code":32,"score":45,"supported":46,"title":47,"abstract":49,"tags":52},20,true,[48],"remote sensing",[50,48,51],"遥感","multispectral",[26,28,27],{"code":54,"score":55,"supported":46,"title":56,"abstract":57,"tags":60},"H2",6,[],[58,59],"土壤","soil",[],{"code":62,"score":55,"supported":46,"title":63,"abstract":64,"tags":67},"H3",[],[65,66],"灌溉","irrigation",[],{"code":69,"score":55,"supported":46,"title":70,"abstract":71,"tags":74},"I4",[],[72,73],"地理信息","geographic information",[],{"code":76,"score":77,"supported":46,"title":78,"abstract":79,"tags":81},"H7",3,[],[80],"climate change",[],{"code":83,"score":77,"supported":46,"title":84,"abstract":85,"tags":87},"I2",[],[86],"large language model",[],[89,90],"Kakhovka Dam 生态遥感","乌克兰农业 生态遥感 遥感监测 Landsat 8","KakhovkaDam生态遥感-3894",2,"10.36023\u002Fujrs.2026.13.3.310",{"doi":93,"openalex_id":95,"authors":96,"venue":10,"cited_by_count":100,"oa_url":6,"card":101,"direction":105,"ingested_from":107},"W7214889788",[97],{"name":98,"orcid":99},"Maksym Tymchyshyn","https:\u002F\u002Forcid.org\u002F0000-0003-2966-4794",0,{"tldr":102,"method":103,"finding":104,"direction":105,"opportunity":106},"基于Landsat 8与GEE计算RSEI，评估乌克兰赫尔松地区2013–2025年生态时空变化。","Google Earth Engine + Landsat 8 OLI\u002FTIRS","2025年RSEI均值由2021年0.381降至0.205，生态危机区由26%扩至60%。","农业遥感与作物表型","可将RSEI框架迁移至战乱或灌溉中断农区，结合作物物候验证生态退化对农业生产的传导。","openalex","2026-10-01T23:30:28.551437Z",{"total":55,"page":21,"page_size":55,"items":110},[111,174,251,324,383,445],{"id":112,"title":113,"url":114,"summary":115,"summary_zh":116,"content":9,"source_name":117,"source_url":114,"published_at":118,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":119,"score_detail":120,"sources":125,"tags":127,"primary_topic":131,"secondary_topics":132,"classification":137,"search_phrases":154,"slug":157,"view_count":92,"doi":158,"paper":159,"created_at":173},4365,"An Index-Based Algorithm for Detecting Water Soil Erosion Indicators from Sentinel-2 Multispectral Data and Its Verification on Field Data of Rostov Oblast and Krasnodar Krai","https:\u002F\u002Fdoi.org\u002F10.23947\u002F2587-8999-2026-10-3-49-57","Introduction . The paper presents the development and testing of an index-based algorithm for detecting indicators of soil erosion by water from Sentinel-2 remote sensing data, considered as the first practical stage in constructing a hybrid physics-based mass-transport model with neural-network parameter identification. Materials and Methods . The algorithm relies on joint analysis of time series of the Normalized Difference Vegetation Index (NDVI) and the Bare Soil Index (BSI), followed by spatial change detection (ΔBSI) with threshold filtering at the 90th percentile. The algorithm was first validated on synthetic data and then applied to real Sentinel-2 imagery for two test sites – the Kamensky District of Rostov Oblast and the vicinity of Moldovanskoye village, Krymsky District, Krasnodar Krai – covering 10 dates within 2024. Results. The algorithm is shown to consistently identify spatially localised zones of increasing bare-soil exposure. Discussion . A key limitation – the inability to distinguish erosion-related exposure from ordinary agrotechnical bare soil — is discussed, along with directions for resolving it (digital elevation model overlay, multi-year analysis). Conclusion . An index-based algorithm for detecting indicators of water-induced soil erosion from Sentinel-2 multispectral time series was developed and validated. Verification on synthetic data and application to two real test areas in southern Russia confirmed its operability while demonstrating the need to separate erosion-related changes from agricultural soil exposure in subsequent model development.","引言。本文介绍了一种基于指数的算法开发与测试，该算法用于从Sentinel-2遥感数据中检测水蚀土壤侵蚀指标，被视为构建基于物理的质量输运混合模型并结合神经网络参数辨识的第一个实践阶段。材料与方法。该算法依赖于对归一化植被指数（NDVI）和裸土指数（BSI）时间序列的联合分析，随后进行空间变化检测（ΔBSI），并在第90百分位数处进行阈值滤波。该算法首先在合成数据上进行了验证，然后应用于两个测试点的真实Sentinel-2影像——罗斯托夫州卡缅斯基区和克拉斯诺达尔边疆区克里姆斯克区摩尔多瓦诺夫斯科耶村附近——覆盖2024年内的10个日期。结果。结果表明，该算法能够一致地识别出裸土暴露增加的空间局部区域。讨论。讨论了关键局限性——无法区分与侵蚀相关的裸土暴露和普通农技作业造成的裸土——以及解决该问题的方向（叠加数字高程模型、多年分析）。结论。开发并验证了一种基于指数的算法，用于从Sentinel-2多光谱时间序列中检测水蚀土壤侵蚀指标。在合成数据上的验证以及在俄罗斯南部两个真实测试区域的应用证实了其可操作性，同时表明在后续模型开发中有必要将与侵蚀相关的变化与农业裸土暴露区分开来。","COMPUTATIONAL MATHEMATICS AND INFORMATION TECHNOLOGIES","2026-10-05T00:00:00Z",70,{"impact":17,"substance":45,"depth":121,"authority":122,"freshness":123,"relevant":21,"comment":124},17,13,8,"提出基于NDVI与BSI时序的土壤水蚀指标遥感识别算法，并在俄罗斯南部两个试验区验证，方法有新意但属区域尺度研究，对国内农业遥感监测有参考价值。",[126],{"name":117,"url":114},[128,129,26,27,130],"智慧农业","Sentinel-2","土壤侵蚀",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[133],{"code":54,"slug":59,"name":134,"path":135,"parent_code":136},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",{"status":39,"locked":14,"version":40,"method":41,"evidence":138},{"candidates":139,"agricultural_evidence":46},[140,144,149],{"code":32,"score":45,"supported":46,"title":141,"abstract":142,"tags":143},[51],[50,48,51],[26,129,27],{"code":54,"score":145,"supported":46,"title":146,"abstract":147,"tags":148},14,[59],[58,59],[],{"code":150,"score":21,"supported":14,"title":151,"abstract":152,"tags":153},"I1",[],[],[128],[155,156],"Sentinel-2 土壤侵蚀 遥感","罗斯托夫州 克拉斯诺达尔 土壤侵蚀","Sentinel-2土壤侵蚀遥感-4365","10.23947\u002F2587-8999-2026-10-3-49-57",{"doi":158,"openalex_id":160,"authors":161,"venue":117,"cited_by_count":100,"oa_url":114,"card":168,"direction":105,"ingested_from":107},"W7220651513",[162,165],{"name":163,"orcid":164},"V. A. Blagin","https:\u002F\u002Forcid.org\u002F0009-0003-3239-6150",{"name":166,"orcid":167},"V. A. Beraia","https:\u002F\u002Forcid.org\u002F0009-0006-2270-5011",{"tldr":169,"method":170,"finding":171,"direction":105,"opportunity":172},"开发基于Sentinel-2时序NDVI与BSI指数的水土流失指标检测算法，并在俄罗斯南部实地验证。","联合NDVI与BSI时序，用ΔBSI阈值（90百分位）检测裸土变化，合成与真实数","算法能稳定识别裸土暴露增加区域，但无法区分侵蚀与农事裸土，需DEM和多年度分析。","可融合DEM与多年度时序，构建区分侵蚀与农事裸土的分类模型，并接入神经网络参数识别。","2026-10-07T23:30:29.080156Z",{"id":175,"title":176,"url":177,"summary":178,"summary_zh":179,"content":9,"source_name":180,"source_url":177,"published_at":181,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":182,"score_detail":183,"sources":185,"tags":187,"primary_topic":191,"secondary_topics":192,"classification":200,"search_phrases":225,"slug":228,"view_count":92,"doi":229,"paper":230,"created_at":250},3551,"Diachronic Assessment of Water Springs in Ribat El Kheir Plateau (Morocco), under Climatic and Anthropogenic Pressure, Using Remote Sensing (1985-2025)","https:\u002F\u002Fdoi.org\u002F10.4028\u002Fp-9o0ojj","The Ribat El Kheir plateau, located in the northern part of the Tabular Middle Atlas (Morocco), is characterized by carbonate formations (Liasic dolomitic limestones) and a dense network of tectonic faults. This study conducts a diachronic assessment of water springs and their interaction with climatic conditions and anthropogenic factors related to the expansion of irrigated agriculture (farms) from 1985 to 2025. A multi-source methodological approach was adopted, combining the inventory and mapping of springs, the application of remote sensing, using Landsat and Sentinel satellite imagery, and the calculation of standard indices, including the Normalized Difference Water Index (NDWI), the Normalized Difference Vegetation Index (NDVI), and the Standardized Precipitation Index (SPI). The results indicate that a combination of geomorphological context primarily influences the spatial distribution of the 101 inventoried springs, the lithological nature of the formations (permeable dolomites), structural features, and climatic factors. However, a significant regression in both the number and flow of these springs has been observed. Concurrently, irrigated fruit agriculture has expanded remarkably over the study period. The SPI analysis further reveals a climatic trend towards increased aridity. These findings highlight the critical and synergistic pressure of climate change and intensive agriculture on water resources in this vulnerable semi-arid region.","位于摩洛哥中阿特拉斯板状山脉北部的里巴特·埃尔·海尔（Ribat El Kheir）高原，以碳酸盐岩地层（里阿斯统白云质灰岩）和密集的构造断裂网络为特征。本研究对1985年至2025年间泉水动态及其与气候条件和灌溉农业（农场）扩张相关人为因素的相互作用进行了历时性评估。研究采用多源方法学途径，结合泉水编录与制图、遥感技术应用（利用Landsat和Sentinel卫星影像）以及标准指数的计算，包括归一化差异水体指数（NDWI）、归一化差异植被指数（NDVI）和标准化降水指数（SPI）。结果表明，101处编录泉水的空间分布主要受地貌背景、地层岩性特征（渗透性白云岩）、构造特征及气候因素的综合影响。然而，观测到这些泉水的数量和流量均出现显著衰退。与此同时，灌溉果树农业在研究期内显著扩张。SPI分析进一步揭示了气候趋于干旱化的趋势。这些发现凸显了气候变化与集约化农业对这一脆弱半干旱地区水资源的临界协同压力。","International journal of engineering research in Africa","2026-09-25T00:00:00Z",67,{"impact":123,"substance":45,"depth":121,"authority":122,"freshness":20,"relevant":21,"comment":184},"基于Landsat与Sentinel遥感的40年泉水退化评估，方法扎实、数据翔实，但属区域案例研究，对国内三农实践的直接参考价值有限。",[186],{"name":180,"url":177},[188,26,27,189,190],"农业水资源","灌溉农业","干旱化",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[193,197],{"code":76,"slug":194,"name":195,"path":196,"parent_code":136},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate",{"code":62,"slug":66,"name":198,"path":199,"parent_code":136},"水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",{"status":39,"locked":14,"version":40,"method":41,"evidence":201},{"candidates":202,"agricultural_evidence":46},[203,208,214,219],{"code":32,"score":204,"supported":46,"title":205,"abstract":206,"tags":207},16,[48],[50,48],[26,27],{"code":76,"score":20,"supported":46,"title":209,"abstract":210,"tags":213},[],[211,212,80],"气候变化","干旱",[],{"code":62,"score":123,"supported":46,"title":215,"abstract":216,"tags":218},[],[65,217],"水资源",[188,189],{"code":220,"score":77,"supported":46,"title":221,"abstract":222,"tags":224},"B2",[],[223],"果树",[],[226,227],"Ribat El Kheir 泉水 遥感","摩洛哥 灌溉农业 水资源","RibatElKheir泉水遥感-3551","10.4028\u002Fp-9o0ojj",{"doi":229,"openalex_id":231,"authors":232,"venue":180,"cited_by_count":100,"oa_url":9,"card":245,"direction":105,"ingested_from":107},"W7214294130",[233,235,236,239,241,242],{"name":234,"orcid":9},"Hamid Achiban",{"name":234,"orcid":9},{"name":237,"orcid":238},"Miloud Afenzar","https:\u002F\u002Forcid.org\u002F0009-0008-0839-0230",{"name":240,"orcid":9},"Hassan Achiban",{"name":240,"orcid":9},{"name":243,"orcid":244},"Nourddine El Gali","https:\u002F\u002Forcid.org\u002F0009-0001-7025-4765",{"tldr":246,"method":247,"finding":248,"direction":105,"opportunity":249},"基于遥感和指数分析，评估摩洛哥Ribat El Kheir高原1985-2025年泉水数量与流量的退","Landsat\u002FSentinel影像、NDWI\u002FNDVI\u002FSPI指数、泉水编目与","泉水数量与流量显著减少，灌溉农业扩张与气候干旱化协同加剧水资源压力。","可结合多源遥感与机器学习，量化灌溉扩张对泉水流量的贡献，并预测未来情景。","2026-09-26T23:30:29.568284Z",{"id":252,"title":253,"url":254,"summary":255,"summary_zh":256,"content":9,"source_name":257,"source_url":254,"published_at":258,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":259,"score_detail":260,"sources":262,"tags":264,"primary_topic":268,"secondary_topics":274,"classification":276,"search_phrases":289,"slug":292,"view_count":293,"doi":294,"paper":295,"created_at":323},3084,"Spatiotemporal evolution and drivers of eco-environmental quality for sustainable rural tourism in China’s Yangtze River Basin: an explainable AI approach","https:\u002F\u002Fdoi.org\u002F10.1080\u002F17538947.2026.2735566","Balancing tourism-driven growth (SDG 8.9) with terrestrial ecosystem conservation (SDG 15) is vital for sustainable watershed management. Focusing on 409 Key Rural Tourism Villages in China’s Yangtze River Basin, this study integrates Google Earth Engine and MODIS data to assess eco-environmental quality (EEQ) from 2000 to 2024 using the Remote Sensing Ecological Index (RSEI), employing an XGBoost-SHAP framework to decode driving mechanisms. Results indicate that these villages exhibit a clustered spatial distribution pattern, with three core agglomerations. The mean RSEI across all villages exceeds 0.73, indicating overall improvement and resilient recovery after 2020. However, a distinct north-south spatial disparity emerged: improved villages were predominantly concentrated north of the Yangtze River mainstem, whereas degraded villages clustered in the Taihu, Poyang, and Dongting Lake basins to the south. Elevation, land-use change, and temperature are the primary drivers, with a critical altitudinal threshold near 2,500 metres, where synergistic effects turn antagonistic. Although the XGBoost model achieved strong predictive performance (R2 = 0.853, RMSE = 0.071), 14.7% of the variance remains unexplained, suggesting the influence of additional unmeasured factors. These findings advance SDG 15 localisation by establishing spatial baselines and threshold-guided carrying-capacity regulations for watershed tourism governance.","在可持续流域管理中，平衡旅游驱动型增长（SDG 8.9）与陆地生态系统保护（SDG 15）至关重要。本研究以中国长江流域409个全国乡村旅游重点村为对象，集成Google Earth Engine与MODIS数据，基于遥感生态指数（RSEI）评估2000—2024年生态环境质量（EEQ），并采用XGBoost-SHAP框架解析其驱动机制。结果表明，这些村庄呈集聚型空间分布格局，形成三个核心集聚区。所有村庄的RSEI均值超过0.73，表明生态环境质量总体改善，并在2020年后呈现韧性恢复。然而，南北空间分异显著：改善型村庄主要集中于长江干流以北，而退化型村庄则聚集于以南的太湖、鄱阳湖和洞庭湖流域。海拔、土地利用变化和气温是主要驱动因子，在约2500 m处存在关键海拔阈值，超过该阈值后协同效应转为拮抗效应。尽管XGBoost模型具有较强预测性能（R² = 0.853，RMSE = 0.071），仍有14.7%的方差未能解释，提示其他未测因素的影响。本研究通过建立空间基线和阈值引导的承载力调控措施，推动了SDG 15的本土化，为流域旅游治理提供了依据。","International Journal of Digital Earth","2026-09-18T00:00:00Z",80,{"impact":19,"substance":18,"depth":19,"authority":145,"freshness":123,"relevant":21,"comment":261},"基于GEE与MODIS的乡村文旅生态质量长时序评估，方法新颖、数据规模大，对流域旅游承载力治理有参考价值。",[263],{"name":257,"url":254},[265,27,266,28,267],"长江流域","乡村文旅","可持续旅游",{"code":269,"slug":270,"name":271,"path":272,"parent_code":273},"G4","rural-industry","乡村产业与县域经济","\u002Ftopic\u002Frural-services\u002Frural-industry","G",[275],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":277},{"candidates":278,"agricultural_evidence":46},[279,285],{"code":269,"score":145,"supported":46,"title":280,"abstract":282,"tags":284},[281],"rural tourism",[283,281],"乡村旅游",[],{"code":32,"score":123,"supported":46,"title":286,"abstract":287,"tags":288},[],[50,48],[28,27],[290,291],"长江流域 乡村旅游 生态质量","RSEI 遥感生态指数 乡村","长江流域乡村旅游生态质量-3084",5,"10.1080\u002F17538947.2026.2735566",{"doi":294,"openalex_id":296,"authors":297,"venue":257,"cited_by_count":100,"oa_url":315,"card":316,"direction":322,"ingested_from":107},"W7213546376",[298,300,303,305,307,309,312],{"name":299,"orcid":9},"Xiaojuan Zhang",{"name":301,"orcid":302},"Zhe Chen","https:\u002F\u002Forcid.org\u002F0000-0001-7579-1968",{"name":304,"orcid":9},"Libin Guo",{"name":306,"orcid":9},"Guoyan Wang",{"name":308,"orcid":9},"Yongxiu Zhou",{"name":310,"orcid":311},"Hui Li","https:\u002F\u002Forcid.org\u002F0000-0002-3565-1773",{"name":313,"orcid":314},"Zhongchang Sun","https:\u002F\u002Forcid.org\u002F0000-0003-3219-0542","https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Fpdf\u002F10.1080\u002F17538947.2026.2735566?needAccess=true",{"tldr":317,"method":318,"finding":319,"direction":320,"opportunity":321},"评估长江流域409个乡村旅游村2000-2024年生态环境质量演变并解析驱动机制。","GEE与MODIS数据、RSEI指数、XGBoost-SHAP可解释AI框架。","整体EEQ改善但南北分异明显，海拔、土地利用与温度为主导驱动，2500米为协同转拮抗阈值。","农业绿色发展与碳","可探究未解释的14.7%方差来源，并针对太湖、鄱阳湖、洞庭湖退化区开展旅游承载力调控研究。","数字乡村与农业信息化","2026-09-21T23:30:36.842989Z",{"id":325,"title":326,"url":327,"summary":328,"summary_zh":329,"content":9,"source_name":330,"source_url":327,"published_at":258,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":331,"score_detail":332,"sources":335,"tags":337,"primary_topic":341,"secondary_topics":346,"classification":348,"search_phrases":361,"slug":364,"view_count":77,"doi":365,"paper":366,"created_at":382},3075,"Mapping and monitoring land usage changes of gum Arabic belt in armed conflict-disturbed areas to support sustainable management of the belt","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-69562-8","Abstract The Gum Arabic Belt (GAB) in Sudan play a key role in sustaining rural livelihoods, supporting biodiversity, and delivering essential ecosystem services. However, this fragile dryland ecosystem is increasingly threatened by armed conflict, large-scale displacement, land use changes, and environmental degradation. Therefore, this study assessed the status of GAB and gum production under conflict-induced stressors using an integrated methodology that combines meteorological, remote sensing, and participatory field survey data. Multi-temporal MODIS NDVI data (2000–2023) were analyzed to detect spatiotemporal changes in vegetation cover, particularly during peak growing seasons. Normalized Difference Vegetation Index (NDVI) trends were evaluated using five-year intervals, except for the last period (2020–2023) to accommodate the eco-anthropogenic signs of the current war. The results reveal that vegetation recovery across large portions of the GAB is correlated with land abandonment due to ongoing conflict and locals’ displacement. Across all assessed years, moderate vegetation class consistently dominated the landscape, particularly in 2020 and 2023, indicating a notable improvement in vegetation cover in recent years. A significant variation was observed in Gum yield, with higher production in 2005. The study underscores the urgent need for target restoration strategies and sustainable management policies. It also demonstrates the value of integrating earth observation data with local knowledge systems for conflict-sensitive environmental monitoring and policy formation in dryland regions.","摘要 苏丹的阿拉伯胶带（Gum Arabic Belt, GAB）在维持农村生计、支持生物多样性和提供关键生态系统服务方面发挥着重要作用。然而，这一脆弱的旱地生态系统正日益受到武装冲突、大规模流离失所、土地利用变化和环境退化的威胁。因此，本研究采用综合气象、遥感和参与式实地调查数据的方法，评估了冲突引发的压力因素下GAB及阿拉伯胶生产的状况。研究分析了多时相MODIS NDVI数据（2000–2023年），以检测植被覆盖的时空变化，尤其是生长旺季期间的变化。归一化植被指数（NDVI）趋势按五年间隔进行评估，但最后一个时段（2020–2023年）除外，以适应当前战争带来的生态-人为影响迹象。结果表明，GAB大部分地区的植被恢复与持续冲突和当地居民流离失所导致的土地撂荒相关。在所有评估年份中，中等植被等级始终主导景观，尤其是在2020年和2023年，表明近年来植被覆盖显著改善。阿拉伯胶产量存在显著差异，2005年产量较高。该研究强调迫切需要有针对性的恢复策略和可持续管理政策。研究还表明，将地球观测数据与当地知识系统相结合，对于旱地地区冲突敏感型环境监测和政策制定具有重要价值。","Scientific Reports",77,{"impact":204,"substance":333,"depth":19,"authority":145,"freshness":123,"relevant":21,"comment":334},21,"以MODIS NDVI长时序遥感结合实地调查评估冲突扰动下阿拉伯胶带植被与胶产量变化，方法扎实、结论有政策价值，但属区域案例研究，对国内三农信息化参考有限。",[336],{"name":330,"url":327},[26,27,338,339,340],"荒漠化防治","可持续管理","苏丹",{"code":342,"slug":343,"name":344,"path":345,"parent_code":136},"H6","biodiversity","生态保护与生物多样性","\u002Ftopic\u002Fenvironment\u002Fbiodiversity",[347],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":349},{"candidates":350,"agricultural_evidence":46},[351,357],{"code":342,"score":13,"supported":46,"title":352,"abstract":353,"tags":356},[],[354,355,343],"生物多样性","生态系统服务",[338],{"code":32,"score":123,"supported":46,"title":358,"abstract":359,"tags":360},[],[50,48],[26,27],[362,363],"苏丹 阿拉伯胶带 NDVI","MODIS NDVI 植被覆盖 冲突","苏丹阿拉伯胶带NDVI-3075","10.1038\u002Fs41598-026-69562-8",{"doi":365,"openalex_id":367,"authors":368,"venue":330,"cited_by_count":100,"oa_url":376,"card":377,"direction":105,"ingested_from":107},"W7213533975",[369,372,374],{"name":370,"orcid":371},"Elmugheira M. I. Mohammed","https:\u002F\u002Forcid.org\u002F0000-0003-0977-9156",{"name":373,"orcid":9},"Abdalrahman A. Ahmed",{"name":375,"orcid":9},"Faisal I. Musa","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-026-69562-8_reference.pdf",{"tldr":378,"method":379,"finding":380,"direction":105,"opportunity":381},"结合遥感与实地调查，评估苏丹武装冲突干扰下阿拉伯胶带土地覆被变化及胶产量。","多时相MODIS NDVI（2000–2023）与气象、参与式实地调查数据集成分","冲突导致人口流离与土地撂荒，反而使大部分区域植被恢复，胶产量年际波动大。","可探究冲突驱动撂荒下植被恢复的生态-社会机制，并开发冲突敏感型遥感监测与可持续管理模型。","2026-09-21T23:30:25.775307Z",{"id":384,"title":385,"url":386,"summary":387,"summary_zh":388,"content":9,"source_name":389,"source_url":386,"published_at":390,"category":12,"cover_url":9,"hotness":391,"is_selected":14,"score":392,"score_detail":393,"sources":396,"tags":400,"primary_topic":402,"secondary_topics":403,"classification":405,"search_phrases":425,"slug":428,"view_count":21,"doi":429,"paper":430,"created_at":444},2321,"ASSESSMENT OF SOIL SALINITY USING THE NDVI VEGETATION INDEX BASED ON REMOTE SENSING DATA","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22702718","This article examines the assessment of soil salinity in the irrigated meadow-sierozem soils of the E. Qahhorov agricultural area in Khovos District, Syrdarya Region, based on remote sensing data. Sentinel-2 satellite data covering the period from 2016 to 2025 were used in the study, and the Normalized Difference Vegetation Index (NDVI) was calculated using geospatial technologies. The long-term and seasonal dynamics of vegetation cover in the study area were analyzed, and the relationship between NDVI values and salinity levels was assessed. Based on an NDVI classification adapted to the natural conditions of the study area, criteria for the indirect assessment of soil salinity levels were proposed. The results demonstrated that the NDVI can be effectively used as an indicator for determining the impact of soil salinity on vegetation cover, assessing salinity spatially, and conducting long-term monitoring of salinity in irrigated agricultural lands.","本文基于遥感数据，对锡尔河州霍沃斯区E. Qahhorov农业区灌溉草甸灰钙土的土壤盐渍化进行了评估。研究使用了2016年至2025年期间的Sentinel-2卫星数据，并利用地理空间技术计算了归一化植被指数（NDVI）。分析了研究区植被覆盖的长期和季节性动态，并评估了NDVI值与盐渍化程度之间的关系。基于适应研究区自然条件的NDVI分类，提出了土壤盐渍化程度间接评估的标准。结果表明，NDVI可有效用作确定土壤盐渍化对植被覆盖影响、空间评估盐渍化以及开展灌溉农田盐渍化长期监测的指标。","Zenodo (CERN European Organization for Nuclear Research)","2026-09-11T00:00:00Z",25,65,{"impact":17,"substance":19,"depth":394,"authority":17,"freshness":123,"relevant":21,"comment":395},15,"基于Sentinel-2长时序NDVI数据提出土壤盐渍化间接评估标准，方法可复用但属区域性案例研究，公共影响有限。",[397,398],{"name":389,"url":386},{"name":389,"url":399},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22702719",[128,26,27,401,189],"土壤盐渍化",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[404],{"code":54,"slug":59,"name":134,"path":135,"parent_code":136},{"status":39,"locked":14,"version":40,"method":41,"evidence":406},{"candidates":407,"agricultural_evidence":46},[408,412,416,421],{"code":32,"score":204,"supported":46,"title":409,"abstract":410,"tags":411},[48],[50,48],[26,27],{"code":54,"score":145,"supported":46,"title":413,"abstract":414,"tags":415},[59],[58,59],[],{"code":62,"score":417,"supported":46,"title":418,"abstract":419,"tags":420},4,[],[65],[189],{"code":150,"score":21,"supported":14,"title":422,"abstract":423,"tags":424},[],[],[128],[426,427],"土壤盐渍化 智慧农业 灌溉农业 遥感监测","土壤盐渍化 智慧农业","土壤盐渍化智慧农业灌溉农业遥感监测-2321","10.5281\u002Fzenodo.22702718",{"doi":429,"openalex_id":431,"authors":432,"venue":389,"cited_by_count":100,"oa_url":386,"card":439,"direction":105,"ingested_from":107},"W7212227143",[433,435,437],{"name":434,"orcid":9},"U.K. Umirova",{"name":436,"orcid":9},"D.A. Kodirova",{"name":438,"orcid":9},"O.O. Davronov",{"tldr":440,"method":441,"finding":442,"direction":105,"opportunity":443},"利用Sentinel-2遥感数据计算NDVI，评估灌溉草甸灰钙土的土壤盐渍化程度。","Sentinel-2数据（2016-2025）与NDVI指数，结合地理空间技术分","NDVI可有效指示盐渍化对植被的影响，实现空间评估与长期监测。","可探索多指数融合与机器学习提升盐渍化反演精度，并推广至不同土壤类型区。","2026-09-13T23:30:22.820810Z",{"id":446,"title":447,"url":448,"summary":449,"summary_zh":450,"content":9,"source_name":451,"source_url":448,"published_at":452,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":100,"score_detail":453,"sources":455,"tags":457,"primary_topic":460,"secondary_topics":461,"classification":462,"search_phrases":485,"slug":488,"view_count":100,"doi":489,"paper":490,"created_at":518},5390,"Land use and socio-economic changes caused by riverbank erosion - case study: Obrenovac municipality, Serbia","https:\u002F\u002Fdoi.org\u002F10.59954\u002Fstnv.797","Lateral bank erosion of meandering rivers represents a significant geomorphological process in the lower part of the Kolubara River Basin in Serbia. This process directly impacts land-use and agricultural productivity and lead to broader environmental, socioeconomic, and demographic changes. Historically, the Kolubara riverbanks have been intensively used for agriculture. Today, lateral channel migration and riverbank erosion, driven by the interaction between natural process and human activities, directly threaten traditionally active land plots along the river. This study investigates the long-term dynamics of riverbank erosion along the four active meanders of the Kolubara River in Obrenovac Municipality over a 97-year period (1930–2026). Main tasks include quantification of lateral channel migration and land loss rates, analysis of land-use changes within the endangered plots, and an investigation of socioeconomic consequences and demographic dynamics in affected settlements. The methodological framework integrates cadastral maps analysis, remote sensing techniques (UAVs), and GIS software, with analysis of demographic and land-use data. The results indicate that maximum lateral channel migration reached 259.3 m during the observed period, while the total land loss amounted to 17.6 ha, consisting mostly of arable land. This reduction has directly affected the local agricultural sector, resulting in an estimated land loss value of approximately 24,122 USD. Demographic analysis reveals population decline exceeding 40% in the analysed settlements (Draževac, Konatice and Poljane) between 1961 and 2022, from over 90% of the economically active population in 1961 to less than 2% in 2022. Ultimately, by highlighting the socioeconomic impacts of riverbank erosion such as irreversible agricultural land loss and rural livelihood disruption, these findings offer valuable insights for spatial planning and sustainable land management.","蜿蜒河流的侧向河岸侵蚀是塞尔维亚科卢巴拉河（Kolubara River）流域下游一个重要的地貌过程。该过程直接影响土地利用和农业生产力，并引发更广泛的环境、社会经济和人口变化。历史上，科卢巴拉河岸曾被密集用于农业生产。如今，在自然过程与人类活动相互作用驱动下的侧向河道迁移和河岸侵蚀，直接威胁着沿河传统上活跃的地块。本研究考察了奥布雷诺瓦茨市（Obrenovac Municipality）科卢巴拉河四个活跃曲流段在97年期间（1930—2026年）河岸侵蚀的长期动态。主要任务包括：量化侧向河道迁移和土地流失速率，分析受威胁地块内的土地利用变化，以及调查受影响居民点的社会经济后果和人口动态。方法框架整合了地籍图分析、遥感技术（无人机，UAVs）和GIS软件，并结合人口与土地利用数据分析。结果表明，在观测期内侧向河道迁移最大距离达259.3 m，土地流失总量为17.6 ha，其中大部分为耕地。这一减少直接影响了当地农业部门，估计土地流失价值约为24,122美元。人口分析显示，1961年至2022年间，所分析居民点（Draževac、Konatice和Poljane）的人口下降幅度超过40%，经济活动人口比例从1961年的超过90%降至2022年的不足2%。最终，通过突出河岸侵蚀的社会经济影响，如不可逆的农业土地流失和农村生计破坏，这些发现为空间规划和可持续土地管理提供了有价值的见解。","Stanovnistvo","2026-10-19T00:00:00Z",{"impact":100,"substance":100,"depth":100,"authority":100,"freshness":100,"relevant":100,"comment":454},"塞尔维亚河岸侵蚀案例研究，属地理与土地利用领域，与三农及农业信息化主题关联弱，不建议进入每日精选。",[456],{"name":451,"url":448},[27,458,130,459],"土地利用","乡村人口",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":463},{"candidates":464,"agricultural_evidence":46},[465,470,475,481],{"code":32,"score":466,"supported":46,"title":467,"abstract":468,"tags":469},7,[],[50,48],[27],{"code":69,"score":77,"supported":46,"title":471,"abstract":472,"tags":474},[],[473],"GIS",[],{"code":476,"score":77,"supported":46,"title":477,"abstract":478,"tags":480},"I7",[],[479],"methodological framework",[],{"code":342,"score":21,"supported":14,"title":482,"abstract":483,"tags":484},[],[],[458],[486,487],"Kolubara 河岸侵蚀","Obrenovac 土地利用","Kolubara河岸侵蚀-5390","10.59954\u002Fstnv.797",{"doi":489,"openalex_id":491,"authors":492,"venue":451,"cited_by_count":100,"oa_url":448,"card":512,"direction":105,"ingested_from":107},"W7222945959",[493,496,499,501,504,507,510],{"name":494,"orcid":495},"Slavoljub Dragićević","https:\u002F\u002Forcid.org\u002F0000-0002-1417-5405",{"name":497,"orcid":498},"Marko Langović","https:\u002F\u002Forcid.org\u002F0000-0002-4614-7265",{"name":500,"orcid":9},"Милан Радовић",{"name":502,"orcid":503},"Radislav Tošić","https:\u002F\u002Forcid.org\u002F0000-0002-3994-125X",{"name":505,"orcid":506},"Milica Langović","https:\u002F\u002Forcid.org\u002F0000-0002-6979-377X",{"name":508,"orcid":509},"Novica Lovrić","https:\u002F\u002Forcid.org\u002F0009-0006-0838-4370",{"name":511,"orcid":9},"Manojlović Stefan",{"tldr":513,"method":514,"finding":515,"direction":516,"opportunity":517},"研究塞尔维亚Kolubara河岸侵蚀97年间的河道迁移、耕地损失及社会经济影响。","结合地籍图、UAV遥感、GIS与人口土地利用数据分析四条曲流。","最大侧向迁移259.3米，损失17.6公顷耕地约2.4万美元，村落人口降超40%。","其他","可将河岸侵蚀遥感监测与农户生计、土地价值评估耦合，构建侵蚀风险预警与补偿决策模型。","2026-10-20T23:30:18.982943Z"]