[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3189":3,"related-3189":66},{"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,"search_phrases":31,"slug":34,"view_count":35,"doi":36,"paper":37,"created_at":65},3189,"Influence of Drought Events on Vegetation and Land Use Dynamics Utilising Orbital Data: A Case Study in the Pajeú River Basin, Pernambuco","https:\u002F\u002Fdoi.org\u002F10.29150\u002Fjhrs.v16i03.269030","Monitoring drought in the northeastern Semi-Arid region is a challenge compounded by high rainfall variability and a scarcity of in situ monitoring networks, which makes the use of geotechnologies for water resource management essential. This study aimed to analyze land use and occupation dynamics from 2002 to 2022 in the Pajeú River basin in Pernambuco, Brazil, and their relationship with drought events, using indices based on remote sensing. The Standardized Precipitation Index (SPI) was applied to characterize meteorological drought, while the Vegetation Health Index (VHI) and Normalized Vegetation Water Supply Index (NVSWI) were used to assess the ecosystem's response. The results indicated that the period from 2011 to 2016 was the most severe and prolonged drought, which was reinforced by low VHI and NVSWI values, indicating water stress on vegetation during the same period. The correlation analysis revealed that land use classes, such as vegetation and water, responded directly to drought, whereas degraded anthropogenic areas, including pasture and exposed soil, exhibited the opposite behavior. The joint analysis of the three indices and land use and occupation data provided a comprehensive understanding of the evolution of drought in the study area, highlighting the importance of a multiple approach to monitoring complex environments.","监测半干旱东北部地区的干旱是一项挑战，降雨变率大且原位监测网络稀缺使这一挑战更加复杂，因此利用地理技术进行水资源管理至关重要。本研究旨在利用基于遥感的指数，分析2002年至2022年巴西伯南布哥州帕热乌河流域的土地利用与覆盖动态及其与干旱事件的关系。采用标准化降水指数（SPI）表征气象干旱，同时使用植被健康指数（VHI）和归一化植被供水指数（NVSWI）评估生态系统的响应。结果表明，2011年至2016年是最严重且持续时间最长的干旱期，同期较低的VHI和NVSWI值进一步证实了这一点，表明植被在此期间受到水分胁迫。相关性分析显示，植被和水体等土地利用类别对干旱有直接响应，而牧场和裸露土壤等退化的人为区域则表现出相反的行为。三个指数与土地利用及覆盖数据的联合分析为理解研究区域干旱演变提供了全面的认识，凸显了多方法途径在监测复杂环境中的重要性。",null,"Journal of Hyperspectral Remote Sensing","2026-09-19T00:00:00Z","论文",10,false,61,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":17,"relevant":21,"comment":22},8,18,15,12,1,"该研究利用遥感指数分析巴西半干旱流域干旱与植被动态，方法扎实但属区域性案例，对国内三农信息化参考价值有限。",[24],{"name":10,"url":6},[26,27,28,29,30],"水资源管理","遥感监测","土地利用","干旱监测","植被指数",[32,33],"Pajeú River basin 干旱 遥感","SPI VHI NVSWI 植被","PajeúRiverbasin干旱遥感-3189",0,"10.29150\u002Fjhrs.v16i03.269030",{"doi":36,"openalex_id":38,"authors":39,"venue":10,"cited_by_count":35,"oa_url":57,"card":58,"direction":62,"ingested_from":64},"W7213792298",[40,43,46,49,52,54],{"name":41,"orcid":42},"Juliana Farias Santos de Moraes","https:\u002F\u002Forcid.org\u002F0000-0002-3241-844X",{"name":44,"orcid":45},"Estephania Silva Jovino","https:\u002F\u002Forcid.org\u002F0000-0002-6694-3533",{"name":47,"orcid":48},"Alex Vinícius de Melo Vieira","https:\u002F\u002Forcid.org\u002F0009-0002-5204-3734",{"name":50,"orcid":51},"Anderson Luiz Ribeiro de Paiva","https:\u002F\u002Forcid.org\u002F0000-0003-3475-1454",{"name":53,"orcid":9},"Sylvana Sylvana Melo dos Santos",{"name":55,"orcid":56},"Leidjane Maria Maciel de Oliveira","https:\u002F\u002Forcid.org\u002F0000-0003-1251-6998","https:\u002F\u002Fperiodicos.ufpe.br\u002Frevistas\u002Fjhrs\u002Farticle\u002Fdownload\u002F269030\u002F52814",{"tldr":59,"method":60,"finding":61,"direction":62,"opportunity":63},"利用遥感指数分析巴西Pajeú河流域2002-2022年干旱对植被与土地利用的影响。","采用SPI、VHI和NVSWI指数，结合遥感数据与土地利用分类。","2011-2016年干旱最严重，植被和水体响应直接，而牧场和裸地呈相反趋势。","农业遥感与作物表型","可融合多源遥感与机器学习，构建半干旱区干旱-植被-土地利用耦合预警模型。","openalex","2026-09-22T23:30:26.557816Z",{"total":67,"page":21,"page_size":67,"items":68},6,[69,118,155,188,229,293],{"id":70,"title":71,"url":72,"summary":73,"summary_zh":74,"content":9,"source_name":75,"source_url":72,"published_at":76,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":77,"score_detail":78,"sources":83,"tags":85,"search_phrases":88,"slug":91,"view_count":35,"doi":92,"paper":93,"created_at":117},2674,"Bi-decadal drought assessment in Northwestern Algeria: Integrating meteorological and remote sensing indices","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00704-026-06526-y","Abstract Drought is an escalating hazard in arid and semi‑arid regions with significant implications for agriculture, ecosystems, and water resources. This study presents a 2003–2023 integrated assessment of meteorological and vegetation-based drought across northwest Algeria, using the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset and Moderate Resolution Imaging Spectroradiometer (MODIS) remotely‑sensed products. Meteorological drought was quantified with the Standardized Precipitation Index (SPI) approximated using standardized precipitation anomalies, at 3‑, 6‑, and 12‑month timescales, whereas vegetation and thermal stress were assessed with MODIS‑derived Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI). Temporal trends were evaluated using the Mann–Kendall test and Sen’s slope estimator, and relationships between precipitation and vegetation were examined with Pearson correlation. We identified recurrent drought episodes in 2007–2009, 2011–2012, and a pronounced dry phase from 2020–2023. Mann–Kendall results indicated widespread drying across all SPI timescales, with 56% of the study area showing significant negative trends at SPI‑3 (mean Sen’s slope = − 0.10 yr⁻ 1 ). Vegetation indices mirrored these changes, with VHI showing substantially more degraded area than improvement (4.89% vs 0.51% of the domain), while VCI and TCI responses were spatially heterogeneous. The correlation analysis showed moderate but statistically significant relationships between SPI and VHI at the short-term scale (SPI-3 vs. VHI, r = 0.567, p = 0.007), followed by SPI-6 ( r = 0.509, p = 0.019), indicating that vegetation response is more strongly associated with short- to medium-term precipitation variability. These results demonstrate the value of combining meteorological and satellite vegetation indices for regional drought monitoring and early warning, and underscore an ongoing shift toward increased aridity with implications for water management and agricultural adaptation.","摘要 干旱是干旱和半干旱地区日益加剧的灾害，对农业、生态系统和水资源具有重大影响。本研究利用气候灾害组红外降水与站点数据（CHIRPS）数据集和中分辨率成像光谱仪（MODIS）遥感产品，对阿尔及利亚西北部2003—2023年气象干旱和基于植被的干旱进行了综合评估。气象干旱采用标准化降水指数（SPI）量化，该指数通过标准化降水距平在3个月、6个月和12个月时间尺度上近似计算；植被和热胁迫则通过MODIS衍生的植被状态指数（VCI）、温度状态指数（TCI）和植被健康指数（VHI）进行评估。采用Mann–Kendall检验和Sen斜率估计器评估时间趋势，并使用Pearson相关分析检验降水与植被之间的关系。我们识别出2007—2009年、2011—2012年的反复干旱事件，以及2020—2023年显著的干旱阶段。Mann–Kendall结果表明，所有SPI时间尺度上均呈现大范围干旱化趋势，研究区56%的面积在SPI-3上表现出显著负趋势（Sen斜率均值 = −0.10 yr⁻¹）。植被指数反映了这些变化，VHI显示退化面积远大于改善面积（分别占研究区的4.89%和0.51%），而VCI和TCI的响应在空间上具有异质性。相关分析表明，SPI与VHI在短期尺度上存在中等但统计显著的关系（SPI-3与VHI，r = 0.567，p = 0.007），其次为SPI-6（r = 0.509，p = 0.019），表明植被响应与短期至中期降水变率的关系更为密切。这些结果证明了结合气象指标和卫星植被指数进行区域干旱监测与预警的价值，并凸显了干旱化持续加剧的趋势及其对水资源管理和农业适应的影响。","Theoretical and Applied Climatology","2026-09-15T00:00:00Z",71,{"impact":20,"substance":79,"depth":80,"authority":81,"freshness":17,"relevant":21,"comment":82},21,17,13,"基于CHIRPS与MODIS的阿尔及利亚西北部20年干旱综合评估，方法整合气象与遥感指标，结论对区域干旱监测与农业适应有参考价值，但属境外区域研究，国内产业影响有限。",[84],{"name":75,"url":72},[86,26,27,30,87],"农业气象","干旱预警",[89,90],"水资源管理 农业气象 干旱预警 植被指数","水资源管理 农业气象","水资源管理农业气象干旱预警植被指数-2674","10.1007\u002Fs00704-026-06526-y",{"doi":92,"openalex_id":94,"authors":95,"venue":75,"cited_by_count":35,"oa_url":72,"card":112,"direction":62,"ingested_from":64},"W7213346236",[96,99,102,105,107,110],{"name":97,"orcid":98},"Ramzi Benhizia","https:\u002F\u002Forcid.org\u002F0000-0002-8967-2051",{"name":100,"orcid":101},"Brahim Abdelkebir","https:\u002F\u002Forcid.org\u002F0000-0002-8761-8537",{"name":103,"orcid":104},"Behnam Ata","https:\u002F\u002Forcid.org\u002F0000-0002-9690-7269",{"name":106,"orcid":9},"Mukovhe Vele Singo",{"name":108,"orcid":109},"Kwanele Phinzi","https:\u002F\u002Forcid.org\u002F0000-0003-1865-7011",{"name":111,"orcid":9},"György Szabó",{"tldr":113,"method":114,"finding":115,"direction":62,"opportunity":116},"整合气象与遥感指数评估阿尔及利亚西北部2003–2023年干旱演变。","CHIRPS降水与MODIS植被指数，SPI、VCI、TCI、VHI，Mann-","全区普遍变干，SPI-3显著负趋势占56%，VHI退化面积远大于改善，短期降水与植被相关性最强。","可引入机器学习融合多源遥感与气象数据，构建区域干旱预警与作物适应性决策模型。","2026-09-16T23:30:30.795285Z",{"id":119,"title":120,"url":121,"summary":122,"summary_zh":123,"content":9,"source_name":124,"source_url":125,"published_at":126,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":127,"score_detail":128,"sources":130,"tags":132,"search_phrases":136,"slug":139,"view_count":35,"doi":140,"paper":141,"created_at":154},3187,"Spatio-temporal analysis of Land Use and Land Cover (LULC) change using high resolution satellite data: A case study of Nagaon, Assam","https:\u002F\u002Fdoi.org\u002F10.31018\u002Fjans.v18i3.7774","Geographic information systems (GIS) coupled with satellite remote sensing (RS) have had a significant impact on the assessment and mapping of land surface dynamics, specifically the analysis of land-use land-cover (LULC) change. This study uses high-resolution multispectral LISS-IV (Linear Imaging Self-Scanning Sensor-IV) imagery with a 5.8-meter resolution to evaluate LULC trends in the Nagaon district of Assam between 2015 and 2024. Land use classes in a variety of categories, including vegetation, water bodies, agricultural land, built-up areas, scrubland, sandbars, tea plantations, and trees outside forests (TOF), were identified applying the maximum likelihood classification algorithm. Overall, The accuracy was 85.7% in 2015 and 90.3% in 2024, with respective Kappa Coefficients of 0.836 and 0.889, respectively. The results showed that between 2015 and 2024, the areas of tea plantations, natural vegetation, scrubland, and agricultural land fell by 0.26%, 6.14%, 0.26%, and 9.83%, respectively. Conversely, the waterbody, sandbar, built-up, and TOF have all increased by 0.29%, 0.91%, 0.82%, and 14.46%, respectively. This noticeable shift from conventional agricultural and natural vegetation landscapes toward tree-based systems and urban expansion on the study area, emphasize on matters concerning climate stress, declining soil fertility, economic benefits, policy support, and the need for resilient livelihoods.","地理信息系统（GIS）与卫星遥感（RS）相结合，对地表动态的评估与制图产生了显著影响，尤其是土地利用与土地覆盖（LULC）变化分析。本研究利用分辨率为5.8米的高分辨率多光谱LISS-IV（线性成像自扫描传感器-IV）影像，评估了阿萨姆邦纳冈县2015年至2024年间的LULC变化趋势。采用最大似然分类算法，识别了植被、水体、农地、建设用地、灌丛地、沙洲、茶园及林外树木（TOF）等多种土地利用类别。总体而言，2015年分类精度为85.7%，2024年为90.3%，Kappa系数分别为0.836和0.889。结果表明，2015年至2024年间，茶园、自然植被、灌丛地和农地面积分别减少了0.26%、6.14%、0.26%和9.83%。相反，水体、沙洲、建设用地和TOF分别增加了0.29%、0.91%、0.82%和14.46%。研究区从传统农业和自然植被景观向林基系统和城市扩张的显著转变，凸显了气候胁迫、土壤肥力下降、经济效益、政策支持以及韧性生计需求等相关问题。","Journal of Applied and Natural Science","https:\u002F\u002Fjournals.ansfoundation.org\u002Findex.php\u002Fjans\u002Farticle\u002Fview\u002F7774","2026-09-20T00:00:00Z",62,{"impact":17,"substance":18,"depth":19,"authority":81,"freshness":17,"relevant":21,"comment":129},"基于高分辨率遥感的区域土地利用变化实证研究，方法规范、数据翔实，对农业遥感监测有参考价值，但属地方性案例，公共影响有限。",[131],{"name":124,"url":125},[133,27,28,134,135],"农业遥感","印度农业","植被覆盖",[137,138],"Nagaon Assam LULC 遥感","LISS-IV 土地利用变化","NagaonAssamLULC遥感-3187","10.31018\u002Fjans.v18i3.7774",{"doi":140,"openalex_id":142,"authors":143,"venue":124,"cited_by_count":35,"oa_url":125,"card":149,"direction":62,"ingested_from":64},"W7213942371",[144,146],{"name":145,"orcid":9},"J. C. Das",{"name":147,"orcid":148},"Prodyut Bhattacharya","https:\u002F\u002Forcid.org\u002F0000-0002-4294-5585",{"tldr":150,"method":151,"finding":152,"direction":62,"opportunity":153},"利用高分辨率卫星影像分析印度阿萨姆邦纳冈地区2015-2024年土地利用\u002F覆盖变化。","LISS-IV 5.8米多光谱影像，最大似然分类，精度与Kappa系数评估。","农业用地和自然植被分别减少9.83%和6.14%，而林外树木和建设用地分别增加14.46%和0.82","可结合时序高分辨率影像与农户调查，探究林外树木扩张对农业韧性和碳汇的驱动机制。","2026-09-22T23:30:25.539323Z",{"id":156,"title":157,"url":158,"summary":159,"summary_zh":160,"content":9,"source_name":161,"source_url":158,"published_at":126,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":162,"score_detail":163,"sources":166,"tags":168,"search_phrases":171,"slug":174,"view_count":35,"doi":175,"paper":176,"created_at":187},3183,"Integrated Remote Sensing and Time Series Analysis for Long-Term Assessment of Vegetation Resilience: Synthesizing Climatic Variables and Land-Use\u002FLand-Cover Trajectories in Al-Ahsa Oasis, Saudi Arabia","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fland15091758","Continuous monitoring of land-use\u002Fland-cover (LULC) change is essential in the Al-Ahsa Oasis, an arid region characterized by a sensitive and fragile environment. This study is the first to integrate vegetation, climate, and land-use frameworks by combining vegetation indicators, climatic variables, and LULC trajectory classification over a 41-year period (1985–2025). Data from three Landsat sensors (Landsat 5-TM, 7-ETM+, and 8-OLI) were processed to derive vegetation indicators and an LULC trajectory classification, while ERA5-Land and CHIRPS data provided surface temperature and rainfall information, respectively. LULC trajectory classification was implemented using a random forest classifier, generating six LULC trajectory classes: stable barren, stable urban, stable water, urban expansion, transition lands, and stable vegetation. Pearson correlation analysis was used to assess the relationships between the vegetation indicators (normalized difference vegetation index [NDVI] and soil-adjusted vegetation index [SAVI]) and climatic variables (temperature and rainfall) at different time lags (0–3 years) and after detrending the time series. The detrending analysis showed no statistically significant associations between the vegetation indicators (NDVI and SAVI) and the climatic variables (temperature and rainfall) across the four examined lags, whereas the original, non-detrended time series showed positive associations that were mainly attributable to long-term trends rather than to interannual climate–vegetation covariation. The accuracy of LULC trajectory classification was high, with an overall accuracy of 0.939 and a kappa coefficient of 0.924, indicating robust mapping performance. Overall vegetation cover improved over the study period. The degradation occurred in the central part of the oasis (stable urban, urban expansion, and stable water classes, accounting for 4.506%, 5.179%, and 41.773% of each trajectory class, respectively), whereas the recovery was observed in the northern, southern, and eastern parts (stable vegetation and transition lands, accounting for 37.656% and 52.891% of each trajectory class, respectively). These findings provide long-term insights into vegetation resilience in the Al-Ahsa Oasis over 41 years, supporting sustainable urban planning and vegetation and agricultural management.","在环境敏感而脆弱的干旱区——哈萨绿洲，持续监测土地利用\u002F土地覆盖（LULC）变化至关重要。本研究首次在41年（1985—2025年）时间跨度内，通过整合植被指标、气候变量与LULC轨迹分类，构建了植被、气候与土地利用的综合框架。研究处理了三颗Landsat传感器（Landsat 5-TM、7-ETM+和8-OLI）的数据，以提取植被指标并进行LULC轨迹分类，同时分别利用ERA5-Land和CHIRPS数据获取地表温度和降雨信息。LULC轨迹分类采用随机森林分类器实现，生成了六类LULC轨迹：稳定裸地、稳定城市、稳定水体、城市扩张、过渡土地和稳定植被。采用Pearson相关分析评估植被指标（归一化差异植被指数[NDVI]和土壤调节植被指数[SAVI]）与气候变量（温度和降雨）在不同时间滞后（0—3年）及时间序列去趋势后的关系。去趋势分析表明，在四个考察滞后下，植被指标（NDVI和SAVI）与气候变量（温度和降雨）之间均无统计学显著关联，而原始未去趋势时间序列则显示出正相关，这主要归因于长期趋势而非年际气候—植被协变。LULC轨迹分类精度较高，总体精度为0.939，kappa系数为0.924，表明制图性能稳健。研究期间整体植被覆盖有所改善。退化发生在绿洲中部（稳定城市、城市扩张和稳定水体类别，分别占各轨迹类别的4.506%、5.179%和41.773%），而恢复则出现在北部、南部和东部（稳定植被和过渡土地，分别占各轨迹类别的37.656%和52.891%）。这些发现为哈萨绿洲41年来的植被恢复力提供了长期见解，可支持可持续城市规划以及植被与农业管理。","Land",73,{"impact":20,"substance":164,"depth":18,"authority":81,"freshness":17,"relevant":21,"comment":165},22,"41年长时序遥感与气候变量整合分析，方法扎实、结论可靠，对干旱区绿洲农业可持续管理有参考价值，但属区域性案例研究，公共影响有限。",[167],{"name":161,"url":158},[169,27,28,135,170],"气候变化","绿洲农业",[172,173],"Al-Ahsa Oasis 遥感 植被","Landsat NDVI 土地利用变化","Al-AhsaOasis遥感植被-3183","10.3390\u002Fland15091758",{"doi":175,"openalex_id":177,"authors":178,"venue":161,"cited_by_count":35,"oa_url":158,"card":182,"direction":62,"ingested_from":64},"W7213862324",[179],{"name":180,"orcid":181},"Amal H. Aljaddani","https:\u002F\u002Forcid.org\u002F0000-0003-1171-8416",{"tldr":183,"method":184,"finding":185,"direction":62,"opportunity":186},"整合41年Landsat植被指数、气候变量与LULC轨迹，评估沙特Al-Ahsa绿洲植被恢复力。","Landsat 5\u002F7\u002F8时序、ERA5-Land与CHIRPS气候数据、随机森","去趋势后植被与气候无显著相关，绿洲整体植被改善，中部退化、南北东恢复。","可引入非线性\u002F因果推断与高分辨率数据，区分灌溉、城市化与气候对干旱区绿洲植被恢复力的驱动。","2026-09-22T23:30:25.304168Z",{"id":189,"title":190,"url":191,"summary":192,"summary_zh":193,"content":9,"source_name":194,"source_url":191,"published_at":195,"category":12,"cover_url":9,"hotness":196,"is_selected":14,"score":197,"score_detail":198,"sources":202,"tags":206,"search_phrases":210,"slug":213,"view_count":35,"doi":214,"paper":215,"created_at":228},3171,"WATER RESOURCES – AN IMPORTANT FACTOR IN HUMAN LIFE AND SUSTAINABLE DEVELOPMENT","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22882203","This thesis discusses the importance of water resources for human life, agriculture, industry and environmental sustainability. Today, climate change, population growth, urbanization and increasing water demand in different economic sectors have made the rational and efficient use of water resources an increasingly important issue. In Central Asia, particularly in Uzbekistan, limited water availability requires improving irrigation efficiency, reducing water losses and expanding modern water-saving technologies. The study examines the main areas of water use, protection of water quality, water conservation in agriculture, wastewater reuse, groundwater protection and the application of digital technologies in water management. Under the conditions of Uzbekistan, drip and sprinkler irrigation, modernization of irrigation canals, automated water accounting, remote sensing and geographic information systems can contribute significantly to improving the efficiency and sustainability of water resources management.","本论文探讨了水资源对人类生活、农业、工业及环境可持续性的重要意义。当今，气候变化、人口增长、城市化以及各经济部门用水需求的不断增加，使水资源的合理高效利用成为日益重要的议题。在中亚地区，尤其是乌兹别克斯坦，水资源可利用量有限，亟需提高灌溉效率、减少水量损失并推广现代节水技术。本研究考察了水资源利用的主要领域、水质保护、农业节水、废水回用、地下水保护以及数字技术在水管理中的应用。在乌兹别克斯坦的条件下，滴灌与喷灌、灌溉渠道现代化改造、自动化水量核算、遥感与地理信息系统可显著提升水资源管理的效率与可持续性。","Zenodo (CERN European Organization for Nuclear Research)","2026-09-21T00:00:00Z",25,60,{"impact":20,"substance":199,"depth":200,"authority":13,"freshness":17,"relevant":21,"comment":201},16,14,"聚焦乌兹别克斯坦水资源与数字灌溉技术，属农业信息化范畴，但为区域性综述论文，公共影响与信源权威度一般。",[203,204],{"name":194,"url":191},{"name":194,"url":205},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22882204",[207,208,26,27,209],"数字农业","节水灌溉","中亚农业",[211,212],"乌兹别克斯坦 节水灌溉","遥感 GIS 水资源管理","乌兹别克斯坦节水灌溉-3171","10.5281\u002Fzenodo.22882203",{"doi":214,"openalex_id":216,"authors":217,"venue":194,"cited_by_count":35,"oa_url":191,"card":222,"direction":62,"ingested_from":64},"W7213866152",[218,220],{"name":219,"orcid":9},"ERGASHALIYEV MUXAMMADAZIZ",{"name":221,"orcid":9},"G'aniyev Samandar",{"tldr":223,"method":224,"finding":225,"direction":226,"opportunity":227},"探讨水资源对人类生活与可持续发展的重要性，并以乌兹别克斯坦为例分析节水灌溉与数字化管理。","文献综述与案例分析，涉及滴灌、喷灌、遥感、GIS和自动化水核算。","在乌兹别克斯坦，滴灌、渠道现代化、遥感与GIS可显著提升水资源管理效率与可持续性。","农业绿色发展与碳","可结合遥感与物联网，量化中亚干旱区节水灌溉对作物产量与碳排放的协同效应。","2026-09-22T23:30:23.028018Z",{"id":230,"title":231,"url":232,"summary":233,"summary_zh":234,"content":9,"source_name":235,"source_url":232,"published_at":236,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":237,"score_detail":238,"sources":240,"tags":242,"search_phrases":245,"slug":248,"view_count":35,"doi":249,"paper":250,"created_at":292},3083,"Multi-index analysis reveals complexity of tundra greening and shrubification on Yamal Peninsula","https:\u002F\u002Fdoi.org\u002F10.1088\u002F2752-664x\u002Faea99e","Abstract Arctic vegetation cover is undergoing rapid structural and spatial change under a warming climate. Shrubification is a major component of these changes, whereby shrubs grow outwards and upwards, infilling existing patches and spreading into new areas. Satellite-derived vegetation indices (VIs), such as the Normalized Difference Vegetation Index (NDVI), show increasing trends across decades in many regions of the Arctic, a phenomenon referred to as greening, and interpreted as an indicator of compositional, structural, spatial and functional changes in vegetation. However, the direct contribution of shrubification on satellite-level greening remains poorly understood, partly due to the spectral limitations of single-index methods and the coarse spatial resolution of multi-decadal satellite records. Here we examine and compare the spatial patterns and magnitude of greening on Yamal Peninsula, Arctic Russia, measured with four commonly used vegetation indices derived from Landsat imagery (1987-2023): NDVI, Enhanced Vegetation Index 2 (EVI2), Soil-Adjusted Vegetation Index (SAVI), and kernel NDVI (kNDVI). We also examine how willow (Salix lanata) cover (%) relates to greening, using cover data derived from field observations, and Unoccupied Aerial Vehicle (UAV) and Very High Resolution WorldView 3 satellite imagery. Vegetation greened in 12–25% of the study area, driven primarily by vegetation regeneration on cryogenic landslides and possibly due to shrub expansion. However, greening magnitude was dependent on the VI selected, as they showed only a maximum of 54% similarity in spatial distribution. Uncertainty in the relationship between spectral greening and shrubification adds complexity to interpreting drivers of vegetation change, including how herbivory, for example by reindeer (Rangifer tarandusi), inhibits shrub expansion and how abiotic and other biotic influences may be detected by different or some combination of VIs. We demonstrate that decadal vegetation greenness changes have not been homogenous on Yamal Peninsula, with contrasting Salix-dominated areas responding differently to shared changes in climate, likely due to herbivore dynamics, soil effects, as well as microclimatic or topographical differences in the area.","摘要 在气候变暖背景下，北极植被覆盖正经历快速的结构和空间变化。灌木化是这些变化的主要组成部分，表现为灌木向外和向上生长，填充现有斑块并向新区域扩散。基于卫星的植被指数（VIs），如归一化差异植被指数（NDVI），在北极许多地区显示出数十年间的增长趋势，这一现象被称为绿化，并被解释为植被组成、结构、空间和功能变化的指标。然而，灌木化对卫星尺度绿化的直接贡献仍知之甚少，部分原因在于单一指数方法的光谱局限性以及多年代际卫星记录的空间分辨率较粗。本研究利用1987—2023年Landsat影像衍生的四种常用植被指数——NDVI、增强植被指数2（EVI2）、土壤调节植被指数（SAVI）和核NDVI（kNDVI）——考察并比较了俄罗斯北极亚马尔半岛绿化的空间格局和幅度。我们还利用野外观测、无人驾驶飞行器（UAV）和甚高分辨率WorldView 3卫星影像获得的覆盖度数据，研究了柳树（Salix lanata）覆盖度（%）与绿化的关系。研究区12%—25%的区域出现植被绿化，主要由低温滑坡上的植被再生驱动，也可能源于灌木扩张。然而，绿化幅度取决于所选用的植被指数，因为它们在空间分布上的相似性最高仅为54%。光谱绿化与灌木化之间关系的不确定性增加了解释植被变化驱动因素的复杂性，包括植食作用（例如驯鹿Rangifer tarandus的啃食）如何抑制灌木扩张，以及非生物和其他生物影响如何通过不同植被指数或其组合被检测到。我们证明，亚马尔半岛数十年尺度的植被绿度变化并非均一，以柳树为主的对比区域对共同的气候变化响应不同，这可能归因于植食动物动态、土壤效应以及该地区微气候或地形的差异。","Environmental Research Ecology","2026-09-18T00:00:00Z",69,{"impact":17,"substance":164,"depth":18,"authority":81,"freshness":17,"relevant":21,"comment":239},"多指数遥感揭示北极苔原绿化与灌木扩张复杂性，方法新颖数据扎实，但属基础生态研究，与三农信息化关联间接，公共价值有限。",[241],{"name":235,"url":232},[169,27,30,243,244],"北极苔原","灌木扩张",[246,247],"北极苔原 灌木扩张 遥感","北极苔原 植被指数 气候变化 灌木扩张","北极苔原灌木扩张遥感-3083","10.1088\u002F2752-664x\u002Faea99e",{"doi":249,"openalex_id":251,"authors":252,"venue":235,"cited_by_count":35,"oa_url":286,"card":287,"direction":62,"ingested_from":64},"W7213598351",[253,256,259,261,263,266,269,272,275,278,280,283],{"name":254,"orcid":255},"Elias Koivisto","https:\u002F\u002Forcid.org\u002F0009-0007-6204-0963",{"name":257,"orcid":258},"Anton Kuzmin","https:\u002F\u002Forcid.org\u002F0000-0001-5066-5535",{"name":260,"orcid":9},"Logan Berner",{"name":262,"orcid":9},"Jeff T Kerby",{"name":264,"orcid":265},"Mariana Verdonen","https:\u002F\u002Forcid.org\u002F0000-0001-9780-0052",{"name":267,"orcid":268},"Anna Skarin","https:\u002F\u002Forcid.org\u002F0000-0003-3221-1024",{"name":270,"orcid":271},"Tiina H. M. Kolari","https:\u002F\u002Forcid.org\u002F0000-0003-0955-2402",{"name":273,"orcid":274},"Teemu Tahvanainen","https:\u002F\u002Forcid.org\u002F0000-0002-7856-299X",{"name":276,"orcid":277},"Pasi Korpelainen","https:\u002F\u002Forcid.org\u002F0009-0005-9956-6016",{"name":279,"orcid":9},"Miguel Villosada",{"name":281,"orcid":282},"Bruce C. Forbes","https:\u002F\u002Forcid.org\u002F0000-0002-4593-5083",{"name":284,"orcid":285},"Timo Kumpula","https:\u002F\u002Forcid.org\u002F0000-0002-2716-7420","https:\u002F\u002Fiopscience.iop.org\u002Farticle\u002F10.1088\u002F2752-664X\u002Faea99e\u002Fpdf",{"tldr":288,"method":289,"finding":290,"direction":62,"opportunity":291},"用四种植被指数分析亚马尔半岛苔原绿化，揭示灌木扩张与光谱绿化的复杂关系。","Landsat 1987-2023年NDVI、EVI2、SAVI、kNDVI及无","绿化面积12-25%，但不同指数空间分布相似度仅54%，灌木扩张与绿化关系不确定。","多指数遥感可揭示植被变化的异质性，需结合地面与高分辨率数据解析生物与非生物驱动机制。","2026-09-21T23:30:27.685080Z",{"id":294,"title":295,"url":296,"summary":297,"summary_zh":298,"content":9,"source_name":10,"source_url":296,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":299,"score_detail":300,"sources":303,"tags":305,"search_phrases":309,"slug":312,"view_count":35,"doi":313,"paper":314,"created_at":333},3074,"Temporal Distribution of Drought Indices Using Remote Sensing in the Desertification Nuclei of Brazil","https:\u002F\u002Fdoi.org\u002F10.29150\u002Fjhrs.v16i03.269019","Desertification is one of the main environmental threats to the Brazilian Semi-Arid region, causing biodiversity loss, soil degradation, and a decline in agricultural productivity. Monitoring droughts through remote sensing is fundamental to understanding climate dynamics and supporting mitigation strategies. In this respect, the objective of this study was to analyze the temporal variability of drought in four recognized desertification nuclei in Northeast Brazil: Cabrobó, Gilbués, Irauçuba, and Seridó, from 2001 to 2024. The methodology consisted of evaluating drought scenarios using the Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI), derived from the MODIS sensor. The results indicated a strong seasonality, with more critical values ​​in the second half of the year, when VCI, TCI, and VHI frequently fell below 30, characterizing moderate to severe drought. The core of the Seridó region presented the highest levels of vulnerability, with average VCI and VHI values ​​below 40 and a strong correlation with precipitation (r > 0.60). The Mann-Kendall test did not indicate statistically significant monthly trends, suggesting stability in the historical drought pattern, although regression analysis revealed signs of worsening in Gilbués. Thus, the effectiveness of SR-derived indices in characterizing drought events and highlighting the combined influence of climatic, edaphic, and anthropogenic factors was confirmed. It is concluded that systematic monitoring using SR is essential to support adaptation and mitigation policies in the face of desertification in the Brazilian Semi-Arid region.","荒漠化是巴西半干旱地区面临的主要环境威胁之一，会导致生物多样性丧失、土壤退化以及农业生产力下降。通过遥感监测干旱是理解气候动态并支撑缓解策略的基础。在此背景下，本研究旨在分析2001年至2024年间巴西东北部四个公认的荒漠化核心区——卡布罗博、吉尔布埃斯、伊拉乌苏巴和塞里多——干旱的时间变异性。研究方法包括利用源自MODIS传感器的植被状态指数（VCI）、温度状态指数（TCI）和植被健康指数（VHI）评估干旱情景。结果表明存在强烈的季节性，下半年数值更为严峻，VCI、TCI和VHI频繁低于30，表现为中度至重度干旱。塞里多核心区脆弱性最高，VCI和VHI平均值低于40，且与降水量呈强相关（r > 0.60）。Mann-Kendall检验未显示统计学显著的月度趋势，表明历史干旱模式具有稳定性，尽管回归分析揭示了吉尔布埃斯存在恶化的迹象。因此，遥感衍生指数在刻画干旱事件以及揭示气候、土壤和人为因素综合影响方面的有效性得到证实。结论是，系统性的遥感监测对于支持巴西半干旱地区应对荒漠化的适应与缓解政策至关重要。",70,{"impact":20,"substance":301,"depth":80,"authority":81,"freshness":17,"relevant":21,"comment":302},20,"基于MODIS遥感指数分析巴西四大荒漠化核心区2001—2024年干旱时序变化，方法规范、数据跨度长，对遥感干旱监测有参考价值，但属区域性研究，公共影响有限。",[304],{"name":10,"url":296},[306,27,29,307,308],"荒漠化","巴西半干旱区","植被健康指数",[310,311],"巴西 荒漠化 遥感 干旱","巴西半干旱区 植被健康指数 干旱监测 遥感监测","巴西荒漠化遥感干旱-3074","10.29150\u002Fjhrs.v16i03.269019",{"doi":313,"openalex_id":315,"authors":316,"venue":10,"cited_by_count":35,"oa_url":296,"card":328,"direction":62,"ingested_from":64},"W7213779605",[317,320,322,325,326,327],{"name":318,"orcid":319},"Juarez Antônio da Silva Júnior","https:\u002F\u002Forcid.org\u002F0000-0002-2898-0309",{"name":321,"orcid":9},"Gabriel Henrique Santos Silva",{"name":323,"orcid":324},"Ubiratan Joaquim da Silva","https:\u002F\u002Forcid.org\u002F0000-0001-7995-6416",{"name":53,"orcid":9},{"name":50,"orcid":51},{"name":55,"orcid":56},{"tldr":329,"method":330,"finding":331,"direction":62,"opportunity":332},"基于MODIS遥感指数分析巴西四个荒漠化核心区2001-2024年干旱时空变化。","用MODIS数据计算VCI、TCI、VHI，结合Mann-Kendall趋势检验","干旱呈强季节性，下半年最严重；Seridó最脆弱，Gilbués有恶化迹象。","可结合多源遥感与机器学习构建荒漠化区干旱预警模型，并量化人为因素贡献。","2026-09-21T23:30:25.707774Z"]