[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3674":3,"related-3674":88},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":9,"secondary_topics":31,"classification":32,"search_phrases":57,"slug":60,"view_count":40,"doi":61,"paper":62,"created_at":87},3674,"Mapping and dynamic monitoring of desertification on the Qinghai-Tibetan Plateau using surface Albedo and Solar-Induced Chlorophyll Fluorescence","https:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pone.0359348","Desertification poses a significant threat to humanity's long-term survival and sustainable development. In this study, four types of 2D desertification assessment models were created by integrating surface albedo with four vegetation-related indicators: NDVI, MSAVI, EVI, and solar-induced chlorophyll fluorescence (SIF). A comprehensive analysis of the spatiotemporal variations in desertification on the Qinghai-Tibetan Plateau (QTP) from 2001 to 2020 was then conducted. Among the four models, the SA-SIF model demonstrated the highest overall accuracy (0.8675; 95% CI: 0.8512-0.8838) and Kappa coefficient (0.8452; 95% CI: 0.8289-0.8615), significantly outperforming the other three models (p \u003C 0.01, McNemar's test). The SA-SIF model's mapping results revealed substantial regional variability in desertification on the QTP, with the degree of desertification decreasing from northwest to southeast. Over the past decade, the expansion of severe and extremely severe desertification on the QTP has shown signs of slowing, although future trends may become more complex due to the interplay of climatic and anthropogenic factors. The SA-SIF model can serve as a reference for future desertification control operations on the QTP.","荒漠化对人类长期生存与可持续发展构成重大威胁。本研究通过将地表反照率与四种植被相关指标——归一化植被指数（NDVI）、修正土壤调整植被指数（MSAVI）、增强型植被指数（EVI）和日光诱导叶绿素荧光（SIF）——相结合，构建了四类二维荒漠化评估模型，并据此对2001年至2020年青藏高原荒漠化的时空变化进行了综合分析。在四种模型中，SA-SIF模型的总体精度（0.8675；95%置信区间：0.8512–0.8838）和Kappa系数（0.8452；95%置信区间：0.8289–0.8615）最高，显著优于其他三种模型（p \u003C 0.01，McNemar检验）。SA-SIF模型的制图结果揭示了青藏高原荒漠化存在显著的区域差异，荒漠化程度自西北向东南递减。过去十年间，青藏高原重度及极重度荒漠化的扩张呈现放缓迹象，但受气候与人为因素交互作用的影响，未来趋势可能趋于复杂。SA-SIF模型可为青藏高原未来的荒漠化治理工作提供参考。",null,"PLoS ONE","2026-09-25T00:00:00Z","论文",10,false,78,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,14,6,1,"提出SA-SIF荒漠化评估模型并揭示青藏高原2001-2020年荒漠化时空演变，方法新颖、结论可靠，对高原生态治理有参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"荒漠化","遥感监测","青藏高原","SIF","生态治理",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":36},"needs_review","2026-10-22.2","rules",{"candidates":37,"agricultural_evidence":14,"reason":56},[38,46,51],{"code":39,"score":40,"supported":41,"title":42,"abstract":43,"tags":45},"H2",3,true,[],[44],"土壤",[],{"code":47,"score":21,"supported":14,"title":48,"abstract":49,"tags":50},"H6",[],[],[26],{"code":52,"score":21,"supported":14,"title":53,"abstract":54,"tags":55},"I3",[],[],[27],"农业相关性需要复核",[58,59],"青藏高原 荒漠化 遥感监测","SA-SIF 模型 叶绿素荧光","青藏高原荒漠化遥感监测-3674","10.1371\u002Fjournal.pone.0359348",{"doi":61,"openalex_id":63,"authors":64,"venue":10,"cited_by_count":78,"oa_url":79,"card":80,"direction":84,"ingested_from":86},"W7214339598",[65,68,71,73,75],{"name":66,"orcid":67},"Zhijian Zhao","https:\u002F\u002Forcid.org\u002F0000-0003-4764-2943",{"name":69,"orcid":70},"Hui Lin","https:\u002F\u002Forcid.org\u002F0000-0003-1278-4351",{"name":72,"orcid":9},"Lei Wu",{"name":74,"orcid":9},"Linling Tang",{"name":76,"orcid":77},"Xin Xiao","https:\u002F\u002Forcid.org\u002F0000-0001-8859-7240",0,"https:\u002F\u002Fjournals.plos.org\u002Fplosone\u002Farticle\u002Ffile?id=10.1371\u002Fjournal.pone.0359348&type=printable",{"tldr":81,"method":82,"finding":83,"direction":84,"opportunity":85},"构建地表反照率与SIF结合的荒漠化评估模型，监测青藏高原2001-2020年荒漠化动态。","融合地表反照率与NDVI、MSAVI、EVI、SIF构建四种二维模型，对比精度。","SA-SIF模型精度最高（总体精度0.8675），荒漠化程度自西北向东南递减，重度扩张减缓。","农业遥感与作物表型","可探索SIF与多源遥感协同的荒漠化早期预警，并量化气候与人类活动贡献。","openalex","2026-09-28T23:30:30.884081Z",{"total":20,"page":21,"page_size":20,"items":89},[90,159,232,307,389,459],{"id":91,"title":92,"url":93,"summary":94,"summary_zh":95,"content":9,"source_name":96,"source_url":93,"published_at":97,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":98,"sources":102,"tags":104,"primary_topic":9,"secondary_topics":108,"classification":109,"search_phrases":127,"slug":130,"view_count":21,"doi":131,"paper":132,"created_at":158},5177,"Long-term associations between land-surface indicators and dust-storm occurrence along the margins of the Taklimakan Desert","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-75251-3","Land-surface change and atmospheric variability jointly shape dust activity in arid regions. We examined land-cover transitions, station dust-storm records, a Sentinel-1 backscatter index, meteorological variables from the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) and dust diagnostics from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) along the margins of the Taklimakan Desert. Within the mapped domain, grassland increased from 9.45% in 1990 to 10.59% in 2023, while barren land decreased from 86.45% to 82.30%. Annual dust-storm-day trends were negative at 21 of 30 stations over available 1990–2024 records, and Sentinel-1 index trends were positive at 22 stations during 2015–2024. Mixed-effects path analysis of 3,804 station-month observations showed that the Sentinel-1 index was negatively associated with modelled dust emission (standardized coefficient = − 0.191; 95% confidence interval: −0.289 to − 0.043). The normalized difference vegetation index (NDVI) and friction velocity had the highest training-set feature importance in the random forest analysis.","地表变化与大气变率共同塑造了干旱地区的沙尘活动。我们沿塔克拉玛干沙漠边缘，研究了土地覆盖转变、台站沙尘暴记录、Sentinel-1后向散射指数、来自欧洲中期天气预报中心第五代再分析资料（ERA5）的气象变量，以及来自现代研究与应用回顾分析第2版（MERRA-2）的沙尘诊断量。在制图范围内，草地面积从1990年的9.45%增加到2023年的10.59%，而裸地面积从86.45%减少到82.30%。在1990—2024年现有记录中，30个台站中有21个台站的年沙尘暴日数呈下降趋势；2015—2024年间，22个台站的Sentinel-1指数呈上升趋势。对3804个台站—月观测值的混合效应路径分析表明，Sentinel-1指数与模拟沙尘排放呈负相关（标准化系数=−0.191；95%置信区间：−0.289至−0.043）。在随机森林分析中，归一化植被指数（NDVI）和摩擦速度在训练集中的特征重要性最高。","Scientific Reports","2026-10-15T00:00:00Z",{"impact":99,"substance":18,"depth":17,"authority":19,"freshness":100,"relevant":21,"comment":101},16,8,"基于多源遥感与30站长期记录，量化地表指标与沙尘暴关联，方法扎实、数据规模可观，对干旱区生态监测有参考价值。",[103],{"name":96,"url":93},[105,26,27,106,107],"NDVI","土地利用","沙尘暴",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":110},{"candidates":111,"agricultural_evidence":14,"reason":56},[112,118,123],{"code":113,"score":40,"supported":41,"title":114,"abstract":115,"tags":117},"H7",[],[116],"干旱",[],{"code":47,"score":119,"supported":14,"title":120,"abstract":121,"tags":122},2,[],[],[106,26],{"code":52,"score":119,"supported":14,"title":124,"abstract":125,"tags":126},[],[],[105,27],[128,129],"塔克拉玛干沙漠 沙尘暴 遥感","Sentinel-1 土地覆盖 沙尘","塔克拉玛干沙漠沙尘暴遥感-5177","10.1038\u002Fs41598-026-75251-3",{"doi":131,"openalex_id":133,"authors":134,"venue":96,"cited_by_count":78,"oa_url":152,"card":153,"direction":84,"ingested_from":86},"W7222086957",[135,137,140,143,145,147,149],{"name":136,"orcid":9},"Yifei Wang",{"name":138,"orcid":139},"Wen Huo","https:\u002F\u002Forcid.org\u002F0000-0002-7861-2424",{"name":141,"orcid":142},"Mayibaier Maihamuti","https:\u002F\u002Forcid.org\u002F0009-0007-4084-5891",{"name":144,"orcid":9},"Fan Yang",{"name":146,"orcid":9},"Chenglong Zhou",{"name":148,"orcid":9},"Xinghua Yang",{"name":150,"orcid":151},"Ali Mamtimin","https:\u002F\u002Forcid.org\u002F0000-0001-7335-801X","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-026-75251-3_reference.pdf",{"tldr":154,"method":155,"finding":156,"direction":84,"opportunity":157},"分析塔克拉玛干沙漠边缘地表指标与沙尘暴发生的长期关联。","结合土地覆盖、站点沙尘记录、Sentinel-1后向散射、ERA5与MERRA-","站点沙尘日数多呈下降趋势，Sentinel-1指数与模拟沙尘排放显著负相关。","可引入多源遥感与机器学习量化地表变化对沙尘的因果贡献，并拓展至绿洲农业防护。","2026-10-17T23:30:30.235613Z",{"id":160,"title":161,"url":162,"summary":163,"summary_zh":164,"content":9,"source_name":165,"source_url":162,"published_at":166,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":167,"score_detail":168,"sources":172,"tags":174,"primary_topic":9,"secondary_topics":178,"classification":179,"search_phrases":206,"slug":209,"view_count":119,"doi":210,"paper":211,"created_at":231},5099,"Geospatial analysis of land degradation and desertification in the semi-arid Shabelle River Basin, Somalia","https:\u002F\u002Fdoi.org\u002F10.1080\u002F10106049.2026.2746835","Land degradation and desertification pose major environmental challenges in semi-arid regions such as the Shabelle River Basin in Somalia. This study assessed vulnerability to land degradation and desertification from 2000 to 2025 using multi-temporal Landsat images, CHIRPS rainfall data, Google Earth Engine and GIS techniques. A Desertification Vulnerability Index (DVI) was developed by combining nine environmental indicators, including NDVI, SAVI, BSI, SI, NDBI, NDMI, MNDWI, LST and rainfall, using a weighted overlay analysis. Results indicate that large parts of the basin are vulnerable, with the Shabelle River corridor and southern regions comparatively less affected, while other areas show declines in vegetation and environmental health. The DVI shows a temporal trend toward higher vulnerability. It has been effectively used to assess spatial desertification vulnerability and validated with 341 reference points, showing good discrimination for 2000, 2015 and 2025.","土地退化与荒漠化是索马里谢贝利河流域等半干旱地区面临的主要环境挑战。本研究利用多时相Landsat影像、CHIRPS降雨数据、Google Earth Engine和GIS技术，评估了2000年至2025年土地退化与荒漠化的脆弱性。通过加权叠加分析，结合NDVI、SAVI、BSI、SI、NDBI、NDMI、MNDWI、LST和降雨量等九项环境指标，构建了荒漠化脆弱性指数(DVI)。结果表明，该流域大部分地区较为脆弱，谢贝利河走廊和南部地区受影响相对较小，而其他地区则呈现植被和环境健康下降的趋势。DVI显示出脆弱性随时间升高的趋势。该指数已有效用于评估空间荒漠化脆弱性，并通过341个参考点进行验证，在2000年、2015年和2025年均表现出良好的区分能力。","Geocarto International","2026-10-14T00:00:00Z",75,{"impact":169,"substance":18,"depth":17,"authority":19,"freshness":170,"relevant":21,"comment":171},12,9,"基于多时相遥感和DVI指数的半干旱区土地退化评估，方法扎实、数据规模可观，对干旱区农业生态监测有参考价值，但区域局限于索马里，公共影响层级有限。",[173],{"name":165,"url":162},[175,26,27,176,177],"土地退化","Google Earth Engine","干旱区农业",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":180},{"candidates":181,"agricultural_evidence":14,"reason":56},[182,187,193,197,202],{"code":113,"score":183,"supported":41,"title":184,"abstract":185,"tags":186},4,[],[116],[177],{"code":188,"score":40,"supported":41,"title":189,"abstract":190,"tags":192},"I4",[],[191],"GIS",[],{"code":52,"score":119,"supported":14,"title":194,"abstract":195,"tags":196},[],[],[176,27],{"code":198,"score":21,"supported":14,"title":199,"abstract":200,"tags":201},"H1",[],[],[175],{"code":47,"score":21,"supported":14,"title":203,"abstract":204,"tags":205},[],[],[26],[207,208],"Shabelle River Basin 荒漠化","索马里 土地退化 遥感","ShabelleRiverBasin荒漠化-5099","10.1080\u002F10106049.2026.2746835",{"doi":210,"openalex_id":212,"authors":213,"venue":165,"cited_by_count":78,"oa_url":225,"card":226,"direction":84,"ingested_from":86},"W7221831999",[214,217,220,223],{"name":215,"orcid":216},"Ismail Mohamoud Ali","https:\u002F\u002Forcid.org\u002F0009-0008-7590-6428",{"name":218,"orcid":219},"Gabriel Tetteh","https:\u002F\u002Forcid.org\u002F0000-0003-3603-1952",{"name":221,"orcid":222},"Mahad Abdullahi Hussein","https:\u002F\u002Forcid.org\u002F0009-0002-4093-6308",{"name":224,"orcid":9},"Abdirahman Mohamed Nor","https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Fpdf\u002F10.1080\u002F10106049.2026.2746835?needAccess=true",{"tldr":227,"method":228,"finding":229,"direction":84,"opportunity":230},"基于多时相遥感与GIS构建荒漠化脆弱性指数，评估索马里谢贝利河流域2000-2025年土地退化与荒漠","Landsat影像、CHIRPS降雨、Google Earth Engine与G","流域大部分区域脆弱，DVI呈升高趋势，谢贝利河走廊和南部相对较轻，341个参考点验证效果良好。","可引入机器学习与高分辨率时序数据提升DVI预测精度，并耦合社会经济因素分析驱动机制。","2026-10-16T23:30:30.183766Z",{"id":233,"title":234,"url":235,"summary":236,"summary_zh":237,"content":9,"source_name":96,"source_url":235,"published_at":238,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":239,"sources":241,"tags":243,"primary_topic":247,"secondary_topics":252,"classification":253,"search_phrases":281,"slug":284,"view_count":78,"doi":285,"paper":286,"created_at":306},4900,"Landscape fragmentation and carbon storage dynamics under co-evolving governance in the Shaanxi Yellow River wetland","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-67308-0","Wetland sustainability emerges from coupled interactions among governance, hydrology, land-use change, landscape structure and ecosystem services. Guided by Evolutionary Governance Theory, this study examines their co-evolution in the Shaanxi Yellow River Wetland from 1992 to 2023. Governance trajectories, hydrological dynamics and human land-use processes are treated as interacting antecedent conditions expressed through land use\u002Fland cover transitions, while multidimensional landscape fragmentation and land use\u002Fland cover-based estimated carbon storage are assessed as complementary structural and functional outcomes. Descriptive policy-document frequency and milestone analyses, multi-source remote sensing, the Integrated Landscape Fragmentation Index, InVEST carbon modelling, spatial autocorrelation, and overlay analysis were integrated to examine the relationships between governance evolution, landscape fragmentation and carbon storage. Estimated total carbon storage increased by 34.64%. Fragmentation, however, followed a fluctuating trajectory, intensifying through 2010, temporarily easing in 2020 and increasing again by 2023, with persistent spatial hotspots. High estimated carbon storage repeatedly co-occurred with high fragmentation, indicating heterogeneous pattern–function alignment and mismatch rather than uniform ecological recovery. Interpreted contextually, these trajectories show that more frequent policy issuance and increasing legal integration coexisted with hydrological variability, cropland transitions, aquaculture expansion and path-dependent land-use pressures. Carbon-storage gains alone therefore cannot indicate landscape recovery. Adaptive wetland governance should align restoration with hydrological processes, landscape configuration and multiple ecosystem functions.","湿地可持续性源于治理、水文、土地利用变化、景观结构与生态系统服务之间的耦合互动。本研究以演化治理理论为指导，考察1992年至2023年陕西黄河湿地上述要素的共演化过程。治理轨迹、水文动态与人类土地利用过程被视为相互作用的前置条件，并通过土地利用\u002F土地覆盖转移加以表征；而多维景观破碎化与基于土地利用\u002F土地覆盖估算的碳储量则作为互补的结构性与功能性结果予以评估。研究综合运用描述性政策文件频次与里程碑分析、多源遥感、综合景观破碎化指数、InVEST碳模型、空间自相关及叠加分析，以考察治理演化、景观破碎化与碳储量之间的关系。估算碳储量总量增加了34.64%。然而，破碎化呈波动轨迹，至2010年持续加剧，2020年暂时缓解，到2023年再度上升，并存在持续的空间热点。高估算碳储量与高破碎化反复共现，表明格局—功能关系呈现异质性的一致与错配，而非均质的生态恢复。结合语境加以解读，这些轨迹表明，政策发布频率增加与法律整合程度提高，与水文变异性、耕地转移、水产养殖扩张及路径依赖型土地利用压力并存。因此，仅凭碳储量增益无法表明景观恢复。适应性湿地治理应将恢复与水文过程、景观配置及多重生态系统功能相协调。","2026-10-12T00:00:00Z",{"impact":99,"substance":18,"depth":17,"authority":19,"freshness":100,"relevant":21,"comment":240},"基于多源遥感与InVEST模型揭示陕西黄河湿地治理—景观—碳储协同演化，方法扎实、结论有政策参考价值。",[242],{"name":96,"url":235},[27,244,245,30,246],"湿地保护","碳储量","景观破碎化",{"code":52,"slug":248,"name":249,"path":250,"parent_code":251},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[],{"status":254,"locked":14,"version":34,"method":35,"evidence":255},"classified",{"candidates":256,"agricultural_evidence":41},[257,264,271,276],{"code":52,"score":258,"supported":41,"title":259,"abstract":260,"tags":263},7,[],[261,262],"遥感","remote sensing",[27],{"code":265,"score":20,"supported":41,"title":266,"abstract":267,"tags":270},"D",[],[268,269],"水产","aquaculture",[],{"code":47,"score":183,"supported":41,"title":272,"abstract":273,"tags":275},[],[274],"生态系统服务",[244],{"code":277,"score":21,"supported":14,"title":278,"abstract":279,"tags":280},"H4",[],[],[245],[282,283],"陕西黄河湿地 碳储量","黄河湿地 景观破碎化","陕西黄河湿地碳储量-4900","10.1038\u002Fs41598-026-67308-0",{"doi":285,"openalex_id":287,"authors":288,"venue":96,"cited_by_count":78,"oa_url":299,"card":300,"direction":84,"ingested_from":86},"W7221528662",[289,291,294,297],{"name":290,"orcid":9},"Menghan Gao",{"name":292,"orcid":293},"Khai Ern Lee","https:\u002F\u002Forcid.org\u002F0000-0002-1463-3787",{"name":295,"orcid":296},"Aida Soraya Shamsuddin","https:\u002F\u002Forcid.org\u002F0000-0001-5212-7714",{"name":298,"orcid":9},"Bing He","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-026-67308-0_reference.pdf",{"tldr":301,"method":302,"finding":303,"direction":304,"opportunity":305},"研究陕西黄河湿地1992-2023年治理、景观破碎化与碳储量的协同演变关系。","政策文本分析、多源遥感、景观破碎化指数、InVEST碳模型与空间自相关。","碳储量增34.64%，但破碎化波动加剧，高碳储量与高破碎化反复共存。","农业绿色发展与碳","可探究治理政策频率与景观格局错配机制，构建水文-格局-碳功能协同的适应性治理评估框架。","2026-10-14T23:30:28.853576Z",{"id":308,"title":309,"url":310,"summary":311,"summary_zh":312,"content":9,"source_name":313,"source_url":310,"published_at":314,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":315,"score_detail":316,"sources":321,"tags":323,"primary_topic":9,"secondary_topics":327,"classification":328,"search_phrases":359,"slug":362,"view_count":40,"doi":363,"paper":364,"created_at":388},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。","Journal of Hyperspectral Remote Sensing","2026-09-19T00:00:00Z",70,{"impact":169,"substance":317,"depth":318,"authority":319,"freshness":100,"relevant":21,"comment":320},20,17,13,"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。",[322],{"name":313,"url":310},[26,27,324,325,326],"干旱监测","巴西半干旱区","植被健康指数",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":329},{"candidates":330,"agricultural_evidence":41,"reason":358},[331,337,341,347,352],{"code":113,"score":332,"supported":41,"title":333,"abstract":335,"tags":336},15,[334],"drought",[116,334],[324],{"code":52,"score":332,"supported":41,"title":338,"abstract":339,"tags":340},[262],[261,262],[27],{"code":47,"score":258,"supported":41,"title":342,"abstract":343,"tags":346},[],[344,345],"生物多样性","biodiversity",[26],{"code":39,"score":20,"supported":41,"title":348,"abstract":349,"tags":351},[],[44,350],"soil",[],{"code":353,"score":40,"supported":41,"title":354,"abstract":355,"tags":357},"I7",[],[356],"研究方法",[],"多个产业证据相当，需要确认主归属",[360,361],"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":363,"openalex_id":365,"authors":366,"venue":313,"cited_by_count":78,"oa_url":310,"card":383,"direction":84,"ingested_from":86},"W7213779605",[367,370,372,375,377,380],{"name":368,"orcid":369},"Juarez Antônio da Silva Júnior","https:\u002F\u002Forcid.org\u002F0000-0002-2898-0309",{"name":371,"orcid":9},"Gabriel Henrique Santos Silva",{"name":373,"orcid":374},"Ubiratan Joaquim da Silva","https:\u002F\u002Forcid.org\u002F0000-0001-7995-6416",{"name":376,"orcid":9},"Sylvana Sylvana Melo dos Santos",{"name":378,"orcid":379},"Anderson Luiz Ribeiro de Paiva","https:\u002F\u002Forcid.org\u002F0000-0003-3475-1454",{"name":381,"orcid":382},"Leidjane Maria Maciel de Oliveira","https:\u002F\u002Forcid.org\u002F0000-0003-1251-6998",{"tldr":384,"method":385,"finding":386,"direction":84,"opportunity":387},"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",{"id":390,"title":391,"url":392,"summary":393,"summary_zh":394,"content":9,"source_name":395,"source_url":392,"published_at":396,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":397,"score_detail":398,"sources":400,"tags":402,"primary_topic":405,"secondary_topics":409,"classification":411,"search_phrases":433,"slug":436,"view_count":21,"doi":437,"paper":438,"created_at":458},2323,"Land cover transformations in northern Algeria from 2001 to 2021: A MODIS-based spatiotemporal analysis","https:\u002F\u002Fdoi.org\u002F10.30493\u002Fdas.2026.011109","Land use\u002Fland cover (LULC) changes in northern Algeria from 2001 to 2021 were investigated in this research. The assessment utilized the MODIS MCD12Q1 dataset combined with Geographic Information System (GIS) techniques. Substantial landscape transformations were highlighted by the findings. Forests (+47.52%), shrublands (+17.65%), wetlands (+58.64%), and natural vegetation (+465.72%) experienced notable growth, whereas a drop of −14.13% was documented for barren lands by the end of study period. Moderate overall growth was displayed by agricultural lands, despite various fluctuations throughout the timeline. Concurrently, a continuous expansion (+3.90%) driven by escalating anthropogenic pressure was recorded in urban and built-up areas. Regional landscape evolution is clearly shaped by a combination of factors. Climatic variability, ecological succession, land management practices, and human activities collectively drive these observed dynamics. Partial alignment with previously documented vegetation recovery and urban expansion trends in Algeria was demonstrated by comparative literature reviews. However, the moderate spatial resolution (500 m) of the MODIS MCD12Q1 product likely caused several identified data discrepancies. Ultimately, the immense value of remote sensing and GIS approaches for regional environmental monitoring is proven by this project. Achieving better classification accuracy in heterogeneous Mediterranean environments, however, strictly necessitates the use of higher-resolution datasets.","本研究探讨了2001年至2021年阿尔及利亚北部土地利用\u002F土地覆盖（LULC）变化。评估采用MODIS MCD12Q1数据集结合地理信息系统（GIS）技术。研究结果凸显了显著的土地景观转变。森林（+47.52%）、灌木地（+17.65%）、湿地（+58.64%）和自然植被（+465.72%）显著增长，而裸地在研究期末则记录了−14.13%的下降。尽管农业用地在时间线上经历了多次波动，但总体上呈现出适度增长。与此同时，城市和建成区因人为压力不断加剧而记录了持续扩张（+3.90%）。区域景观演变显然由多种因素共同塑造。气候变率、生态演替、土地管理实践和人类活动共同驱动了这些观测到的动态。比较文献综述表明，这与阿尔及利亚先前记录的植被恢复和城市扩张趋势部分吻合。然而，MODIS MCD12Q1产品的中等空间分辨率（500米）可能导致了若干已识别的数据差异。最终，本项目证明了遥感和GIS方法在区域环境监测中的巨大价值。然而，要在异质性较强的地中海环境中实现更好的分类精度，严格需要使用更高分辨率的数据集。","DYSONA – Applied Science","2026-09-11T00:00:00Z",62,{"impact":100,"substance":17,"depth":332,"authority":169,"freshness":170,"relevant":21,"comment":399},"基于MODIS数据的阿尔及利亚北部20年土地覆被变化分析，方法规范、数据翔实，对遥感监测与区域生态评估有参考价值，但属境外区域研究，国内产业影响有限。",[401],{"name":395,"url":392},[403,26,27,106,404],"农业信息化","植被恢复",{"code":188,"slug":406,"name":407,"path":408,"parent_code":251},"gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis",[410],{"code":52,"slug":248,"name":249,"path":250,"parent_code":251},{"status":254,"locked":14,"version":34,"method":35,"evidence":412},{"candidates":413,"agricultural_evidence":41},[414,420,424,428],{"code":188,"score":170,"supported":41,"title":415,"abstract":416,"tags":419},[],[417,191,418],"地理信息","geographic information",[],{"code":52,"score":100,"supported":41,"title":421,"abstract":422,"tags":423},[],[261,262],[404,27],{"code":47,"score":119,"supported":14,"title":425,"abstract":426,"tags":427},[],[],[106,26],{"code":429,"score":21,"supported":14,"title":430,"abstract":431,"tags":432},"I1",[],[],[403],[434,435],"农业信息化 土地利用 植被恢复 遥感监测","农业信息化 土地利用","农业信息化土地利用植被恢复遥感监测-2323","10.30493\u002Fdas.2026.011109",{"doi":437,"openalex_id":439,"authors":440,"venue":395,"cited_by_count":78,"oa_url":392,"card":453,"direction":84,"ingested_from":86},"W7212238590",[441,443,446,449,451],{"name":442,"orcid":9},"Bilel Zerouali",{"name":444,"orcid":445},"Richarde Marques da Silva","https:\u002F\u002Forcid.org\u002F0000-0001-6601-5174",{"name":447,"orcid":448},"Nadjem Bailek","https:\u002F\u002Forcid.org\u002F0000-0001-9051-8548",{"name":450,"orcid":9},"Valeriano Carneiro de Lima Silva",{"name":452,"orcid":9},"Celso Augusto Guimarães Santos",{"tldr":454,"method":455,"finding":456,"direction":84,"opportunity":457},"基于MODIS数据分析了2001—2021年阿尔及利亚北部土地覆盖的时空变化。","使用MODIS MCD12Q1数据集结合GIS技术进行LULC分类与变化检测。","森林、灌丛、湿地和自然植被显著增长，裸地减少，建设用地持续扩张。","可引入高分辨率遥感数据提升地中海异质景观分类精度，并耦合气候与人为驱动因子做归因分析。","2026-09-13T23:30:23.070977Z",{"id":460,"title":461,"url":462,"summary":463,"summary_zh":464,"content":9,"source_name":313,"source_url":462,"published_at":465,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":466,"sources":468,"tags":470,"primary_topic":9,"secondary_topics":474,"classification":475,"search_phrases":500,"slug":503,"view_count":78,"doi":504,"paper":505,"created_at":521},5577,"Assessing Land Use and Land Cover Change in the Jamanxim River Region (Brazilian Amazon) from 2015 to 2025 Using CBERS-4\u002FPAN Imagery","https:\u002F\u002Fdoi.org\u002F10.29150\u002Fjhrs.v16i4.269068","Land use and land cover (LULC) changes in the Amazon are among the main drivers of biodiversity loss, ecosystem degradation, and the intensification of climate change. This study aimed to analyze the multitemporal dynamics of LULC around the Jamanxim River, Pará, Brazilian Amazon, between 2015 and 2025, using high-resolution imagery from the CBERS-4\u002FPAN satellite. The study area covers 492.74 km², including part of the Jamanxim National Forest, a conservation unit under strong pressure from agricultural expansion and logging activities. The methodology included geometric correction of the images, Gram–Schmidt pansharpening, and supervised classification with the Random Forest algorithm, validated with historical imagery from Google Earth Pro. Thematic maps of land use and cover were generated, and performance metrics such as overall accuracy, omission and commission errors, and F1-scores were assessed. The results indicated a significant reduction in forest cover, from 412.28 km² in 2015 to 355.47 km² in 2025 (–13.78%). Non-vegetated areas increased by 132.47%, while agricultural areas expanded by 54.97%. The forest and water body classes showed high accuracy (F1-score > 0.95), while confusion persisted between agricultural and bare soil classes. Overall accuracy remained above 90% across all years, with the highest performance recorded in 2020 (96.31%). These results highlight the potential of CBERS-4\u002FPAN imagery for monitoring multitemporal changes in tropical forest landscapes. At the same time, they reveal the intensification of deforestation and the growing threats to conservation in the Amazon, reinforcing the importance of remote sensing for environmental management and policy support.","亚马逊地区的土地利用与土地覆盖（LULC）变化是生物多样性丧失、生态系统退化以及气候变化加剧的主要驱动因素之一。本研究旨在利用CBERS-4\u002FPAN卫星的高分辨率影像，分析2015年至2025年间巴西亚马孙州雅曼辛河（Jamanxim River）周边土地利用与土地覆盖的多时相动态。研究区面积为492.74 km²，包括雅曼辛国家森林（Jamanxim National Forest）的一部分，该保护区正面临农业扩张和采伐活动的强烈压力。研究方法包括影像几何校正、Gram–Schmidt全色锐化以及基于随机森林（Random Forest）算法的监督分类，并利用Google Earth Pro的历史影像进行验证。研究生成了土地利用与覆盖专题图，并评估了总体精度、漏分误差与错分误差以及F1分数等性能指标。结果表明，森林覆盖显著减少，从2015年的412.28 km²降至2025年的355.47 km²（–13.78%）。无植被区域增加了132.47%，农业区域扩张了54.97%。森林和水体类别表现出较高精度（F1分数 > 0.95），而农业类别与裸土类别之间仍存在混淆。各年份总体精度均保持在90%以上，其中2020年性能最高（96.31%）。这些结果凸显了CBERS-4\u002FPAN影像在监测热带森林景观多时相变化方面的潜力，同时揭示了亚马逊地区森林砍伐的加剧以及保护面临的日益增长的威胁，进一步强调了遥感在环境管理和政策支持中的重要性。","2026-10-20T00:00:00Z",{"impact":17,"substance":18,"depth":318,"authority":169,"freshness":170,"relevant":21,"comment":467},"该研究利用CBERS-4\u002FPAN影像量化亚马逊保护区十年间森林减少13.78%，方法规范、结论可靠，对遥感监测与生态保护有参考价值，但地域性强、与国内三农直接关联有限。",[469],{"name":313,"url":462},[27,106,471,472,473],"森林保护","亚马逊","CBERS-4",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":476},{"candidates":477,"agricultural_evidence":41,"reason":358},[478,482,486,492,496],{"code":47,"score":258,"supported":41,"title":479,"abstract":480,"tags":481},[],[344,345],[106],{"code":52,"score":258,"supported":41,"title":483,"abstract":484,"tags":485},[],[261,262],[27],{"code":113,"score":20,"supported":41,"title":487,"abstract":488,"tags":491},[],[489,490],"气候变化","climate change",[],{"code":39,"score":40,"supported":41,"title":493,"abstract":494,"tags":495},[],[350],[],{"code":353,"score":40,"supported":41,"title":497,"abstract":498,"tags":499},[],[356],[],[501,502],"CBERS-4 亚马逊 土地利用","Jamanxim 森林覆盖 遥感","CBERS-4亚马逊土地利用-5577","10.29150\u002Fjhrs.v16i4.269068",{"doi":504,"openalex_id":506,"authors":507,"venue":313,"cited_by_count":78,"oa_url":462,"card":516,"direction":84,"ingested_from":86},"W7223141286",[508,509,510,512,513,514],{"name":373,"orcid":374},{"name":371,"orcid":9},{"name":511,"orcid":369},"Juarez Antonio da Silva",{"name":378,"orcid":379},{"name":381,"orcid":382},{"name":515,"orcid":9},"Sylvana Melo dos Santos",{"tldr":517,"method":518,"finding":519,"direction":84,"opportunity":520},"用CBERS-4\u002FPAN影像分析亚马逊Jamanxim河流域2015-2025年土地利用变化。","几何校正、Gram-Schmidt融合、随机森林监督分类，Google Eart","森林覆盖减少13.78%，农业扩张54.97%，裸地增132.47%，总体精度超90%。","可探索中巴地球资源卫星在热带森林退化监测中的业务化应用与多源数据融合。","2026-10-22T11:20:42.901761Z"]