[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2327":3,"related-2327":76},{"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":18,"tags":20,"primary_topic":9,"secondary_topics":24,"classification":25,"search_phrases":56,"slug":59,"view_count":60,"doi":61,"paper":62,"created_at":75},2327,"Land Use and Land Cover Dynamics of Tertiary Institutions as Growth Poles in Zaria Urban Area, Nigeria","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fijgem.vol.12.no3.2026.pg71.82","Tertiary institutions are increasingly recognised as important drivers of urban land transformation and spatial development. The study examines the land use and land cover (LULC) dynamics associated with tertiary institutions in the Zaria Urban Area (ZUA), Kaduna State, Nigeria. Using Geographic Information Systems (GIS) and remote sensing techniques, multi‑temporal spatial data covering the period 1924–2024 were analysed to examine institutional land acquisition and built‑up development. The results show that Zaria Urban Area currently hosts 23 tertiary institutions. Institutional land acquisition increased to 10,825.22 hectares over the study period, representing significant spatial expansion, with only about 32.88% of the acquired land having been developed into built‑up areas. However, residential and circulation accounted for the largest proportions of campus development with 29.26% and 29.53%, respectively, demonstrating that tertiary institutions function as growth poles that influence urban spatial development and land transformation within Zaria. Based on these facts, the study recommended that KADSUPDA should develop institutional land‑use planning frameworks, strengthening collaboration between KADSUPDA and tertiary institutions, promoting sustainable campus development strategies, and integrating institutional expansion into urban master planning.","高等教育机构日益被视为城市土地转型与空间发展的重要驱动力。本研究考察了尼日利亚卡杜纳州扎里亚城市区（ZUA）高等教育机构相关的土地利用与土地覆盖（LULC）动态。研究运用地理信息系统（GIS）和遥感技术，分析了覆盖1924年至2024年的多时相空间数据，以考察机构土地获取与建成区开发情况。结果表明，扎里亚城市区目前拥有23所高等教育机构。在研究期内，机构土地获取面积增至10,825.22公顷，呈现出显著的空间扩张，但其中仅有约32.88%的已获取土地被开发为建成区。然而，住宅和交通用地在校园开发中占比最大，分别为29.26%和29.53%，表明高等教育机构作为增长极，影响着扎里亚的城市空间发展和土地转型。基于上述事实，研究建议卡杜纳州城市规划和开发局（KADSUPDA）制定机构土地利用规划框架，加强KADSUPDA与高等教育机构之间的合作，推广可持续校园发展策略，并将机构扩张纳入城市总体规划。",null,"IIARD INTERNATIONAL JOURNAL OF GEOGRAPHY AND ENVIRONMENTAL MANAGEMENT","2026-09-10T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"研究尼日利亚扎里亚高校驱动的土地利用变化，属城市地理与遥感领域，与三农、农业信息化、智慧农业无关，不建议进入每日精选。",[19],{"name":10,"url":6},[21,22,23],"遥感监测","土地利用","城市扩张",[],{"status":26,"locked":14,"version":27,"method":28,"evidence":29},"needs_review","2026-10-22.2","rules",{"candidates":30,"agricultural_evidence":14,"reason":55},[31,41,49],{"code":32,"score":33,"supported":34,"title":35,"abstract":36,"tags":40},"I4",9,true,[],[37,38,39],"地理信息","GIS","geographic information",[],{"code":42,"score":43,"supported":34,"title":44,"abstract":45,"tags":48},"I3",7,[],[46,47],"遥感","remote sensing",[21],{"code":50,"score":51,"supported":14,"title":52,"abstract":53,"tags":54},"H6",1,[],[],[22],"农业相关性需要复核",[57,58],"土地利用 城市扩张 遥感监测","土地利用 城市扩张","土地利用城市扩张遥感监测-2327",2,"10.56201\u002Fijgem.vol.12.no3.2026.pg71.82",{"doi":61,"openalex_id":63,"authors":64,"venue":10,"cited_by_count":15,"oa_url":67,"card":68,"direction":72,"ingested_from":74},"W7212149575",[65],{"name":66,"orcid":9},"Baba E. Bahago","https:\u002F\u002Fiiardjournals.org\u002Fget\u002FIJGEM\u002FVOL. 12 NO. 3 2026\u002FLAND USE AND LAND COVER DYNAMICS 71-82.pdf",{"tldr":69,"method":70,"finding":71,"direction":72,"opportunity":73},"用GIS与遥感分析尼日利亚扎里亚高校1924-2024年土地利用变化，揭示其作为城市增长极的作用。","GIS与遥感，1924-2024年多时相空间数据，分析机构征地与建成区扩展。","高校征地达10825公顷，仅32.88%建成，住宅与道路占比最大，高校成为城市增长极。","农业遥感与作物表型","可延伸研究高校扩张对周边农业用地与粮食生产的挤压效应及可持续规划。","openalex","2026-09-13T23:30:24.647147Z",{"total":77,"page":51,"page_size":77,"items":78},6,[79,151,198,244,306,366],{"id":80,"title":81,"url":82,"summary":83,"summary_zh":84,"content":9,"source_name":85,"source_url":82,"published_at":86,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":87,"sources":89,"tags":91,"primary_topic":93,"secondary_topics":99,"classification":104,"search_phrases":128,"slug":131,"view_count":15,"doi":132,"paper":133,"created_at":150},5485,"Integrating machine learning and geospatial technologies for spatio-temporal analysis of urban expansion and land use transformation in Gambella Town, Ethiopia","https:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pone.0360419","Rapid urbanization and the associated expansion of built-up areas are transforming land resources, ecosystem functions, and the spatial structure of cities. Distinguishing urban growth, urban expansion, and urban sprawl is essential for understanding the processes and patterns of urban transformation and supporting sustainable urban planning. This study integrates machine learning and geospatial technologies to analyze spatio-temporal land use and land cover (LULC) dynamics and urban expansion in Gambella Town, Ethiopia. Multi-temporal Landsat satellite images from 2005, 2015, and 2025 were processed using remote sensing techniques and a supervised machine learning approach based on the Random Forest (RF) classifier. Six major LULC classes were identified: Agricultural Land, Bush with Grass, Built-Up Area, Bare Land, Forest Land, and Water Bodies. The classification achieved overall accuracies of 90%, 90%, and 89% for 2005, 2015, and 2025, respectively. The results revealed substantial land transformation and rapid physical urban expansion, with the built-up area increasing from 93 ha (2.0%) in 2005–1,956 ha (41.3%) in 2025. This expansion was accompanied by major transformations of surrounding land resources, particularly the conversion of Bush with Grass and other open areas to built-up land. Agricultural land increased from 634 ha (13.4%) to 1,750 ha (36.9%), whereas Bush with Grass declined from 3,375 ha (71.1%) to 652 ha (13.7%). Socio-economic information collected from 277 respondents indicated that population growth, rural–urban migration, housing demand, employment opportunities, and infrastructure development were major drivers of urban expansion. The study distinguishes urban expansion, represented by the increase in built-up land, from urban sprawl, which refers to the spatial pattern and form of outward urban development. The integration of Random Forest classification and GIS-based spatial analysis provides valuable evidence of land transformation, vegetation loss, and increasing pressure on urban services, supporting more sustainable urban planning and land management in Gambella Town.","快速城市化及与之相关的建成区扩张正在改变土地资源、生态系统功能和城市空间结构。区分城市增长（urban growth）、城市扩张（urban expansion）和城市蔓延（urban sprawl），对于理解城市转型的过程与格局、支撑可持续城市规划至关重要。本研究融合机器学习与地理空间技术，分析埃塞俄比亚甘贝拉镇（Gambella Town）土地利用与土地覆盖（LULC）的时空动态及城市扩张。采用遥感技术和基于随机森林（RF）分类器的监督机器学习方法，处理了2005年、2015年和2025年的多时相Landsat卫星影像。研究识别出六类主要LULC类型：农业用地、灌草地、建成区、裸地、林地和水体。2005年、2015年和2025年的分类总体精度分别为90%、90%和89%。结果表明，土地发生了显著转变，城市实体空间快速扩张，建成区面积从2005年的93公顷（2.0%）增至2025年的1,956公顷（41.3%）。这一扩张伴随着周边土地资源的重大转变，尤其是灌草地及其他开阔地被转化为建成用地。农业用地从634公顷（13.4%）增至1,750公顷（36.9%），而灌草地则从3,375公顷（71.1%）降至652公顷（13.7%）。从277名受访者收集的社会经济信息表明，人口增长、城乡迁移、住房需求、就业机会和基础设施建设是城市扩张的主要驱动因素。本研究将城市扩张（以建成用地增加为表征）与城市蔓延（指城市向外发展的空间格局与形态）加以区分。随机森林分类与基于GIS的空间分析的融合，为土地转变、植被丧失及城市服务压力加剧提供了有价值的证据，有助于甘贝拉镇实现更可持续的城市规划与土地管理。","PLoS ONE","2026-10-20T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":88},"研究聚焦埃塞俄比亚城市扩张与土地利用变化，属城市地理与遥感应用，与三农、农业信息化主题无直接关联，不建议进入每日精选。",[90],{"name":85,"url":82},[92,21,22,23],"机器学习",{"code":94,"slug":95,"name":96,"path":97,"parent_code":98},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[100],{"code":32,"slug":101,"name":102,"path":103,"parent_code":98},"gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis",{"status":105,"locked":14,"version":27,"method":28,"evidence":106},"classified",{"candidates":107,"agricultural_evidence":34},[108,114,120,124],{"code":94,"score":109,"supported":34,"title":110,"abstract":112,"tags":113},15,[111],"machine learning",[92,111],[92],{"code":32,"score":33,"supported":34,"title":115,"abstract":116,"tags":119},[],[117,38,118],"空间分析","spatial analysis",[],{"code":42,"score":43,"supported":34,"title":121,"abstract":122,"tags":123},[],[46,47],[21],{"code":50,"score":51,"supported":14,"title":125,"abstract":126,"tags":127},[],[],[22],[129,130],"Gambella Town 城市扩张","Random Forest 土地利用分类","GambellaTown城市扩张-5485","10.1371\u002Fjournal.pone.0360419",{"doi":132,"openalex_id":134,"authors":135,"venue":85,"cited_by_count":15,"oa_url":82,"card":145,"direction":72,"ingested_from":74},"W7223022155",[136,139,141,143],{"name":137,"orcid":138},"Kanenus Fufa Dararo","https:\u002F\u002Forcid.org\u002F0009-0007-5747-1558",{"name":140,"orcid":9},"Goanar Jal Dup",{"name":142,"orcid":9},"Weyesa Merga Chemeda",{"name":144,"orcid":9},"Shankar Karuppannan",{"tldr":146,"method":147,"finding":148,"direction":72,"opportunity":149},"用机器学习与遥感分析埃塞俄比亚甘贝拉镇2005-2025年城市扩张与土地利用变化。","Landsat多时相影像、随机森林分类与GIS空间分析，结合277份问卷。","建成区从93公顷增至1956公顷，灌草地大幅转为建成区和农地。","可将随机森林时序分类与驱动力调查结合，扩展到更多非洲小城镇并耦合城市增长模拟。","2026-10-21T23:30:23.271293Z",{"id":152,"title":153,"url":154,"summary":155,"summary_zh":156,"content":9,"source_name":157,"source_url":154,"published_at":158,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":159,"sources":161,"tags":163,"primary_topic":164,"secondary_topics":168,"classification":169,"search_phrases":180,"slug":183,"view_count":15,"doi":184,"paper":185,"created_at":197},5094,"An Investigation of Built-up Area Expansion in the Syrian Coastal Mountain Environment","https:\u002F\u002Fdoi.org\u002F10.14246\u002Firspsd.14.4_109","As built-up expansion in the Syrian coastal mountainous areas intensifies, its environmental impacts are becoming increasingly severe. Existing research, however, offers limited quantitative evidence to elucidate the dynamics of this phenomenon. This study addresses this gap by employing mixed-method techniques at the district level of Safita. Landsat satellite imagery, remote sensing, and ArcGIS software were used to classify and analyze geospatial data from 2010 to 2020. Statistical methodologies were then applied to investigate spatio-temporal built-up growth, identify the drivers of expansion, and evaluate resultant spatial patterns. The analysis reveals accelerated built-up expansion, with the most dramatic growth occurring in southern peripheral zones, recording increases of 150-169%. The study identifies a persistent trend of low-density, dispersed sprawl following a non-linear trajectory, evidenced by Shannon's entropy increasing steadily to 0.89 by 2020. Analysis of Urban Expansion Rate and Intensity indices shows a distinct shift from moderate, semi-efficient growth (2010–2015) to rapid and extensive sprawl (2015–2020). Furthermore, the Built-up Expansion Index demonstrates an evolution from initial economically driven leapfrog expansion through conflict-induced infilling consolidation to a final hybrid pattern combining edge-expansion and ribbon development. Kernel Density Estimation reveals a fundamental spatial transformation from semi-concentrated hotspots to widespread medium-density sprawl, strongly constrained by physical factors. Specifically, 93% of built-up areas concentrated on gentle slopes (0-15%), and 68% were located within 200 meters of road networks. These findings underscore the urgent need for planning decision-makers to implement strict regulatory measures that curb built-up sprawl, protect agricultural lands and natural resources, and guide growth through updated master plans to achieve sustainable development.","随着叙利亚沿海山区建成区扩张不断加剧，其环境影响日益严重。然而，现有研究在阐明这一现象的动态方面提供的定量证据有限。本研究通过在萨菲塔区级层面采用混合方法技术来填补这一空白。利用Landsat卫星影像、遥感技术和ArcGIS软件对2010年至2020年的地理空间数据进行分类和分析。随后应用统计方法研究建成区的时空增长，识别扩张的驱动因素，并评估由此产生的空间格局。分析揭示了建成区扩张的加速，最显著的增长发生在南部边缘地带，增幅达150%至169%。研究识别出低密度、分散式蔓延的持续趋势，呈非线性轨迹，香农熵（Shannon's entropy）到2020年稳步上升至0.89即为明证。城市扩张速率和强度指数的分析显示，从2010至2015年的温和、半高效增长明显转向2015至2020年的快速、广泛蔓延。此外，建成区扩张指数（Built-up Expansion Index）表明，扩张从最初经济驱动的跳跃式扩展，经过冲突引发的填充式整合，演变为边缘扩展与带状发展相结合的最终混合模式。核密度估计（Kernel Density Estimation）揭示了从半集中热点向广泛中密度蔓延的根本性空间转变，且受自然因素的强烈制约。具体而言，93%的建成区集中在缓坡（0-15%）上，68%位于道路网络200米范围内。这些发现凸显了规划决策者迫切需要实施严格的监管措施，以遏制建成区蔓延，保护农田和自然资源，并通过更新总体规划引导增长，以实现可持续发展。","International Review for Spatial Planning and Sustainable Development","2026-10-14T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":160},"研究叙利亚沿海山区建成区扩张，属城市规划与环境领域，与三农、农业信息化、数字乡村无关。",[162],{"name":157,"url":154},[21,22,23],{"code":42,"slug":165,"name":166,"path":167,"parent_code":98},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",[],{"status":105,"locked":14,"version":27,"method":28,"evidence":170},{"candidates":171,"agricultural_evidence":34},[172,176],{"code":42,"score":43,"supported":34,"title":173,"abstract":174,"tags":175},[],[46,47],[21],{"code":50,"score":51,"supported":14,"title":177,"abstract":178,"tags":179},[],[],[22],[181,182],"叙利亚沿海山区 建成区扩张","Safita 遥感 土地利用","叙利亚沿海山区建成区扩张-5094","10.14246\u002Firspsd.14.4_109",{"doi":184,"openalex_id":186,"authors":187,"venue":157,"cited_by_count":15,"oa_url":191,"card":192,"direction":72,"ingested_from":74},"W7221786958",[188],{"name":189,"orcid":190},"Tarek Rahmoun","https:\u002F\u002Forcid.org\u002F0000-0001-5112-2487","https:\u002F\u002Fwww.jstage.jst.go.jp\u002Farticle\u002Firspsd\u002F14\u002F4\u002F14_6\u002F_pdf",{"tldr":193,"method":194,"finding":195,"direction":72,"opportunity":196},"研究叙利亚沿海山区萨菲塔地区2010-2020年建设用地扩张动态、驱动因素与空间格局。","Landsat影像、遥感与ArcGIS分类，结合统计方法分析时空扩张。","建设用地加速低密度蔓延，93%集中于缓坡、68%靠近道路，熵值升至0.89。","可结合遥感与机器学习，量化山区建设用地扩张对农地流失和生态的长期影响。","2026-10-16T23:30:28.556800Z",{"id":199,"title":200,"url":201,"summary":202,"summary_zh":203,"content":9,"source_name":204,"source_url":201,"published_at":205,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":206,"sources":208,"tags":210,"primary_topic":211,"secondary_topics":212,"classification":213,"search_phrases":228,"slug":229,"view_count":51,"doi":230,"paper":231,"created_at":243},4679,"Spatio-temporal variation of urban sprawl in Tura town using the Shannon entropy model","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23277607","Abstract Urbanization is driving substantial transformation of cities worldwide, with unmanaged expansion often resulting in urban sprawl and the loss of agricultural land, forests, and environmentally sensitive areas. Tura Town, headquarters of West Garo Hills District, has experienced steady urban growth over the past two decades, yet few studies have examined its expansion pattern. This study aims to analyse the spatio-temporal variation and assessing the degree and directional patterns of urban sprawl from 2006 to 2026 using Remote Sensing, GIS, and Shannon's Entropy Index. Landsat imagery was classified into LULC categories, with accuracy validated through a confusion matrix, achieving satisfactory results (77–81%). Built-up area increased from 10 km² to 17 km²—a 70% rise, with faster growth occurring during 2006–2016 (40%) than 2016–2026 (21.4%). Shannon's Entropy Index revealed the compactness or dispersal of growth, while buffer and directional analyses identified expansion patterns. The findings offer valuable insights for sustainable urban planning and land-use management in Tura Town. Keyword: Urban sprawl, Urbanization, Land use\u002Fland cover (LULC), Remote Sensing, GIS, Shannon's Entropy Index, Built-up area, Tura Town, Spatio-temporal analysis, Sustainable urban planning","摘要 城市化正推动全球城市发生深刻转型，而无序扩张往往导致城市蔓延以及农田、森林和环境敏感区域的丧失。作为西加罗丘陵县首府的图拉镇，过去二十年经历了稳定的城市增长，但对其扩张模式的研究却很少。本研究旨在利用遥感、地理信息系统和香农熵指数，分析2006年至2026年城市蔓延的时空变化，并评估其程度与方向性模式。研究将Landsat影像分类为土地利用\u002F土地覆盖（LULC）类别，并通过混淆矩阵验证精度，取得了令人满意的结果（77%–81%）。建成区面积从10平方公里增至17平方公里，增长了70%，其中2006—2016年（40%）的增长快于2016—2026年（21.4%）。香农熵指数揭示了增长的紧凑或分散特征，而缓冲区和方向性分析则识别了扩张模式。研究结果为图拉镇的可持续城市规划和土地利用管理提供了有价值的见解。关键词：城市蔓延，城市化，土地利用\u002F土地覆盖（LULC），遥感，地理信息系统，香农熵指数，建成区，图拉镇，时空分析，可持续城市规划","Zenodo (CERN European Organization for Nuclear Research)","2026-10-10T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":207},"该论文研究印度图拉镇城市扩张的遥感与熵模型分析，属城市地理与土地利用范畴，与三农、农业信息化、智慧农业无直接关联，不建议进入每日精选。",[209],{"name":204,"url":201},[21,22,23],{"code":42,"slug":165,"name":166,"path":167,"parent_code":98},[],{"status":105,"locked":14,"version":27,"method":28,"evidence":214},{"candidates":215,"agricultural_evidence":34},[216,220,224],{"code":42,"score":43,"supported":34,"title":217,"abstract":218,"tags":219},[],[46,47],[21],{"code":32,"score":77,"supported":34,"title":221,"abstract":222,"tags":223},[],[37,38],[],{"code":50,"score":51,"supported":14,"title":225,"abstract":226,"tags":227},[],[],[22],[57,58],"土地利用城市扩张遥感监测-4679","10.5281\u002Fzenodo.23277607",{"doi":230,"openalex_id":232,"authors":233,"venue":204,"cited_by_count":15,"oa_url":201,"card":238,"direction":72,"ingested_from":74},"W7221355035",[234,236],{"name":235,"orcid":9},"Kambai Ch. Marak",{"name":237,"orcid":9},"Bring Blessing L Ryntathiang",{"tldr":239,"method":240,"finding":241,"direction":72,"opportunity":242},"用遥感、GIS和香农熵分析印度图拉镇2006-2026年城市蔓延的时空变化。","Landsat影像分类LULC，混淆矩阵验证精度77-81%，结合香农熵、缓冲与","建成区从10增至17平方公里（增70%），2006-2016年增长快于2016-2026年，熵值揭示","可结合耕地流失与农业用地破碎化，评估城市蔓延对农业生态系统的长期影响。","2026-10-11T23:30:30.230545Z",{"id":245,"title":246,"url":247,"summary":248,"summary_zh":249,"content":9,"source_name":250,"source_url":247,"published_at":251,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":252,"sources":254,"tags":256,"primary_topic":9,"secondary_topics":258,"classification":259,"search_phrases":286,"slug":288,"view_count":60,"doi":289,"paper":290,"created_at":305},4349,"Empirical Urban Growth Dynamics (2000–2025) and A Conceptual Architectural Framework for Spatial Digital Twins in Secondary African Cities: A Case Study of Owerri, Nigeria","https:\u002F\u002Fdoi.org\u002F10.14419\u002F66ab3y55","Rapid urban expansion in secondary cities of Sub-Saharan Africa has intensified pressure on land resources and infrastructure, exposing the limitations of conventional planning systems reliant on periodic assessments. While Geographic Information Systems (GIS), Remote Sensing (RS), and Artificial Intelligence (AI) have improved monitoring, their integration into continuous Spatial Digital Twin (SDT) environments remain limited in Nigeria. To address this gap, this study presents an empirical baseline analysis and formulates a conceptual Spatial Digital Twin framework for sustainable urban growth monitoring in Owerri Metropolis, Nigeria. Historical land use and land cover dynamics between 2000 and 2025 were first quantified using multi-temporal Landsat imagery in Google Earth Engine via Random Forest classification to establish the empirical foundation. Based on observed growth patterns, the study identified key spatial, environmental, and administrative data requirements and formulated a five-layer system architecture. Comprising Physical Environment, Data Acquisition, Spatial Integration, Analytical Intelligence, and Application layers, the framework establishes an architectural roadmap for integrating multi-source spatial data, scenario simulations, and predictive analysis into local planning. The practical utility of the framework is demonstrated through targeted applications in urban expansion tracking, flood hazard evaluation, and Sustainable Development Goal (SDG) 11 monitoring. This study provides a scalable, transferable blueprint to guide municipal authorities rather than claiming an active, fully deployed live software or sensor environment..","撒哈拉以南非洲次级城市的快速城市扩张加剧了土地资源和基础设施的压力，暴露出依赖周期性评估的传统规划体系的局限性。尽管地理信息系统（GIS）、遥感（RS）和人工智能（AI）已改善了监测手段，但在尼日利亚，将其整合到连续的空间数字孪生（SDT）环境中仍存在局限。为弥补这一差距，本研究提出了实证基线分析，并构建了一个概念性空间数字孪生框架，用于尼日利亚奥韦里大都市的可持续城市增长监测。研究首先利用Google Earth Engine中的多时相Landsat影像，通过随机森林分类对2000年至2025年间的历史土地利用与土地覆盖动态进行了量化，以建立实证基础。基于观测到的增长模式，研究识别了关键的空间、环境和行政数据需求，并构建了一个五层系统架构。该框架由物理环境层、数据采集层、空间集成层、分析智能层和应用层组成，为将多源空间数据、情景模拟和预测分析整合到地方规划中建立了架构路线图。该框架的实际效用通过在城市扩张追踪、洪水灾害评估和可持续发展目标（SDG）11监测中的针对性应用得到了验证。本研究提供了一个可扩展、可迁移的蓝图，以指导市政当局，而非声称已建成一个活跃的、全面部署的实时软件或传感器环境。","SPC Journal of Environmental Sciences","2026-10-05T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":253},"研究聚焦尼日利亚城市空间数字孪生与土地利用监测，属城市地理与遥感领域，与三农、农业信息化、智慧农业无直接关联，不建议进入每日精选。",[255],{"name":250,"url":247},[257,21,22,23],"数字孪生",[],{"status":26,"locked":14,"version":27,"method":28,"evidence":260},{"candidates":261,"agricultural_evidence":14,"reason":55},[262,266,272,276,282],{"code":32,"score":33,"supported":34,"title":263,"abstract":264,"tags":265},[],[37,38,39],[],{"code":267,"score":43,"supported":34,"title":268,"abstract":269,"tags":271},"I1",[],[257,270],"digital twin",[257],{"code":42,"score":43,"supported":34,"title":273,"abstract":274,"tags":275},[],[46,47],[21],{"code":94,"score":277,"supported":34,"title":278,"abstract":279,"tags":281},3,[],[280],"artificial intelligence",[],{"code":50,"score":51,"supported":14,"title":283,"abstract":284,"tags":285},[],[],[22],[287,58],"土地利用 城市扩张 数字孪生 遥感监测","土地利用城市扩张数字孪生遥感监测-4349","10.14419\u002F66ab3y55",{"doi":289,"openalex_id":291,"authors":292,"venue":250,"cited_by_count":15,"oa_url":297,"card":298,"direction":304,"ingested_from":74},"W7220677187",[293,295],{"name":294,"orcid":9},"Chukwudi Andy Okereke",{"name":296,"orcid":9},"Prince Chinomso Onuoha","https:\u002F\u002Fwww.sciencepubco.com\u002Findex.php\u002FJES\u002Farticle\u002Fdownload\u002F38502\u002F20173",{"tldr":299,"method":300,"finding":301,"direction":302,"opportunity":303},"基于Landsat影像分析尼日利亚Owerri市2000-2025年城市扩张，提出五层空间数字孪生框","Google Earth Engine多时相Landsat影像与随机森林分类，构","城市扩张显著，SDT框架可支持扩张追踪、洪水评估与SDG11监测。","数字乡村与农业信息化","在非洲次级城市验证SDT实时数据集成与预测能力，并拓展至农业用地监测。","智慧农业 \u002F 农业物联网","2026-10-07T23:30:12.781769Z",{"id":307,"title":308,"url":309,"summary":310,"summary_zh":311,"content":9,"source_name":312,"source_url":309,"published_at":313,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":314,"sources":316,"tags":318,"primary_topic":320,"secondary_topics":325,"classification":326,"search_phrases":349,"slug":352,"view_count":277,"doi":353,"paper":354,"created_at":365},4104,"Urban Expansion as a Driver of Forest Loss: Geospatial Evidence from Asaba Metropolis, Delta State, Nigeria (1991-2021)","https:\u002F\u002Fdoi.org\u002F10.54117\u002Ffyk4yw69","Urban expansion is increasingly recognised as a primary driver of forest loss across sub-Saharan Africa, with far-reaching consequences for biodiversity, climate regulation, carbon sequestration, and human well-being. This paper examines urban expansion as a major cause of forest loss in Asaba metropolis, Delta State, Nigeria, drawing on geospatial analysis of four epochs of Landsat satellite imagery spanning 1991 to 2021. Supervised Maximum Likelihood Classification (MLC) was applied to extract land use and land cover (LULC) data across six categories, while Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI), Land Surface Temperature (LST), and Urban Heat Island (UHI) indices were computed to assess the spatial dimensions of urban-induced environmental change. Overall classification accuracy exceeded 97% for all epochs, with Kappa coefficients ranging from 0.92 to 0.98. Findings reveal that built-up area expanded from 0.91% of the total metropolitan land mass in 1991 to 26.56% in 2021, while vegetation cover declined from 18.19% to 8.83% over the same period. Farm land also contracted from 68.34% to 53.17%, confirming the compound nature of green land loss. NDBI values rose progressively from -0.18 to 0.17 in 1991 to 4.7 to 9.4 in 2021, while NDVI values contracted sharply to a range of -0.09 to 0.39 by 2021, indicating widespread vegetation degradation. Land surface temperature and urban heat island intensity also increased across the study period, reflecting the thermal consequences of reduced green cover and expanding impervious surfaces. Projections indicate that built-up area could reach approximately 51% of the metropolitan land mass by 2051 under current growth trajectories. The study concludes that urban expansion is a primary and ongoing cause of forest loss in Asaba metropolis and calls for integrated land use planning, green infrastructure policies, and strict enforcement of forest conservation regulations as essential steps toward sustainable urban development in peri-urban areas.","城市扩张日益被视为撒哈拉以南非洲森林丧失的主要驱动因素，对生物多样性、气候调节、碳汇和人类福祉产生深远影响。本文基于对1991年至2021年四个时期Landsat卫星影像的地理空间分析，考察了城市扩张作为尼日利亚三角洲州阿萨巴大都市森林丧失主因的作用。研究采用监督最大似然分类法（MLC）提取六类土地利用与土地覆盖（LULC）数据，同时计算归一化植被指数（NDVI）、归一化建筑指数（NDBI）、地表温度（LST）和城市热岛（UHI）指数，以评估城市引发的环境变化的空间维度。所有时期的总体分类精度均超过97%，Kappa系数介于0.92至0.98之间。研究结果表明，建成区面积从1991年占大都市土地总面积的0.91%扩展至2021年的26.56%，而植被覆盖同期从18.19%下降至8.83%。农田也从68.34%缩减至53.17%，证实了绿地丧失的复合性质。NDBI值从1991年的-0.18至0.17逐步上升至2021年的4.7至9.4，而NDVI值到2021年急剧收缩至-0.09至0.39之间，表明植被广泛退化。地表温度和城市热岛强度在研究期间也持续上升，反映了绿地覆盖减少和不透水面扩张的热效应。预测表明，在当前增长轨迹下，到2051年建成区面积可能达到大都市土地总面积的约51%。研究结论认为，城市扩张是阿萨巴大都市森林丧失的主要且持续的原因，并呼吁将综合土地利用规划、绿色基础设施政策和森林保护法规的严格执行作为城郊地区可持续城市发展的必要举措。","OpenAlex","2026-09-30T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":315},"研究尼日利亚城市扩张致森林损失，属城市地理与遥感领域，与三农、农业信息化、数字乡村主题无关，不建议入选。",[317],{"name":312,"url":309},[21,22,23,319],"森林损失",{"code":50,"slug":321,"name":322,"path":323,"parent_code":324},"biodiversity","生态保护与生物多样性","\u002Ftopic\u002Fenvironment\u002Fbiodiversity","H",[],{"status":105,"locked":14,"version":27,"method":28,"evidence":327},{"candidates":328,"agricultural_evidence":34},[329,334,341,345],{"code":50,"score":43,"supported":34,"title":330,"abstract":331,"tags":333},[],[332,321],"生物多样性",[22],{"code":335,"score":77,"supported":34,"title":336,"abstract":337,"tags":340},"H4",[],[338,339],"碳汇","carbon sequestration",[],{"code":32,"score":277,"supported":34,"title":342,"abstract":343,"tags":344},[],[117],[],{"code":42,"score":51,"supported":14,"title":346,"abstract":347,"tags":348},[],[],[21],[350,351],"Asaba 城市扩张 森林损失","尼日利亚 Landsat 遥感","Asaba城市扩张森林损失-4104","10.54117\u002Ffyk4yw69",{"doi":353,"openalex_id":355,"authors":356,"venue":9,"cited_by_count":15,"oa_url":359,"card":360,"direction":72,"ingested_from":74},"W7214933722",[357],{"name":358,"orcid":9},"Ifeanyi Patricia Egwunyenga","https:\u002F\u002Fjournals.ipsintelligentsia.com\u002Fenvironmental-science\u002Findex.php\u002Fijes\u002Farticle\u002Fdownload\u002F44\u002F41",{"tldr":361,"method":362,"finding":363,"direction":72,"opportunity":364},"用1991-2021年Landsat影像分析尼日利亚阿萨巴城市扩张导致的森林与绿地损失。","Landsat影像、最大似然监督分类、NDVI\u002FNDBI\u002FLST\u002FUHI指数与趋","建设用地由0.91%升至26.56%，植被由18.19%降至8.83%，地表温度与热岛强度同步上升。","可结合多源遥感与CA-Markov模型，量化城市扩张对周边农地与碳汇的耦合影响并模拟未来情景。","2026-10-03T23:30:38.105052Z",{"id":367,"title":368,"url":369,"summary":370,"summary_zh":371,"content":9,"source_name":372,"source_url":369,"published_at":373,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":374,"sources":376,"tags":378,"primary_topic":380,"secondary_topics":381,"classification":382,"search_phrases":406,"slug":408,"view_count":277,"doi":409,"paper":410,"created_at":424},3774,"Mapping the Evolution of Urban Sprawl Research: A PRISMA-Based Systematic and Bibliometric Synthesis","https:\u002F\u002Fdoi.org\u002F10.46488\u002Fnept.2026.v25i04.b4435","Urban sprawl represents a major spatial manifestation of contemporary urbanization, reshaping land systems, ecological stability, and sustainability trajectories. This study presents a PRISMA-based systematic review combined with bibliometric and thematic synthesis to examine global urban sprawl research. Following structured screening of 183 records, 54 peer-reviewed journal articles were retained for detailed analysis. Bibliometric mapping using VOSviewer, quantitative comparison, and thematic synthesis were integrated to assess methodological evolution, geographic concentration, and sustainability integration. The findings reveal three developmental phases: an early exploratory stage, a consolidation phase dominated by spatial modeling, and a recent shift toward environmental and climaterelated assessment. Methodologically, Cellular Automata and CA–Markov models account for 40.74% of studies, followed by remote sensing change detection (25.93%), while spatial regression approaches remain limited (3.70%). Urban expansion magnitudes show substantial heterogeneity, with a mean built-up growth of 119.7% and a strongly right-skewed distribution (Sk = 1.97; K = 2.38). Reported growth ranges from below 20% to over 500%, frequently associated with agricultural land conversion and land surface temperature intensification. Classification accuracies typically range from 83% to 91%, indicating high technical reliability. Research output is geographically concentrated in Asia (61.11%), particularly in China and India, while governance-oriented scholarship remains comparatively underrepresented. Overlay analysis indicates an emerging focus on climate change and ecosystem impacts, yet institutional evaluation remains peripheral. Overall, the field demonstrates strong technical maturity but limited integration of policy assessment, underscoring the need for cross-scale causal modeling and standardized sustainability metrics.","城市蔓延是当代城市化的主要空间表现形式，重塑了土地系统、生态稳定性和可持续发展轨迹。本研究基于PRISMA框架开展系统综述，并结合文献计量与主题综合分析，考察全球城市蔓延研究。经过对183条记录的结构化筛选，最终保留54篇同行评审期刊论文进行详细分析。研究整合了基于VOSviewer的文献计量图谱、定量比较和主题综合分析，以评估方法论演进、地理集中度和可持续性整合情况。研究结果揭示了三个发展阶段：早期探索阶段、以空间建模为主导的巩固阶段，以及近期向环境与气候相关评估的转向。在方法论上，元胞自动机（Cellular Automata）和CA–Markov模型占研究的40.74%，其次是遥感变化检测（25.93%），而空间回归方法的运用仍然有限（3.70%）。城市扩张幅度呈现显著异质性，建成区平均增长率为119.7%，分布呈强右偏（Sk = 1.97；K = 2.38）。报告的增长范围从低于20%到超过500%，且常与农用地转换和地表温度加剧相关。分类精度通常在83%至91%之间，表明技术可靠性较高。研究成果在地理上集中于亚洲（61.11%），尤其是中国和印度，而面向治理的学术研究相对不足。叠加分析表明，气候变化和生态系统影响正成为新兴关注焦点，但制度评估仍处于边缘地位。总体而言，该领域展现出较强的技术成熟度，但政策评估的整合有限，凸显了跨尺度因果建模和标准化可持续性指标的必要性。","Nature Environment and Pollution Technology","2026-09-28T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":375},"该文为城市扩张研究的文献计量综述，属城市地理与生态环境领域，与三农、农业信息化、智慧农业无直接关联，不建议进入每日精选。",[377],{"name":372,"url":369},[379,21,22,23],"文献计量",{"code":42,"slug":165,"name":166,"path":167,"parent_code":98},[],{"status":105,"locked":14,"version":27,"method":28,"evidence":383},{"candidates":384,"agricultural_evidence":34},[385,391,395,402],{"code":386,"score":109,"supported":34,"title":387,"abstract":389,"tags":390},"I7",[388],"bibliometric",[379,388],[379],{"code":42,"score":43,"supported":34,"title":392,"abstract":393,"tags":394},[],[46,47],[21],{"code":396,"score":77,"supported":34,"title":397,"abstract":398,"tags":401},"H7",[],[399,400],"气候变化","climate change",[],{"code":50,"score":51,"supported":14,"title":403,"abstract":404,"tags":405},[],[],[22],[407,58],"土地利用 城市扩张 文献计量 遥感监测","土地利用城市扩张文献计量遥感监测-3774","10.46488\u002Fnept.2026.v25i04.b4435",{"doi":409,"openalex_id":411,"authors":412,"venue":372,"cited_by_count":15,"oa_url":369,"card":418,"direction":304,"ingested_from":74},"W7214666438",[413,416],{"name":414,"orcid":415},"Jaswant Singh","https:\u002F\u002Forcid.org\u002F0009-0003-4653-4972",{"name":417,"orcid":9},"Kranti Kumar Maurya",{"tldr":419,"method":420,"finding":421,"direction":422,"opportunity":423},"基于PRISMA系统综述与文献计量，梳理全球城市蔓延研究的演化阶段、方法分布与地理格局。","PRISMA筛选54篇文献，结合VOSviewer文献计量、定量比较与主题综合。","研究历经三阶段，CA与CA-Markov占40.74%，成果集中于亚洲，政策评估与制度研究薄弱。","农业绿色发展与碳","可结合遥感与因果建模，研究城市蔓延导致的农地转换、地表升温及跨尺度可持续性评估。","2026-09-29T23:30:10.523829Z"]