[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2307":3,"related-2307":91},{"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":70,"slug":73,"view_count":74,"doi":75,"paper":76,"created_at":90},2307,"Population Growth and Environmental Impacts of Changing Land use And Landcover in the FCC, Abuja, Nigeria","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fijgem.vol.12.no3.2026.pg80.87","This study examined the trend in population growth in the Federal Capital City between 1994 and 2024, as well as the environmental impacts of changing land use and landcover (LULC). Population datasets of the study area were acquired from the National Population Commission (NPC) and used to examine population trend in the last thirty (30) years using quantitative techniques. Questionnaire was used to elicit the perceived environmental impact of changing LULC in the the study area. The study established that FCC in 1994 had a population of 125,125 people with 11.55% at the growth rate of 3.68%. In 2004 the population was 198,866 at the rate of 3.70% with a change of 73,741 people representing 20.76%. In 2014 at the rate of 3.74%, the population was 299,991 people with an increase of 101,125 people representing 31.32% growth. Lastly, in 2024 at the growth rate of 3.75%, the population increased to 458,884people with increase of 158,893 people representing 47.91%. The study further established climate change, Biodiversity loss, altered hydrological cycles, soil degradation and pollution as the major environmental impact of LULC change as a result of urbanization processes. The study therefore recommended; introduction and further expansion of family planning policies to control birth rate, incorporate the use of remote sensing and GIS in its entire sectors to enhance data sharing and monitoring and planning for a better and sustainable development. In addition, incorporating the use of geo-tech analysis (remote sensing and GIS) in its entire sectors to enhance data sharing and monitoring of a better and sustainable development is recommended. There should also be a strict adherence to land use control measures in order to strike a balance between economic development and eco-system conservation, constantly monitor land developments activities; to check land resource degradation and improving management through involvement of local communities.","本研究考察了1994年至2024年间联邦首都区的人口增长趋势，以及土地利用与土地覆盖（LULC）变化所带来的环境影响。研究区域的人口数据集来自国家人口委员会（NPC），并采用定量技术分析了过去三十（30）年的人口趋势。研究使用问卷来获取研究区域LULC变化对环境影响的感知。研究确定，1994年联邦首都区人口为125,125人，增长率为3.68%，增幅为11.55%。2004年人口为198,866人，增长率为3.70%，变化人数为73,741人，占20.76%。2014年，在3.74%的增长率下，人口为299,991人，增加101,125人，占31.32%的增长。最后，2024年在3.75%的增长率下，人口增至458,884人，增加158,893人，占47.91%。研究进一步确定，气候变化、生物多样性丧失、水文循环改变、土壤退化以及污染是城市化进程导致LULC变化的主要环境影响。因此，研究建议：引入并进一步扩展计划生育政策以控制出生率；在其所有部门中纳入遥感和GIS的应用，以加强数据共享、监测和规划，从而实现更好和可持续的发展。此外，建议在其所有部门中纳入地理技术分析（遥感和GIS）的应用，以加强数据共享和监测，促进更好和可持续的发展。还应严格遵守土地利用控制措施，以在经济开发与生态系统保护之间取得平衡，持续监测土地开发活动；通过地方社区参与来遏制土地资源退化并改善管理。",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},"研究对象为尼日利亚阿布贾土地利用与人口增长，与三农、农业信息化及中国数字乡村议题无直接关联，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","城市化",[],{"status":26,"locked":14,"version":27,"method":28,"evidence":29},"needs_review","2026-10-22.2","rules",{"candidates":30,"agricultural_evidence":14,"reason":69},[31,40,47,55,62],{"code":32,"score":33,"supported":34,"title":35,"abstract":36,"tags":39},"H6",7,true,[],[37,38],"生物多样性","biodiversity",[22],{"code":41,"score":33,"supported":34,"title":42,"abstract":43,"tags":46},"I3",[],[44,45],"遥感","remote sensing",[21],{"code":48,"score":49,"supported":34,"title":50,"abstract":51,"tags":54},"H2",6,[],[52,53],"土壤","soil",[],{"code":56,"score":49,"supported":34,"title":57,"abstract":58,"tags":61},"H7",[],[59,60],"气候变化","climate change",[],{"code":63,"score":64,"supported":34,"title":65,"abstract":66,"tags":68},"I4",3,[],[67],"GIS",[],"农业相关性需要复核",[71,72],"土地利用 遥感监测 城市化","土地利用 遥感监测","土地利用遥感监测城市化-2307",2,"10.56201\u002Fijgem.vol.12.no3.2026.pg80.87",{"doi":75,"openalex_id":77,"authors":78,"venue":10,"cited_by_count":15,"oa_url":81,"card":82,"direction":88,"ingested_from":89},"W7212143894",[79],{"name":80,"orcid":9},"Innocent E. Bello","https:\u002F\u002Fiiardjournals.org\u002Fget\u002FIJGEM\u002FVOL. 12 NO. 3 2026\u002FPOPULATION GROWTH AND ENVIRONMENTAL 80-87.pdf",{"tldr":83,"method":84,"finding":85,"direction":86,"opportunity":87},"研究尼日利亚阿布贾30年人口增长与土地利用变化的环境影响。","用NPC人口数据、问卷及遥感GIS分析LULC变化。","人口从12.5万增至45.9万，引发气候变化、生物多样性丧失等环境问题。","农业遥感与作物表型","可结合遥感GIS与人口数据，构建土地利用变化环境影响的动态监测与预警模型。","智慧农业 \u002F 农业物联网","openalex","2026-09-13T23:30:11.160057Z",{"total":49,"page":92,"page_size":49,"items":93},1,[94,146,222,294,345,421],{"id":95,"title":96,"url":97,"summary":98,"summary_zh":99,"content":9,"source_name":100,"source_url":97,"published_at":101,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":102,"score_detail":103,"sources":110,"tags":112,"primary_topic":9,"secondary_topics":115,"classification":116,"search_phrases":129,"slug":132,"view_count":15,"doi":133,"paper":134,"created_at":145},5182,"Land Use Land Cover (LULC) Change Detection in Delhi NCT Using Multi-Sensor Satellite Data and Google Earth Engine","https:\u002F\u002Fdoi.org\u002F10.21275\u002Fsr26903183702","Land Use Land Cover (LULC) change detection is essential for understanding the dynamics of human modified landscapes and for supporting effective land management and urban planning. This study analyses LULC change across the Delhi National Capital Territory over a fifteen-year period, from 2010 to 2025, to assess urban sprawl and its environmental impact in one of India's fastest growing metropolitan regions. Multi temporal Landsat imagery was used as the primary data source, processed on Google Earth Engine, the cloud-based platform that enabled efficient handling and visualisation of large geospatial datasets. Five classes, built up area, agricultural land, vegetation, water, and barren land, were mapped and monitored, and classification accuracy was assessed for both dates. The Normalised Difference Vegetation Index was additionally employed to track vegetation vigour and ecological change. Results reveal a marked expansion of built-up areas alongside a substantial decline in agricultural and vegetated land, driven by peri urban growth along the northwestern and southwestern fringe. NDVI analysis shows rising greenness across the outer belt, reflecting more intensive cultivation on land that remains under crops, a pattern that complements rather than contradicts the measured loss of vegetated area. Combining classification based and an index-based approach provides a robust, scalable framework for LULC monitoring. By revealing where and how urban growth is reshaping the landscape, the study offers a transferable basis for environmental assessment, resource management, and sustainable urban planning in rapidly urbanising regions worldwide.","土地利用\u002F土地覆盖（LULC）变化检测对于理解人类改造景观的动态以及支撑有效的土地管理和城市规划至关重要。本研究分析了德里国家首都辖区在2010年至2025年十五年间的土地利用\u002F土地覆盖变化，以评估印度增长最快的大都市区之一的城市蔓延及其环境影响。研究以多时相Landsat影像作为主要数据源，在Google Earth Engine这一基于云的平台上进行处理，该平台能够高效处理和可视化大型地理空间数据集。研究对建成区、农业用地、植被、水体与裸地五个类别进行了制图和监测，并对两个时相的分类精度进行了评估。此外，研究采用归一化植被指数（NDVI）追踪植被长势与生态变化。结果表明，建成区显著扩张，农业用地和植被用地大幅减少，这一变化主要由西北部和西南部边缘的近郊增长所驱动。NDVI分析显示外围地带的绿度上升，反映出仍处于耕作状态的土地上集约化种植程度提高，这一格局与所测得的植被面积损失相辅相成而非相互矛盾。将基于分类的方法与基于指数的方法相结合，为土地利用\u002F土地覆盖监测提供了一个稳健且可扩展的框架。通过揭示城市增长在何处以及如何重塑景观，本研究为全球快速城市化地区的环境评估、资源管理和可持续城市规划提供了可迁移的基础。","International Journal of Science and Research (IJSR)","2026-10-15T00:00:00Z",62,{"impact":104,"substance":105,"depth":106,"authority":107,"freshness":108,"relevant":92,"comment":109},12,18,15,8,9,"方法可迁移的遥感LULC变化检测研究，对快速城市化地区土地管理有参考价值，但属区域案例、非三农核心议题。",[111],{"name":100,"url":97},[113,21,22,114,23],"NDVI","Google Earth Engine",[],{"status":117,"locked":14,"version":27,"method":28,"evidence":118},"unclassified",{"candidates":119,"agricultural_evidence":34,"reason":128},[120,124],{"code":41,"score":64,"supported":14,"title":121,"abstract":122,"tags":123},[],[],[114,113,21],{"code":32,"score":92,"supported":14,"title":125,"abstract":126,"tags":127},[],[],[22],"缺少足够的主题证据",[130,131],"德里 土地利用 遥感","Google Earth Engine 城市扩张","德里土地利用遥感-5182","10.21275\u002Fsr26903183702",{"doi":133,"openalex_id":135,"authors":136,"venue":100,"cited_by_count":15,"oa_url":139,"card":140,"direction":86,"ingested_from":89},"W7222341300",[137],{"name":138,"orcid":9},"Neil Rohatgi","https:\u002F\u002Fwww.ijsr.net\u002Farchive\u002Fv15i10\u002FSR26903183702.pdf",{"tldr":141,"method":142,"finding":143,"direction":86,"opportunity":144},"基于多时相Landsat与GEE分析德里国家首都辖区2010-2025年土地利用变化。","多时相Landsat影像、Google Earth Engine平台、五类分类与","建设用地显著扩张，农业与植被用地大幅减少，城郊西北和西南边缘增长驱动。","可结合分类与指数方法构建可迁移框架，拓展至城乡交错带耕地保护与可持续规划研究。","2026-10-17T23:30:31.767409Z",{"id":147,"title":148,"url":149,"summary":150,"summary_zh":151,"content":9,"source_name":152,"source_url":149,"published_at":153,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":154,"sources":156,"tags":158,"primary_topic":159,"secondary_topics":164,"classification":165,"search_phrases":191,"slug":194,"view_count":195,"doi":196,"paper":197,"created_at":221},3493,"Urbanization and Land Use\u002FLand Cover Change in Jalingo Local Government Area, Taraba State, Nigeria: A Multi-Temporal Remote Sensing and Socio-Economic Assessment","https:\u002F\u002Fdoi.org\u002F10.54117\u002Fcanhm718","Rapid urbanization is a major driver of land use and land cover (LULC) transformation, particularly in rapidly developing cities of sub-Saharan Africa. This study examined the impact of urbanization on LULC in Jalingo Local Government Area of Taraba State, Nigeria, with particular emphasis on the period 1994–2024. The study integrated multi-temporal Landsat satellite imagery, Geographic Information Systems (GIS), post-classification change detection and questionnaire data to assess the spatial and temporal dynamics of urban growth and its environmental and socio-economic implications. Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 OLI\u002FTIRS imagery for 1994, 2004, 2014 and 2024 were classified into four major LULC categories: built-up area, vegetation, bare surface and water body. A questionnaire survey involving 384 respondents was also used to assess perceived drivers and consequences of urbanization. The results revealed substantial transformation of the Jalingo landscape. Vegetation declined from 170.56 km² (87.47%) in 1994 to 50.39 km² (25.84%) in 2024, representing a net loss of 120.17 km². In contrast, built-up land increased from 4.30 km² (2.20%) to 18.06 km² (9.26%), while bare surfaces expanded from 18.60 km² (9.54%) to 124.68 km² (63.94%). The most rapid transformation occurred between 2004 and 2014, when vegetation declined by 81.57 km² while bare surfaces increased by 71.79 km² and built-up land by 10.46 km². Survey results indicated that government policies and initiatives, economic opportunities, population growth and infrastructure development were important perceived drivers of urbanization. Most respondents also perceived significant negative effects on agricultural land, livelihoods, food security and access to essential natural resources. The study concludes that urban growth in Jalingo has generated important economic and infrastructural benefits but has also produced substantial environmental degradation and socio-economic pressures. Strengthened land-use planning, protection of agricultural and ecological areas, urban greening, sustainable livelihood programmes, community participation and continuous GIS-based monitoring are recommended.","快速城市化是土地利用与土地覆盖(LULC)变化的主要驱动力，在撒哈拉以南非洲快速发展的城市中尤为突出。本研究考察了尼日利亚塔拉巴州贾林戈地方政府辖区城市化对土地利用与土地覆盖的影响，重点关注1994—2024年这一时期。研究综合运用多时相Landsat卫星影像、地理信息系统(GIS)、分类后变化检测和问卷调查数据，评估城市增长的空间与时间动态及其环境和社会经济影响。将1994年、2004年、2014年和2024年的Landsat 5 TM、Landsat 7 ETM+和Landsat 8 OLI\u002FTIRS影像分为四个主要土地利用与土地覆盖类别：建设用地、植被、裸地表和水体。同时开展了一项涉及384名受访者的问卷调查，以评估城市化的感知驱动因素及其后果。结果表明，贾林戈景观发生了显著转变。植被从1994年的170.56 km²(87.47%)下降至2024年的50.39 km²(25.84%)，净损失120.17 km²。相比之下，建设用地从4.30 km²(2.20%)增至18.06 km²(9.26%)，而裸地表从18.60 km²(9.54%)扩展至124.68 km²(63.94%)。变化最快的时期为2004—2014年，期间植被减少81.57 km²，裸地表增加71.79 km²，建设用地增加10.46 km²。调查结果表明，政府政策和举措、经济机会、人口增长和基础设施建设是城市化的重要感知驱动因素。大多数受访者还认为，城市化对农业用地、生计、粮食安全和基本自然资源的获取产生了显著的负面影响。研究认为，贾林戈的城市增长带来了重要的经济和基础设施效益，但也造成了严重的环境退化和社会经济压力。建议加强土地利用规划、保护农业和生态区域、推进城市绿化、实施可持续生计项目、促进社区参与以及持续开展基于GIS的监测。","OpenAlex","2026-09-24T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":155},"研究对象为尼日利亚Jalingo地区城市化与土地利用变化，属国际区域地理研究，与三农、农业信息化、智慧农业等主题无直接关联，不建议进入每日精选。",[157],{"name":152,"url":149},[21,22,23],{"code":160,"slug":161,"name":162,"path":163,"parent_code":9},"I","digital-agriculture","数字农业与前沿技术","\u002Ftopic\u002Fdigital-agriculture",[],{"status":166,"locked":14,"version":27,"method":28,"evidence":167},"partial",{"candidates":168,"agricultural_evidence":34,"reason":190},[169,173,179,186],{"code":41,"score":108,"supported":34,"title":170,"abstract":171,"tags":172},[45],[],[21],{"code":63,"score":108,"supported":34,"title":174,"abstract":175,"tags":178},[],[176,67,177],"地理信息","geographic information",[],{"code":180,"score":49,"supported":34,"title":181,"abstract":182,"tags":185},"A8",[],[183,184],"粮食安全","food security",[],{"code":32,"score":92,"supported":14,"title":187,"abstract":188,"tags":189},[],[],[22],"一级领域明确，二级方向需要细分",[192,193],"尼日利亚 Jalingo 土地利用","Landsat 遥感 城市化","尼日利亚Jalingo土地利用-3493",4,"10.54117\u002Fcanhm718",{"doi":196,"openalex_id":198,"authors":199,"venue":9,"cited_by_count":15,"oa_url":149,"card":216,"direction":86,"ingested_from":89},"W7214145360",[200,203,206,208,210,212,214],{"name":201,"orcid":202},"Mohammed Bakoji Yusuf","https:\u002F\u002Forcid.org\u002F0000-0002-8719-2396",{"name":204,"orcid":205},"Ambrose Audu Zemba","https:\u002F\u002Forcid.org\u002F0000-0002-7692-9911",{"name":207,"orcid":9},"Huzaima Abubakar Bakoji",{"name":209,"orcid":9},"AUWAL ADAMU BAKAKU",{"name":211,"orcid":9},"UMAR ABBA JAURO",{"name":213,"orcid":9},"Aliyu Mohammed Jingudo",{"name":215,"orcid":9},"Abubakar Isa",{"tldr":217,"method":218,"finding":219,"direction":86,"opportunity":220},"用多时相遥感和问卷评估尼日利亚Jalingo 1994–2024年城市化驱动的土地利用变化。","Landsat 5\u002F7\u002F8影像分类、GIS变化检测与384份问卷。","植被减少120.17 km²，建设用地和裸地大幅扩张，2004–2014变化最快。","可结合多源遥感与农户调查，研究西非城市扩张对农地流失和粮食安全的驱动机制。","2026-09-25T23:30:30.441601Z",{"id":223,"title":224,"url":225,"summary":226,"summary_zh":227,"content":9,"source_name":228,"source_url":225,"published_at":229,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":230,"score_detail":231,"sources":233,"tags":235,"primary_topic":237,"secondary_topics":241,"classification":246,"search_phrases":266,"slug":269,"view_count":74,"doi":270,"paper":271,"created_at":293},3069,"Impact of Urbanization on Agriculture and Wetland Management in Makurdi LGA of Benue State, Nigeria","https:\u002F\u002Fdoi.org\u002F10.65757\u002Fhjev1n22","Wetlands are among the most productive ecosystems, providing essential ecological, hydrological, and socio-economic services, including flood regulation, groundwater recharge, water purification, biodiversity conservation, and agricultural support. However, rapid urbanization has accelerated the conversion of wetlands to built-up areas and agricultural land, threatening their ecological integrity. This study assessed the impact of urbanization on agriculture and wetland management in Makurdi Local Government Area, Benue State, over a twenty-year period (2004–2024). The specific objectives were to examine the spatial distribution and extent of wetlands, evaluate the relationship between urban growth and wetland dynamics, and determine the extent of wetland encroachment resulting from urban development. The study employed Geographic Information Systems (GIS) and Remote Sensing techniques using Landsat 7 ETM+, Landsat 8 OLI\u002FTIRS, and Landsat 9 OLI-2\u002FTIRS-2 satellite imagery acquired for 2004, 2014, and 2024. Image preprocessing, supervised classification, change detection, cross-tabulation matrix analysis, and accuracy assessment were performed in ArcGIS and ERDAS Imagine, while field observations and GPS data were used for ground-truthing and validation. Seven land-use\u002Fland-cover classes were identified: wetlands, farmland, shrubland, forest, water bodies, sandbars, and settlements. The findings revealed significant land-use and land-cover changes over the study period. Wetland coverage declined from 4,478.76 ha (5.37%) in 2004 to 2,664.36 ha (2.39%) in 2024, while settlements expanded from 1,182.60 ha (1.42%) to 5,119.22 ha (4.61%) during the same period. Farmland increased from 39.23% to 41.09%, indicating continued conversion of natural ecosystems to agricultural and urban uses. Cross-tabulation analysis further demonstrated substantial transitions of wetlands and farmlands into settlement areas, confirming that urban expansion has become a major driver of wetland degradation in Makurdi. Classification accuracy assessments yielded overall accuracies ranging from 72.15% to 75.93%, with Kappa coefficients between 0.60 and 0.68, indicating that the classified maps were sufficiently reliable for land-use change analysis. The study concludes that rapid urbanization has significantly contributed to wetland loss and fragmentation and has increasingly encroached on agricultural lands, posing serious threats to ecosystem sustainability, biodiversity conservation, flood regulation, and long-term food security. To address these challenges, the study recommends strengthening wetland protection policies, implementing continuous GIS-based monitoring, promoting sustainable urban development, and establishing institutional frameworks to conserve and effectively manage wetlands and agricultural lands in Makurdi","湿地是最具生产力的生态系统之一，提供重要的生态、水文和社会经济服务，包括洪水调节、地下水补给、水质净化、生物多样性保护和农业支持。然而，快速城市化加速了湿地向建成区和农业用地的转化，威胁其生态完整性。本研究评估了贝努埃州马库尔迪地方政府区二十年期间（2004—2024年）城市化对农业和湿地管理的影响。具体目标包括：考察湿地的空间分布与范围，评估城市增长与湿地动态之间的关系，并确定城市发展导致的湿地侵占程度。研究采用地理信息系统（GIS）和遥感技术，使用2004年、2014年和2024年的Landsat 7 ETM+、Landsat 8 OLI\u002FTIRS和Landsat 9 OLI-2\u002FTIRS-2卫星影像。在ArcGIS和ERDAS Imagine中进行了影像预处理、监督分类、变化检测、交叉列联表矩阵分析和精度评估，同时利用实地观测和GPS数据进行地面验证与确认。研究识别出七类土地利用\u002F土地覆盖类型：湿地、农田、灌丛、森林、水体、沙洲和居民点。研究结果显示，研究期间土地利用和土地覆盖发生了显著变化。湿地覆盖面积从2004年的4,478.76公顷（5.37%）下降至2024年的2,664.36公顷（2.39%），而居民点面积同期从1,182.60公顷（1.42%）扩张至5,119.22公顷（4.61%）。农田面积从39.23%增至41.09%，表明自然生态系统持续向农业和城市用途转化。交叉列联表分析进一步表明，湿地和农田大量转变为居民点用地，证实城市扩张已成为马库尔迪湿地退化的主要驱动因素。分类精度评估的总体精度为72.15%至75.93%，Kappa系数在0.60至0.68之间，表明分类图对于土地利用变化分析具有足够的可靠性。研究认为，快速城市化显著加剧了湿地丧失和破碎化，并日益侵占农业用地，对生态系统可持续性、生物多样性保护","Hensard Journal of Environment","2026-09-20T00:00:00Z",56,{"impact":107,"substance":105,"depth":106,"authority":49,"freshness":108,"relevant":92,"comment":232},"基于Landsat遥感与GIS的尼日利亚湿地退化实证研究，数据扎实但属区域案例，公共影响有限。",[234],{"name":228,"url":225},[183,21,22,23,236],"湿地保护",{"code":63,"slug":238,"name":239,"path":240,"parent_code":160},"gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis",[242],{"code":32,"slug":38,"name":243,"path":244,"parent_code":245},"生态保护与生物多样性","\u002Ftopic\u002Fenvironment\u002Fbiodiversity","H",{"status":247,"locked":14,"version":27,"method":28,"evidence":248},"classified",{"candidates":249,"agricultural_evidence":34},[250,254,258,262],{"code":63,"score":108,"supported":34,"title":251,"abstract":252,"tags":253},[],[176,67,177],[],{"code":32,"score":107,"supported":34,"title":255,"abstract":256,"tags":257},[],[37,38],[22,236],{"code":41,"score":33,"supported":34,"title":259,"abstract":260,"tags":261},[],[44,45],[21],{"code":180,"score":195,"supported":34,"title":263,"abstract":264,"tags":265},[],[184],[183],[267,268],"Makurdi 湿地 城市化","Benue State 遥感","Makurdi湿地城市化-3069","10.65757\u002Fhjev1n22",{"doi":270,"openalex_id":272,"authors":273,"venue":228,"cited_by_count":15,"oa_url":225,"card":288,"direction":86,"ingested_from":89},"W7213745048",[274,276,278,280,282,284,286],{"name":275,"orcid":9},"Joy Iganya Agene",{"name":277,"orcid":9},"Onoja Sunday",{"name":279,"orcid":9},"Akintunde Elijah",{"name":281,"orcid":9},"Ugese Ayangeaor Andrew",{"name":283,"orcid":9},"Kebiru Umoru",{"name":285,"orcid":9},"Aku Umaku Esther",{"name":287,"orcid":9},"Ombugu Gideon",{"tldr":289,"method":290,"finding":291,"direction":86,"opportunity":292},"用遥感与GIS评估尼日利亚马库尔迪20年间城市化对湿地和农业用地的侵占影响。","Landsat 7\u002F8\u002F9影像，监督分类、变化检测与交叉表分析，GPS实地验证。","湿地占比由5.37%降至2.39%，建设用地由1.42%升至4.61%，城市化是湿地退化主因。","可结合多源高分辨率遥感与CA-Markov模型，预测湿地-农田-城市冲突并支撑国土空间优化。","2026-09-21T23:30:24.084401Z",{"id":295,"title":296,"url":297,"summary":298,"summary_zh":299,"content":9,"source_name":10,"source_url":297,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":300,"sources":302,"tags":304,"primary_topic":305,"secondary_topics":309,"classification":310,"search_phrases":330,"slug":331,"view_count":92,"doi":332,"paper":333,"created_at":344},2166,"Household Survey and Geospatial Analysis of Urban Land Use Changes in Uyo Capital City, Akwa Ibom State","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fijgem.vol.12.no3.2026.pg117.137","This study provides a comprehensive assessment of urban expansion in Uyo Capital City from 1986 to 2024, utilizing remote sensing, GIS, and socio-economic analysis. The findings reveal substantial land use\u002Fland cover transformations, particularly the decline in forest cover and agricultural land, and a significant increase in built-up areas. NDVI analysis confirmed a notable reduction in vegetation due to infrastructural development. Population and economic growth emerged as the dominant drivers of urban expansion, corroborated by weighted average analysis, while secondary factors such as infrastructure and policy also contributed. Farmland loss was and land use transformations was identified as the most critical impact, underscoring threats to food security and ecosystem services. The spatial pattern of urbanization followed a concentric model driven by road infrastructure and socio-economic dynamics, with pronounced growth in southeastern Uyo and surrounding LGAs. Future projections using the MOLLUSC model suggest that by 2050, built-up areas will increase by 79%, with corresponding declines in agricultural land, forests, and water bodies. These findings call for proactive, sustainable land-use strategies and integrated urban planning to address the challenges posed by rapid urbanization, ensuring ecological sustainability, socio economic equity, and spatial resilience in Uyo Capital City and similar urbanizing regions.","本研究综合运用遥感、地理信息系统（GIS）和社会经济分析，对1986年至2024年间乌约首府城市的城市扩张进行了全面评估。研究结果揭示了土地利用\u002F土地覆盖的显著变化，尤其是森林覆盖和农业用地的减少，以及建成区面积的大幅增加。归一化植被指数（NDVI）分析证实，基础设施建设导致植被明显减少。人口和经济增长成为城市扩张的主要驱动力，加权平均分析对此予以佐证，而基础设施和政策等次要因素亦有所贡献。农田流失和土地利用转型被确定为最突出的影响，凸显了对粮食安全和生态系统服务的威胁。城市化空间格局遵循以道路基础设施和社会经济动态为驱动的同心圆模式，乌约东南部及周边地方政府区域增长尤为显著。基于MOLLUSC模型的未来预测表明，到2050年，建成区面积将增加79%，农业用地、森林和水体相应减少。这些发现呼吁采取积极主动的可持续土地利用策略和综合城市规划，以应对快速城市化带来的挑战，确保乌约首府城市及类似城市化地区的生态可持续性、社会经济公平和空间韧性。",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":301},"研究尼日利亚乌约市城市扩张与农地流失，属城市地理与遥感领域，与三农、农业信息化主题关联薄弱，不建议进入每日精选。",[303],{"name":10,"url":297},[21,22,23],{"code":41,"slug":306,"name":307,"path":308,"parent_code":160},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",[],{"status":247,"locked":14,"version":27,"method":28,"evidence":311},{"candidates":312,"agricultural_evidence":34},[313,317,321,325],{"code":41,"score":33,"supported":34,"title":314,"abstract":315,"tags":316},[],[44,45],[21],{"code":180,"score":49,"supported":34,"title":318,"abstract":319,"tags":320},[],[183,184],[],{"code":63,"score":49,"supported":34,"title":322,"abstract":323,"tags":324},[],[176,67],[],{"code":32,"score":195,"supported":34,"title":326,"abstract":327,"tags":329},[],[328],"生态系统服务",[22],[71,72],"土地利用遥感监测城市化-2166","10.56201\u002Fijgem.vol.12.no3.2026.pg117.137",{"doi":332,"openalex_id":334,"authors":335,"venue":10,"cited_by_count":15,"oa_url":338,"card":339,"direction":86,"ingested_from":89},"W7212186540",[336],{"name":337,"orcid":9},"D. U. Elijah","https:\u002F\u002Fiiardjournals.org\u002Fget\u002FIJGEM\u002FVOL. 12 NO. 3 2026\u002FHOUSEHOLD SURVEY AND GEOSPATIAL 117-137.pdf",{"tldr":340,"method":341,"finding":342,"direction":86,"opportunity":343},"结合遥感、GIS与入户调查，分析尼日利亚Uyo市1986-2024年城市扩张及其驱动与影响。","遥感、GIS、NDVI、入户调查与MOLLUSC模型预测。","建设用地大增、林农地减少，人口经济是主因，2050年建设用地将再增79%。","可将城市扩张与耕地流失耦合建模，评估粮食安全与生态服务权衡，服务城乡规划。","2026-09-11T23:30:30.079525Z",{"id":346,"title":347,"url":348,"summary":349,"summary_zh":350,"content":9,"source_name":351,"source_url":348,"published_at":352,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":353,"score_detail":354,"sources":358,"tags":360,"primary_topic":9,"secondary_topics":364,"classification":365,"search_phrases":391,"slug":394,"view_count":15,"doi":395,"paper":396,"created_at":420},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。","Journal of Hyperspectral Remote Sensing","2026-10-20T00:00:00Z",78,{"impact":105,"substance":355,"depth":356,"authority":104,"freshness":108,"relevant":92,"comment":357},22,17,"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。",[359],{"name":351,"url":348},[21,22,361,362,363],"森林保护","亚马逊","CBERS-4",[],{"status":26,"locked":14,"version":27,"method":28,"evidence":366},{"candidates":367,"agricultural_evidence":34,"reason":390},[368,372,376,380,384],{"code":32,"score":33,"supported":34,"title":369,"abstract":370,"tags":371},[],[37,38],[22],{"code":41,"score":33,"supported":34,"title":373,"abstract":374,"tags":375},[],[44,45],[21],{"code":56,"score":49,"supported":34,"title":377,"abstract":378,"tags":379},[],[59,60],[],{"code":48,"score":64,"supported":34,"title":381,"abstract":382,"tags":383},[],[53],[],{"code":385,"score":64,"supported":34,"title":386,"abstract":387,"tags":389},"I7",[],[388],"研究方法",[],"多个产业证据相当，需要确认主归属",[392,393],"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":395,"openalex_id":397,"authors":398,"venue":351,"cited_by_count":15,"oa_url":348,"card":415,"direction":86,"ingested_from":89},"W7223141286",[399,402,404,407,410,413],{"name":400,"orcid":401},"Ubiratan Joaquim da Silva","https:\u002F\u002Forcid.org\u002F0000-0001-7995-6416",{"name":403,"orcid":9},"Gabriel Henrique Santos Silva",{"name":405,"orcid":406},"Juarez Antonio da Silva","https:\u002F\u002Forcid.org\u002F0000-0002-2898-0309",{"name":408,"orcid":409},"Anderson Luiz Ribeiro de Paiva","https:\u002F\u002Forcid.org\u002F0000-0003-3475-1454",{"name":411,"orcid":412},"Leidjane Maria Maciel de Oliveira","https:\u002F\u002Forcid.org\u002F0000-0003-1251-6998",{"name":414,"orcid":9},"Sylvana Melo dos Santos",{"tldr":416,"method":417,"finding":418,"direction":86,"opportunity":419},"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",{"id":422,"title":423,"url":424,"summary":425,"summary_zh":426,"content":9,"source_name":427,"source_url":424,"published_at":352,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":428,"sources":430,"tags":432,"primary_topic":435,"secondary_topics":440,"classification":442,"search_phrases":464,"slug":467,"view_count":15,"doi":468,"paper":469,"created_at":486},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",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":429},"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。",[431],{"name":427,"url":424},[433,21,22,434],"机器学习","城市扩张",{"code":436,"slug":437,"name":438,"path":439,"parent_code":160},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",[441],{"code":63,"slug":238,"name":239,"path":240,"parent_code":160},{"status":247,"locked":14,"version":27,"method":28,"evidence":443},{"candidates":444,"agricultural_evidence":34},[445,450,456,460],{"code":436,"score":106,"supported":34,"title":446,"abstract":448,"tags":449},[447],"machine learning",[433,447],[433],{"code":63,"score":108,"supported":34,"title":451,"abstract":452,"tags":455},[],[453,67,454],"空间分析","spatial analysis",[],{"code":41,"score":33,"supported":34,"title":457,"abstract":458,"tags":459},[],[44,45],[21],{"code":32,"score":92,"supported":14,"title":461,"abstract":462,"tags":463},[],[],[22],[465,466],"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":468,"openalex_id":470,"authors":471,"venue":427,"cited_by_count":15,"oa_url":424,"card":481,"direction":86,"ingested_from":89},"W7223022155",[472,475,477,479],{"name":473,"orcid":474},"Kanenus Fufa Dararo","https:\u002F\u002Forcid.org\u002F0009-0007-5747-1558",{"name":476,"orcid":9},"Goanar Jal Dup",{"name":478,"orcid":9},"Weyesa Merga Chemeda",{"name":480,"orcid":9},"Shankar Karuppannan",{"tldr":482,"method":483,"finding":484,"direction":86,"opportunity":485},"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"]