[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4596":3,"related-4596":98},{"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":24,"tags":26,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":66,"slug":69,"view_count":70,"doi":71,"paper":72,"created_at":97},4596,"Spatio-temporal analysis of land use\u002Fland cover (LULC) changes using GIS techniques in Upper Bhavani River Basin, Nilgiri Hills, India","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44274-026-00915-w","The study investigates the land use and land cover (LULC) changes in Upper Bhavani River basin of the Western Ghats over the past four decades (1989–2019) using remote sensing (RS) and geographic information system (GIS) techniques. It also explores the correlation between LULC changes and population growth during this period. The study highlights the importance of mapping and monitoring LULC changes in developing better management strategies for the sustainable development of natural resources. The iterative self-organising data analysis technique was used for unsupervised classification to create LULC maps of the riverbasin.The study identified and categorised seven LULC categories, namely water bodies, deciduous forest, evergreen forest, agriculture, plantation, barren land, and settlement. The results of the study showed a complex series of modifications in the LULC in the study basin over the past forty years due to policy changes and conventional agroforestry systems. The study revealed a decrease in agriculture, evergreen forest, and deciduous forest by − 6.88%, − 31.42%, and − 9.88%, respectively, while water bodies, plantations, barren land, and settlement area increased by 7.06%, 17.64%, 13.29%, and 10.23%, respectively. The findings of the study provide insights into specific changes in LULC and help predict which land uses will be impacted in the future. The overall accuracy of the classification was0.73.Overall, this study emphasised the importance of monitoring and mapping LULC changes using RS and GIS techniques to develop better management strategies for the sustainable development of natural resources. The findings of the study were useful for policymakers, land-use planners, and conservationists in developing effective strategies to maintain the ecological balance of the Western Ghats.","本研究利用遥感（RS）和地理信息系统（GIS）技术，探讨了过去四十年（1989—2019年）西高止山脉上巴瓦尼河流域的土地利用与土地覆盖（LULC）变化，并分析了该时期LULC变化与人口增长之间的相关性。研究强调了制图和监测LULC变化对于制定自然资源可持续发展管理策略的重要性。采用迭代自组织数据分析技术进行非监督分类，以生成该流域的LULC图。研究识别并划分了七类LULC，分别为水体、落叶林、常绿林、农业、种植园、裸地和居民点。研究结果表明，受政策变化和传统农林业系统的影响，过去四十年研究流域的LULC经历了一系列复杂的改变。研究揭示，农业、常绿林和落叶林分别减少了−6.88%、−31.42%和−9.88%，而水体、种植园、裸地和居民点面积分别增加了7.06%、17.64%、13.29%和10.23%。研究结果揭示了LULC的具体变化，有助于预测未来哪些土地利用类型将受到影响。分类总体精度为0.73。总体而言，本研究强调了利用RS和GIS技术监测和制图LULC变化对于制定自然资源可持续发展管理策略的重要性。研究结果有助于政策制定者、土地利用规划者和保护主义者制定有效策略，以维持西高止山脉的生态平衡。",null,"Discover Environment","2026-10-08T00:00:00Z","论文",10,false,70,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,20,17,13,8,1,"基于遥感与GIS的四十年土地利用变化实证研究，数据翔实、结论可靠，对流域生态管理与土地规划有参考价值，但属区域案例研究，公共影响层级有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"遥感监测","土地利用","GIS","流域治理","西高止山",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis","I",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,53,61],{"code":33,"score":46,"supported":47,"title":48,"abstract":49,"tags":52},18,true,[29],[50,29,51],"地理信息","geographic information",[29],{"code":54,"score":55,"supported":47,"title":56,"abstract":57,"tags":60},"I3",7,[],[58,59],"遥感","remote sensing",[27],{"code":62,"score":22,"supported":14,"title":63,"abstract":64,"tags":65},"H6",[],[],[28],[67,68],"土地利用 流域治理 西高止山 遥感监测","土地利用 流域治理","土地利用流域治理西高止山遥感监测-4596",2,"10.1007\u002Fs44274-026-00915-w",{"doi":71,"openalex_id":73,"authors":74,"venue":10,"cited_by_count":88,"oa_url":89,"card":90,"direction":94,"ingested_from":96},"W7221028855",[75,77,80,82,84,86],{"name":76,"orcid":9},"Sapna Kinattinkara",{"name":78,"orcid":79},"Thangavelu Arumugam","https:\u002F\u002Forcid.org\u002F0000-0002-2984-283X",{"name":81,"orcid":9},"Karpagamani Vellingiri",{"name":83,"orcid":9},"Manoj Kumar Patley",{"name":85,"orcid":9},"Manimaran Arumugam",{"name":87,"orcid":9},"Nigatu Wondrade",0,"https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs44274-026-00915-w.pdf",{"tldr":91,"method":92,"finding":93,"direction":94,"opportunity":95},"用遥感与GIS分析印度上巴瓦尼河流域1989-2019年土地利用变化及其与人口增长的关系。","遥感与GIS、ISODATA非监督分类，划分七类LULC，总体精度0.73。","农业、常绿林和落叶林分别减少6.88%、31.42%、9.88%，水体、种植园、裸地和居民地增加。","农业遥感与作物表型","可结合高精度分类与人口、政策数据，构建LULC变化驱动力模型并预测未来情景。","openalex","2026-10-10T23:30:30.955766Z",{"total":99,"page":22,"page_size":99,"items":100},6,[101,172,245,309,376,433],{"id":102,"title":103,"url":104,"summary":105,"summary_zh":106,"content":9,"source_name":107,"source_url":104,"published_at":108,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":109,"score_detail":110,"sources":114,"tags":116,"primary_topic":119,"secondary_topics":123,"classification":125,"search_phrases":147,"slug":150,"view_count":70,"doi":151,"paper":152,"created_at":171},2943,"SPATIO-TEMPORAL DYNAMICS OF LAND USE AND LAND COVER IN A GRANITE QUARRYING AREA IN MANÉAH, GUINEA: A REMOTE SENSING AND GIS-BASED ANALYSIS FROM 1980 TO 2024","https:\u002F\u002Fdoi.org\u002F10.30574\u002Fgscarr.2026.28.3.0222","Quarrying is a major driver of transformation in peri-urban areas, particularly in spaces experiencing both rapid urbanization and increasing pressure on natural resources. This study analyzes the spatio-temporal dynamics of land cover in the urban commune of Manéah, Guinea, between 1980, 2020, and 2024, in order to characterize the territorial changes associated with the development of extractive activities and urban expansion. The methodological approach relies on the use of multi-temporal satellite imagery, its processing in a GIS environment, supervised classification of the main land cover classes, diachronic analysis of changes, construction of a transition matrix, and evaluation of the quality of the classifications using the Kappa index. The results highlight a profound transformation of the landscape. Between 1980 and 2024, the proportion of built-up areas increased from 7.22% to 32.67%, a rise of 25.45 percentage points, while quarries and construction sites, absent in 1980, represented 2.05% of the territory in 2024, after reaching 7.50% in 2020. Conversely, cultivated land and fallow land increased overall by 18.58 percentage points. In contrast, natural formations experienced a sharp decline: shrub savannas decreased from 40.50% to 1.73%, bodies of water from 31.46% to 11.30%, and mangroves from 8.85% to 0.84%. The Kappa values of 0.76, 0.79, and 0.82 indicate a satisfactory agreement between the classifications. These changes reflect the increasing human impact on the territory, resulting from the combined effects of urbanization, agriculture, and extractive activities. The change matrix also confirms a structural recomposition of the territory, with built-up areas increasing from 963.406 ha to 4,357.55 ha, while shrub savannas decreased from 5,401.819 ha to only 230.389 ha over the entire study period. The study thus highlights the need to further integrate remote sensing data and GIS tools into land-use planning, environmental monitoring, and the spatial management of quarries in Manéah.","采石活动是城郊地区转型的主要驱动力，尤其是在同时经历快速城市化和自然资源压力加剧的区域。本研究分析了几内亚马内阿（Manéah）城市公社在1980年、2020年和2024年的土地覆盖时空动态，以刻画与采掘活动发展和城市扩张相关的领土变化。研究方法依赖于多时相卫星影像的使用、在GIS环境中的处理、主要土地覆盖类别的监督分类、变化的历史对比分析、转移矩阵的构建，以及利用Kappa指数评估分类质量。结果揭示了景观的深刻转变。1980年至2024年间，建成区比例从7.22%增至32.67%，上升了25.45个百分点；而采石场和建筑工地1980年尚不存在，2020年达到7.50%，2024年占领土的2.05%。相反，耕地和休耕地总体增加了18.58个百分点。相比之下，自然 formations 急剧减少：灌木草原从40.50%降至1.73%，水体从31.46%降至11.30%，红树林从8.85%降至0.84%。Kappa值分别为0.76、0.79和0.82，表明分类之间具有令人满意的一致性。这些变化反映了人类对领土日益加剧的影响，这是城市化、农业和采掘活动共同作用的结果。变化矩阵也证实了领土的结构性重组，建成区从963.406公顷增至4，357.55公顷，而灌木草原在整个研究期内从5，401.819公顷降至仅230.389公顷。因此，本研究强调了进一步将遥感数据和GIS工具纳入马内阿的土地利用规划、环境监测和采石场空间管理的必要性。","GSC Advanced Research and Reviews","2026-09-18T00:00:00Z",60,{"impact":21,"substance":46,"depth":111,"authority":13,"freshness":112,"relevant":22,"comment":113},15,9,"基于多时相遥感与GIS的矿区土地利用变化研究，方法规范、数据翔实，但地域性强、与国内农业信息化关联有限，可作为遥感应用案例参考。",[115],{"name":107,"url":104},[117,27,28,29,118],"城镇化","矿区生态",{"code":54,"slug":120,"name":121,"path":122,"parent_code":37},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",[124],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":126},{"candidates":127,"agricultural_evidence":47},[128,132,136,143],{"code":54,"score":111,"supported":47,"title":129,"abstract":130,"tags":131},[59],[58,59],[27],{"code":33,"score":17,"supported":47,"title":133,"abstract":134,"tags":135},[29],[29],[29],{"code":137,"score":138,"supported":47,"title":139,"abstract":140,"tags":142},"I7",3,[],[141],"研究方法",[],{"code":62,"score":70,"supported":14,"title":144,"abstract":145,"tags":146},[],[],[28,118],[148,149],"Manéah 几内亚 土地利用","遥感 GIS 采石场 土地覆盖","Manéah几内亚土地利用-2943","10.30574\u002Fgscarr.2026.28.3.0222",{"doi":151,"openalex_id":153,"authors":154,"venue":107,"cited_by_count":88,"oa_url":104,"card":166,"direction":94,"ingested_from":96},"W7213550535",[155,157,159,162,164],{"name":156,"orcid":9},"Sogbè KEITA",{"name":158,"orcid":9},"Mamady Minata CONDÉ",{"name":160,"orcid":161},"Ibrahima Thiam","https:\u002F\u002Forcid.org\u002F0000-0001-8553-1043",{"name":163,"orcid":9},"Lucien SOLIE",{"name":165,"orcid":9},"Alpha Issaga Pallé Diallo",{"tldr":167,"method":168,"finding":169,"direction":94,"opportunity":170},"基于遥感与GIS分析几内亚Manéah采石区1980-2024年土地利用与覆盖的时空变化。","多时相卫星影像、GIS监督分类、变化矩阵与Kappa精度评价。","建设用地由7.22%升至32.67%，灌丛草原由40.50%降至1.73%，采石场2024年占2.0","可延伸至采石与城市化对周边农地、红树林的耦合影响及生态修复监测研究。","2026-09-19T23:30:32.836654Z",{"id":173,"title":174,"url":175,"summary":176,"summary_zh":177,"content":9,"source_name":178,"source_url":175,"published_at":179,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":180,"score_detail":181,"sources":184,"tags":186,"primary_topic":189,"secondary_topics":190,"classification":192,"search_phrases":226,"slug":229,"view_count":230,"doi":231,"paper":232,"created_at":244},2319,"Assessing Forest Resource Depletion and Rural Livelihood Sustainability in Ovia Southwest, Nigeria using Remote Sensing, GIS, and Qualitative Socio-Economic Data","https:\u002F\u002Fdoi.org\u002F10.70882\u002Fjosrar.2026.v3i5.278","Forest resources are fundamental to rural livelihoods in sub-Saharan Africa, yet rapid land-use change threatens their sustainability. This study assessed forest cover change, available forest resources, socio-economic drivers of household dependence, and community perceptions of forest contributions to socio-economic development in Ovia Southwest LGA., Edo State, Nigeria. A mixed-methods approach was used to integrate remote sensing and GIS analysis of Landsat imagery (1987–2024), a household survey (n = 390), factor analysis, multiple regression, and chi-square tests. Land use land cover classification revealed that natural environment (forest cover) declined from 76.95% (202,031.28ha) in 1987 to 42.07% (110,449.55ha) in 2024, representing a 50% loss. Disturbed forest increased from 13.48% to 27.80%, while farmland expanded from 6.90% to 26.08%. Factor analysis identified four dominant forest resource categories: timber\u002Fcharcoal\u002Ffibres (35.4% variance), medicinal plants\u002Froots\u002Fforest soil (14.8%), fruits\u002Fanimal fodder (9.9%), and meat\u002Fhoney (7.0%). Multiple regression showed socio-economic factors significantly influenced household forest dependence (R² = 0.279, F = 29.779, p \u003C 0.001), with education, age, and occupation as the strongest predictors. Chi-square analysis confirmed that communities perceive a significant contribution of forest resources to socio-economic development (χ² = 221.718, df = 32, p \u003C 0.001). The study concludes that agricultural expansion and timber extraction are primary drivers of forest degradation, and livelihood diversification interventions are urgently needed to reduce forest dependence while sustaining rural well-being. And recommended implementation of community-participatory forest conservation programmes; investment in rural education\u002Fexpanded vocational training to provide alternative income sources; and regular monitoring using remote sensing should continue to track forest cover trends and inform adaptive management.","森林资源是撒哈拉以南非洲农村生计的基础，但快速的土地利用变化威胁着其可持续性。本研究评估了尼日利亚埃多州奥维亚西南地方政府区的森林覆盖变化、可利用森林资源、家庭依赖的社会经济驱动因素以及社区对森林促进社会经济发展的认知。研究采用混合方法，整合了1987—2024年Landsat影像的遥感与GIS分析、入户调查（n = 390）、因子分析、多元回归和卡方检验。土地利用\u002F土地覆盖分类显示，自然环境（森林覆盖）从1987年的76.95%（202,031.28公顷）下降至2024年的42.07%（110,449.55公顷），减少了50%。受干扰森林从13.48%增至27.80%，农田从6.90%扩展至26.08%。因子分析识别出四类主要森林资源：木材\u002F木炭\u002F纤维（方差贡献率35.4%）、药用植物\u002F根茎\u002F森林土壤（14.8%）、水果\u002F动物饲料（9.9%）以及肉类\u002F蜂蜜（7.0%）。多元回归表明，社会经济因素显著影响家庭对森林的依赖（R² = 0.279，F = 29.779，p \u003C 0.001），其中教育程度、年龄和职业是最强的预测因子。卡方分析证实，社区认为森林资源对社会经济发展具有显著贡献（χ² = 221.718，df = 32，p \u003C 0.001）。研究结论认为，农业扩张和木材采伐是森林退化的主要驱动因素，亟需通过生计多样化干预措施来减少对森林的依赖，同时维持农村福祉。研究建议：实施社区参与式森林保护项目；投资农村教育\u002F扩大职业培训以提供替代收入来源；持续利用遥感进行定期监测，以追踪森林覆盖趋势并为适应性管理提供依据。","Journal of Science Research and Reviews","2026-09-12T00:00:00Z",65,{"impact":21,"substance":18,"depth":182,"authority":17,"freshness":112,"relevant":22,"comment":183},16,"基于Landsat长时序遥感与入户调查的尼日利亚森林退化与生计依赖研究，方法扎实、数据翔实，但属区域案例，对国内三农信息化仅有方法借鉴价值。",[185],{"name":178,"url":175},[27,28,29,187,188],"森林资源","农村生计",{"code":54,"slug":120,"name":121,"path":122,"parent_code":37},[191],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":193},{"candidates":194,"agricultural_evidence":47},[195,199,203,210,216,222],{"code":54,"score":111,"supported":47,"title":196,"abstract":197,"tags":198},[59],[58,59],[27],{"code":33,"score":17,"supported":47,"title":200,"abstract":201,"tags":202},[29],[29],[29],{"code":204,"score":99,"supported":47,"title":205,"abstract":206,"tags":209},"H2",[],[207,208],"土壤","soil",[],{"code":211,"score":138,"supported":47,"title":212,"abstract":213,"tags":215},"B6",[],[214],"药用植物",[],{"code":217,"score":138,"supported":47,"title":218,"abstract":219,"tags":221},"C4",[],[220],"饲料",[],{"code":62,"score":22,"supported":14,"title":223,"abstract":224,"tags":225},[],[],[28],[227,228],"农村生计 土地利用 森林资源 遥感监测","农村生计 土地利用","农村生计土地利用森林资源遥感监测-2319",4,"10.70882\u002Fjosrar.2026.v3i5.278",{"doi":231,"openalex_id":233,"authors":234,"venue":178,"cited_by_count":88,"oa_url":175,"card":239,"direction":94,"ingested_from":96},"W7212392638",[235,237],{"name":236,"orcid":9},"David E. Eighemhenrio",{"name":238,"orcid":9},"Akan A. Tom",{"tldr":240,"method":241,"finding":242,"direction":94,"opportunity":243},"结合遥感与入户调查，评估尼日利亚Ovia西南部森林资源枯竭及农户生计依赖。","Landsat影像(1987–2024)、GIS分类、390户问卷、因子分析与回","森林覆盖减少50%，农业扩张与伐木为主因，教育、年龄和职业显著影响生计依赖。","可延伸至多时相遥感与农户生计耦合建模，识别森林退化热点并评估替代生计干预效果。","2026-09-13T23:30:22.724040Z",{"id":246,"title":247,"url":248,"summary":249,"summary_zh":250,"content":9,"source_name":251,"source_url":248,"published_at":252,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":253,"score_detail":254,"sources":257,"tags":259,"primary_topic":262,"secondary_topics":263,"classification":264,"search_phrases":289,"slug":292,"view_count":88,"doi":293,"paper":294,"created_at":308},5572,"Potential erosion risk assessment of Kanak stream basin (Sivas, Sarkisla) with the ICONA model","https:\u002F\u002Fdoi.org\u002F10.51753\u002Fflsrt.1828829","The rapid development of technology following the Industrial Revolution has increased human domination over nature. Erosion, which plays a critical role in the process of natural shaping of the earth, can accelerate over time because of improper utilization of the natural environment by humans. The main objective of this study is to determine the erosion susceptibility of the Kanak Creek Basin, one of the sub-basins in the upper reaches of the Kizilirmak River, using the ICONA model, whose main parameters are slope, lithology, land use and vegetation cover, and Geographic Information Systems (GIS) and Remote Sensing techniques, and to list the measures that can be taken against erosion. According to the results of the ICONA model potential erosion level map, 48% of the study area has low erosion susceptibility. These areas largely correspond to the vicinity of Sama Mountain, which has volcanic rocks resistant to erosion, and the base of Sarkisla Plain where the slope is very low. The plain floor is largely covered with agricultural lands. The expansion of irrigated agriculture in this region is one of the main measures that can be taken against erosion. Erosion susceptibility increases around Turna Mountain on the northern border of the basin and Cal Mountain in the south due to both the increase in slope and the lack of resistance of the rocks in the region to erosion, and corresponds to 30% of the study area. In 22% of the basin, susceptibility to erosion is at a medium level. Most of these areas consist of natural meadows and pastures. It is essential to take measures against overgrazing in these areas to prevent the complete loss of the already sparse vegetation cover. Planning land use in the basin in a sustainable manner, arranging fields and layers perpendicular to the slope, expanding irrigated agriculture, and preventing overgrazing are of vital importance in terms of combating soil erosion.","工业革命以来技术的迅猛发展增强了人类对自然的支配能力。侵蚀在地球自然塑造过程中起着关键作用，而人类对自然环境的不当利用会加速侵蚀进程。本研究的主要目标是利用ICONA模型（其主要参数为坡度、岩性、土地利用和植被覆盖）以及地理信息系统（GIS）和遥感技术，确定克孜勒河上游子流域之一卡纳克溪流域的侵蚀敏感性，并列出可采取的侵蚀防治措施。根据ICONA模型潜在侵蚀等级图的结果，研究区48%的区域侵蚀敏感性较低。这些区域主要对应于具有抗侵蚀火山岩的萨马山附近以及坡度极低的萨尔基什拉平原底部。平原底部大部分为农业用地覆盖。在该地区扩大灌溉农业是防治侵蚀的主要措施之一。在流域北部边界的图尔纳山和南部的恰尔山周围，由于坡度增大以及该地区岩石抗侵蚀能力不足，侵蚀敏感性增加，占研究区面积的30%。流域22%的区域侵蚀敏感性为中等水平。这些区域大部分为天然草甸和牧场。在这些地区采取措施防止过度放牧至关重要，以避免本已稀疏的植被覆盖完全丧失。以可持续方式规划流域土地利用、沿垂直于坡向布置田块和土层、扩大灌溉农业以及防止过度放牧，对防治土壤侵蚀具有至关重要的意义。","Frontiers in Life Sciences and Related Technologies","2026-10-21T00:00:00Z",61,{"impact":21,"substance":46,"depth":255,"authority":17,"freshness":112,"relevant":22,"comment":256},14,"该研究以ICONA模型结合GIS与遥感评估土耳其小流域侵蚀风险，方法规范、结论具体，但属区域性案例，公共影响有限，可作为专业参考而非每日精选。",[258],{"name":251,"url":248},[58,28,260,29,261],"土壤侵蚀","水土保持",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":265},{"candidates":266,"agricultural_evidence":47},[267,271,275,279,285],{"code":33,"score":13,"supported":47,"title":268,"abstract":269,"tags":270},[],[50,29,51],[29],{"code":54,"score":55,"supported":47,"title":272,"abstract":273,"tags":274},[],[58,59],[58],{"code":204,"score":99,"supported":47,"title":276,"abstract":277,"tags":278},[],[207,208],[],{"code":280,"score":138,"supported":47,"title":281,"abstract":282,"tags":284},"H3",[],[283],"灌溉",[],{"code":62,"score":70,"supported":14,"title":286,"abstract":287,"tags":288},[],[],[28,261],[290,291],"ICONA 模型 侵蚀风险","Kanak 流域 侵蚀","ICONA模型侵蚀风险-5572","10.51753\u002Fflsrt.1828829",{"doi":293,"openalex_id":295,"authors":296,"venue":251,"cited_by_count":88,"oa_url":9,"card":302,"direction":94,"ingested_from":96},"W7223117733",[297,299],{"name":298,"orcid":9},"MERİÇ KURT",{"name":300,"orcid":301},"Celal ŞENOL","https:\u002F\u002Forcid.org\u002F0000-0003-0857-866X",{"tldr":303,"method":304,"finding":305,"direction":306,"opportunity":307},"用ICONA模型评估土耳其Kanak流域潜在侵蚀风险并列出防治措施。","ICONA模型结合GIS与遥感，输入坡度、岩性、土地利用与植被覆盖。","48%区域低侵蚀风险，30%高敏感，22%中等，主因坡度与岩性。","农业绿色发展与碳","可将ICONA与遥感时序数据结合，动态监测流域侵蚀并评估农业管理措施效果。","2026-10-22T11:20:39.475037Z",{"id":310,"title":311,"url":312,"summary":313,"summary_zh":314,"content":9,"source_name":315,"source_url":312,"published_at":316,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":88,"score_detail":317,"sources":319,"tags":321,"primary_topic":324,"secondary_topics":329,"classification":331,"search_phrases":353,"slug":356,"view_count":88,"doi":357,"paper":358,"created_at":375},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":88,"substance":88,"depth":88,"authority":88,"freshness":88,"relevant":88,"comment":318},"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。",[320],{"name":315,"url":312},[322,27,28,323],"机器学习","城市扩张",{"code":325,"slug":326,"name":327,"path":328,"parent_code":37},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",[330],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":332},{"candidates":333,"agricultural_evidence":47},[334,339,345,349],{"code":325,"score":111,"supported":47,"title":335,"abstract":337,"tags":338},[336],"machine learning",[322,336],[322],{"code":33,"score":112,"supported":47,"title":340,"abstract":341,"tags":344},[],[342,29,343],"空间分析","spatial analysis",[],{"code":54,"score":55,"supported":47,"title":346,"abstract":347,"tags":348},[],[58,59],[27],{"code":62,"score":22,"supported":14,"title":350,"abstract":351,"tags":352},[],[],[28],[354,355],"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":357,"openalex_id":359,"authors":360,"venue":315,"cited_by_count":88,"oa_url":312,"card":370,"direction":94,"ingested_from":96},"W7223022155",[361,364,366,368],{"name":362,"orcid":363},"Kanenus Fufa Dararo","https:\u002F\u002Forcid.org\u002F0009-0007-5747-1558",{"name":365,"orcid":9},"Goanar Jal Dup",{"name":367,"orcid":9},"Weyesa Merga Chemeda",{"name":369,"orcid":9},"Shankar Karuppannan",{"tldr":371,"method":372,"finding":373,"direction":94,"opportunity":374},"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":377,"title":378,"url":379,"summary":380,"summary_zh":381,"content":9,"source_name":382,"source_url":379,"published_at":383,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":384,"score_detail":385,"sources":387,"tags":389,"primary_topic":392,"secondary_topics":393,"classification":394,"search_phrases":409,"slug":412,"view_count":88,"doi":413,"paper":414,"created_at":432},5323,"Impact of Land Use and Land Cover Change on Vegetation Cover Loss in Rwanda: Evidence from Muhoza Sector, Musanze District (2015–2025)","https:\u002F\u002Fdoi.org\u002F10.38124\u002Fijisrt\u002F26oct696","This study analyzed the impact of land use and land cover (LULC) change on vegetation cover loss in Muhoza Sector, Musanze District, Rwanda, between 2015 and 2025. A quantitative geospatial research design was adopted using multi-temporal Landsat and Sentinel-2 satellite imagery, field-based GPS validation, Geographic Information Systems, and Normalized Difference Vegetation Index (NDVI) analysis. Six land-cover classes—forestland, grassland, cropland, urbanized land, wetland, and water bodies—were mapped using supervised classification and post-classification change detection.","本研究分析了2015年至2025年间卢旺达穆桑泽区穆霍扎地区土地利用与土地覆盖（LULC）变化对植被覆盖丧失的影响。研究采用定量地理空间研究设计，运用多时相Landsat和Sentinel-2卫星影像、基于实地GPS验证、地理信息系统以及归一化植被指数（NDVI）分析。通过监督分类和分类后变化检测，对林地、草地、耕地、城市化用地、湿地和水体六类土地覆盖类型进行了制图。","International Journal of Innovative Science and Research Technology (IJISRT)","2026-10-17T00:00:00Z",55,{"impact":21,"substance":46,"depth":255,"authority":99,"freshness":112,"relevant":22,"comment":386},"基于Landsat与Sentinel-2多时相影像的卢旺达局部土地利用变化与植被损失实证研究，方法规范但属区域案例，国际参考价值有限。",[388],{"name":382,"url":379},[27,28,390,391],"植被覆盖","卢旺达农业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":395},{"candidates":396,"agricultural_evidence":47},[397,401,405],{"code":33,"score":99,"supported":47,"title":398,"abstract":399,"tags":400},[],[50,51],[],{"code":54,"score":70,"supported":14,"title":402,"abstract":403,"tags":404},[],[],[390,27],{"code":62,"score":22,"supported":14,"title":406,"abstract":407,"tags":408},[],[],[28],[410,411],"Muhoza Sector 土地利用","卢旺达 NDVI 植被覆盖","MuhozaSector土地利用-5323","10.38124\u002Fijisrt\u002F26oct696",{"doi":413,"openalex_id":415,"authors":416,"venue":382,"cited_by_count":88,"oa_url":426,"card":427,"direction":94,"ingested_from":96},"W7222817253",[417,419,421,423],{"name":418,"orcid":9},"Vincent Hategekimana",{"name":420,"orcid":9},"Richard Mind J. E.",{"name":422,"orcid":9},"Aboubakar Gasirabo",{"name":424,"orcid":425},"Didier Ntwali","https:\u002F\u002Forcid.org\u002F0000-0002-6914-6652","https:\u002F\u002Fwww.ijisrt.com\u002Fassets\u002Fupload\u002Ffiles\u002FIJISRT26OCT696.pdf",{"tldr":428,"method":429,"finding":430,"direction":94,"opportunity":431},"分析卢旺达Muhoza地区2015–2025年土地利用变化对植被覆盖丧失的影响。","多时相Landsat与Sentinel-2影像、GPS实地验证、GIS与NDVI","六类地物制图揭示建设用地扩张等LULC变化是植被覆盖减少的主要驱动。","可结合高分辨率时序遥感与驱动因子模型，量化小农户尺度城镇化对耕地与植被的胁迫。","2026-10-19T23:30:23.040351Z",{"id":434,"title":435,"url":436,"summary":437,"summary_zh":438,"content":9,"source_name":439,"source_url":436,"published_at":440,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":441,"score_detail":442,"sources":444,"tags":446,"primary_topic":449,"secondary_topics":450,"classification":451,"search_phrases":470,"slug":473,"view_count":22,"doi":474,"paper":475,"created_at":500},4585,"Integrated multi-criteria decision analysis and bivariate statistical modeling for landslide susceptibility zonation in the northwestern Ethiopian highlands","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44475-026-00073-w","Landslides represent a critical geo-environmental hazard in the Ethiopian highlands, specifically within the Telemt, Janamora, and Beyeda districts, where they frequently result in fatalities and the destruction of vital infrastructure and agricultural land. This study integrated Geographic Information Systems (GIS) and remote sensing data to perform landslide susceptibility mapping (LSM) using two distinct modeling approaches: the Frequency Ratio (FR) and the Analytical Hierarchy Process (AHP). A total of 140 data points (98 for training (70%) and 42 for testing (30%)) were considered for modeling and validation. Eleven geo-environmental conditioning factors: Slope, rainfall, lithology, density of lineaments, curvature, aspect, normalized difference vegetation index, land use\u002Fland cover, distance to drainage, drainage density, and soil were analyzed to evaluate their influence on landslide occurrence. According to the AHP model, 13.69% and 26.91% of the study area were classified as very high and high susceptibility zones, respectively. In comparison, the FR model identified 12.09% as very high and 23.78% as high susceptibility zones. Both models underscored that steep slopes, porphyritic basalt unit, high lineament density, proximity to drainage systems, and concave terrain curvature are the primary drivers of slope instability. Conversely, gentle slopes, sandstone unit, and dense vegetation cover were strongly associated with low-susceptibility regions. Model performance was validated using the Receiver Operating Characteristic (ROC) curve, yielding an Area Under the Curve (AUC) value of 0.812 for the AHP model and 0.793 for the FR model, alongside a prediction rate AUC value of 77.4% (0.774) for the AHP model and 70.4% for the FR model, confirming the predictive reliability of both methods. These results provide essential geospatial intelligence for policy-makers and stakeholders to guide disaster risk management, sustainable land-use planning, and targeted rehabilitation efforts in the region.","滑坡是埃塞俄比亚高地，特别是Telemt、Janamora和Beyeda地区面临的严重地质环境灾害，频繁造成人员伤亡以及重要基础设施和农田的破坏。本研究综合地理信息系统（GIS）和遥感数据，采用频率比（FR）和层次分析法（AHP）两种不同的建模方法进行滑坡易发性制图（LSM）。建模与验证共考虑了140个数据点（98个用于训练（70%），42个用于测试（30%））。分析了十一个地质环境条件因子：坡度、降雨量、岩性、线理密度、曲率、坡向、归一化植被指数、土地利用\u002F土地覆被、距水系距离、水系密度和土壤，以评估它们对滑坡发生的影响。根据AHP模型，研究区分别有13.69%和26.91%的区域被划分为极高和高易发区。相比之下，FR模型将12.09%的区域划为极高易发区，23.78%划为高易发区。两种模型均强调，陡坡、斑状玄武岩单元、高线理密度、邻近水系以及凹形地形曲率是斜坡失稳的主要驱动因素。相反，缓坡、砂岩单元和茂密植被覆盖与低易发区密切相关。采用受试者工作特征（ROC）曲线对模型性能进行验证，AHP模型的曲线下面积（AUC）值为0.812，FR模型为0.793，同时AHP模型的预测率AUC值为77.4%（0.774），FR模型为70.4%，证实了两种方法的预测可靠性。这些结果为政策制定者和利益相关者提供了重要的地理空间情报，可指导该地区的灾害风险管理、可持续土地利用规划和有针对性的修复工作。","Discover Hazards","2026-10-09T00:00:00Z",64,{"impact":21,"substance":18,"depth":182,"authority":17,"freshness":21,"relevant":22,"comment":443},"GIS与遥感结合的滑坡易发性制图研究，方法规范、数据扎实，对农业灾害风险管理和土地规划有参考价值，但属区域性案例，公共影响有限。",[445],{"name":439,"url":436},[58,28,29,447,448],"灾害风险","滑坡易发性",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":452},{"candidates":453,"agricultural_evidence":47},[454,458,462,466],{"code":33,"score":13,"supported":47,"title":455,"abstract":456,"tags":457},[],[50,29,51],[29],{"code":54,"score":55,"supported":47,"title":459,"abstract":460,"tags":461},[],[58,59],[58],{"code":204,"score":99,"supported":47,"title":463,"abstract":464,"tags":465},[],[207,208],[],{"code":62,"score":22,"supported":14,"title":467,"abstract":468,"tags":469},[],[],[28],[471,472],"埃塞俄比亚高原 滑坡易发性","GIS 遥感 滑坡风险制图","埃塞俄比亚高原滑坡易发性-4585","10.1007\u002Fs44475-026-00073-w",{"doi":474,"openalex_id":476,"authors":477,"venue":439,"cited_by_count":88,"oa_url":436,"card":495,"direction":94,"ingested_from":96},"W7221122595",[478,481,483,485,487,489,491,493],{"name":479,"orcid":480},"Engdaw Gulbet Tebege","https:\u002F\u002Forcid.org\u002F0009-0008-4252-1249",{"name":482,"orcid":9},"Belete Getahun",{"name":484,"orcid":9},"Yohannes Dessalegn Girma",{"name":486,"orcid":9},"Yibeltal Awoke Temeche",{"name":488,"orcid":9},"Worku Birhan Fenklew",{"name":490,"orcid":9},"Ayalnesh Mihrete Tagele",{"name":492,"orcid":9},"Gashaw Tesfaw Chekole",{"name":494,"orcid":9},"Muluken Mintesinot",{"tldr":496,"method":497,"finding":498,"direction":94,"opportunity":499},"用GIS与遥感结合FR和AHP模型，对埃塞俄比亚高原滑坡易发性进行分区制图与验证。","GIS与遥感数据，11个孕灾因子，频率比与层次分析法，ROC曲线验证。","AHP精度略高（AUC 0.812），陡坡、玄武岩、高线密度与近水系为主要致灾因子。","可将滑坡易发性与农田地块、作物分布叠加，评估农业用地风险并支撑山区土地整治决策。","2026-10-10T23:30:27.880607Z"]