[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2529":3,"related-2529":92},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":43,"search_phrases":72,"slug":75,"view_count":63,"doi":76,"paper":77,"created_at":91},2529,"Flood Risk Assessment and Environmental Change Analysis Using GIS and Remote Sensing","https:\u002F\u002Fdoi.org\u002F10.34248\u002Fbsengineering.1994338","Floods can be very destructive natural hazard; it causes significant environmental, social, and economic impacts. Havza is a district in Northern part of Türkiye, experienced major flood events in May 1998 and May 2026, which emphasize the need of identify flood-prone areas and analyze the factors that influence flood vulnerability. The aim of this study is to asses flood risk and analyzes land use\u002Fland cover (LULC) monitoring derived from remote sensing data in Havza. Furthermore, topographic characteristics were also obtained from Shuttle Radar Topography Mission (SRTM) and Digital Elevation Model (DEM) using Geographic Information Systems (GIS). Hydrological analyses include slope and flow accumulation models, and these analyses were used to identify susceptible areas. It has been observed that the mean NDVI value increased from 0.4239 in 1998 to 0.7447 in 2026, indicating a substantial increase in vegetation cover. LULC classification results also showed that urban areas increased from 16% to 20% while agricultural land decreased 54% to 50% in approximately last 3 decades. 3-Dimensional (3D) terrain visualization and river corridor-based flood risk mapping revealed that low elevation valley floors and settlements located very near to stream channels, which is the most vulnerable areas of floods. The findings of this study demonstrate the effectiveness of integration of GIS and remote sensing, topographic analysis, and LULC change detection within a single framework for flood risk assessment and sustainable land management. The results provide valuable support for disaster risk reduction, urban planning, and future development strategies in Havza and similar watershed environments.","洪水是一种极具破坏性的自然灾害，会对环境、社会和经济造成显著影响。哈夫扎（Havza）是土耳其北部的一个区，1998年5月和2026年5月经历了重大洪水事件，这凸显了识别洪水易发区域并分析影响洪水脆弱性因素的必要性。本研究旨在评估哈夫扎的洪水风险，并分析基于遥感数据获得的土地利用\u002F土地覆盖（LULC）监测结果。此外，还利用地理信息系统（GIS）从航天飞机雷达地形测绘任务（SRTM）和数字高程模型（DEM）中获取了地形特征。水文分析包括坡度和汇流累积模型，这些分析用于识别易受洪水影响的区域。研究发现，NDVI均值从1998年的0.4239上升至2026年的0.7447，表明植被覆盖显著增加。LULC分类结果还显示，在近三十年间，城市面积从16%增加至20%，而农业用地从54%减少至50%。三维（3D）地形可视化和基于河流廊道的洪水风险制图表明，低海拔河谷底部和紧邻河道的居民点是洪水最脆弱的区域。本研究结果表明，将GIS与遥感、地形分析以及LULC变化检测整合于同一框架内，对于洪水风险评估和可持续土地管理具有有效性。研究结果为哈夫扎及类似流域环境的减灾、城市规划和未来发展战略提供了有价值的支持。",null,"Black Sea Journal of Engineering and Science","2026-09-14T00:00:00Z","论文",10,false,61,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":17,"relevant":21,"comment":22},8,18,15,12,1,"以GIS与遥感融合评估土耳其流域洪水风险与土地利用变化，方法框架对农业防灾与乡村空间规划有参考价值，但属区域案例研究，公共影响有限。",[24],{"name":10,"url":6},[26,27,28,29,30],"防灾减灾","遥感","洪水风险评估","GIS","土地利用变化",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis","I",[38],{"code":39,"slug":40,"name":41,"path":42,"parent_code":36},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"status":44,"locked":14,"version":45,"method":46,"evidence":47},"classified","2026-10-22.2","rules",{"candidates":48,"agricultural_evidence":50},[49,56,61,67],{"code":32,"score":18,"supported":50,"title":51,"abstract":52,"tags":55},true,[29],[53,29,54],"地理信息","geographic information",[29],{"code":39,"score":19,"supported":50,"title":57,"abstract":59,"tags":60},[58],"remote sensing",[27,58],[27],{"code":62,"score":63,"supported":14,"title":64,"abstract":65,"tags":66},"H7",2,[],[],[28,26],{"code":68,"score":21,"supported":14,"title":69,"abstract":70,"tags":71},"H6",[],[],[30],[73,74],"土地利用变化 洪水风险评估 防灾减灾 遥感","土地利用变化 洪水风险评估","土地利用变化洪水风险评估防灾减灾遥感-2529","10.34248\u002Fbsengineering.1994338",{"doi":76,"openalex_id":78,"authors":79,"venue":10,"cited_by_count":83,"oa_url":6,"card":84,"direction":88,"ingested_from":90},"W7212642487",[80],{"name":81,"orcid":82},"Sibel Canaz","https:\u002F\u002Forcid.org\u002F0000-0001-5552-6067",0,{"tldr":85,"method":86,"finding":87,"direction":88,"opportunity":89},"结合GIS与遥感评估土耳其Havza地区洪水风险，并分析近30年土地利用与植被变化。","使用SRTM\u002FDEM地形分析、坡度与汇流模型、NDVI及LULC分类。","低海拔河谷与近河道居民点最易受灾；城区扩张、农地减少、植被覆盖显著增加。","农业遥感与作物表型","可引入时序遥感与机器学习，构建流域尺度洪水风险动态预警与土地利用协同优化模型。","openalex","2026-09-15T23:30:20.567355Z",{"total":93,"page":21,"page_size":93,"items":94},6,[95,154,231,306,393,450],{"id":96,"title":97,"url":98,"summary":99,"summary_zh":100,"content":9,"source_name":101,"source_url":98,"published_at":102,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":83,"score_detail":103,"sources":105,"tags":107,"primary_topic":110,"secondary_topics":111,"classification":118,"search_phrases":136,"slug":139,"view_count":83,"doi":140,"paper":141,"created_at":153},5326,"Flood Hazard and Vulnerability Assessment of Chitrakoot District, Uttar Pradesh: An Integrated Geographical, GIS and Remote Sensing Approach","https:\u002F\u002Fdoi.org\u002F10.36948\u002Fijfmr.2026.v08i05.89708","Flood is one of the most important hydro-meteorological hazards affecting human settlements, agriculture, infrastructure and regional economies. Chitrakoot district of Uttar Pradesh presents a distinctive case of hydro-climatic vulnerability because it belongs to the drought-prone Bundelkhand region but simultaneously experiences recurrent riverine and flash-flood conditions during intense monsoon rainfall. The present study assesses the spatial characteristics and determinants of flood hazard and vulnerability in Chitrakoot district using an integrated geographical, GIS and remote sensing approach. The analysis incorporates the Digital Elevation Model (DEM), drainage network, physiography, river proximity, historical flood information, satellite-based flood observations and socio-economic exposure. The district's DEM indicates a marked elevation gradient, approximately from 66 m to 451 m, with relatively higher terrain in the southern part and lower terrain towards the northern Yamuna valley. This topographic configuration facilitates rapid surface runoff from elevated southern terrain towards comparatively low-lying riverine areas. The drainage system is dominated by the Yamuna and Mandakini\u002FPaisuni systems along with Baghain, Gunta, Bardaha and smaller tributaries. The Uttar Pradesh Flood Hazard Atlas identifies 5,114 ha of flood-hazard area in Chitrakoot for 1998–2020, of which 4,129 ha (81%) falls in the very-low hazard category and 985 ha (19%) in the low-hazard category. However, the historical classification does not fully represent the potential consequences of extreme rainfall events. The August 2026 flood provides compelling evidence: the Mandakini at Chitrakoot reached a reported new high flood level of 145.60 m on 29 August 2026, approximately 2.95 m above the previous reported high level, while the water level rose by about 7.5 m within six hours. The study concludes that flood risk in Chitrakoot is spatially concentrated around river corridors, low-elevation areas, floodplains, agricultural land, settlements and tourism infrastructure. A shift from conventional relief-oriented flood management towards integrated floodplain regulation, watershed management, GIS-based risk zonation, real-time monitoring and community-based preparedness is therefore essential.","洪水是影响人类住区、农业、基础设施和区域经济的最重要的水文气象灾害之一。北方邦吉德古德（Chitrakoot）县在水文气候脆弱性方面呈现出独特案例，因为它属于易受干旱影响的本德尔坎德（Bundelkhand）地区，但同时在强季风降雨期间反复遭遇河流洪水和山洪状况。本研究采用地理学、地理信息系统（GIS）和遥感相结合的综合方法，评估吉德古德县洪水灾害与脆弱性的空间特征及其决定因素。分析纳入了数字高程模型（DEM）、河网、地貌、距河流远近、历史洪水信息、基于卫星的洪水观测以及社会经济暴露度。该县的DEM显示出明显的高程梯度，大约从66米到451米，南部地形相对较高，向北部的亚穆纳（Yamuna）河谷地势降低。这种地形格局促使地表径流从较高的南部地形快速流向相对低洼的河流区域。排水系统以亚穆纳河和曼达基尼\u002F派苏尼（Mandakini\u002FPaisuni）水系为主，另有巴盖恩（Baghain）、贡塔（Gunta）、巴尔达哈（Bardaha）及较小支流。北方邦洪水灾害图集确认，1998—2020年吉德古德县洪水灾害面积为5，114公顷，其中4，129公顷（81%）属于极低灾害类别，985公顷（19%）属于低灾害类别。然而，历史分类并不能充分反映极端降雨事件的潜在后果。2026年8月的洪水提供了有力证据：据报道，2026年8月29日吉德古德的曼达基尼河达到145.60米的新高洪水位，比此前报告的高水位高出约2.95米，而水位在六小时内上升了约7.5米。研究得出结论，吉德古德的洪水风险在空间上集中于河流廊道、低海拔地区、洪泛平原、农业用地、住区和旅游基础设施周围。因此，必须从传统的以救济为导向的洪水管理转向洪泛平原综合调控、流域管理、基于GIS的风险区划、实时监测和社区为基础的备灾。","International Journal For Multidisciplinary Research","2026-10-17T00:00:00Z",{"impact":83,"substance":83,"depth":83,"authority":83,"freshness":83,"relevant":83,"comment":104},"该研究聚焦印度北方邦的洪水灾害评估，虽涉及GIS与遥感方法，但与三农、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。",[106],{"name":101,"url":98},[26,108,28,109],"遥感监测","GIS应用",{"code":39,"slug":40,"name":41,"path":42,"parent_code":36},[112,113],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"code":62,"slug":114,"name":115,"path":116,"parent_code":117},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"status":44,"locked":14,"version":45,"method":46,"evidence":119},{"candidates":120,"agricultural_evidence":50},[121,125,130],{"code":39,"score":19,"supported":50,"title":122,"abstract":123,"tags":124},[58],[27,58],[108],{"code":32,"score":126,"supported":50,"title":127,"abstract":128,"tags":129},14,[29],[53,29],[],{"code":62,"score":17,"supported":50,"title":131,"abstract":132,"tags":135},[],[133,134],"干旱","drought",[28,26],[137,138],"Chitrakoot 洪水风险 GIS","Yamuna 洪水脆弱性 遥感","Chitrakoot洪水风险GIS-5326","10.36948\u002Fijfmr.2026.v08i05.89708",{"doi":140,"openalex_id":142,"authors":143,"venue":101,"cited_by_count":83,"oa_url":147,"card":148,"direction":88,"ingested_from":90},"W7222885988",[144],{"name":145,"orcid":146},"Birendra Yadav","https:\u002F\u002Forcid.org\u002F0009-0007-0864-474X","https:\u002F\u002Fwww.ijfmr.com\u002Fpapers\u002F2026\u002F5\u002F89708.pdf",{"tldr":149,"method":150,"finding":151,"direction":88,"opportunity":152},"用GIS与遥感综合评估Chitrakoot区洪水灾害与脆弱性空间分布。","DEM、河网、历史洪水与卫星观测及社会经济数据叠加分析。","洪水风险集中于河谷低地、农田与居民点，历史分级低估极端降雨风险。","可结合时序遥感与水文模型，构建极端降雨情景下的农田洪涝风险动态制图与预警。","2026-10-19T23:30:24.356743Z",{"id":155,"title":156,"url":157,"summary":158,"summary_zh":159,"content":9,"source_name":160,"source_url":157,"published_at":161,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":162,"score_detail":163,"sources":166,"tags":168,"primary_topic":172,"secondary_topics":173,"classification":175,"search_phrases":207,"slug":210,"view_count":83,"doi":211,"paper":212,"created_at":230},5321,"GIS and remote sensing based multicriteria analysis for identifying potential agricultural land: A case study on Savar Upazila, Bangladesh","https:\u002F\u002Fdoi.org\u002F10.3329\u002Fbrds.v26i1.94265","Despite of gradually decreasing its contribution to gross domestic product (GDP), agriculture, however, is the backbone of the Bangladeshi economy. Farming is the primary mean of rural livelihoods in Bangladesh but agricultural land is slowly declining day by day. Although, at present, Bangladesh is self-sufficient in terms of producing food, especially rice and some other major agricultural products, it is predicted that, in near future, the country is going to face immense challenges due to climate related threats. The research aims to identify the potential lands for suitable farming in Savar Upazila (sub-district) under Dhaka district applying a geographic information system (GIS) and remote sensing (RS) based multicriteria analysis. Relevant biophysical characteristics of soil, terrain, and landuse and land cover (LULC) were considered. Soil and evelvation data was collected from Soil Resource Development Institute (SRDI)and Shuttle Radar Topography Mission (SRTM), respectively, whereas satellite images were collected from Landsat-8. The maximum likelihood supervised classification technique was used for LULC classification, and the multicriteria evaluation (MCE) and analytical hierarchy process (AHP) approach was employed to identify suitable areas for farming. The research finds the LULC classes are agricultural land, built-up area, fallow land, vegetation cover, waterbodies, and wetland are 12.42%, 31.01%, 25.69%, 25.98%, 4.81%, and 0.09%, respectively. This research also finds that agricultural land suitability was classified as highly suitable, moderately suitable, marginally suitable, and not suitable are 24.28%, 29.53%, 24.66%, and 21.53%, respectively. In contrast, the current agricultural land usage accounts for just 12.42% of the total land area in this research area. The Kappa accuracy has been measured at a value of 0.88 and an overall accuracy value of 0.90 which indicates that the LULC classification is done almost perfectly. This study offered information at the local level that farmers may utilize to decide on cropping patterns and appropriateness. Bangladesh Rural Development Studies, 26(1), 2023 (13-26)","尽管农业在国内生产总值（GDP）中的贡献逐渐下降，但它仍是孟加拉国经济的支柱。农耕是孟加拉国农村生计的主要方式，但农业用地正日益减少。虽然目前孟加拉国在粮食生产方面，尤其是稻米和其他一些主要农产品方面已实现自给自足，但据预测，在不久的将来，该国将因气候相关威胁而面临巨大挑战。本研究旨在运用地理信息系统（GIS）和遥感（RS）基础上的多准则分析，确定达卡县萨瓦尔乡（分区）适宜耕作的土地潜力。研究考虑了土壤、地形以及土地利用与土地覆盖（LULC）等相关生物物理特征。土壤数据来自土壤资源开发研究所（SRDI），高程数据来自航天飞机雷达地形测绘任务（SRTM），卫星影像则来自Landsat-8。土地利用与土地覆盖分类采用最大似然监督分类技术，适宜耕作区的识别则运用多准则评价（MCE）和层次分析法（AHP）。研究发现，土地利用与土地覆盖类别中，农业用地、建成区、休耕地、植被覆盖、水体及湿地分别占12.42%、31.01%、25.69%、25.98%、4.81%和0.09%。研究还发现，农业用地适宜性分为高度适宜、中度适宜、勉强适宜和不适宜，分别占24.28%、29.53%、24.66%和21.53%。相比之下，当前农业用地仅占本研究区土地总面积的12.42%。Kappa精度值为0.88，总体精度值为0.90，表明土地利用与土地覆盖分类近乎完美。本研究提供了地方层面的信息，可供农民在决定种植模式和适宜性时参考。《孟加拉国农村发展研究》，第26卷第1期，2023年（第13-26页）","OpenAlex","2026-10-18T00:00:00Z",60,{"impact":17,"substance":18,"depth":19,"authority":13,"freshness":164,"relevant":21,"comment":165},9,"方法规范、数据可靠的区域农用地适宜性案例研究，但属孟加拉地方尺度，对国内三农信息化仅有方法借鉴价值，不宜进入每日精选。",[167],{"name":160,"url":157},[27,29,169,170,171],"农用地适宜性","土地覆被","孟加拉农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[174],{"code":39,"slug":40,"name":41,"path":42,"parent_code":36},{"status":44,"locked":14,"version":45,"method":46,"evidence":176},{"candidates":177,"agricultural_evidence":50},[178,182,186,193,200],{"code":32,"score":18,"supported":50,"title":179,"abstract":180,"tags":181},[29],[53,29,54],[29],{"code":39,"score":19,"supported":50,"title":183,"abstract":184,"tags":185},[58],[27,58],[27],{"code":187,"score":93,"supported":50,"title":188,"abstract":189,"tags":192},"A1",[],[190,191],"稻米","rice",[],{"code":194,"score":93,"supported":50,"title":195,"abstract":196,"tags":199},"G",[],[197,198],"农村发展","rural development",[],{"code":201,"score":93,"supported":50,"title":202,"abstract":203,"tags":206},"H2",[],[204,205],"土壤","soil",[],[208,209],"Savar Upazila 农用地适宜性","Landsat-8 土地覆被分类","SavarUpazila农用地适宜性-5321","10.3329\u002Fbrds.v26i1.94265",{"doi":211,"openalex_id":213,"authors":214,"venue":224,"cited_by_count":83,"oa_url":157,"card":225,"direction":88,"ingested_from":90},"W7222895468",[215,217,219,221],{"name":216,"orcid":9},"Raju Ahmed",{"name":218,"orcid":9},"Shaikh Mehdee Mohammad",{"name":220,"orcid":9},"Ummul Momanin Coalee",{"name":222,"orcid":223},"Khandakar Hasan Mahmud","https:\u002F\u002Forcid.org\u002F0000-0003-1222-0791","The Bangladesh Rural Development Studies",{"tldr":226,"method":227,"finding":228,"direction":88,"opportunity":229},"用GIS与遥感多准则分析评估孟加拉Savar地区潜在农业用地适宜性。","Landsat-8监督分类提取土地利用，结合土壤、地形数据用AHP与MCE做适宜","仅12.42%为农地，高、中、边缘、不适宜分别占24.28%、29.53%、24.66%、21.53","可引入时序遥感与气候情景，动态评估适宜性变化并耦合作物种植决策支持。","2026-10-19T23:30:22.906704Z",{"id":232,"title":233,"url":234,"summary":235,"summary_zh":236,"content":9,"source_name":237,"source_url":234,"published_at":238,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":239,"score_detail":240,"sources":245,"tags":247,"primary_topic":251,"secondary_topics":252,"classification":259,"search_phrases":285,"slug":288,"view_count":83,"doi":289,"paper":290,"created_at":305},4753,"Mapping groundwater potential zones using GIS, remote sensing and analytical hierarchy process (AHP) in Pader and Kitgum Districts, Uganda","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs43621-026-04943-7","Groundwater is a crucial source of freshwater in semi-arid regions, particularly in water-stressed areas, such as northern Uganda, where the surface water is scarce and unreliable precipitation patterns changes. This province lacks sufficient clean water for human consumption and only 20% of the water for agriculture extracted from the ground due to inaccessibility and insufficient information regarding the groundwater. With regard to these difficulties in water that are faced by the local communities, it has not been yet studied the distribution of groundwater in Kitgum and Pader districts. Therefore, the result of this research contributes preliminary groundwater investigation for contacting this indispensable source of water. The study employed a geospatial approach integrated with multi-criteria analysis to identify groundwater potential zones in Kitgum and Pader districts of Acholi subregion. The Utilization of Geographic Information Systems (GIS), remote sensing, and the Analytic Hierarchy Process (AHP) and six thematic layers; rainfall, drainage density, slope, soil type, geology, and land use\u002Fland cover were selected based on their hydrogeological influence and the accessibility of the data. After standardizing, and assigning normalized weights,a weighted overlay analysis in ArcGIS Pro version 3.1.0 was used to synthesize these layers into a comprehensive groundwater potential zonation map. The result categorized the study area into five zones; very low, low, medium, high, and very high potential. The analysis revealed that Kitgum District is predominantly characterized by very low to low groundwater potential zones of 67.24% when it is combined both, constrained by factors such as higher drainage density, and steeper slopes. Conversely, Pader District showed favorable conditions, with 85.5% of its area classified as high to very high groundwater potential, attributed to gentle slopes, and higher rainfall, that enhance infiltration capacity. Validation against yield data from 18 existing boreholes demonstrated a 75.0% alignment between the model and actual well performance, confirming the model’s reliability at acceptable result. This study demonstrated the effectiveness of GIS-based and AHP as a cost-effective tool for preliminary groundwater exploration in data-scarce environments. The resulting groundwater potential map provides a vital scientific foundation for sustainable water resource management, enabling targeted borehole siting, informed aquifer development, and resilience-building strategies to enhance water security for communities and livelihoods in the Acholi sub-region.","地下水是半干旱地区重要的淡水来源，尤其是在乌干达北部等水资源紧张地区，那里地表水稀缺且降水模式变化不可靠。该地区缺乏足够的清洁饮用水供人类消费，由于地下水难以获取且信息不足，仅有20%的农业用水来自地下开采。鉴于当地社区面临这些水资源困难，基特古姆和帕德尔地区的地下水分布尚未得到研究。因此，本研究结果为接触这一不可或缺的水源提供了初步的地下水调查。本研究采用地理空间方法与多准则分析相结合，识别阿乔利次区域基特古姆和帕德尔地区的地下水潜力区。利用地理信息系统（GIS）、遥感技术和层次分析法（AHP），基于其水文地质影响和数据可获取性，选取了六个主题图层：降雨量、河网密度、坡度、土壤类型、地质和土地利用\u002F土地覆盖。经过标准化和归一化权重赋值后，使用ArcGIS Pro 3.1.0版本中的加权叠加分析将这些图层综合成一张全面的地下水潜力分区图。结果将研究区划分为五个区域：极低、低、中等、高和极高潜力。分析表明，基特古姆区主要以极低至低地下水潜力区为主，两者合计占67.24%，受较高河网密度和较陡坡度等因素制约。相反，帕德尔区表现出有利条件，其85.5%的面积被归类为高至极高地下水潜力，这归因于平缓的坡度和较高的降雨量，增强了入渗能力。利用18口现有钻孔的出水量数据进行验证，模型与实际井表现之间的一致率达到75.0%，证实了模型在可接受结果范围内的可靠性。本研究证明了基于GIS和AHP的方法作为数据稀缺环境中初步地下水勘探的成本效益工具的有效性。所生成的地下水潜力图为可持续水资源管理提供了重要的科学基础，有助于有针对性地选址钻孔，为知情决策提供依据。","Discover Sustainability","2026-10-10T00:00:00Z",67,{"impact":17,"substance":241,"depth":242,"authority":243,"freshness":164,"relevant":21,"comment":244},20,17,13,"基于GIS、遥感与AHP的乌干达北部地下水潜力制图研究，方法成熟、验证可靠，对缺水地区农业水资源规划有参考价值，但属区域性初步研究，公共影响有限。",[246],{"name":237,"url":234},[27,248,29,249,250],"水资源管理","地下水潜力","乌干达农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[253,254],{"code":39,"slug":40,"name":41,"path":42,"parent_code":36},{"code":255,"slug":256,"name":257,"path":258,"parent_code":117},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",{"status":44,"locked":14,"version":45,"method":46,"evidence":260},{"candidates":261,"agricultural_evidence":50},[262,266,270,276,280],{"code":32,"score":18,"supported":50,"title":263,"abstract":264,"tags":265},[29],[53,29,54],[29],{"code":39,"score":19,"supported":50,"title":267,"abstract":268,"tags":269},[58],[27,58],[27],{"code":255,"score":17,"supported":50,"title":271,"abstract":272,"tags":275},[],[273,274],"水资源","water resource",[249,248],{"code":201,"score":93,"supported":50,"title":277,"abstract":278,"tags":279},[],[204,205],[],{"code":62,"score":281,"supported":50,"title":282,"abstract":283,"tags":284},3,[],[133],[],[286,287],"乌干达 Kitgum Pader 地下水","GIS AHP 地下水潜力","乌干达KitgumPader地下水-4753","10.1007\u002Fs43621-026-04943-7",{"doi":289,"openalex_id":291,"authors":292,"venue":237,"cited_by_count":83,"oa_url":234,"card":300,"direction":88,"ingested_from":90},"W7221339030",[293,296,298],{"name":294,"orcid":295},"Ahmed Abdirizak Dirie","https:\u002F\u002Forcid.org\u002F0009-0002-8109-0724",{"name":297,"orcid":9},"Abdulkadir Ahmed Mohamed",{"name":299,"orcid":9},"Ambiga Kannapiran",{"tldr":301,"method":302,"finding":303,"direction":88,"opportunity":304},"用GIS、遥感和AHP制图评估乌干达两区地下水潜力并验证。","GIS与遥感结合AHP，加权叠加6个主题图层，用18口井数据验证。","Kitgum区67.24%为低潜力，Pader区85.5%为高潜力，模型与井数据吻合75%。","可将该地下水潜力制图方法迁移到其他数据稀缺区，并结合农业灌溉需求优化井位。","2026-10-12T23:30:24.761508Z",{"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":314,"is_selected":14,"score":315,"score_detail":316,"sources":319,"tags":323,"primary_topic":327,"secondary_topics":328,"classification":335,"search_phrases":366,"slug":369,"view_count":83,"doi":370,"paper":371,"created_at":392},4294,"GIS- and Remote Sensing-Based Identification of Suitable Agricultural Waste Landfill Sites for Climate-Smart Agriculture in Ilorin, Nigeria","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23168428","Abstract Lack of a designated landfill for agricultural waste management (AWM) in Ilorin municipalities led to indiscriminate disposal of agricultural waste within the city and the only existing Sokoto-Ayekale general solid waste dumpsite, posing environmental and public health risks while undermining climate-smart agriculture (CSA). The study identifies suitable landfill sites for AWM by integrating Geographic Information System (GIS), Remote Sensing (RS), and Multi-Criteria Decision Analysis (MCDA) to locate environmentally and climate-resilient sites. Spatial data employed for the study include Shuttle Radar Topography Mission (SRTM), Landsat 9 imagery, Digital Elevation Model (DEM), road networks, waterbodies, built-up areas, soil quality, slope, and geology, which were processed in ArcGIS 10.3 to develop constraint thematic suitability maps. The Analytical Hierarchy Process (AHP) was employed to derive criterion weights, and the Weighted Linear Combination (WLC) was used to generate the map. AHP consistency ratio (CR) was used to validate the model’s consistency (CR=0.016), which falls within the acceptable CR \u003C0.1. The AHP weighted results were 0.41, 0.2, 0.14, 0.10, 0.08, and 0.07 for waterbodies, built-up area, slope, soil quality, geology, and road network, respectively. Maps were created for each criterion, reclassified, and integrated using the weighted linear combination method to generate an overall AWM suitability map. The study identified four potential locations for AWM. Approximately 507.23 km² are unsuitable, 1204.21 km² are marginally suitable, 4899.28 km² are moderately suitable, and 2021.7 km² are highly suitable for AWM landfill development. The findings present a scientifically based decision-support framework to guide policymakers, environmental agencies, and urban planners in developing sustainable AWM strategies that minimize environmental risk while advancing climate-smart agriculture. Keywords: Agricultural waste, Climate-smart agriculture, Landfill, Suitability, Sustainability","摘要 伊洛林各市镇缺乏用于农业废弃物管理（AWM）的指定填埋场，导致农业废弃物在城市内部及唯一现有的索科托-阿耶卡莱一般固体废弃物倾倒场被随意处置，既构成环境和公共健康风险，也削弱了气候智慧型农业（CSA）。本研究通过整合地理信息系统（GIS）、遥感（RS）和多准则决策分析（MCDA），识别适用于AWM的填埋场选址，以确定具有环境韧性和气候韧性的场址。研究采用的空间数据包括航天飞机雷达地形测绘任务（SRTM）数据、Landsat 9影像、数字高程模型（DEM）、道路网络、水体、建成区、土壤质量、坡度和地质，并在ArcGIS 10.3中进行处理以生成约束性专题适宜性图。采用层次分析法（AHP）推导准则权重，并运用加权线性组合（WLC）生成地图。使用AHP一致性比率（CR）验证模型的一致性（CR=0.016），该值处于可接受的CR\u003C0.1范围内。AHP加权结果分别为：水体0.41、建成区0.2、坡度0.14、土壤质量0.10、地质0.08、道路网络0.07。针对每个准则生成地图，经重分类后采用加权线性组合方法进行整合，生成总体AWM适宜性图。研究确定了四个潜在的AWM选址。约507.23 km²不适宜，1204.21 km²勉强适宜，4899.28 km²中等适宜，2021.7 km²高度适宜建设AWM填埋场。研究结果为政策制定者、环境机构和城市规划者提供了基于科学的决策支持框架，以指导制定可持续的AWM策略，在降低环境风险的同时推进气候智慧型农业。关键词：农业废弃物，气候智慧型农业，填埋场，适宜性，可持续性","Zenodo (CERN European Organization for Nuclear Research)","2026-10-05T00:00:00Z",25,72,{"impact":20,"substance":317,"depth":242,"authority":243,"freshness":164,"relevant":21,"comment":318},21,"GIS与遥感结合MCDA为农业废弃物填埋选址提供决策框架，方法规范、数据翔实，但属区域性案例研究，公共影响有限。",[320,321],{"name":312,"url":309},{"name":312,"url":322},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23168429",[27,324,325,29,326],"农业废弃物","气候智慧农业","选址评估",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[329,334],{"code":330,"slug":331,"name":332,"path":333,"parent_code":117},"H5","waste","面源污染与废弃物利用","\u002Ftopic\u002Fenvironment\u002Fwaste",{"code":39,"slug":40,"name":41,"path":42,"parent_code":36},{"status":44,"locked":14,"version":45,"method":46,"evidence":336},{"candidates":337,"agricultural_evidence":50},[338,342,347,351,358,362],{"code":32,"score":18,"supported":50,"title":339,"abstract":340,"tags":341},[29],[53,29,54],[29],{"code":330,"score":19,"supported":50,"title":343,"abstract":345,"tags":346},[344],"agricultural waste",[324,344],[324],{"code":39,"score":19,"supported":50,"title":348,"abstract":349,"tags":350},[58],[27,58],[27],{"code":352,"score":353,"supported":50,"title":354,"abstract":356,"tags":357},"I1",11,[355],"smart agriculture",[355],[],{"code":201,"score":93,"supported":50,"title":359,"abstract":360,"tags":361},[],[204,205],[],{"code":62,"score":21,"supported":14,"title":363,"abstract":364,"tags":365},[],[],[325],[367,368],"Ilorin 农业废弃物 填埋场 选址","GIS 遥感 农业废弃物 填埋场","Ilorin农业废弃物填埋场选址-4294","10.5281\u002Fzenodo.23168428",{"doi":370,"openalex_id":372,"authors":373,"venue":312,"cited_by_count":83,"oa_url":309,"card":385,"direction":391,"ingested_from":90},"W7220389353",[374,376,378,380,383],{"name":375,"orcid":9},"Saheed Mohammed Ishaq",{"name":377,"orcid":9},"Alamin Adedeji Adenekan",{"name":379,"orcid":9},"Ibrahim Dauda",{"name":381,"orcid":382},"Afeez Oladeji Amoo","https:\u002F\u002Forcid.org\u002F0000-0002-0412-9333",{"name":384,"orcid":9},"Nureni Babatunde Amoo",{"tldr":386,"method":387,"finding":388,"direction":389,"opportunity":390},"用GIS、遥感和多准则决策为尼日利亚Ilorin筛选农业废弃物填埋场适宜选址。","GIS\u002FRS结合AHP与加权线性组合，基于DEM、Landsat 9等空间数据。","识别出4处潜在选址，约2021.7 km²高度适宜，模型一致性良好。","农业绿色发展与碳","可将该选址框架与温室气体排放、运输成本及气候情景耦合，拓展到其他区域。","智慧农业 \u002F 农业物联网","2026-10-06T23:30:07.715522Z",{"id":394,"title":395,"url":396,"summary":397,"summary_zh":398,"content":9,"source_name":399,"source_url":396,"published_at":400,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":401,"score_detail":402,"sources":404,"tags":406,"primary_topic":410,"secondary_topics":411,"classification":413,"search_phrases":433,"slug":436,"view_count":63,"doi":437,"paper":438,"created_at":449},4102,"Application of GIS and Remote Sensing Techniques in Geospatial Mapping of Gully Statuses of an Alfisols in Yola South Local Government Area, Adamawa State","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fwjimt.v10.no1.2026.pg155.165","This research work saddled to study the application of GIS and Remote Sensing (RS) Techniques in geospatial mapping of gully erosion statuses of an Alfisols in Yola South LGA. Bole farmland was selected where expansion and development of gully was geospatially mapped out for the period of 20 years (2004-2024) at interval of five (5) years using GIS and RS techniques. The results reveal a concerning trend of increasing gully erosion, with significant growth in affected areas over the years. The highest percentage of increase occurred at 2014-2019 with about 58,069.00 m2 (65.5 %) and in 2019-2024was increased with 14,154.00 m2 (15.97 %). The total area affected in the area within the study period was 88,627.00 m2 caused by heavy rainfall and deforestation. Therefore, there are needs for effective land management practices, policy interventions, and community engagement to mitigate the effects of gully erosion.","本研究旨在探讨GIS与遥感（RS）技术在约拉南部地方政府区淋溶土冲沟侵蚀状况地理空间制图中的应用。选取博莱农田为研究区，利用GIS与遥感技术，以5年为间隔，对2004—2024年共20年间冲沟的扩展与发育进行了地理空间制图。结果表明，冲沟侵蚀呈令人担忧的加剧趋势，受影响面积逐年显著增长。增幅最大的时段为2014—2019年，约增加58 069.00 m²（65.5%）；2019—2024年增加14 154.00 m²（15.97%）。研究期内该区域受影响总面积为88 627.00 m²，主要由强降雨和森林砍伐所致。因此，需要采取有效的土地管理措施、政策干预和社区参与，以减轻冲沟侵蚀的影响。","WORLD JOURNAL OF INNOVATION AND MODERN TECHNOLOGY","2026-09-30T00:00:00Z",54,{"impact":17,"substance":18,"depth":126,"authority":93,"freshness":17,"relevant":21,"comment":403},"基于GIS与遥感的20年沟蚀动态监测，数据具体、结论明确，但属区域案例研究，公共影响有限。",[405],{"name":399,"url":396},[407,27,408,29,409],"数字乡村","土壤侵蚀","水土保持",{"code":39,"slug":40,"name":41,"path":42,"parent_code":36},[412],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":44,"locked":14,"version":45,"method":46,"evidence":414},{"candidates":415,"agricultural_evidence":50},[416,420,424,428],{"code":39,"score":19,"supported":50,"title":417,"abstract":418,"tags":419},[58],[27,58],[27],{"code":32,"score":20,"supported":50,"title":421,"abstract":422,"tags":423},[29],[29],[29],{"code":68,"score":21,"supported":14,"title":425,"abstract":426,"tags":427},[],[],[409],{"code":429,"score":21,"supported":14,"title":430,"abstract":431,"tags":432},"I6",[],[],[407],[434,435],"Yola South 沟蚀 遥感","Alfisols 沟蚀 GIS 制图","YolaSouth沟蚀遥感-4102","10.56201\u002Fwjimt.v10.no1.2026.pg155.165",{"doi":437,"openalex_id":439,"authors":440,"venue":399,"cited_by_count":83,"oa_url":443,"card":444,"direction":88,"ingested_from":90},"W7214920253",[441],{"name":442,"orcid":9},"Mohammed Pakra Umar","https:\u002F\u002Fiiardjournals.org\u002Fget\u002FWJIMT\u002FVOL. 10 NO. 1 2026\u002FAPPLICATION OF GIS AND REMOTE 156-165.pdf",{"tldr":445,"method":446,"finding":447,"direction":88,"opportunity":448},"用GIS和遥感技术对尼日利亚Yola South地区20年沟蚀动态进行空间制图与监测。","基于GIS与遥感影像，按5年间隔提取2004-2024年沟蚀范围并计算面积变化。","沟蚀面积持续扩大，2014-2019年增幅最大达65.5%，20年累计影响88,627平方米。","可结合多源高分辨率遥感与机器学习，构建沟蚀风险预警模型并评估保护性耕作等治理措施效果。","2026-10-03T23:30:37.949646Z",{"id":451,"title":452,"url":453,"summary":454,"summary_zh":455,"content":9,"source_name":456,"source_url":453,"published_at":457,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":458,"score_detail":459,"sources":462,"tags":464,"primary_topic":468,"secondary_topics":469,"classification":472,"search_phrases":496,"slug":499,"view_count":500,"doi":501,"paper":502,"created_at":531},4085,"Seasonal Snow Water Resources and Spring Runoff Harvesting Potential in the North Kazakhstan Region: An Integrated Remote Sensing and GIS-Based Multi-Criteria Assessment","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fearth7050163","Seasonal snow is a critical water resource in Northern Kazakhstan, where spring snowmelt dominates surface runoff and agricultural water supply. However, traditional rainwater harvesting frameworks often neglect snow water equivalent (SWE), limiting their applicability in cold, snow-dominated steppe environments. This study develops an integrated remote sensing and GIS-based approach to identify potential sites for spring runoff harvesting. Using Sentinel-2 imagery, snow cover fraction (SCF) was derived and combined with a digital elevation model (DEM) to estimate snow depth through a quadratic regression model, validated against in situ data from 23 meteorological stations. Snow water equivalent was then calculated by incorporating field-measured snow density. Alongside SWE, six additional parameters—slope, drainage density, land use\u002Fland cover (LULC), and soil texture (sand, silt, clay)—were integrated within an Analytical Hierarchy Process (AHP) multi-criteria decision analysis. Results show that SWE, drainage density, and LULC collectively contributed 75% of the weight in site suitability, underscoring their dominant role in snowmelt-driven hydrology. The final suitability map indicates that 28.03% of the region falls into the “Very High” class, concentrated in central and northwestern districts. Developing just 30% of these potential zones could yield approximately 4.2 × 108 m3 of usable meltwater, supporting up to 105,000 ha under full irrigation or 280,000 ha under deficit irrigation. The study demonstrates that integrating high-resolution SWE with MCDA provides a scalable framework for enhancing agricultural resilience, mitigating floods, and strengthening water security in cold, semi-arid landscapes.","季节性积雪是哈萨克斯坦北部的重要水资源，春季融雪主导着地表径流和农业供水。然而，传统的雨水收集框架往往忽视雪水当量（SWE），限制了其在寒冷、以积雪为主的草原环境中的适用性。本研究开发了一种集成遥感和GIS的方法，用于识别春季径流收集的潜在场址。利用Sentinel-2影像提取积雪覆盖率（SCF），并结合数字高程模型（DEM）通过二次回归模型估算雪深，利用23个气象站的实地数据进行验证。随后，结合实地测量的雪密度计算雪水当量。除SWE外，还将坡度、河网密度、土地利用\u002F土地覆盖（LULC）以及土壤质地（砂、粉砂、黏土）等六个附加参数纳入层次分析法（AHP）多准则决策分析。结果表明，SWE、河网密度和LULC在场地适宜性评价中合计贡献了75%的权重，凸显了它们在融雪驱动水文中的主导作用。最终适宜性图显示，该区域28.03%的面积属于“极高”等级，集中在中部和西北部地区。仅开发这些潜在区域的30%，即可产生约4.2 × 10⁸ m³的可用融水，可支持多达105,000公顷的充分灌溉或280,000公顷的亏缺灌溉。本研究表明，将高分辨率SWE与多准则决策分析相结合，为增强农业韧性、减轻洪水和加强寒冷半干旱地区的水安全提供了一个可扩展的框架。","Earth","2026-10-02T00:00:00Z",77,{"impact":460,"substance":317,"depth":18,"authority":243,"freshness":164,"relevant":21,"comment":461},16,"该研究将遥感与GIS多准则评估结合，量化了北哈萨克斯坦融雪水资源与灌溉潜力，方法新颖、数据扎实，对寒区农业水资源管理有参考价值，但地域性较强，属细分领域进展。",[463],{"name":456,"url":453},[465,466,27,29,467],"农业水资源","哈萨克斯坦","融雪灌溉",{"code":39,"slug":40,"name":41,"path":42,"parent_code":36},[470,471],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"code":255,"slug":256,"name":257,"path":258,"parent_code":117},{"status":44,"locked":14,"version":45,"method":46,"evidence":473},{"candidates":474,"agricultural_evidence":50},[475,479,483,488,492],{"code":39,"score":19,"supported":50,"title":476,"abstract":477,"tags":478},[58],[27,58],[27],{"code":32,"score":20,"supported":50,"title":480,"abstract":481,"tags":482},[29],[29],[29],{"code":255,"score":13,"supported":50,"title":484,"abstract":485,"tags":487},[],[486,273,256,274],"灌溉",[465],{"code":201,"score":93,"supported":50,"title":489,"abstract":490,"tags":491},[],[204,205],[],{"code":62,"score":281,"supported":50,"title":493,"abstract":494,"tags":495},[],[133],[],[497,498],"北哈萨克斯坦 融雪 灌溉潜力","Sentinel-2 雪水当量 遥感","北哈萨克斯坦融雪灌溉潜力-4085",5,"10.3390\u002Fearth7050163",{"doi":501,"openalex_id":503,"authors":504,"venue":456,"cited_by_count":83,"oa_url":453,"card":526,"direction":88,"ingested_from":90},"W7216430083",[505,508,511,513,515,517,520,523],{"name":506,"orcid":507},"Zhanassyl Teleubay","https:\u002F\u002Forcid.org\u002F0000-0003-4783-5489",{"name":509,"orcid":510},"Erkin Ussalinov","https:\u002F\u002Forcid.org\u002F0000-0003-1907-9532",{"name":512,"orcid":9},"Laura Ryskulbekova",{"name":514,"orcid":9},"Asset Arystanov",{"name":516,"orcid":9},"Ibragim Seitassanov",{"name":518,"orcid":519},"Улжан Онласын","https:\u002F\u002Forcid.org\u002F0000-0001-5789-5464",{"name":521,"orcid":522},"Nuray Kutymova","https:\u002F\u002Forcid.org\u002F0009-0000-7214-1708",{"name":524,"orcid":525},"Farabi Yermekov","https:\u002F\u002Forcid.org\u002F0000-0002-0290-3866",{"tldr":527,"method":528,"finding":529,"direction":88,"opportunity":530},"结合遥感与GIS评估哈萨克斯坦北部季节性雪水资源及春季径流收集潜力。","Sentinel-2与DEM估算雪深和SWE，结合AHP多准则决策分析选址。","SWE、河网密度和土地利用贡献75%权重，28%区域为极高适宜区。","可将SWE驱动的选址框架推广至其他寒旱区，并耦合气候情景与灌溉效率优化。","2026-10-03T23:30:32.427699Z"]