[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1646":3,"related-1646":140},{"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":29,"secondary_topics":35,"classification":41,"search_phrases":95,"slug":98,"view_count":99,"doi":100,"paper":101,"created_at":139},1646,"Assessment of groundwater potential zones and artificial recharge structures mapping for sustainable water resources planning based on remote sensing and GIS approaches","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffenvs.2026.1854608","The efficient management of groundwater requires judicious use of resources, considering the limited surface water availability and unprecedented rainfall occurrence. The Tikamgarh district area is a need more effective policy for sustainable groundwater development and management due to severe groundwater stress, over-extraction, limited recharge capacity, and recurrent drought conditions. Artificial recharge is another method for enhancing groundwater and surface water resources. The various thematics layers such as soil, geomorphology, lineament density, slope, land use and land cover (LULC), drainage density (DD), geology, and aspect have been used in this study. These layers were normalized using the analytic hierarchy process (AHP) eigenvector method and weighted based on Saaty’s five-point scale in order to identify groundwater potential zones (GWPZs) and recommend suitable sites for artificial recharge structures by using geographic information system (GIS) framework throughout the district area. Spatial maps have been created from satellite datasets using ArcGIS10.5 software. These maps provide valuable information related to the study area. The developed GWPZs were divided into five classes according to the statistical data, which ranges from very high to very low potential zones. The accuracy and the feasibility of the recharge sites recommended by the GWPZ maps are validated using ROC curve analysis. During validation of recharge sites map accuracy is showing the area under the curve (AUC) of 0.79%, while the GWPZ map showing training and testing accuracy is 0.724 and 0.704, respectively. After the investigate of the study area, we have suggested artificial recharge structures, such as cement nala bunds (CNBs), check dams, dams, farm ponds, and wells. This results of study area can helpful and valuable information for planning groundwater resources and sustainable farming practices and enhance local water security.","地下水资源的高效管理需要合理利用资源，同时考虑到有限的地表水可用性和前所未有的降雨事件。Tikamgarh地区由于严重的地下水压力、过度开采、有限的补给能力以及频繁的干旱条件，亟需制定更有效的政策以促进地下水的可持续开发与管理。人工补给是增强地下水和地表水资源的另一种方法。本研究采用了多种专题图层，如土壤、地貌、线性构造密度、坡度、土地利用与土地覆盖（LULC）、排水密度（DD）、地质和坡向等。这些图层通过层次分析法（AHP）特征向量方法进行归一化处理，并基于Saaty五级标度进行加权，以识别地下水潜力区（GWPZs），并利用地理信息系统（GIS）框架在整个区域范围内推荐适合的人工补给结构选址。利用ArcGIS10.5软件从卫星数据集中生成了空间地图。这些地图提供了与研究区域相关的宝贵信息。所开发的地下水潜力区根据统计数据被划分为五类，范围从极高潜力区到极低潜力区。通过ROC曲线分析验证了GWPZ地图推荐补给点的准确性和可行性。在补给点地图的验证过程中，准确率显示曲线下面积（AUC）为0.79%，而GWPZ地图的训练和测试准确率分别为0.724和0.704。经过对研究区域的调查，我们建议采用人工补给结构，如水泥沟渠拦水坝（CNBs）、检查坝、水坝、农场池塘和水井。该研究结果可为地下水资源规划、可持续农业实践以及增强当地水安全提供有益且宝贵的信息。",null,"Frontiers in Environmental Science","2026-09-02T00:00:00Z","论文",10,false,61,{"impact":17,"substance":18,"depth":19,"authority":17,"freshness":20,"relevant":21,"comment":22},12,18,16,3,1,"研究利用遥感和GIS技术评估地下水潜力区并规划人工补给结构，对农业水资源可持续管理有参考价值。",[24],{"name":10,"url":6},[26,27,28],"农业信息化","水资源管理","遥感技术",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis","I",[36],{"code":37,"slug":38,"name":39,"path":40,"parent_code":34},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"status":42,"locked":14,"version":43,"method":44,"evidence":45},"classified","2026-10-22.2","rules",{"candidates":46,"agricultural_evidence":49},[47,56,62,70,77,84,90],{"code":30,"score":48,"supported":49,"title":50,"abstract":52,"tags":55},17,true,[51],"GIS",[53,51,54],"地理信息","geographic information",[],{"code":37,"score":57,"supported":49,"title":58,"abstract":60,"tags":61},9,[59],"remote sensing",[],[28],{"code":63,"score":64,"supported":49,"title":65,"abstract":66,"tags":69},"H2",6,[],[67,68],"土壤","soil",[],{"code":71,"score":64,"supported":49,"title":72,"abstract":73,"tags":76},"H7",[],[74,75],"干旱","drought",[],{"code":78,"score":79,"supported":49,"title":80,"abstract":81,"tags":83},"H3",4,[],[82],"水资源",[27],{"code":85,"score":20,"supported":49,"title":86,"abstract":87,"tags":89},"H8",[],[88],"可持续农业",[],{"code":91,"score":21,"supported":14,"title":92,"abstract":93,"tags":94},"I1",[],[],[26],[96,97],"农业信息化 水资源管理 遥感技术","农业信息化 水资源管理","农业信息化水资源管理遥感技术-1646",2,"10.3389\u002Ffenvs.2026.1854608",{"doi":100,"openalex_id":102,"authors":103,"venue":10,"cited_by_count":130,"oa_url":131,"card":132,"direction":136,"ingested_from":138},"W7204989208",[104,106,109,111,113,115,118,121,123,125,128],{"name":105,"orcid":9},"Kanak N. Moharir",{"name":107,"orcid":108},"Neyara Radwan","https:\u002F\u002Forcid.org\u002F0000-0001-8756-4834",{"name":110,"orcid":9},"Chaitanya Baliram Pande",{"name":112,"orcid":9},"Balamurugan Paneerselvam",{"name":114,"orcid":9},"Jawaher Saud Alrashood",{"name":116,"orcid":117},"Samyah Salem Refadah","https:\u002F\u002Forcid.org\u002F0009-0006-8909-1448",{"name":119,"orcid":120},"Akshay Kumar","https:\u002F\u002Forcid.org\u002F0009-0000-4417-8976",{"name":122,"orcid":9},"Vinay Kumar Gautam",{"name":124,"orcid":9},"Malay Pramanik",{"name":126,"orcid":127},"Mohd Yawar Ali Khan","https:\u002F\u002Forcid.org\u002F0000-0001-6524-4733",{"name":129,"orcid":9},"Ali Salem",0,"https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fenvironmental-science\u002Farticles\u002F10.3389\u002Ffenvs.2026.1854608\u002Fpdf",{"tldr":133,"method":134,"finding":135,"direction":136,"opportunity":137},"利用遥感和GIS评估地下水潜力区并规划人工补给结构，以促进可持续水资源管理。","结合AHP层次分析法和GIS，对多主题图层加权叠加，并用ROC曲线验证。","识别出地下水潜力分区，推荐人工补给结构位置，模型精度约0.79。","农业遥感与作物表型","可结合高分辨率遥感与机器学习，提升地下水潜力预测精度，并扩展至农业用水优化与干旱预警。","openalex","2026-09-04T23:30:33.653821Z",{"total":64,"page":21,"page_size":64,"items":141},[142,206,278,350,417,474],{"id":143,"title":144,"url":145,"summary":146,"summary_zh":147,"content":9,"source_name":148,"source_url":145,"published_at":149,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":150,"score_detail":151,"sources":155,"tags":157,"primary_topic":162,"secondary_topics":163,"classification":165,"search_phrases":190,"slug":193,"view_count":130,"doi":194,"paper":195,"created_at":205},5008,"ASSESSING THE GEOECOLOGICAL IMPACT OF LARGE HYDRAULIC STRUCTURES IN ARID REGIONS USING REMOTE SENSING AND GIS TECHNOLOGIES (A CASE STUDY OF THE CENTRAL FERGANA RESERVOIR)","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23359723","This article presents a comprehensive study of the geoecological and ameliorative impacts of large hydraulic structures built under arid subtropical conditions on adjacent agricultural landscapes, using the Central Fergana Reservoir (CFR) as a case study. The main objective of the study is to assess landscape changes, the spatial dynamics of vegetation cover, and secondary soil salinization processes across 29,330 hectares within the reservoir’s impact zone between 2010 and 2025 using remote sensing and GIS technologies. The study calculates the Normalized Difference Vegetation Index (NDVI) based on Landsat satellite imagery (Landsat 5 TM, Landsat 8 OLI\u002FTIRS, and Landsat 9 OLI-2) and analyzes long-term changes. The results show that the water surface area expanded from 1% (293.3 ha) in 2010 to 15% (4,399.5 ha) by 2025. Furthermore, analyses of 27 soil profiles and laboratory measurements of electrical conductivity (\\(EC_e\\)) and moisture content confirmed the formation of localized waterlogged areas and highly saline solonchaks in the 500-meter coastal buffer zone as a result of a rise in the groundwater table to 1.0–1.5 m. Environmental stress factors identified through comparative analyses with a control (background) site were scientifically substantiated, and practical recommendations for sustainable regional management were developed.","本文以中央费尔干纳水库（Central Fergana Reservoir, CFR）为例，对干旱亚热带条件下大型水利设施对邻近农业景观的地质生态与土壤改良影响进行了综合研究。研究的主要目标在于利用遥感与GIS技术，评估2010年至2025年间水库影响区内29330公顷土地上的景观变化、植被覆盖空间动态以及次生土壤盐渍化过程。研究基于Landsat卫星影像（Landsat 5 TM、Landsat 8 OLI\u002FTIRS和Landsat 9 OLI-2）计算归一化植被指数（Normalized Difference Vegetation Index, NDVI），并分析其长期变化。结果表明，水域面积从2010年的1%（293.3公顷）扩大至2025年的15%（4399.5公顷）。此外，对27个土壤剖面的分析以及电导率（\\(EC_e\\)）和含水量的实验室测定证实，由于地下水位上升至1.0–1.5米，在500米沿岸缓冲带内形成了局部渍水区和重度盐化盐土。通过与对照（背景）样地的比较分析，科学地证实了所识别的环境胁迫因子，并提出了区域可持续管理的实践建议。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-14T00:00:00Z",74,{"impact":17,"substance":152,"depth":18,"authority":153,"freshness":57,"relevant":21,"comment":154},22,13,"基于Landsat长时序遥感与GIS评估干旱区大型水利工程对灌区植被与次生盐渍化的影响，方法规范、数据翔实，对农业遥感与灌区生态监测有参考价值，但属区域案例研究，公共影响有限。",[156],{"name":148,"url":145},[158,159,27,160,161],"农业遥感","遥感","灌溉农业","盐渍化",{"code":37,"slug":38,"name":39,"path":40,"parent_code":34},[164],{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},{"status":42,"locked":14,"version":43,"method":44,"evidence":166},{"candidates":167,"agricultural_evidence":49},[168,172,177,182,186],{"code":37,"score":19,"supported":49,"title":169,"abstract":170,"tags":171},[59],[159,59],[158,159],{"code":30,"score":173,"supported":49,"title":174,"abstract":175,"tags":176},11,[51],[51],[],{"code":63,"score":178,"supported":49,"title":179,"abstract":180,"tags":181},7,[],[67,68],[161],{"code":71,"score":20,"supported":49,"title":183,"abstract":184,"tags":185},[],[74],[],{"code":78,"score":99,"supported":14,"title":187,"abstract":188,"tags":189},[],[],[27,160],[191,192],"费尔干纳水库 遥感 盐渍化","Landsat NDVI 灌区 土壤盐渍化","费尔干纳水库遥感盐渍化-5008","10.5281\u002Fzenodo.23359723",{"doi":194,"openalex_id":196,"authors":197,"venue":148,"cited_by_count":130,"oa_url":145,"card":200,"direction":136,"ingested_from":138},"W7221819099",[198],{"name":199,"orcid":9},"Akbarov Sarvarbek",{"tldr":201,"method":202,"finding":203,"direction":136,"opportunity":204},"用遥感和GIS评估费尔干纳中部水库对周边农业景观的生态影响。","Landsat影像NDVI分析、27个土壤剖面及ECe与含水量测定。","水库水面从1%扩至15%，500米缓冲带地下水位升至1.0–1.5米，形成盐渍化。","可结合多源遥感与土壤盐分模型，构建干旱区水库周边盐渍化预警与灌溉调控方案。","2026-10-15T23:30:29.814507Z",{"id":207,"title":208,"url":209,"summary":210,"summary_zh":211,"content":9,"source_name":212,"source_url":209,"published_at":213,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":214,"score_detail":215,"sources":219,"tags":221,"primary_topic":224,"secondary_topics":225,"classification":232,"search_phrases":257,"slug":260,"view_count":130,"doi":261,"paper":262,"created_at":277},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":216,"substance":217,"depth":48,"authority":153,"freshness":57,"relevant":21,"comment":218},8,20,"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。",[220],{"name":212,"url":209},[159,27,51,222,223],"地下水潜力","乌干达农业",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[226,227],{"code":37,"slug":38,"name":39,"path":40,"parent_code":34},{"code":78,"slug":228,"name":229,"path":230,"parent_code":231},"irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",{"status":42,"locked":14,"version":43,"method":44,"evidence":233},{"candidates":234,"agricultural_evidence":49},[235,239,244,249,253],{"code":30,"score":18,"supported":49,"title":236,"abstract":237,"tags":238},[51],[53,51,54],[51],{"code":37,"score":240,"supported":49,"title":241,"abstract":242,"tags":243},15,[59],[159,59],[159],{"code":78,"score":216,"supported":49,"title":245,"abstract":246,"tags":248},[],[82,247],"water resource",[222,27],{"code":63,"score":64,"supported":49,"title":250,"abstract":251,"tags":252},[],[67,68],[],{"code":71,"score":20,"supported":49,"title":254,"abstract":255,"tags":256},[],[74],[],[258,259],"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":261,"openalex_id":263,"authors":264,"venue":212,"cited_by_count":130,"oa_url":209,"card":272,"direction":136,"ingested_from":138},"W7221339030",[265,268,270],{"name":266,"orcid":267},"Ahmed Abdirizak Dirie","https:\u002F\u002Forcid.org\u002F0009-0002-8109-0724",{"name":269,"orcid":9},"Abdulkadir Ahmed Mohamed",{"name":271,"orcid":9},"Ambiga Kannapiran",{"tldr":273,"method":274,"finding":275,"direction":136,"opportunity":276},"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":279,"title":280,"url":281,"summary":282,"summary_zh":283,"content":9,"source_name":284,"source_url":281,"published_at":285,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":286,"score_detail":287,"sources":289,"tags":291,"primary_topic":293,"secondary_topics":294,"classification":296,"search_phrases":325,"slug":328,"view_count":79,"doi":329,"paper":330,"created_at":349},4027,"Groundwater Potential Zonation of Unchehra Watershed, Central India using AHP, Remote Sensing, and GIS Techniques","https:\u002F\u002Fdoi.org\u002F10.17491\u002Fjgsi.2026.174637","ABSTRACT Groundwater is the primary source of domestic and agricultural water in the semi-arid regions of central India. Despite receiving moderate annual rainfall, Unchehra watershed experiences seasonal water shortages, especially during summer, highlighting the need for scientific assessment of groundwater resources. This study delineates groundwater potential zones (GWPZs) in the Unchehra watershed using an integrated Remote Sensing (RS), Geographic Information System (GIS), and Analytical Hierarchy Process (AHP) approach. Seven major factors influencing groundwater occurrence lineament density, geology, land use and land cover (LULC), drainage density, geomorphology, slope and soil type were considered in the analysis. Spatial thematic layers for these parameters were prepared from satellite imagery and Digital Elevation Model (DEM) data using ArcGIS. The relative importance of each factor and its classes was determined through AHP, providing a systematic weighting scheme for groundwater potential assessment. The weighted layers were integrated to generate a groundwater potential zonation map. The resulting map classified the watershed into five groundwater potential zones: very low, low, moderate, high, and very high. The analysis revealed that 7.88% of the watershed falls under very low potential, while significant portions of the area exhibit moderate (28.07%) to very high (22.61%) groundwater potential. To assess the reliability of the generated model, validation was carried out using 41 randomly selected dug wells and Receiver Operating Characteristic (ROC) curve analysis. The near-zero Consistency Ratio (CR) confirms the reliability of the AHP weighting scheme, while the Area Under the Curve (AUC) value of 0.763 indicates good predictive accuracy of the groundwater potential model. The identified high and very high groundwater potential zones are suitable for groundwater development and artificial recharge measures such as check dams, percolation tanks, and recharge wells. The integrated RS-GIS-AHP framework developed in this study provides a reliable decision-support tool for groundwater exploration, recharge planning, and sustainable groundwater management in Unchehra watershed and similar hydrogeological settings.","摘要 地下水是印度中部半干旱地区生活用水和农业用水的主要来源。尽管Unchehra流域年降水量适中，但仍面临季节性缺水问题，尤其是在夏季，这凸显了对地下水资源进行科学评估的必要性。本研究采用遥感（RS）、地理信息系统（GIS）和层次分析法（AHP）相结合的方法，对Unchehra流域的地下水潜力区（GWPZs）进行了划分。分析中考虑了影响地下水赋存的七个主要因素：线性构造密度、地质、土地利用与土地覆盖（LULC）、河网密度、地貌、坡度和土壤类型。利用ArcGIS从卫星影像和数字高程模型（DEM）数据中制备了这些参数的空间专题图层。通过AHP确定各因素及其类别的相对重要性，为地下水潜力评估提供了系统化的权重方案。将加权图层进行叠加整合，生成了地下水潜力分区图。所得图件将流域划分为五个地下水潜力区：极低、低、中等、高和极高。分析表明，流域面积的7.88%属于极低潜力区，而相当部分区域表现出中等（28.07%）至极高（22.61%）的地下水潜力。为评估所生成模型的可靠性，利用41口随机选取的民井和受试者工作特征（ROC）曲线分析进行了验证。接近零的一致性比率（CR）证实了AHP权重方案的可靠性，而曲线下面积（AUC）值为0.763表明地下水潜力模型具有良好的预测精度。所识别的高和极高地下水潜力区适宜进行地下水开发和人工补给措施，如拦水坝、渗滤池和回灌井。本研究开发的RS-GIS-AHP集成框架为Unchehra流域及类似水文地质条件下的地下水勘探、补给规划和可持续地下水管理提供了可靠的决策支持工具。","Journal of the Geological Society of India","2026-10-01T00:00:00Z",66,{"impact":216,"substance":217,"depth":48,"authority":153,"freshness":216,"relevant":21,"comment":288},"方法扎实、验证可靠的区域地下水潜力评估论文，对农业水资源管理有参考价值，但属印度区域研究，公共影响有限。",[290],{"name":284,"url":281},[159,27,51,292,222],"印度农业",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[295],{"code":37,"slug":38,"name":39,"path":40,"parent_code":34},{"status":42,"locked":14,"version":43,"method":44,"evidence":297},{"candidates":298,"agricultural_evidence":49},[299,303,307,311,316,320],{"code":30,"score":18,"supported":49,"title":300,"abstract":301,"tags":302},[51],[53,51,54],[51],{"code":37,"score":240,"supported":49,"title":304,"abstract":305,"tags":306},[59],[159,59],[159],{"code":63,"score":64,"supported":49,"title":308,"abstract":309,"tags":310},[],[67,68],[],{"code":78,"score":312,"supported":49,"title":313,"abstract":314,"tags":315},5,[],[82],[222,27],{"code":71,"score":20,"supported":49,"title":317,"abstract":318,"tags":319},[],[74],[],{"code":321,"score":21,"supported":14,"title":322,"abstract":323,"tags":324},"J3",[],[],[292],[326,327],"地下水潜力 水资源管理 印度农业 遥感","地下水潜力 水资源管理","地下水潜力水资源管理印度农业遥感-4027","10.17491\u002Fjgsi.2026.174637",{"doi":329,"openalex_id":331,"authors":332,"venue":284,"cited_by_count":130,"oa_url":9,"card":344,"direction":136,"ingested_from":138},"W7215068088",[333,335,337,339,341],{"name":334,"orcid":9},"Rabindra Nath Tiwari",{"name":336,"orcid":9},"Brahmanand Sharma",{"name":338,"orcid":9},"Sarvesh Kumar Patel",{"name":340,"orcid":9},"Aditya Singh Baghel",{"name":342,"orcid":343},"Ashish Kumar Mishra","https:\u002F\u002Forcid.org\u002F0000-0002-9953-4576",{"tldr":345,"method":346,"finding":347,"direction":136,"opportunity":348},"用RS、GIS与AHP集成方法划分印度Unchehra流域地下水潜力区并验证精度。","基于遥感与DEM提取7个因子，AHP加权叠加，41口井与ROC验证。","流域分五级潜力区，高与极高潜力占22.61%，模型AUC达0.763，精度良好。","可将该框架与实时灌溉需水、作物布局耦合，支撑半干旱区精准补灌与地下水回补选址。","2026-10-02T23:30:24.566714Z",{"id":351,"title":352,"url":353,"summary":354,"summary_zh":355,"content":9,"source_name":356,"source_url":353,"published_at":357,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":358,"score_detail":359,"sources":361,"tags":363,"primary_topic":368,"secondary_topics":369,"classification":371,"search_phrases":391,"slug":394,"view_count":21,"doi":395,"paper":396,"created_at":416},2323,"Land cover transformations in northern Algeria from 2001 to 2021: A MODIS-based spatiotemporal analysis","https:\u002F\u002Fdoi.org\u002F10.30493\u002Fdas.2026.011109","Land use\u002Fland cover (LULC) changes in northern Algeria from 2001 to 2021 were investigated in this research. The assessment utilized the MODIS MCD12Q1 dataset combined with Geographic Information System (GIS) techniques. Substantial landscape transformations were highlighted by the findings. Forests (+47.52%), shrublands (+17.65%), wetlands (+58.64%), and natural vegetation (+465.72%) experienced notable growth, whereas a drop of −14.13% was documented for barren lands by the end of study period. Moderate overall growth was displayed by agricultural lands, despite various fluctuations throughout the timeline. Concurrently, a continuous expansion (+3.90%) driven by escalating anthropogenic pressure was recorded in urban and built-up areas. Regional landscape evolution is clearly shaped by a combination of factors. Climatic variability, ecological succession, land management practices, and human activities collectively drive these observed dynamics. Partial alignment with previously documented vegetation recovery and urban expansion trends in Algeria was demonstrated by comparative literature reviews. However, the moderate spatial resolution (500 m) of the MODIS MCD12Q1 product likely caused several identified data discrepancies. Ultimately, the immense value of remote sensing and GIS approaches for regional environmental monitoring is proven by this project. Achieving better classification accuracy in heterogeneous Mediterranean environments, however, strictly necessitates the use of higher-resolution datasets.","本研究探讨了2001年至2021年阿尔及利亚北部土地利用\u002F土地覆盖（LULC）变化。评估采用MODIS MCD12Q1数据集结合地理信息系统（GIS）技术。研究结果凸显了显著的土地景观转变。森林（+47.52%）、灌木地（+17.65%）、湿地（+58.64%）和自然植被（+465.72%）显著增长，而裸地在研究期末则记录了−14.13%的下降。尽管农业用地在时间线上经历了多次波动，但总体上呈现出适度增长。与此同时，城市和建成区因人为压力不断加剧而记录了持续扩张（+3.90%）。区域景观演变显然由多种因素共同塑造。气候变率、生态演替、土地管理实践和人类活动共同驱动了这些观测到的动态。比较文献综述表明，这与阿尔及利亚先前记录的植被恢复和城市扩张趋势部分吻合。然而，MODIS MCD12Q1产品的中等空间分辨率（500米）可能导致了若干已识别的数据差异。最终，本项目证明了遥感和GIS方法在区域环境监测中的巨大价值。然而，要在异质性较强的地中海环境中实现更好的分类精度，严格需要使用更高分辨率的数据集。","DYSONA – Applied Science","2026-09-11T00:00:00Z",62,{"impact":216,"substance":18,"depth":240,"authority":17,"freshness":57,"relevant":21,"comment":360},"基于MODIS数据的阿尔及利亚北部20年土地覆被变化分析，方法规范、数据翔实，对遥感监测与区域生态评估有参考价值，但属境外区域研究，国内产业影响有限。",[362],{"name":356,"url":353},[26,364,365,366,367],"荒漠化","遥感监测","土地利用","植被恢复",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[370],{"code":37,"slug":38,"name":39,"path":40,"parent_code":34},{"status":42,"locked":14,"version":43,"method":44,"evidence":372},{"candidates":373,"agricultural_evidence":49},[374,378,382,387],{"code":30,"score":57,"supported":49,"title":375,"abstract":376,"tags":377},[],[53,51,54],[],{"code":37,"score":216,"supported":49,"title":379,"abstract":380,"tags":381},[],[159,59],[367,365],{"code":383,"score":99,"supported":14,"title":384,"abstract":385,"tags":386},"H6",[],[],[366,364],{"code":91,"score":21,"supported":14,"title":388,"abstract":389,"tags":390},[],[],[26],[392,393],"农业信息化 土地利用 植被恢复 遥感监测","农业信息化 土地利用","农业信息化土地利用植被恢复遥感监测-2323","10.30493\u002Fdas.2026.011109",{"doi":395,"openalex_id":397,"authors":398,"venue":356,"cited_by_count":130,"oa_url":353,"card":411,"direction":136,"ingested_from":138},"W7212238590",[399,401,404,407,409],{"name":400,"orcid":9},"Bilel Zerouali",{"name":402,"orcid":403},"Richarde Marques da Silva","https:\u002F\u002Forcid.org\u002F0000-0001-6601-5174",{"name":405,"orcid":406},"Nadjem Bailek","https:\u002F\u002Forcid.org\u002F0000-0001-9051-8548",{"name":408,"orcid":9},"Valeriano Carneiro de Lima Silva",{"name":410,"orcid":9},"Celso Augusto Guimarães Santos",{"tldr":412,"method":413,"finding":414,"direction":136,"opportunity":415},"基于MODIS数据分析了2001—2021年阿尔及利亚北部土地覆盖的时空变化。","使用MODIS MCD12Q1数据集结合GIS技术进行LULC分类与变化检测。","森林、灌丛、湿地和自然植被显著增长，裸地减少，建设用地持续扩张。","可引入高分辨率遥感数据提升地中海异质景观分类精度，并耦合气候与人为驱动因子做归因分析。","2026-09-13T23:30:23.070977Z",{"id":418,"title":419,"url":420,"summary":421,"summary_zh":422,"content":9,"source_name":423,"source_url":420,"published_at":424,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":130,"score_detail":425,"sources":427,"tags":429,"primary_topic":433,"secondary_topics":434,"classification":440,"search_phrases":456,"slug":459,"view_count":130,"doi":460,"paper":461,"created_at":473},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":130,"substance":130,"depth":130,"authority":130,"freshness":130,"relevant":130,"comment":426},"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。",[428],{"name":423,"url":420},[430,365,431,432],"防灾减灾","洪水风险评估","GIS应用",{"code":37,"slug":38,"name":39,"path":40,"parent_code":34},[435,436],{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},{"code":71,"slug":437,"name":438,"path":439,"parent_code":231},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate",{"status":42,"locked":14,"version":43,"method":44,"evidence":441},{"candidates":442,"agricultural_evidence":49},[443,447,452],{"code":37,"score":240,"supported":49,"title":444,"abstract":445,"tags":446},[59],[159,59],[365],{"code":30,"score":448,"supported":49,"title":449,"abstract":450,"tags":451},14,[51],[53,51],[],{"code":71,"score":216,"supported":49,"title":453,"abstract":454,"tags":455},[],[74,75],[431,430],[457,458],"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":460,"openalex_id":462,"authors":463,"venue":423,"cited_by_count":130,"oa_url":467,"card":468,"direction":136,"ingested_from":138},"W7222885988",[464],{"name":465,"orcid":466},"Birendra Yadav","https:\u002F\u002Forcid.org\u002F0009-0007-0864-474X","https:\u002F\u002Fwww.ijfmr.com\u002Fpapers\u002F2026\u002F5\u002F89708.pdf",{"tldr":469,"method":470,"finding":471,"direction":136,"opportunity":472},"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":475,"title":476,"url":477,"summary":478,"summary_zh":479,"content":9,"source_name":480,"source_url":477,"published_at":481,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":482,"score_detail":483,"sources":485,"tags":487,"primary_topic":491,"secondary_topics":492,"classification":494,"search_phrases":523,"slug":526,"view_count":130,"doi":527,"paper":528,"created_at":546},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":216,"substance":18,"depth":240,"authority":13,"freshness":57,"relevant":21,"comment":484},"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。",[486],{"name":480,"url":477},[159,51,488,489,490],"农用地适宜性","土地覆被","孟加拉农业",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[493],{"code":37,"slug":38,"name":39,"path":40,"parent_code":34},{"status":42,"locked":14,"version":43,"method":44,"evidence":495},{"candidates":496,"agricultural_evidence":49},[497,501,505,512,519],{"code":30,"score":18,"supported":49,"title":498,"abstract":499,"tags":500},[51],[53,51,54],[51],{"code":37,"score":240,"supported":49,"title":502,"abstract":503,"tags":504},[59],[159,59],[159],{"code":506,"score":64,"supported":49,"title":507,"abstract":508,"tags":511},"A1",[],[509,510],"稻米","rice",[],{"code":513,"score":64,"supported":49,"title":514,"abstract":515,"tags":518},"G",[],[516,517],"农村发展","rural development",[],{"code":63,"score":64,"supported":49,"title":520,"abstract":521,"tags":522},[],[67,68],[],[524,525],"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":527,"openalex_id":529,"authors":530,"venue":540,"cited_by_count":130,"oa_url":477,"card":541,"direction":136,"ingested_from":138},"W7222895468",[531,533,535,537],{"name":532,"orcid":9},"Raju Ahmed",{"name":534,"orcid":9},"Shaikh Mehdee Mohammad",{"name":536,"orcid":9},"Ummul Momanin Coalee",{"name":538,"orcid":539},"Khandakar Hasan Mahmud","https:\u002F\u002Forcid.org\u002F0000-0003-1222-0791","The Bangladesh Rural Development Studies",{"tldr":542,"method":543,"finding":544,"direction":136,"opportunity":545},"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"]