[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1308":3,"related-1308":106},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"primary_topic":24,"secondary_topics":30,"classification":31,"search_phrases":87,"slug":90,"view_count":78,"doi":91,"paper":92,"created_at":105},1308,"A Bibliometric Analysis of Land Degradation and Desertification Monitoring Based on the Scopus Database (2021–2025)","https:\u002F\u002Fdoi.org\u002F10.52939\u002Fijg.v22i8.5142","Land degradation and desertification threaten ecological balance, agricultural productivity, and human well-being, particularly in arid and semi-arid zones. This study presents a bibliometric analysis of global research on land degradation and desertification monitoring using remote sensing and geographic information systems (GIS) for the period 2021–2025, based on the Scopus database. A total of 655 peer-reviewed articles were retrieved and analysed with the Bibliometrix package in R to examine publication trends, leading journals, productive authors, institutions, contributing countries, collaboration patterns, and thematic structure. The results show an overall upward trend in scientific output, especially after 2022, alongside the rapid integration of machine learning, cloud computing, and advanced satellite data into monitoring workflows; remote sensing, land degradation, and GIS were the most frequent keywords. Output and citations were highly concentrated in a few countries, led by China, and the insti","土地退化与荒漠化威胁着生态平衡、农业生产力和人类福祉，尤其是在干旱和半干旱地区。本研究基于Scopus数据库，对2021—2025年期间利用遥感（remote sensing）和地理信息系统（GIS）监测土地退化与荒漠化的全球研究进行了文献计量分析。共检索到655篇同行评审论文，并使用R语言中的Bibliometrix软件包进行分析，以考察发文趋势、主要期刊、高产作者、研究机构、贡献国家、合作模式及主题结构。结果表明，科学产出总体呈上升趋势，尤其是2022年之后，同时机器学习（machine learning）、云计算（cloud computing）和先进卫星数据正迅速融入监测工作流程；遥感、土地退化（land degradation）和地理信息系统是最常见的关键词。产出和引用高度集中于少数国家，其中中国居首，研究机构方面也呈现类似的集中态势。",null,"International Journal of Geoinformatics","2026-08-31T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"主题为土地退化与荒漠化监测的文献计量分析，不直接涉及农业信息化或智慧农业，相关性不足。",[19],{"name":10,"url":6},[21,22,23],"遥感","土地退化","荒漠化",{"code":25,"slug":26,"name":27,"path":28,"parent_code":29},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis","I",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":35},"classified","2026-10-22.2","rules",{"candidates":36,"agricultural_evidence":40},[37,46,54,61,69,76,82],{"code":38,"score":39,"supported":40,"title":41,"abstract":43,"tags":45},"I7",14,true,[42],"bibliometric",[44,42],"文献计量",[],{"code":25,"score":47,"supported":40,"title":48,"abstract":49,"tags":53},9,[],[50,51,52],"地理信息","GIS","geographic information",[],{"code":55,"score":56,"supported":40,"title":57,"abstract":58,"tags":60},"I3",7,[],[21,59],"remote sensing",[21],{"code":62,"score":63,"supported":40,"title":64,"abstract":65,"tags":68},"I2",6,[],[66,67],"机器学习","machine learning",[],{"code":70,"score":71,"supported":40,"title":72,"abstract":73,"tags":75},"H7",3,[],[74],"干旱",[],{"code":77,"score":78,"supported":14,"title":79,"abstract":80,"tags":81},"H1",1,[],[],[22],{"code":83,"score":78,"supported":14,"title":84,"abstract":85,"tags":86},"H6",[],[],[23],[88,89],"土地退化 荒漠化 遥感","土地退化 荒漠化","土地退化荒漠化遥感-1308","10.52939\u002Fijg.v22i8.5142",{"doi":91,"openalex_id":93,"authors":94,"venue":10,"cited_by_count":15,"oa_url":6,"card":98,"direction":102,"ingested_from":104},"W7204753905",[95],{"name":96,"orcid":97},"B. Oralbaev","https:\u002F\u002Forcid.org\u002F0009-0003-7616-8192",{"tldr":99,"method":100,"finding":101,"direction":102,"opportunity":103},"基于Scopus数据库，对2021-2025年土地退化与荒漠化监测研究进行文献计量分析。","使用R的Bibliometrix包分析655篇论文，包括发文趋势、作者、机构、合","发文量上升，机器学习、云计算和卫星数据集成加速，中国领先，但产出和引用高度集中。","农业遥感与作物表型","可探索发展中国家或区域合作中的监测技术应用，或结合多源数据与AI提升荒漠化预警精度。","openalex","2026-09-01T23:30:19.857413Z",{"total":63,"page":78,"page_size":63,"items":107},[108,179,256,340,401,470],{"id":109,"title":110,"url":111,"summary":112,"summary_zh":113,"content":9,"source_name":114,"source_url":111,"published_at":115,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":116,"score_detail":117,"sources":122,"tags":124,"primary_topic":128,"secondary_topics":129,"classification":130,"search_phrases":159,"slug":162,"view_count":15,"doi":163,"paper":164,"created_at":178},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":118,"substance":119,"depth":39,"authority":120,"freshness":47,"relevant":78,"comment":121},8,18,12,"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。",[123],{"name":114,"url":111},[21,125,126,51,127],"土地利用","土壤侵蚀","水土保持",{"code":25,"slug":26,"name":27,"path":28,"parent_code":29},[],{"status":32,"locked":14,"version":33,"method":34,"evidence":131},{"candidates":132,"agricultural_evidence":40},[133,137,141,148,154],{"code":25,"score":13,"supported":40,"title":134,"abstract":135,"tags":136},[],[50,51,52],[51],{"code":55,"score":56,"supported":40,"title":138,"abstract":139,"tags":140},[],[21,59],[21],{"code":142,"score":63,"supported":40,"title":143,"abstract":144,"tags":147},"H2",[],[145,146],"土壤","soil",[],{"code":149,"score":71,"supported":40,"title":150,"abstract":151,"tags":153},"H3",[],[152],"灌溉",[],{"code":83,"score":155,"supported":14,"title":156,"abstract":157,"tags":158},2,[],[],[125,127],[160,161],"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":163,"openalex_id":165,"authors":166,"venue":114,"cited_by_count":15,"oa_url":9,"card":172,"direction":102,"ingested_from":104},"W7223117733",[167,169],{"name":168,"orcid":9},"MERİÇ KURT",{"name":170,"orcid":171},"Celal ŞENOL","https:\u002F\u002Forcid.org\u002F0000-0003-0857-866X",{"tldr":173,"method":174,"finding":175,"direction":176,"opportunity":177},"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":180,"title":181,"url":182,"summary":183,"summary_zh":184,"content":9,"source_name":185,"source_url":182,"published_at":186,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":187,"score_detail":188,"sources":191,"tags":193,"primary_topic":197,"secondary_topics":198,"classification":203,"search_phrases":232,"slug":235,"view_count":15,"doi":236,"paper":237,"created_at":255},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":118,"substance":119,"depth":189,"authority":13,"freshness":47,"relevant":78,"comment":190},15,"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。",[192],{"name":185,"url":182},[21,51,194,195,196],"农用地适宜性","土地覆被","孟加拉农业",{"code":25,"slug":26,"name":27,"path":28,"parent_code":29},[199],{"code":55,"slug":200,"name":201,"path":202,"parent_code":29},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"status":32,"locked":14,"version":33,"method":34,"evidence":204},{"candidates":205,"agricultural_evidence":40},[206,210,214,221,228],{"code":25,"score":119,"supported":40,"title":207,"abstract":208,"tags":209},[51],[50,51,52],[51],{"code":55,"score":189,"supported":40,"title":211,"abstract":212,"tags":213},[59],[21,59],[21],{"code":215,"score":63,"supported":40,"title":216,"abstract":217,"tags":220},"A1",[],[218,219],"稻米","rice",[],{"code":222,"score":63,"supported":40,"title":223,"abstract":224,"tags":227},"G",[],[225,226],"农村发展","rural development",[],{"code":142,"score":63,"supported":40,"title":229,"abstract":230,"tags":231},[],[145,146],[],[233,234],"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":236,"openalex_id":238,"authors":239,"venue":249,"cited_by_count":15,"oa_url":182,"card":250,"direction":102,"ingested_from":104},"W7222895468",[240,242,244,246],{"name":241,"orcid":9},"Raju Ahmed",{"name":243,"orcid":9},"Shaikh Mehdee Mohammad",{"name":245,"orcid":9},"Ummul Momanin Coalee",{"name":247,"orcid":248},"Khandakar Hasan Mahmud","https:\u002F\u002Forcid.org\u002F0000-0003-1222-0791","The Bangladesh Rural Development Studies",{"tldr":251,"method":252,"finding":253,"direction":102,"opportunity":254},"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":257,"title":258,"url":259,"summary":260,"summary_zh":261,"content":9,"source_name":262,"source_url":259,"published_at":263,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":264,"score_detail":265,"sources":271,"tags":273,"primary_topic":278,"secondary_topics":279,"classification":285,"search_phrases":325,"slug":328,"view_count":155,"doi":9,"paper":329,"created_at":339},5013,"REMOTE SENSING AND GIS-BASED ASSESSMENT OF SOIL SALINITY IN IRRIGATED LANDS: METHODS, CHALLENGES AND PROSPECTS FOR PRECISION AGRICULTURE","http:\u002F\u002Fwww.arabianjournalofscience.com\u002Findex.php\u002Findex\u002Farticle\u002Fview\u002F1223","Soil salinization is a major land degradation process affecting the sustainability of irrigated agriculture, particularly in arid and semi-arid regions. Conventional soil sampling provides essential information about salinity levels but may be insufficient for continuous monitoring of large agricultural territories because of spatial variability, sampling costs, and temporal limitations. Remote sensing (RS) and geographic information systems (GIS) offer complementary approaches for identifying spatial patterns of salinity, monitoring land conditions, and supporting agricultural management. This article examines the scientific and methodological foundations of integrating multispectral satellite imagery, spectral indices, geospatial analysis, and machine learning for soil salinity assessment in irrigated lands. Particular attention is given to Landsat and Sentinel-2 imagery, the interpretation of vegetation and soil reflectance indicators, the role of electrical conductivity measurements in model calibration, and the limitations associated with vegetation cover, soil moisture, and seasonal variability. The analysis indicates that reliable salinity assessment requires the integration of satellite observations with field measurements and environmental variables rather than the isolated application of spectral indices. The article proposes a methodological framework for developing spatially explicit salinity assessment systems applicable to irrigated agricultural landscapes, including those of Central Asia. The framework provides a basis for improving monitoring strategies and supporting evidence-based land management without assuming unverified local measurement results.","土壤盐渍化是影响灌溉农业可持续性的主要土地退化过程，在干旱和半干旱地区尤为突出。传统土壤采样可提供盐分水平的基本信息，但由于空间变异性、采样成本和时间限制，可能不足以对大面积农业区域进行持续监测。遥感（RS）和地理信息系统（GIS）为识别盐渍化空间格局、监测土地状况和支持农业管理提供了互补性方法。本文探讨了整合多光谱卫星影像、光谱指数、地理空间分析和机器学习进行灌溉土地土壤盐渍化评估的科学与方法学基础。文章特别关注Landsat和Sentinel-2影像、植被与土壤反射率指标的解译、电导率测量在模型校准中的作用，以及与植被覆盖、土壤湿度和季节变异性相关的局限性。分析表明，可靠的盐渍化评估需要将卫星观测与野外测量和环境变量相结合，而非孤立地应用光谱指数。本文提出了一个方法学框架，用于开发适用于灌溉农业景观（包括中亚地区）的空间显式盐渍化评估系统。该框架为改进监测策略和支持基于证据的土地管理提供了基础，且不以未经核实的当地测量结果为假设前提。","Arabian journal of science.","2026-10-13T00:00:00Z",74,{"impact":266,"substance":267,"depth":268,"authority":269,"freshness":118,"relevant":78,"comment":270},16,20,17,13,"系统综述遥感与GIS在灌溉农田盐渍化评估中的方法框架与挑战，对盐碱地治理和精准农业有参考价值，但属综述性论文，非突破性成果。",[272],{"name":262,"url":259},[274,275,21,276,277],"智慧农业","精准农业","盐碱地治理","土壤监测",{"code":55,"slug":200,"name":201,"path":202,"parent_code":29},[280,281],{"code":25,"slug":26,"name":27,"path":28,"parent_code":29},{"code":142,"slug":146,"name":282,"path":283,"parent_code":284},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",{"status":32,"locked":14,"version":33,"method":34,"evidence":286},{"candidates":287,"agricultural_evidence":40},[288,293,298,302,308,312,316,320],{"code":55,"score":119,"supported":40,"title":289,"abstract":290,"tags":292},[59],[21,59,291],"multispectral",[21],{"code":25,"score":268,"supported":40,"title":294,"abstract":295,"tags":297},[51],[50,296,51,52],"空间分析",[],{"code":142,"score":189,"supported":40,"title":299,"abstract":300,"tags":301},[146],[145,146],[276],{"code":303,"score":13,"supported":40,"title":304,"abstract":306,"tags":307},"I1",[305],"precision agriculture",[],[274,275],{"code":62,"score":63,"supported":40,"title":309,"abstract":310,"tags":311},[],[66,67],[],{"code":149,"score":71,"supported":40,"title":313,"abstract":314,"tags":315},[],[152],[],{"code":70,"score":71,"supported":40,"title":317,"abstract":318,"tags":319},[],[74],[],{"code":38,"score":71,"supported":40,"title":321,"abstract":322,"tags":324},[],[323],"methodological framework",[],[326,327],"遥感 GIS 土壤盐渍化","Landsat Sentinel-2 盐分监测","遥感GIS土壤盐渍化-5013",{"doi":9,"openalex_id":330,"authors":331,"venue":262,"cited_by_count":15,"oa_url":259,"card":334,"direction":102,"ingested_from":104},"W7221843179",[332],{"name":333,"orcid":9},"Sadullayev Sardor Zokirjon o'g'li",{"tldr":335,"method":336,"finding":337,"direction":102,"opportunity":338},"综述遥感与GIS评估灌溉地土壤盐渍化的方法、挑战与前景，并提出空间显式评估框架。","整合多光谱卫星影像、光谱指数、GIS空间分析与机器学习，结合电导率校准。","可靠盐渍化评估需卫星观测与实地测量及环境变量融合，而非孤立使用光谱指数。","可探索多源遥感与机器学习融合的盐渍化动态监测，并验证于中亚等干旱灌区。","2026-10-15T23:30:32.401626Z",{"id":341,"title":342,"url":343,"summary":344,"summary_zh":345,"content":9,"source_name":346,"source_url":343,"published_at":347,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":264,"score_detail":348,"sources":351,"tags":353,"primary_topic":358,"secondary_topics":359,"classification":361,"search_phrases":385,"slug":388,"view_count":15,"doi":389,"paper":390,"created_at":400},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",{"impact":120,"substance":349,"depth":119,"authority":269,"freshness":47,"relevant":78,"comment":350},22,"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。",[352],{"name":346,"url":343},[354,21,355,356,357],"农业遥感","水资源管理","灌溉农业","盐渍化",{"code":55,"slug":200,"name":201,"path":202,"parent_code":29},[360],{"code":25,"slug":26,"name":27,"path":28,"parent_code":29},{"status":32,"locked":14,"version":33,"method":34,"evidence":362},{"candidates":363,"agricultural_evidence":40},[364,368,373,377,381],{"code":55,"score":266,"supported":40,"title":365,"abstract":366,"tags":367},[59],[21,59],[354,21],{"code":25,"score":369,"supported":40,"title":370,"abstract":371,"tags":372},11,[51],[51],[],{"code":142,"score":56,"supported":40,"title":374,"abstract":375,"tags":376},[],[145,146],[357],{"code":70,"score":71,"supported":40,"title":378,"abstract":379,"tags":380},[],[74],[],{"code":149,"score":155,"supported":14,"title":382,"abstract":383,"tags":384},[],[],[355,356],[386,387],"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":389,"openalex_id":391,"authors":392,"venue":346,"cited_by_count":15,"oa_url":343,"card":395,"direction":102,"ingested_from":104},"W7221819099",[393],{"name":394,"orcid":9},"Akbarov Sarvarbek",{"tldr":396,"method":397,"finding":398,"direction":102,"opportunity":399},"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":402,"title":403,"url":404,"summary":405,"summary_zh":406,"content":9,"source_name":407,"source_url":404,"published_at":408,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":409,"score_detail":410,"sources":412,"tags":414,"primary_topic":417,"secondary_topics":418,"classification":424,"search_phrases":449,"slug":452,"view_count":15,"doi":453,"paper":454,"created_at":469},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":118,"substance":267,"depth":268,"authority":269,"freshness":47,"relevant":78,"comment":411},"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。",[413],{"name":407,"url":404},[21,355,51,415,416],"地下水潜力","乌干达农业",{"code":25,"slug":26,"name":27,"path":28,"parent_code":29},[419,420],{"code":55,"slug":200,"name":201,"path":202,"parent_code":29},{"code":149,"slug":421,"name":422,"path":423,"parent_code":284},"irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",{"status":32,"locked":14,"version":33,"method":34,"evidence":425},{"candidates":426,"agricultural_evidence":40},[427,431,435,441,445],{"code":25,"score":119,"supported":40,"title":428,"abstract":429,"tags":430},[51],[50,51,52],[51],{"code":55,"score":189,"supported":40,"title":432,"abstract":433,"tags":434},[59],[21,59],[21],{"code":149,"score":118,"supported":40,"title":436,"abstract":437,"tags":440},[],[438,439],"水资源","water resource",[415,355],{"code":142,"score":63,"supported":40,"title":442,"abstract":443,"tags":444},[],[145,146],[],{"code":70,"score":71,"supported":40,"title":446,"abstract":447,"tags":448},[],[74],[],[450,451],"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":453,"openalex_id":455,"authors":456,"venue":407,"cited_by_count":15,"oa_url":404,"card":464,"direction":102,"ingested_from":104},"W7221339030",[457,460,462],{"name":458,"orcid":459},"Ahmed Abdirizak Dirie","https:\u002F\u002Forcid.org\u002F0009-0002-8109-0724",{"name":461,"orcid":9},"Abdulkadir Ahmed Mohamed",{"name":463,"orcid":9},"Ambiga Kannapiran",{"tldr":465,"method":466,"finding":467,"direction":102,"opportunity":468},"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":471,"title":472,"url":473,"summary":474,"summary_zh":475,"content":9,"source_name":476,"source_url":473,"published_at":477,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":478,"score_detail":479,"sources":481,"tags":483,"primary_topic":486,"secondary_topics":487,"classification":488,"search_phrases":507,"slug":510,"view_count":78,"doi":511,"paper":512,"created_at":537},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":118,"substance":267,"depth":266,"authority":120,"freshness":118,"relevant":78,"comment":480},"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。",[482],{"name":476,"url":473},[21,125,51,484,485],"灾害风险","滑坡易发性",{"code":25,"slug":26,"name":27,"path":28,"parent_code":29},[],{"status":32,"locked":14,"version":33,"method":34,"evidence":489},{"candidates":490,"agricultural_evidence":40},[491,495,499,503],{"code":25,"score":13,"supported":40,"title":492,"abstract":493,"tags":494},[],[50,51,52],[51],{"code":55,"score":56,"supported":40,"title":496,"abstract":497,"tags":498},[],[21,59],[21],{"code":142,"score":63,"supported":40,"title":500,"abstract":501,"tags":502},[],[145,146],[],{"code":83,"score":78,"supported":14,"title":504,"abstract":505,"tags":506},[],[],[125],[508,509],"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":511,"openalex_id":513,"authors":514,"venue":476,"cited_by_count":15,"oa_url":473,"card":532,"direction":102,"ingested_from":104},"W7221122595",[515,518,520,522,524,526,528,530],{"name":516,"orcid":517},"Engdaw Gulbet Tebege","https:\u002F\u002Forcid.org\u002F0009-0008-4252-1249",{"name":519,"orcid":9},"Belete Getahun",{"name":521,"orcid":9},"Yohannes Dessalegn Girma",{"name":523,"orcid":9},"Yibeltal Awoke Temeche",{"name":525,"orcid":9},"Worku Birhan Fenklew",{"name":527,"orcid":9},"Ayalnesh Mihrete Tagele",{"name":529,"orcid":9},"Gashaw Tesfaw Chekole",{"name":531,"orcid":9},"Muluken Mintesinot",{"tldr":533,"method":534,"finding":535,"direction":102,"opportunity":536},"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"]