[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3279":3,"related-3279":111},{"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":27,"primary_topic":33,"secondary_topics":39,"classification":51,"search_phrases":88,"slug":91,"view_count":78,"doi":92,"paper":93,"created_at":110},3279,"ASSESSMENT OF SOIL SALINIZATION IN IRRIGATED LANDS BASED ON REMOTE SENSING AND GIS TECHNOLOGIES","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22900049","This thesis analyzes modern approaches to monitoring and assessing soil salinity in irrigated areas of Uzbekistan and Central Asia. Soil salinization is one of the major land degradation processes affecting the reclamation condition of irrigated lands, crop growth and agricultural productivity. Although conventional field and laboratory surveys provide detailed information, they have limitations in terms of regular monitoring of large areas. Therefore, remote sensing and geographic information systems provide promising tools for rapid and spatial assessment of soil salinity. The study considers the application of satellite imagery, particularly Sentinel-2 and Landsat data, for soil salinity assessment, including the use of spectral bands and salinity indices, GIS-based thematic mapping, and validation using field and laboratory observations. Recent studies demonstrate the potential of remote sensing data for spatial assessment and mapping of soil salinity under the conditions of Uzbekistan. Such an integrated approach can support rapid monitoring of the reclamation status of irrigated lands, identification of salt-affected areas and spatial planning of appropriate reclamation measures.","本论文分析了乌兹别克斯坦和中亚灌溉区土壤盐分监测与评估的现代方法。土壤盐渍化是影响灌溉土地改良状况、作物生长和农业生产力的主要土地退化过程之一。尽管传统的野外调查和实验室分析能够提供详细信息，但在大范围定期监测方面存在局限性。因此，遥感与地理信息系统为土壤盐分的快速空间评估提供了有前景的工具。本研究探讨了卫星影像，特别是Sentinel-2和Landsat数据在土壤盐分评估中的应用，包括光谱波段和盐分指数的使用、基于GIS的主题制图，以及利用野外和实验室观测数据进行验证。近期研究表明，遥感数据在乌兹别克斯坦条件下用于土壤盐分空间评估与制图具有潜力。这种综合方法可支持灌溉土地改良状况的快速监测、盐渍化区域的识别以及适当改良措施的空间规划。",null,"Zenodo (CERN European Organization for Nuclear Research)","2026-09-22T00:00:00Z","论文",25,false,66,{"impact":17,"substance":18,"depth":19,"authority":17,"freshness":20,"relevant":21,"comment":22},12,18,15,9,1,"基于遥感与GIS的灌溉区土壤盐渍化监测论文，方法成熟、结论可靠，对盐碱地治理与农业信息化有参考价值，但属区域性研究，影响层级有限。",[24,25],{"name":10,"url":6},{"name":10,"url":26},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22900048",[28,29,30,31,32],"土地退化","遥感监测","GIS","土壤盐渍化","灌溉农业",{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis","I",[40,46],{"code":41,"slug":42,"name":43,"path":44,"parent_code":45},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",{"code":47,"slug":48,"name":49,"path":50,"parent_code":38},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"status":52,"locked":14,"version":53,"method":54,"evidence":55},"classified","2026-10-22.2","rules",{"candidates":56,"agricultural_evidence":58},[57,64,70,76,83],{"code":34,"score":18,"supported":58,"title":59,"abstract":60,"tags":63},true,[30],[61,30,62],"地理信息","geographic information",[30],{"code":47,"score":19,"supported":58,"title":65,"abstract":67,"tags":69},[66],"remote sensing",[68,66],"遥感",[29],{"code":41,"score":71,"supported":58,"title":72,"abstract":73,"tags":75},14,[42],[74,42],"土壤",[],{"code":77,"score":78,"supported":58,"title":79,"abstract":80,"tags":82},"H3",4,[],[81],"灌溉",[32],{"code":84,"score":21,"supported":14,"title":85,"abstract":86,"tags":87},"H1",[],[],[28],[89,90],"乌兹别克斯坦 土壤盐渍化 遥感","Sentinel-2 盐渍化 灌溉","乌兹别克斯坦土壤盐渍化遥感-3279","10.5281\u002Fzenodo.22900049",{"doi":92,"openalex_id":94,"authors":95,"venue":10,"cited_by_count":102,"oa_url":6,"card":103,"direction":107,"ingested_from":109},"W7214052773",[96,98,100],{"name":97,"orcid":9},"Mardiyev",{"name":99,"orcid":9},"Ergashaliyev",{"name":101,"orcid":9},"G'aniyev",0,{"tldr":104,"method":105,"finding":106,"direction":107,"opportunity":108},"综述遥感与GIS评估乌兹别克斯坦及中亚灌溉土壤盐渍化的方法。","Sentinel-2与Landsat影像、光谱盐分指数、GIS制图及野外验证。","遥感与GIS可快速空间评估盐渍化，支持灌溉地改良状态监测与规划。","农业遥感与作物表型","可探索多源遥感与机器学习融合的盐分指数模型，提升干旱区盐渍化反演精度与时效。","openalex","2026-09-23T23:30:19.341486Z",{"total":112,"page":21,"page_size":112,"items":113},6,[114,194,247,331,404,462],{"id":115,"title":116,"url":117,"summary":118,"summary_zh":119,"content":9,"source_name":120,"source_url":117,"published_at":121,"category":12,"cover_url":9,"hotness":122,"is_selected":14,"score":123,"score_detail":124,"sources":128,"tags":130,"primary_topic":134,"secondary_topics":135,"classification":138,"search_phrases":171,"slug":174,"view_count":126,"doi":175,"paper":176,"created_at":193},1768,"Remote Sensing and GIS-Based Spatial Planning of Soil and Water Conservation Measures in a Semi-Arid Watershed Maliwadgaon of Maharashtra, India","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fijecc\u002F2026\u002Fv16i95662","Site-specific planning of water harvesting and soil and water conservation (SWC) measures is important for improving water availability and watershed resilience in semi-arid regions. This study aimed to identify and prioritise suitable locations for SWC structures in the 43 km² Maliwadgaon watershed of Chhatrapati Sambhajinagar district, Maharashtra, India, using an integrated remote sensing (RS) and Geographic Information System (GIS) approach. A 30 m Shuttle Radar Topography Mission (SRTM) Digital Elevation Model and Landsat-8 imagery were used to derive terrain, drainage, land use\u002Fland cover (LULC), and vegetation characteristics. Elevation, slope, drainage density, stream order, dissection index, LULC, and normalized difference vegetation index (NDVI) were integrated through multi-criteria evaluation (MCE) for site-suitability assessment. The watershed has an elevation range of approximately 509–591 m and a dendritic, fourth-order drainage network with a drainage density of 0.991 km\u002Fkm². The MCE identified 40 potential conservation structures: 13 farm ponds, 13 cement nala bunds, 5 percolation tanks, 4 underground barriers, and 5 gully plugs. The proposed locations provide a spatial basis for runoff interception, erosion control, water storage, groundwater recharge, and agricultural water management. The findings demonstrate the practical utility of RS–GIS-based MCE as a decision-support approach for prioritising site-specific SWC interventions in a semi-arid watershed.","在半干旱地区，水资源收集及水土保持（SWC）措施的定点规划对于改善水资源可利用性和增强流域韧性至关重要。本研究旨在利用遥感（RS）与地理信息系统（GIS）集成方法，识别并优先确定印度马哈拉施特拉邦恰特拉帕蒂·桑巴吉纳加尔区Maliwadgaon流域（面积43平方公里）内适宜建设水土保持设施的位置。研究采用30米分辨率的航天飞机雷达地形任务（SRTM）数字高程模型和Landsat-8影像，提取地形、水系、土地利用\u002F土地覆盖（LULC）及植被特征。通过多准则评价（MCE）整合高程、坡度、排水密度、河流等级、切割指数、土地利用\u002F土地覆盖及归一化差异植被指数（NDVI），进行选址适宜性评估。该流域海拔范围约为509–591米，水系呈树枝状，为四级排水网络，排水密度为0.991公里\u002F平方公里。多准则评价识别出40处潜在的水土保持设施：13座田间池塘、13座水泥沟壑拦水坝、5座渗滤池、4座地下屏障及5处冲沟堵截设施。所提出的选址为径流拦截、侵蚀控制、蓄水、地下水补给及农业水资源管理提供了空间依据。研究结果表明，基于遥感与地理信息系统的多准则评价作为一种决策支持方法，在半干旱流域优先确定定点水土保持干预措施方面具有实际应用价值。","International Journal of Environment and Climate Change","2026-09-05T00:00:00Z",10,60,{"impact":17,"substance":18,"depth":125,"authority":17,"freshness":126,"relevant":21,"comment":127},16,2,"研究利用遥感和GIS技术在半干旱流域进行水土保持措施选址，方法实用，但时效性较低。",[129],{"name":120,"url":117},[131,68,30,132,133],"农业水资源","水土保持","半干旱区",{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},[136,137],{"code":47,"slug":48,"name":49,"path":50,"parent_code":38},{"code":41,"slug":42,"name":43,"path":44,"parent_code":45},{"status":52,"locked":14,"version":53,"method":54,"evidence":139},{"candidates":140,"agricultural_evidence":58},[141,145,149,154,159,164],{"code":34,"score":18,"supported":58,"title":142,"abstract":143,"tags":144},[30],[61,30,62],[30],{"code":47,"score":19,"supported":58,"title":146,"abstract":147,"tags":148},[66],[68,66],[68],{"code":41,"score":150,"supported":58,"title":151,"abstract":152,"tags":153},11,[42],[42],[],{"code":77,"score":78,"supported":58,"title":155,"abstract":156,"tags":158},[],[157],"水资源",[131],{"code":160,"score":78,"supported":58,"title":161,"abstract":162,"tags":163},"H6",[],[132],[132],{"code":165,"score":166,"supported":58,"title":167,"abstract":168,"tags":170},"H7",3,[],[169],"干旱",[],[172,173],"农业水资源 半干旱区 水土保持 遥感","农业水资源 半干旱区","农业水资源半干旱区水土保持遥感-1768","10.9734\u002Fijecc\u002F2026\u002Fv16i95662",{"doi":175,"openalex_id":177,"authors":178,"venue":120,"cited_by_count":102,"oa_url":117,"card":188,"direction":107,"ingested_from":109},"W7208812908",[179,182,184,186],{"name":180,"orcid":181},"Prasannajit D. Gangurde","https:\u002F\u002Forcid.org\u002F0009-0002-9266-8931",{"name":183,"orcid":9},"Sanjay N. Pawar",{"name":185,"orcid":9},"M. S. Pendke",{"name":187,"orcid":9},"Anilkumar M. Kamble",{"tldr":189,"method":190,"finding":191,"direction":107,"opportunity":192},"利用遥感和GIS对半干旱流域进行水土保持措施的空间规划与选址。","集成SRTM DEM、Landsat-8影像，通过多准则评价进行选址。","识别出40个潜在保护结构，包括池塘、堤坝等，用于水资源管理。","可扩展至其他半干旱流域，结合高分辨率影像和机器学习优化选址精度。","2026-09-06T23:30:27.290464Z",{"id":195,"title":196,"url":197,"summary":198,"summary_zh":199,"content":9,"source_name":200,"source_url":197,"published_at":201,"category":12,"cover_url":9,"hotness":122,"is_selected":14,"score":102,"score_detail":202,"sources":204,"tags":206,"primary_topic":207,"secondary_topics":208,"classification":211,"search_phrases":227,"slug":228,"view_count":102,"doi":229,"paper":230,"created_at":246},5091,"Assessing the impacts of gold mining on vegetation and soil degradation using multi-temporal remote sensing in Kintinian, Siguiri prefecture, Guinea","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.indic.2026.101570","Gold mining, while economically significant, has increasingly driven environmental degradation in many parts of West Africa, including Kintinian in the Siguiri Prefecture of the Republic of Guinea. This study evaluated the extent and environmental impacts of gold mining on soil and vegetation dynamics between 1990 and 2016, with an emphasis on landscape transformation and ecological degradation. The study integrated field observations and ground-truthing with multi-temporal satellite imagery (Landsat 1990, 2000, 2010, and 2016; and Sentinel-1) within the Geographical Pathways to Environmental Sustainability (GPES) framework. Geographic Information Systems (GIS) were employed for change detection analysis, while the Soil-Adjusted Vegetation Index (SAVI) quantified vegetation dynamics and Analytical Hierarchical Principles (AHP) weighed the vulnerability degradation threshold. Findings reveal substantial land-use dynamics associated with intensified mining activities. Agricultural land declined by 13%, while forest cover decreased by 23% over the study period. Vegetation condition deteriorated as SAVI values declined from 0.928 (1990) to 0.602 (2016), indicating reduced vegetative vigor and increasing soil exposure. Soil vulnerability was weighted using Land Use Land Cover (10%), Iron Oxide (35%), Enhanced Built-up and Bare Soil (15%), Ground Soil Index (15%), and Land Surface Temperature (25%), demonstrating significant degradation found at the abandoned industrial mining sites that were reconverted for artisanal mining purposes. The study concluded that gold mining has significantly accelerated landscape transformation, vegetation loss, and soil exposure, suggesting sustainable mining practices and targeted land restoration strategies in the mining-affected regions.","金矿开采虽具有重要经济意义，却在包括几内亚共和国锡吉里省金蒂尼安在内的西非许多地区日益加剧环境退化。本研究评估了1990年至2016年间金矿开采对土壤和植被动态的影响范围及环境效应，重点关注景观转变与生态退化。研究在“环境可持续性地理路径”（GPES）框架内，将实地观测和地面验证与多时相卫星影像（1990、2000、2010和2016年Landsat影像；以及Sentinel-1影像）相结合。采用地理信息系统（GIS）进行变化检测分析，利用土壤调节植被指数（SAVI）量化植被动态，并运用层次分析法（AHP）对脆弱性退化阈值进行加权。研究结果揭示了与采矿活动加剧相关的显著土地利用动态。研究期内，农用地减少13%，森林覆盖减少23%。植被状况恶化，SAVI值从0.928（1990年）降至0.602（2016年），表明植被活力下降、土壤裸露增加。土壤脆弱性采用土地利用\u002F土地覆盖（10%）、氧化铁（35%）、增强型建成区与裸土（15%）、地表土壤指数（15%）和地表温度（25%）进行加权，结果显示，在重新转为手工采矿用途的废弃工业采矿场址，土壤退化显著。研究结论认为，金矿开采显著加速了景观转变、植被丧失和土壤裸露，建议在受采矿影响地区推行可持续采矿实践并实施有针对性的土地恢复策略。","Environmental and Sustainability Indicators","2026-10-15T00:00:00Z",{"impact":102,"substance":102,"depth":102,"authority":102,"freshness":102,"relevant":102,"comment":203},"该论文研究几内亚金矿开采对植被与土壤退化的遥感评估，与三农、农业信息化、智慧农业等主题无关，不建议进入每日精选。",[205],{"name":200,"url":197},[12],{"code":41,"slug":42,"name":43,"path":44,"parent_code":45},[209,210],{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},{"code":47,"slug":48,"name":49,"path":50,"parent_code":38},{"status":52,"locked":14,"version":53,"method":54,"evidence":212},{"candidates":213,"agricultural_evidence":58},[214,218,222],{"code":41,"score":71,"supported":58,"title":215,"abstract":216,"tags":217},[42],[74,42],[],{"code":34,"score":20,"supported":58,"title":219,"abstract":220,"tags":221},[],[61,30,62],[],{"code":47,"score":223,"supported":58,"title":224,"abstract":225,"tags":226},8,[66],[],[],[],"Assessingtheimpactsofgoldminingonvegetat-5091","10.1016\u002Fj.indic.2026.101570",{"doi":229,"openalex_id":231,"authors":232,"venue":200,"cited_by_count":102,"oa_url":197,"card":241,"direction":107,"ingested_from":109},"W7222305702",[233,235,238],{"name":234,"orcid":9},"Mohamed Traoré",{"name":236,"orcid":237},"Opeyemi Aniramu","https:\u002F\u002Forcid.org\u002F0000-0002-5111-0221",{"name":239,"orcid":240},"Oluwagbenga O. I. Orimoogunje","https:\u002F\u002Forcid.org\u002F0000-0001-8070-5040",{"tldr":242,"method":243,"finding":244,"direction":107,"opportunity":245},"评估几内亚金矿开采对植被与土壤退化的影响。","多时相Landsat\u002FSentinel-1影像、GIS变化检测、SAVI与AHP","1990-2016年农地减13%、林地减23%，SAVI由0.928降至0.602，土壤退化严重。","可结合时序遥感与机器学习，构建矿区复垦动态监测与生态恢复评估模型。","2026-10-16T23:30:27.217565Z",{"id":248,"title":249,"url":250,"summary":251,"summary_zh":252,"content":9,"source_name":253,"source_url":250,"published_at":254,"category":12,"cover_url":9,"hotness":122,"is_selected":14,"score":255,"score_detail":256,"sources":261,"tags":263,"primary_topic":268,"secondary_topics":269,"classification":272,"search_phrases":316,"slug":319,"view_count":126,"doi":9,"paper":320,"created_at":330},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":125,"substance":257,"depth":258,"authority":259,"freshness":223,"relevant":21,"comment":260},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。",[262],{"name":253,"url":250},[264,265,68,266,267],"智慧农业","精准农业","盐碱地治理","土壤监测",{"code":47,"slug":48,"name":49,"path":50,"parent_code":38},[270,271],{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},{"code":41,"slug":42,"name":43,"path":44,"parent_code":45},{"status":52,"locked":14,"version":53,"method":54,"evidence":273},{"candidates":274,"agricultural_evidence":58},[275,280,285,289,295,302,306,310],{"code":47,"score":18,"supported":58,"title":276,"abstract":277,"tags":279},[66],[68,66,278],"multispectral",[68],{"code":34,"score":258,"supported":58,"title":281,"abstract":282,"tags":284},[30],[61,283,30,62],"空间分析",[],{"code":41,"score":19,"supported":58,"title":286,"abstract":287,"tags":288},[42],[74,42],[266],{"code":290,"score":122,"supported":58,"title":291,"abstract":293,"tags":294},"I1",[292],"precision agriculture",[],[264,265],{"code":296,"score":112,"supported":58,"title":297,"abstract":298,"tags":301},"I2",[],[299,300],"机器学习","machine learning",[],{"code":77,"score":166,"supported":58,"title":303,"abstract":304,"tags":305},[],[81],[],{"code":165,"score":166,"supported":58,"title":307,"abstract":308,"tags":309},[],[169],[],{"code":311,"score":166,"supported":58,"title":312,"abstract":313,"tags":315},"I7",[],[314],"methodological framework",[],[317,318],"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":321,"authors":322,"venue":253,"cited_by_count":102,"oa_url":250,"card":325,"direction":107,"ingested_from":109},"W7221843179",[323],{"name":324,"orcid":9},"Sadullayev Sardor Zokirjon o'g'li",{"tldr":326,"method":327,"finding":328,"direction":107,"opportunity":329},"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":332,"title":333,"url":334,"summary":335,"summary_zh":336,"content":9,"source_name":337,"source_url":334,"published_at":338,"category":12,"cover_url":9,"hotness":122,"is_selected":14,"score":339,"score_detail":340,"sources":342,"tags":344,"primary_topic":347,"secondary_topics":348,"classification":350,"search_phrases":388,"slug":391,"view_count":21,"doi":392,"paper":393,"created_at":403},3364,"Geographical Analysis of Desertification and Environmental Degradation and the Spatial Variation of Their Manifestations in Parts of the Jifara Plain","https:\u002F\u002Fdoi.org\u002F10.65405\u002Fsjh.2.3.85","This research aims to analyze the spatial variation of desertification and environmental degradation manifestations in the Al-Jfara Plain, identify the degrees, intensity, and geographical distribution of desertification, and determine the main manifestations associated with land degradation. It also seeks to identify the effects of natural and human factors on the spread of desertification and determine the areas most vulnerable to it, thereby contributing to efforts to conserve natural resources and reduce land degradation. The research adopted the analytical approach as the main method for analyzing data related to degraded lands, vegetation cover, rangelands, rainfall, erosion, and agricultural and livestock production. It also employed the descriptive approach to present the natural and human characteristics of the research area, as well as the comparative approach to compare different spatial units and time periods. The research further relied on geographical references, scientific studies, and available data, using percentages and rates of change to compare levels of degradation. The research concluded that there is clear spatial variation in the manifestations of desertification and environmental degradation across the Al-Jfara Plain. Wind erosion, declining vegetation cover, drought, and rainfall variability emerged as the most prominent manifestations of degradation. In addition, overgrazing, excessive exploitation of soil and groundwater resources, and urban expansion contributed to increasing pressure on natural resources. The research recommends reducing overgrazing, rationalizing groundwater use, combating erosion, increasing vegetation cover, regulating land use, and enhancing environmental awareness. It also proposes periodic monitoring of desertification using remote sensing and Geographic Information Systems (GIS), preparing updated maps of land degradation, and implementing projects for the rehabilitation of degraded lands.","本研究旨在分析贾法拉平原荒漠化与环境退化表现的空间差异，识别荒漠化的程度、强度及地理分布，并确定与土地退化相关的主要表现。研究还力求查明自然因素和人为因素对荒漠化蔓延的影响，确定最易受荒漠化影响的区域，从而为保护自然资源和减少土地退化的努力作出贡献。研究采用分析方法作为分析与退化土地、植被覆盖、牧场、降雨、侵蚀以及农牧业生产相关数据的主要方法，同时运用描述性方法呈现研究区域的自然和人文特征，并采用比较方法对不同空间单元和时间段进行比较。研究还依托地理文献、科学研究和现有数据，利用百分比和变化率来比较退化程度。研究得出结论：贾法拉平原各地荒漠化与环境退化表现在明显的空间差异。风蚀、植被覆盖下降、干旱和降雨变率是最突出的退化表现。此外，过度放牧、土壤和地下水资源的过程开发以及城市扩张也加剧了对自然资源的压力。研究建议减少过度放牧、合理利用地下水、防治侵蚀、增加植被覆盖、规范土地利用并增强环境意识。研究还提出利用遥感和地理信息系统（GIS）对荒漠化进行定期监测，编制更新的土地退化地图，并实施退化土地恢复项目。","Shihab Journal of Humanities","2026-09-23T00:00:00Z",55,{"impact":223,"substance":18,"depth":71,"authority":112,"freshness":20,"relevant":21,"comment":341},"区域荒漠化空间分析研究，方法常规、结论有参考价值，但属地方性学术成果，公共影响有限。",[343],{"name":337,"url":334},[28,29,30,345,346],"植被覆盖","荒漠化防治",{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},[349],{"code":47,"slug":48,"name":49,"path":50,"parent_code":38},{"status":52,"locked":14,"version":53,"method":54,"evidence":351},{"candidates":352,"agricultural_evidence":58},[353,357,361,365,370,376,380,384],{"code":34,"score":122,"supported":58,"title":354,"abstract":355,"tags":356},[],[61,30,62],[30],{"code":47,"score":223,"supported":58,"title":358,"abstract":359,"tags":360},[],[68,66],[345,29],{"code":41,"score":112,"supported":58,"title":362,"abstract":363,"tags":364},[],[74,42],[],{"code":165,"score":112,"supported":58,"title":366,"abstract":367,"tags":369},[],[169,368],"drought",[],{"code":371,"score":166,"supported":58,"title":372,"abstract":373,"tags":375},"C",[],[374],"livestock",[],{"code":77,"score":166,"supported":58,"title":377,"abstract":378,"tags":379},[],[157],[],{"code":84,"score":21,"supported":14,"title":381,"abstract":382,"tags":383},[],[],[28],{"code":160,"score":21,"supported":14,"title":385,"abstract":386,"tags":387},[],[],[346],[389,390],"GIS 荒漠化 遥感监测","荒漠化防治 土地退化 植被覆盖 遥感监测","GIS荒漠化遥感监测-3364","10.65405\u002Fsjh.2.3.85",{"doi":392,"openalex_id":394,"authors":395,"venue":337,"cited_by_count":102,"oa_url":334,"card":398,"direction":107,"ingested_from":109},"W7214127171",[396],{"name":397,"orcid":9},"حسنية السني رجب البكوري",{"tldr":399,"method":400,"finding":401,"direction":107,"opportunity":402},"分析吉法拉平原荒漠化与环境退化的空间差异及主要表现，并提出防治建议。","采用分析法、描述法与比较法，结合地理文献和统计数据评估退化程度。","风蚀、植被减少、干旱和降水变率是主要退化表现，过度放牧与地下水超采加剧压力。","可结合遥感与GIS开展荒漠化动态监测，构建多因子退化风险评估模型。","2026-09-24T23:30:21.130938Z",{"id":405,"title":406,"url":407,"summary":408,"summary_zh":409,"content":9,"source_name":10,"source_url":407,"published_at":410,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":411,"score_detail":412,"sources":414,"tags":418,"primary_topic":420,"secondary_topics":421,"classification":423,"search_phrases":442,"slug":445,"view_count":21,"doi":446,"paper":447,"created_at":461},2321,"ASSESSMENT OF SOIL SALINITY USING THE NDVI VEGETATION INDEX BASED ON REMOTE SENSING DATA","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22702718","This article examines the assessment of soil salinity in the irrigated meadow-sierozem soils of the E. Qahhorov agricultural area in Khovos District, Syrdarya Region, based on remote sensing data. Sentinel-2 satellite data covering the period from 2016 to 2025 were used in the study, and the Normalized Difference Vegetation Index (NDVI) was calculated using geospatial technologies. The long-term and seasonal dynamics of vegetation cover in the study area were analyzed, and the relationship between NDVI values and salinity levels was assessed. Based on an NDVI classification adapted to the natural conditions of the study area, criteria for the indirect assessment of soil salinity levels were proposed. The results demonstrated that the NDVI can be effectively used as an indicator for determining the impact of soil salinity on vegetation cover, assessing salinity spatially, and conducting long-term monitoring of salinity in irrigated agricultural lands.","本文基于遥感数据，对锡尔河州霍沃斯区E. Qahhorov农业区灌溉草甸灰钙土的土壤盐渍化进行了评估。研究使用了2016年至2025年期间的Sentinel-2卫星数据，并利用地理空间技术计算了归一化植被指数（NDVI）。分析了研究区植被覆盖的长期和季节性动态，并评估了NDVI值与盐渍化程度之间的关系。基于适应研究区自然条件的NDVI分类，提出了土壤盐渍化程度间接评估的标准。结果表明，NDVI可有效用作确定土壤盐渍化对植被覆盖影响、空间评估盐渍化以及开展灌溉农田盐渍化长期监测的指标。","2026-09-11T00:00:00Z",65,{"impact":17,"substance":18,"depth":19,"authority":17,"freshness":223,"relevant":21,"comment":413},"基于Sentinel-2长时序NDVI数据提出土壤盐渍化间接评估标准，方法可复用但属区域性案例研究，公共影响有限。",[415,416],{"name":10,"url":407},{"name":10,"url":417},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22702719",[264,419,29,31,32],"NDVI",{"code":47,"slug":48,"name":49,"path":50,"parent_code":38},[422],{"code":41,"slug":42,"name":43,"path":44,"parent_code":45},{"status":52,"locked":14,"version":53,"method":54,"evidence":424},{"candidates":425,"agricultural_evidence":58},[426,430,434,438],{"code":47,"score":125,"supported":58,"title":427,"abstract":428,"tags":429},[66],[68,66],[419,29],{"code":41,"score":71,"supported":58,"title":431,"abstract":432,"tags":433},[42],[74,42],[],{"code":77,"score":78,"supported":58,"title":435,"abstract":436,"tags":437},[],[81],[32],{"code":290,"score":21,"supported":14,"title":439,"abstract":440,"tags":441},[],[],[264],[443,444],"土壤盐渍化 智慧农业 灌溉农业 遥感监测","土壤盐渍化 智慧农业","土壤盐渍化智慧农业灌溉农业遥感监测-2321","10.5281\u002Fzenodo.22702718",{"doi":446,"openalex_id":448,"authors":449,"venue":10,"cited_by_count":102,"oa_url":407,"card":456,"direction":107,"ingested_from":109},"W7212227143",[450,452,454],{"name":451,"orcid":9},"U.K. Umirova",{"name":453,"orcid":9},"D.A. Kodirova",{"name":455,"orcid":9},"O.O. Davronov",{"tldr":457,"method":458,"finding":459,"direction":107,"opportunity":460},"利用Sentinel-2遥感数据计算NDVI，评估灌溉草甸灰钙土的土壤盐渍化程度。","Sentinel-2数据（2016-2025）与NDVI指数，结合地理空间技术分","NDVI可有效指示盐渍化对植被的影响，实现空间评估与长期监测。","可探索多指数融合与机器学习提升盐渍化反演精度，并推广至不同土壤类型区。","2026-09-13T23:30:22.820810Z",{"id":463,"title":464,"url":465,"summary":466,"summary_zh":467,"content":9,"source_name":468,"source_url":465,"published_at":469,"category":12,"cover_url":9,"hotness":122,"is_selected":14,"score":470,"score_detail":471,"sources":473,"tags":475,"primary_topic":479,"secondary_topics":480,"classification":486,"search_phrases":507,"slug":510,"view_count":112,"doi":511,"paper":512,"created_at":526},3174,"Remote sensing and geospatial modeling for the detection of war-induced land use abandonment, soil disturbance, and degradation in Sumy region of Ukraine: a systematic review","https:\u002F\u002Fdoi.org\u002F10.31548\u002Fzemleustriy2026.03.015","The full-scale military invasion of Ukraine has caused multidimensional transformations of agricultural landscapes, land cover, and ecosystems. The Sumy region, located along the northeastern border with the Russian Federation, is a critical region that has suffered from intense fighting, prolonged artillery shelling, and ongoing border clashes during the study period from 2022 to May 2026. This paper systematically evaluates the application of remote sensing and geospatial modeling techniques to detect, quantify, and monitor war-induced land abandonment, as well as physical land cover disturbances, chemical contamination, and broader environmental degradation in this theater of war. Combining recent scientific publications on the war in Ukraine and comparative global examples (Syria, Iraq, and Sudan), the effectiveness of integrating multi-sensor data, including optical (Sentinel-2, Landsat), synthetic aperture radar (SAR; Sentinel-1), thermal, and very high resolution (VHR; Maxar, WorldView) platforms, as well as advanced machine and deep learning algorithms (Random Forest, Deep Learning) and time series analysis (FANTA, two-period curve approximation), is assessed. The results of the study show that while geospatial modeling is an indispensable tool for rapid, large-scale, and non-contact damage assessment in active conflict settings, significant critical research gaps remain, namely separating short-term cessation of agricultural use from actual land abandonment caused by war, verifying such facts in the face of a severe shortage of reliable ground data, and managing sensitive geospatial information. This systematic review highlights existing methodological gaps and outlines future perspectives needed to build a harmonized spatial monitoring system capable of guiding post-conflict recovery and environmental remediation based on actual remote sensing data at the regional scale.Received: 01.07.2026;Accepted:26.08.2026;","乌克兰遭受的大规模军事入侵已导致农业景观、土地覆盖和生态系统发生多维转变。苏梅州位于乌克兰与俄罗斯联邦东北部接壤的边境沿线，是一个关键地区，在研究期间（2022年至2026年5月）遭受了激烈战斗、长期炮击以及持续边境冲突的影响。本文系统评估了遥感与地理空间建模技术在探测、量化和监测该战区战争导致的土地撂荒、土地覆盖物理扰动、化学污染及更广泛环境退化方面的应用。结合近期关于乌克兰战争的科学出版物及全球比较案例（叙利亚、伊拉克和苏丹），本文评估了多传感器数据整合的有效性，包括光学（Sentinel-2、Landsat）、合成孔径雷达（SAR；Sentinel-1）、热红外及甚高分辨率（VHR；Maxar、WorldView）平台，以及先进的机器学习和深度学习算法（随机森林、深度学习）和时间序列分析（FANTA、两期曲线近似）。研究结果表明，尽管地理空间建模是在活跃冲突环境中进行快速、大规模、非接触式损害评估不可或缺的工具，但仍存在重要的关键研究空白，即如何区分农业利用的短期中止与战争导致的实际土地撂荒，如何在严重缺乏可靠地面数据的情况下核实此类事实，以及如何管理敏感的地理空间信息。本系统综述指出了现有的方法论空白，并勾勒了未来前景，以构建一个协调的空间监测系统，从而基于区域尺度上的实际遥感数据指导冲突后恢复和环境修复。收稿日期：2026年7月1日；接受日期：2026年8月26日；","Zemleustrìj kadastr ì monìtorìng zemelʹ","2026-09-21T00:00:00Z",75,{"impact":18,"substance":257,"depth":258,"authority":17,"freshness":223,"relevant":21,"comment":472},"系统综述遥感与地理空间建模在战区耕地撂荒与土壤退化识别中的应用，方法体系与数据源梳理扎实，对农业遥感监测有参考价值，但属境外冲突场景研究，国内落地关联度有限。",[474],{"name":468,"url":465},[476,28,29,477,478],"农业人工智能","耕地撂荒","冲突农业",{"code":47,"slug":48,"name":49,"path":50,"parent_code":38},[481,485],{"code":296,"slug":482,"name":483,"path":484,"parent_code":38},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",{"code":41,"slug":42,"name":43,"path":44,"parent_code":45},{"status":52,"locked":14,"version":53,"method":54,"evidence":487},{"candidates":488,"agricultural_evidence":58},[489,493,499,503],{"code":47,"score":19,"supported":58,"title":490,"abstract":491,"tags":492},[66],[68,66],[29],{"code":296,"score":122,"supported":58,"title":494,"abstract":495,"tags":498},[],[496,299,497],"深度学习","deep learning",[476],{"code":41,"score":223,"supported":58,"title":500,"abstract":501,"tags":502},[42],[],[],{"code":84,"score":21,"supported":14,"title":504,"abstract":505,"tags":506},[],[],[28],[508,509],"乌克兰 苏梅州 遥感 耕地撂荒","Sentinel-1 合成孔径雷达 土地退化监测","乌克兰苏梅州遥感耕地撂荒-3174","10.31548\u002Fzemleustriy2026.03.015",{"doi":511,"openalex_id":513,"authors":514,"venue":468,"cited_by_count":102,"oa_url":465,"card":521,"direction":107,"ingested_from":109},"W7213890485",[515,517,519],{"name":516,"orcid":9},"V. Bogdanets",{"name":518,"orcid":9},"Ye. Berezhniak",{"name":520,"orcid":9},"D. Brovko",{"tldr":522,"method":523,"finding":524,"direction":107,"opportunity":525},"系统综述遥感与地理空间建模在乌克兰苏梅地区检测战争导致的土地弃耕、土壤扰动与退化的应用。","综述多源遥感（Sentinel-2\u002F1、Landsat、VHR）与机器学习、时间","遥感是冲突区快速非接触损害评估的关键工具，但区分短期停耕与真正弃耕、地面数据匮乏及敏感信息管理仍是重","可研究多源时序遥感与弱监督学习结合，构建冲突区弃耕识别与地面验证缺失下的不确定性量化框架。","2026-09-22T23:30:23.289241Z"]