[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1442":3,"related-1442":174},{"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":30,"secondary_topics":36,"classification":49,"search_phrases":123,"slug":126,"view_count":21,"doi":127,"paper":128,"created_at":173},1442,"Morphological, Taxonomic and Soil Suitability Evaluation for Sustainable Crop Production Using GIS and Remote Sensing in Gudvella Block, Balangir District, Odisha State, India","https:\u002F\u002Fdoi.org\u002F10.56557\u002Fjoban\u002F2026\u002Fv18i211054","A comprehensive soil-landscape assessment was undertaken to characterise the morphological, physicochemical and taxonomic properties of soils and to evaluate their suitability for major crops using a GIS-based approach. The study area exhibited considerable physiographic heterogeneity, comprising upper and lower pedi-plains, depressions, hillside slopes, foothill slopes, hillocks and stream-bank positions. Twenty-five representative pedons were examined for morphological and physicochemical characteristics and classified according to Soil Taxonomy. Soil depth varied from 14 to 125 cm, while textures ranged from loamy-skeletal to fine. Soil reaction ranged from strongly acidic to slightly alkaline (pH 4.97-7.85), whereas electrical conductivity (0.01-0.08 dS m-1) and exchangeable sodium percentage (0.56-8.35%) indicated negligible salinity and sodicity constraints. Organic carbon was generally low (0.05-0.50%), while CEC (3.85-37.69 cmol(p⁺) kg-1) and base saturation (21.04-72.90%) varied substantially among pedons. The soils were classified mainly as Entisols, Inceptisols and Alfisols, with Aquic, Lithic, Vertic and related intergrades reflecting contrasting soil-forming environments. Crop suitability assessment revealed marked differences among land-use types. Paddy had 68.3% of the area within the S1-S3 classes, whereas maize, potato and sugarcane each occupied approximately 86% within S2-S3. Cotton, mustard and sunflower were predominantly marginally suitable, with substantial areas classified as N1. Approximately 4% of the area was permanently unsuitable (N2). The results demonstrate that soil suitability is controlled by the interaction of soil properties and landscape processes. The integration of soil survey, taxonomy and GIS-based suitability evaluation provides a robust basis for crop-specific land-use planning, soil and water conservation and sustainable agricultural intensification.","为表征土壤的形态学、物理化学及分类学特性，并采用基于GIS的方法评估其对主要作物的适宜性，开展了一项综合的土壤-景观评估。研究区域表现出显著的地貌异质性，包括上、下麓原、洼地、山坡、山麓坡、丘陵及河岸带。对25个代表性土壤剖面进行了形态学和物理化学特性分析，并根据土壤系统分类法进行分类。土壤深度变化范围为14至125厘米，质地从壤质砾石到细质不等。土壤反应范围从强酸性到微碱性（pH 4.97-7.85），而电导率（0.01-0.08 dS m⁻¹）和交换性钠百分比（0.56-8.35%）表明盐分和钠质限制可忽略不计。有机碳普遍较低（0.05-0.50%），而阳离子交换量（3.85-37.69 cmol(p⁺) kg⁻¹）和盐基饱和度（21.04-72.90%）在各剖面间差异显著。土壤主要归类为新成土、始成土和淋溶土，其中包含潮湿润、石质、变性及相关的过渡类型，反映了不同的成土环境。作物适宜性评估揭示了不同土地利用类型间的显著差异。水稻有68.3%的面积属于S1-S3等级，而玉米、马铃薯和甘蔗在S2-S3等级中各占约86%。棉花、芥菜和向日葵主要为边缘适宜，有相当面积的区域被归类为N1。约4%的区域为永久不适宜（N2）。结果表明，土壤适宜性受土壤性质与景观过程相互作用的控制。土壤调查、分类学与基于GIS的适宜性评价的整合，为特定作物的土地利用规划、水土保持及可持续农业集约化提供了坚实基础。",null,"Journal of biology and nature","2026-09-01T00:00:00Z","论文",10,false,52,{"impact":17,"substance":18,"depth":19,"authority":17,"freshness":20,"relevant":21,"comment":22},8,18,16,2,1,"区域土壤适宜性评价研究，数据详实，但影响范围有限，时效性较低。",[24],{"name":10,"url":6},[26,27,28,29],"农业遥感","土壤调查","作物适宜性","GIS",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",[37,43],{"code":38,"slug":39,"name":40,"path":41,"parent_code":42},"A6","cash-crops","棉麻糖与特色经作","\u002Ftopic\u002Ffield-crops\u002Fcash-crops","A",{"code":44,"slug":45,"name":46,"path":47,"parent_code":48},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis","I",{"status":50,"locked":14,"version":51,"method":52,"evidence":53},"classified","2026-10-22.2","rules",{"candidates":54,"agricultural_evidence":57},[55,62,67,76,82,90,97,104,111,117],{"code":31,"score":56,"supported":57,"title":58,"abstract":59,"tags":61},14,true,[32],[60,32],"土壤",[],{"code":44,"score":63,"supported":57,"title":64,"abstract":65,"tags":66},12,[29],[29],[29],{"code":38,"score":68,"supported":57,"title":69,"abstract":70,"tags":75},9,[],[71,72,73,74],"棉花","甘蔗","cotton","sugarcane",[],{"code":77,"score":68,"supported":57,"title":78,"abstract":80,"tags":81},"I3",[79],"remote sensing",[],[26],{"code":83,"score":84,"supported":57,"title":85,"abstract":86,"tags":89},"A1",6,[],[87,88],"水稻","paddy",[],{"code":91,"score":84,"supported":57,"title":92,"abstract":93,"tags":96},"A3",[],[94,95],"玉米","maize",[],{"code":98,"score":84,"supported":57,"title":99,"abstract":100,"tags":103},"A5",[],[101,102],"马铃薯","potato",[],{"code":105,"score":106,"supported":57,"title":107,"abstract":108,"tags":110},"A4",3,[],[109],"向日葵",[],{"code":112,"score":106,"supported":57,"title":113,"abstract":114,"tags":116},"H6",[],[115],"水土保持",[],{"code":118,"score":106,"supported":57,"title":119,"abstract":120,"tags":122},"H8",[],[121],"可持续农业",[],[124,125],"作物适宜性 农业遥感 土壤调查 GIS","作物适宜性 农业遥感","作物适宜性农业遥感土壤调查GIS-1442","10.56557\u002Fjoban\u002F2026\u002Fv18i211054",{"doi":127,"openalex_id":129,"authors":130,"venue":10,"cited_by_count":165,"oa_url":6,"card":166,"direction":170,"ingested_from":172},"W7204891281",[131,133,135,138,140,143,145,147,149,151,153,155,157,159,161,163],{"name":132,"orcid":9},"D. N. Roy",{"name":134,"orcid":9},"Shaikh Mohitpasha",{"name":136,"orcid":137},"Saumen Saha","https:\u002F\u002Forcid.org\u002F0000-0003-2768-883X",{"name":139,"orcid":9},"D. C. Sarkar",{"name":141,"orcid":142},"M. K. Singh","https:\u002F\u002Forcid.org\u002F0000-0003-0118-3614",{"name":144,"orcid":9},"Sumit Raizada",{"name":146,"orcid":9},"Ravi Gautam",{"name":148,"orcid":9},"Monika",{"name":150,"orcid":9},"Indra Bahadur",{"name":152,"orcid":9},"R.T. Bankar",{"name":154,"orcid":9},"R. K. Setia",{"name":156,"orcid":9},"R. L. Meena",{"name":158,"orcid":9},"N. S. Gahlod",{"name":160,"orcid":9},"Y. Suresh Kumar",{"name":162,"orcid":9},"Kumar Rajeev",{"name":164,"orcid":9},"S. K. Tripathi",0,{"tldr":167,"method":168,"finding":169,"direction":170,"opportunity":171},"利用GIS和遥感评估印度某地块土壤特性及作物适宜性，为可持续生产提供规划依据。","土壤调查、形态理化分析、土壤分类及GIS适宜性评价。","水稻适宜性高，棉花等边际适宜，约4%永久不宜，需针对性规划。","农业遥感与作物表型","可结合高分辨率遥感与机器学习，动态监测土壤属性并预测作物适宜性，提升区域精准农业决策。","openalex","2026-09-02T23:30:53.627384Z",{"total":84,"page":21,"page_size":84,"items":175},[176,255,339,411,463,543],{"id":177,"title":178,"url":179,"summary":180,"summary_zh":181,"content":9,"source_name":182,"source_url":179,"published_at":183,"category":12,"cover_url":9,"hotness":184,"is_selected":14,"score":185,"score_detail":186,"sources":189,"tags":193,"primary_topic":198,"secondary_topics":199,"classification":205,"search_phrases":235,"slug":238,"view_count":225,"doi":239,"paper":240,"created_at":254},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。","Zenodo (CERN European Organization for Nuclear Research)","2026-09-22T00:00:00Z",25,66,{"impact":63,"substance":18,"depth":187,"authority":63,"freshness":68,"relevant":21,"comment":188},15,"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。",[190,191],{"name":182,"url":179},{"name":182,"url":192},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22900048",[194,195,29,196,197],"土地退化","遥感监测","土壤盐渍化","灌溉农业",{"code":44,"slug":45,"name":46,"path":47,"parent_code":48},[200,204],{"code":77,"slug":201,"name":202,"path":203,"parent_code":48},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":50,"locked":14,"version":51,"method":52,"evidence":206},{"candidates":207,"agricultural_evidence":57},[208,214,219,223,230],{"code":44,"score":18,"supported":57,"title":209,"abstract":210,"tags":213},[29],[211,29,212],"地理信息","geographic information",[29],{"code":77,"score":187,"supported":57,"title":215,"abstract":216,"tags":218},[79],[217,79],"遥感",[195],{"code":31,"score":56,"supported":57,"title":220,"abstract":221,"tags":222},[32],[60,32],[],{"code":224,"score":225,"supported":57,"title":226,"abstract":227,"tags":229},"H3",4,[],[228],"灌溉",[197],{"code":231,"score":21,"supported":14,"title":232,"abstract":233,"tags":234},"H1",[],[],[194],[236,237],"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":239,"openalex_id":241,"authors":242,"venue":182,"cited_by_count":165,"oa_url":179,"card":249,"direction":170,"ingested_from":172},"W7214052773",[243,245,247],{"name":244,"orcid":9},"Mardiyev",{"name":246,"orcid":9},"Ergashaliyev",{"name":248,"orcid":9},"G'aniyev",{"tldr":250,"method":251,"finding":252,"direction":170,"opportunity":253},"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。","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。","2026-09-23T23:30:19.341486Z",{"id":256,"title":257,"url":258,"summary":259,"summary_zh":260,"content":9,"source_name":261,"source_url":258,"published_at":262,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":263,"score_detail":264,"sources":267,"tags":269,"primary_topic":272,"secondary_topics":273,"classification":275,"search_phrases":313,"slug":316,"view_count":20,"doi":317,"paper":318,"created_at":338},3020,"Spatial variability of soil fertility indicators using GIS for sustainable land management in Banaskantha district western India","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44378-026-00320-y","Soil fertility assessment is fundamental for sustainable land management and precision agriculture, particularly in semi-arid regions where soil properties exhibit considerable spatial variability. This study investigated the spatial distribution of major soil fertility indicators across Banaskantha district, Gujarat, India, using a systematic 15 × 15 km grid-based sampling approach integrated with Geographic Information System (GIS) analysis and multivariate statistics. A total of 46 geo-referenced composite soil samples were collected from agricultural fields representing all fourteen talukas and analysed for soil moisture, pH, electrical conductivity (EC), organic carbon (OC), available nitrogen (AvN), available phosphorus (AvP), and available potassium (AvK). GIS-based Inverse Distance Weighting (IDW) interpolation was employed to visualize the regional distribution of soil properties, while Pearson correlation analysis and Principal Component Analysis (PCA) were used to examine relationships among soil fertility indicators and identify the major factors influencing soil variability. The results revealed substantial spatial heterogeneity across the district, with alkaline and saline soils predominantly occurring in the western region, whereas comparatively higher soil moisture and organic carbon were observed in the eastern and northern areas. Available phosphorus was generally deficient throughout the district, while available nitrogen and potassium exhibited pronounced spatial variation associated with parent material, land use, and agricultural management practices. PCA identified salinity-related factors and organic matter–nutrient interactions as the principal contributors to soil fertility variability. The generated spatial distribution maps provide valuable baseline information for identifying nutrient-deficient zones and understanding regional patterns of soil fertility. Although the proposed nutrient management strategies require further validation through field-based agronomic studies, the integration of laboratory soil analysis, GIS, and multivariate statistical techniques provides an effective framework for regional soil fertility assessment and supports informed decision-making for sustainable land management in semi-arid environments.","土壤肥力评估是可持续土地管理和精准农业的基础，尤其是在土壤属性表现出显著空间变异性的半干旱地区。本研究采用基于15 × 15 km网格的系统采样方法，结合地理信息系统（GIS）分析和多元统计方法，调查了印度古吉拉特邦巴纳斯坎塔县主要土壤肥力指标的空间分布。共从代表全部十四个乡的农田中采集了46个地理参照复合土壤样品，并分析了土壤水分、pH、电导率（EC）、有机碳（OC）、有效氮（AvN）、有效磷（AvP）和有效钾（AvK）。采用基于GIS的反距离加权（IDW）插值法可视化土壤属性的区域分布，同时运用Pearson相关分析和主成分分析（PCA）考察土壤肥力指标之间的关系，并识别影响土壤变异性的主要因素。结果表明，该县土壤存在显著的空间异质性，碱性和盐渍化土壤主要分布在西部地区，而东部和北部地区土壤水分和有机碳相对较高。有效磷在整个县域普遍缺乏，而有效氮和有效钾则表现出与母质、土地利用和农业管理措施相关的显著空间变异。PCA识别出盐分相关因子和有机质—养分相互作用是土壤肥力变异性的主要贡献因素。所生成的空间分布图为识别养分缺乏区和理解土壤肥力区域格局提供了有价值的基线信息。尽管所提出的养分管理策略需要通过田间农艺研究进一步验证，但实验室土壤分析、GIS和多元统计技术的整合为区域土壤肥力评估提供了有效框架，并为半干旱环境下可持续土地管理的科学决策提供了支持。","Discover Soil.","2026-09-19T00:00:00Z",65,{"impact":17,"substance":265,"depth":19,"authority":63,"freshness":68,"relevant":21,"comment":266},20,"基于GIS与多元统计的区域土壤肥力空间变异研究，方法规范、数据翔实，对精准农业与可持续土地管理有参考价值，但属区域性案例，公共影响有限。",[268],{"name":261,"url":258},[270,121,217,29,271],"精准农业","土壤肥力",{"code":44,"slug":45,"name":46,"path":47,"parent_code":48},[274],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":50,"locked":14,"version":51,"method":52,"evidence":276},{"candidates":277,"agricultural_evidence":57},[278,282,286,293,299,305,309],{"code":44,"score":18,"supported":57,"title":279,"abstract":280,"tags":281},[29],[211,29,212],[29],{"code":31,"score":187,"supported":57,"title":283,"abstract":284,"tags":285},[32],[60,32],[271],{"code":287,"score":288,"supported":57,"title":289,"abstract":290,"tags":292},"I1",7,[],[270,291],"precision agriculture",[270],{"code":294,"score":106,"supported":57,"title":295,"abstract":296,"tags":298},"F3",[],[297],"养分管理",[],{"code":300,"score":106,"supported":57,"title":301,"abstract":302,"tags":304},"H7",[],[303],"干旱",[],{"code":118,"score":21,"supported":14,"title":306,"abstract":307,"tags":308},[],[],[121],{"code":77,"score":21,"supported":14,"title":310,"abstract":311,"tags":312},[],[],[217],[314,315],"Banaskantha 土壤肥力 GIS","印度 半干旱区 土壤养分","Banaskantha土壤肥力GIS-3020","10.1007\u002Fs44378-026-00320-y",{"doi":317,"openalex_id":319,"authors":320,"venue":261,"cited_by_count":165,"oa_url":258,"card":332,"direction":337,"ingested_from":172},"W7213587271",[321,324,326,328,330],{"name":322,"orcid":323},"Mukesh P. Chaudhari","https:\u002F\u002Forcid.org\u002F0009-0000-2187-2375",{"name":325,"orcid":9},"Ruchi Nair",{"name":327,"orcid":9},"Pratik Chavda",{"name":329,"orcid":9},"Dharmik Patel",{"name":331,"orcid":9},"Divya Mishra",{"tldr":333,"method":334,"finding":335,"direction":170,"opportunity":336},"用GIS与多元统计评估印度半干旱区Banaskantha土壤肥力指标的空间变异。","15×15 km网格采样46个样点，结合IDW插值、Pearson相关与PCA分","西部土壤偏碱盐化，东部北部有机碳较高，全区分区有效磷普遍缺乏。","可结合遥感植被指数与机器学习提升半干旱区土壤肥力制图精度并验证养分管理策略。","农业人工智能与决策模型","2026-09-20T23:30:43.716518Z",{"id":340,"title":341,"url":342,"summary":343,"summary_zh":344,"content":9,"source_name":345,"source_url":342,"published_at":346,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":347,"score_detail":348,"sources":350,"tags":352,"primary_topic":355,"secondary_topics":356,"classification":359,"search_phrases":388,"slug":391,"view_count":20,"doi":392,"paper":393,"created_at":410},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",60,{"impact":63,"substance":18,"depth":19,"authority":63,"freshness":20,"relevant":21,"comment":349},"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。",[351],{"name":345,"url":342},[353,217,29,115,354],"农业水资源","半干旱区",{"code":44,"slug":45,"name":46,"path":47,"parent_code":48},[357,358],{"code":77,"slug":201,"name":202,"path":203,"parent_code":48},{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":50,"locked":14,"version":51,"method":52,"evidence":360},{"candidates":361,"agricultural_evidence":57},[362,366,370,375,380,384],{"code":44,"score":18,"supported":57,"title":363,"abstract":364,"tags":365},[29],[211,29,212],[29],{"code":77,"score":187,"supported":57,"title":367,"abstract":368,"tags":369},[79],[217,79],[217],{"code":31,"score":371,"supported":57,"title":372,"abstract":373,"tags":374},11,[32],[32],[],{"code":224,"score":225,"supported":57,"title":376,"abstract":377,"tags":379},[],[378],"水资源",[353],{"code":112,"score":225,"supported":57,"title":381,"abstract":382,"tags":383},[],[115],[115],{"code":300,"score":106,"supported":57,"title":385,"abstract":386,"tags":387},[],[303],[],[389,390],"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":392,"openalex_id":394,"authors":395,"venue":345,"cited_by_count":165,"oa_url":342,"card":405,"direction":170,"ingested_from":172},"W7208812908",[396,399,401,403],{"name":397,"orcid":398},"Prasannajit D. Gangurde","https:\u002F\u002Forcid.org\u002F0009-0002-9266-8931",{"name":400,"orcid":9},"Sanjay N. Pawar",{"name":402,"orcid":9},"M. S. Pendke",{"name":404,"orcid":9},"Anilkumar M. Kamble",{"tldr":406,"method":407,"finding":408,"direction":170,"opportunity":409},"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":412,"title":413,"url":414,"summary":415,"summary_zh":416,"content":9,"source_name":417,"source_url":414,"published_at":418,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":165,"score_detail":419,"sources":421,"tags":423,"primary_topic":424,"secondary_topics":425,"classification":428,"search_phrases":443,"slug":444,"view_count":165,"doi":445,"paper":446,"created_at":462},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":165,"substance":165,"depth":165,"authority":165,"freshness":165,"relevant":165,"comment":420},"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。",[422],{"name":417,"url":414},[12],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[426,427],{"code":44,"slug":45,"name":46,"path":47,"parent_code":48},{"code":77,"slug":201,"name":202,"path":203,"parent_code":48},{"status":50,"locked":14,"version":51,"method":52,"evidence":429},{"candidates":430,"agricultural_evidence":57},[431,435,439],{"code":31,"score":56,"supported":57,"title":432,"abstract":433,"tags":434},[32],[60,32],[],{"code":44,"score":68,"supported":57,"title":436,"abstract":437,"tags":438},[],[211,29,212],[],{"code":77,"score":17,"supported":57,"title":440,"abstract":441,"tags":442},[79],[],[],[],"Assessingtheimpactsofgoldminingonvegetat-5091","10.1016\u002Fj.indic.2026.101570",{"doi":445,"openalex_id":447,"authors":448,"venue":417,"cited_by_count":165,"oa_url":414,"card":457,"direction":170,"ingested_from":172},"W7222305702",[449,451,454],{"name":450,"orcid":9},"Mohamed Traoré",{"name":452,"orcid":453},"Opeyemi Aniramu","https:\u002F\u002Forcid.org\u002F0000-0002-5111-0221",{"name":455,"orcid":456},"Oluwagbenga O. I. Orimoogunje","https:\u002F\u002Forcid.org\u002F0000-0001-8070-5040",{"tldr":458,"method":459,"finding":460,"direction":170,"opportunity":461},"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":464,"title":465,"url":466,"summary":467,"summary_zh":468,"content":9,"source_name":469,"source_url":466,"published_at":470,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":471,"score_detail":472,"sources":476,"tags":478,"primary_topic":482,"secondary_topics":483,"classification":486,"search_phrases":528,"slug":531,"view_count":20,"doi":9,"paper":532,"created_at":542},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":19,"substance":265,"depth":473,"authority":474,"freshness":17,"relevant":21,"comment":475},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。",[477],{"name":469,"url":466},[479,270,217,480,481],"智慧农业","盐碱地治理","土壤监测",{"code":77,"slug":201,"name":202,"path":203,"parent_code":48},[484,485],{"code":44,"slug":45,"name":46,"path":47,"parent_code":48},{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":50,"locked":14,"version":51,"method":52,"evidence":487},{"candidates":488,"agricultural_evidence":57},[489,494,499,503,507,514,518,522],{"code":77,"score":18,"supported":57,"title":490,"abstract":491,"tags":493},[79],[217,79,492],"multispectral",[217],{"code":44,"score":473,"supported":57,"title":495,"abstract":496,"tags":498},[29],[211,497,29,212],"空间分析",[],{"code":31,"score":187,"supported":57,"title":500,"abstract":501,"tags":502},[32],[60,32],[480],{"code":287,"score":13,"supported":57,"title":504,"abstract":505,"tags":506},[291],[],[479,270],{"code":508,"score":84,"supported":57,"title":509,"abstract":510,"tags":513},"I2",[],[511,512],"机器学习","machine learning",[],{"code":224,"score":106,"supported":57,"title":515,"abstract":516,"tags":517},[],[228],[],{"code":300,"score":106,"supported":57,"title":519,"abstract":520,"tags":521},[],[303],[],{"code":523,"score":106,"supported":57,"title":524,"abstract":525,"tags":527},"I7",[],[526],"methodological framework",[],[529,530],"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":533,"authors":534,"venue":469,"cited_by_count":165,"oa_url":466,"card":537,"direction":170,"ingested_from":172},"W7221843179",[535],{"name":536,"orcid":9},"Sadullayev Sardor Zokirjon o'g'li",{"tldr":538,"method":539,"finding":540,"direction":170,"opportunity":541},"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":544,"title":545,"url":546,"summary":547,"summary_zh":548,"content":9,"source_name":549,"source_url":546,"published_at":550,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":471,"score_detail":551,"sources":554,"tags":556,"primary_topic":561,"secondary_topics":562,"classification":564,"search_phrases":589,"slug":592,"view_count":165,"doi":593,"paper":594,"created_at":624},4797,"Beyond single-element toxicity: chromium-salinity interactions, food-chain transfer and mitigation in sugarcane agroecosystems","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1942892","Chromium contamination in sugarcane soils is often combined with co-metals and salinity caused by tannery effluent, electroplating effluent, paper mill wastewater, vinasse fertigation and filter cake. Hence, single element toxicity assessment does not provide realistic assessment of its exposure. The present review summarizes research on chromium behaviour along the soil, root, stalk and cane juice in sugarcane. Cr mobility depends on soil pH and redox potential (Eh), while salinity adds an additional control through ionic strength and chloride complexation. Sequential extraction and speciation analysis prove that bioavailable fraction is more important for plant toxicity than total Cr concentration. Cr(VI) enters roots via sulphate and phosphate transporters via mimicking oxyanions and this mechanism differs from that of other metal ions that use ion channels, a route that salt-induced PHT1 expression could plausibly modulate, although this has not been tested in sugarcane. In proxy species, combined Cr and salinity exposure raises reactive oxygen species production and membrane damage beyond the level induced by either stress alone, whereas in sugarcane the downregulation of PEP carboxylase, pyruvate orthophosphate dikinase and photosystem proteins has so far been documented only under salinity applied by itself. Whether the two stresses interact on C4 carbon assimilation in cane remains untested. Root-to-stalk transfer of Cr is low at most sites examined, but not at all of them, and measurable Cr reaches cane juice at concentrations that have driven hazard quotients above unity in two of the four field studies assessed. Bagasse biochar, biochar with nZVI, halotolerant Cr-reducing microorganisms and water management based on redox reactions all reduce Cr bioavailability, but field experiments in cane are lacking. Factorial experiments investigating Cr behaviour depending on salinity gradient, juice level speciation and field trials in ratoons are required.","甘蔗土壤中的铬污染通常与制革废水、电镀废水、造纸厂废水、酒糟灌溉和滤泥带入的伴生金属及盐分复合存在。因此，单一元素毒性评估无法对其暴露状况作出符合实际的评价。本文综述了铬在甘蔗土壤、根系、茎秆及蔗汁中行为的研究进展。铬的迁移性取决于土壤pH和氧化还原电位（Eh），而盐分通过离子强度和氯络合作用对其施加额外调控。连续提取和形态分析表明，生物有效态组分对植物毒性的意义大于总铬浓度。Cr(VI)通过模拟含氧阴离子经硫酸盐和磷酸盐转运蛋白进入根系，这一机制不同于其他利用离子通道的金属离子，而盐诱导的PHT1表达可能调控该途径，但尚未在甘蔗中验证。在替代物种中，铬与盐分复合暴露引起的活性氧产生和膜损伤超过单一胁迫诱导的水平，而在甘蔗中，磷酸烯醇式丙酮酸羧化酶、丙酮酸磷酸双激酶和光系统蛋白的下调目前仅在单独盐胁迫下得到证实。两种胁迫是否在甘蔗C4碳同化过程中发生交互作用仍未经检验。在多数已考察的位点，铬从根系向茎秆的转移量较低，但并非所有位点均如此；在所评估的四项田间研究中，有两项显示可检测到的铬到达蔗汁，其浓度已使危害商数超过1。蔗渣生物炭、负载纳米零价铁（nZVI）的生物炭、耐盐铬还原微生物以及基于氧化还原反应的水分管理均可降低铬的生物有效性，但甘蔗田间试验尚属缺乏。有必要开展考察铬行为随盐度梯度变化的析因实验、蔗汁水平上的形态分析以及宿根蔗田间试验。","Frontiers in Sustainable Food Systems","2026-10-12T00:00:00Z",{"impact":63,"substance":552,"depth":18,"authority":474,"freshness":68,"relevant":21,"comment":553},22,"综述系统梳理铬-盐交互、食物链迁移与阻控手段，指出甘蔗田间试验空白，对污染蔗区安全利用有参考价值，但属机理综述、非产业级突破。",[555],{"name":549,"url":546},[72,557,558,559,560],"食品安全","盐渍化","土壤重金属","生物炭修复",{"code":38,"slug":39,"name":40,"path":41,"parent_code":42},[563],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":50,"locked":14,"version":51,"method":52,"evidence":565},{"candidates":566,"agricultural_evidence":57},[567,571,575,580,584],{"code":38,"score":187,"supported":57,"title":568,"abstract":569,"tags":570},[74],[72,74],[72],{"code":31,"score":17,"supported":57,"title":572,"abstract":573,"tags":574},[],[60,32],[559,558],{"code":294,"score":106,"supported":57,"title":576,"abstract":577,"tags":579},[],[578],"fertigation",[],{"code":224,"score":106,"supported":57,"title":581,"abstract":582,"tags":583},[],[228],[],{"code":585,"score":21,"supported":14,"title":586,"abstract":587,"tags":588},"E4",[],[],[557],[590,591],"甘蔗 铬污染 盐渍化","甘蔗汁 风险","甘蔗铬污染盐渍化-4797","10.3389\u002Ffsufs.2026.1942892",{"doi":593,"openalex_id":595,"authors":596,"venue":549,"cited_by_count":165,"oa_url":546,"card":618,"direction":622,"ingested_from":172},"W7221577366",[597,600,602,604,606,608,610,612,614,616],{"name":598,"orcid":599},"Gowtham Sornam","https:\u002F\u002Forcid.org\u002F0009-0009-1150-1568",{"name":601,"orcid":9},"Sugumaran Melkumaramangalam Palani",{"name":603,"orcid":9},"Parameswari Ettiyagounder",{"name":605,"orcid":9},"Kalaiselvi Thangavel",{"name":607,"orcid":9},"Saravanan Naaganoor Ananthan",{"name":609,"orcid":9},"Elayarajan Maharajan",{"name":611,"orcid":9},"Selva Kumar Manikkam",{"name":613,"orcid":9},"Sassikumar Datchinamoorthy",{"name":615,"orcid":9},"Sinduja Murugaiyan",{"name":617,"orcid":9},"Priyatharsini Sengottaiyan",{"tldr":619,"method":620,"finding":621,"direction":622,"opportunity":623},"综述甘蔗农业生态系统中铬与盐分交互作用、食物链传递及缓解措施，指出单元素毒性评估不足。","综述土壤-根-茎-汁中铬形态、转运与缓解技术，结合顺序提取与形态分析。","铬与盐分交互对C4碳同化影响未测，蔗汁铬危害商在部分田间研究中超1，缓解技术缺乏田间验证。","农业绿色发展与碳","可开展盐度梯度下铬形态与C4光合交互的因子实验，并验证生物炭等缓解措施的田间效果。","2026-10-13T23:30:07.200287Z"]