[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2321":3},{"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,"view_count":33,"doi":34,"paper":35,"created_at":51},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。",null,"Zenodo (CERN European Organization for Nuclear Research)","2026-09-11T00:00:00Z","论文",25,false,65,{"impact":17,"substance":18,"depth":19,"authority":17,"freshness":20,"relevant":21,"comment":22},12,18,15,8,1,"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。",[24,25],{"name":10,"url":6},{"name":10,"url":26},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22702719",[28,29,30,31,32],"智慧农业","NDVI","遥感监测","土壤盐渍化","灌溉农业",0,"10.5281\u002Fzenodo.22702718",{"doi":34,"openalex_id":36,"authors":37,"venue":10,"cited_by_count":33,"oa_url":6,"card":44,"direction":48,"ingested_from":50},"W7212227143",[38,40,42],{"name":39,"orcid":9},"U.K. Umirova",{"name":41,"orcid":9},"D.A. Kodirova",{"name":43,"orcid":9},"O.O. Davronov",{"tldr":45,"method":46,"finding":47,"direction":48,"opportunity":49},"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。","农业遥感与作物表型","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。","openalex","2026-09-13T23:30:22.820810Z"]