[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"topic-CA-Markov":3},{"name":4,"kind":5,"tokens":6,"total":7,"page":7,"page_size":8,"items":9},"CA-Markov","tag",[4],1,100,[10],{"id":11,"title":12,"url":13,"summary":14,"summary_zh":15,"content":16,"source_name":17,"source_url":13,"published_at":18,"category":19,"cover_url":16,"hotness":20,"is_selected":21,"score":22,"score_detail":23,"sources":29,"tags":31,"primary_topic":36,"secondary_topics":42,"classification":43,"search_phrases":75,"slug":78,"view_count":79,"doi":80,"paper":81,"created_at":97},5391,"Spatio-temporal analysis and forecasting of land use\u002Fland cover change in East Medinipur district, India using CA-Markov model","https:\u002F\u002Fdoi.org\u002F10.3846\u002Fgac.2026.23669","Land Use\u002FLand Cover (LU\u002FLC) serve as essential indicators of global environmental changes. This study examined the LU\u002FLC change in the East Medinipur district of West Bengal, India, using remote sensing data and the CA-Markov modeling approach. Through GIS tools and satellite imagery, the study maps, monitors, and analyzes LU\u002FLC changes over a 20-year period (2001–2021), utilizing data from Landsat 4–5 and Landsat 8. Analytical tools including ArcGIS 9, IDRISI Terset, and ERDAS 2014 are employed to project LU\u002FLC trends up to 2041. The results highlight significant transformations, notable reductions in agriculture, vegetation, barren land, and water bodies, alongside substantial increases in aquaculture and built-up areas from 2001 to 2021. Projections indicates that these trends will continue through 2041, with further declines in agriculture, vegetation, barren land, and water bodies, accompanied by continued growth in aquaculture and built-up areas.","土地利用\u002F土地覆盖（Land Use\u002FLand Cover，LU\u002FLC）是全球环境变化的重要指标。本研究利用遥感数据和CA-Markov建模方法，考察了印度西孟加拉邦东梅迪尼普尔县的土地利用\u002F土地覆盖变化。通过GIS工具和卫星影像，研究利用Landsat 4–5和Landsat 8数据，对2001—2021年20年间的土地利用\u002F土地覆盖变化进行了制图、监测与分析。研究采用ArcGIS 9、IDRISI Terset和ERDAS 2014等分析工具，对至2041年的土地利用\u002F土地覆盖趋势进行预测。结果表明，2001年至2021年间发生了显著转变，农业、植被、裸地和水体明显减少，水产养殖和建成区则大幅增加。预测显示，这些趋势将持续至2041年，农业、植被、裸地和水体进一步减少，水产养殖和建成区持续增长。",null,"Geodesy and Cartography","2026-10-19T00:00:00Z","论文",10,false,61,{"impact":24,"substance":25,"depth":26,"authority":27,"freshness":24,"relevant":7,"comment":28},8,18,15,12,"该研究基于遥感与CA-Markov模型分析印度区域土地利用变化，方法规范、结论明确，但属区域性案例，对国内三农与农业信息化的直接参考价值有限，可作为遥感应用类论文收录，不宜进入每日精选。",[30],{"name":17,"url":13},[32,33,34,35,4],"水产养殖","遥感","土地利用","耕地变化",{"code":37,"slug":38,"name":39,"path":40,"parent_code":41},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[],{"status":44,"locked":21,"version":45,"method":46,"evidence":47},"classified","2026-10-22.2","rules",{"candidates":48,"agricultural_evidence":52},[49,58,63,70],{"code":50,"score":51,"supported":52,"title":53,"abstract":54,"tags":57},"D",7,true,[],[55,56],"水产","aquaculture",[32],{"code":37,"score":51,"supported":52,"title":59,"abstract":60,"tags":62},[],[33,61],"remote sensing",[33],{"code":64,"score":65,"supported":52,"title":66,"abstract":67,"tags":69},"I4",3,[],[68],"GIS",[],{"code":71,"score":7,"supported":21,"title":72,"abstract":73,"tags":74},"H6",[],[],[34],[76,77],"Landsat 土地利用 遥感监测","土地利用 水产养殖 耕地变化 遥感","Landsat土地利用遥感监测-5391",0,"10.3846\u002Fgac.2026.23669",{"doi":80,"openalex_id":82,"authors":83,"venue":17,"cited_by_count":79,"oa_url":89,"card":90,"direction":94,"ingested_from":96},"W7222963948",[84,87],{"name":85,"orcid":86},"Parag Jyoti Kashyap","https:\u002F\u002Forcid.org\u002F0000-0003-4273-841X",{"name":88,"orcid":16},"Sahana Bose","https:\u002F\u002Fjournals.vilniustech.lt\u002Findex.php\u002FGAC\u002Farticle\u002Fdownload\u002F23669\u002F13567",{"tldr":91,"method":92,"finding":93,"direction":94,"opportunity":95},"用遥感与CA-Markov模型分析印度东梅迪尼普尔2001-2021年土地利用变化并预测至2041年","Landsat影像、GIS与IDRISI\u002FERDAS，CA-Markov模型做L","农业、植被、裸地和水体持续减少，水产养殖与建设用地显著扩张并将延续至2041年。","农业遥感与作物表型","可将CA-Markov与作物适宜性\u002F粮食安全模型耦合，评估养殖与建设用地扩张对农业生产的长期威胁。","openalex","2026-10-20T23:30:19.057951Z"]