[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4678":3,"related-4678":99},{"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":31,"secondary_topics":37,"classification":38,"search_phrases":71,"slug":74,"view_count":21,"doi":75,"paper":76,"created_at":98},4678,"Remote Sensing-based Integration of Land Use\u002FLand Cover, Vegetation Cover, and Land Surface Temperature with Hydrological Implications in Tikrit City, Iraq","https:\u002F\u002Fdoi.org\u002F10.14445\u002F23488352\u002Fijce-v13i9p115","This study examines the integrated relationship among Land Use\u002FLand Cover (LULC), Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST), with hydrological implications, in Tikrit City, Iraq, using Landsat data acquired in 2017 and 2025. LULC, NDVI, and LST layers were prepared using the same spatial boundary, and 4124 paired sample points were extracted from identical locations to support temporal and statistical comparison. The LULC results showed a clear reduction in Soil from 70.52% in 2017 to 49.88% in 2025, whereas Vegetation increased from 25.49% to 44.12%. Built Area also increased from 3.08% to 4.90%, indicating moderate urban expansion. The dominant land-cover transition was from Soil to Vegetation, covering 66,014.66 ha. Mean NDVI increased significantly from 0.061 to 0.075, while mean LST remained statistically stable, changing only from 41.992°C to 42.031°C. However, non-parametric tests indicated that the spatial distribution of LST changed significantly. The NDVI–LST relationship was positive in both years, with Pearson correlation increasing from 0.670 in 2017 to 0.709 in 2025. Regression analysis showed that NDVI explained 44.9% and 50.2% of LST variation in 2017 and 2025, respectively. Class-based analysis indicated that the dominant heat-contributing class shifted from Soil in 2017 to Built Area in 2025. These findings show that surface thermal behavior in Tikrit City cannot be explained by vegetation cover alone, but depends on land-cover composition, mixed pixels, agricultural activity, soil exposure, surface moisture, and seasonal conditions. From a hydrological perspective, the reduction of exposed soil, expansion of vegetation, and growth of built-up areas have implications for infiltration opportunity, runoff potential, evapotranspiration tendency, and surface moisture retention.","本研究利用2017年和2025年获取的Landsat数据，考察了伊拉克提克里特市土地利用\u002F土地覆盖（LULC）、归一化植被指数（NDVI）和地表温度（LST）之间的综合关系及其水文意义。LULC、NDVI和LST图层采用相同的空间边界制备，并从相同位置提取了4124对样本点，以支持时间与统计比较。LULC结果显示，土壤占比从2017年的70.52%明显下降至2025年的49.88%，而植被占比从25.49%上升至44.12%。建成区面积也从3.08%增至4.90%，表明存在中等程度的城市扩张。主导性土地覆盖转变为由土壤转为植被，覆盖面积达66,014.66公顷。平均NDVI从0.061显著增至0.075，而平均LST在统计上保持稳定，仅从41.992°C变为42.031°C。然而，非参数检验表明LST的空间分布发生了显著变化。NDVI与LST的关系在两年中均为正相关，Pearson相关系数从2017年的0.670增至2025年的0.709。回归分析表明，NDVI在2017年和2025年分别解释了LST变异的44.9%和50.2%。基于类别的分析表明，主要的热贡献类别从2017年的土壤转变为2025年的建成区。这些发现表明，提克里特市的地表热行为不能仅由植被覆盖来解释，而是取决于土地覆盖组成、混合像元、农业活动、土壤裸露、地表湿度和季节条件。从水文角度看，裸露土壤减少、植被扩张和建成区增长对下渗机会、径流潜力、蒸散发趋势和地表水分保持具有影响。",null,"International Journal of Civil Engineering","2026-10-10T00:00:00Z","论文",10,false,68,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":13,"relevant":21,"comment":22},8,20,17,13,1,"基于Landsat双期影像量化伊拉克提克里特市土地利用、植被与地表温度耦合关系及其水文效应，数据扎实、结论明确，对农业遥感与土地变化研究有参考价值，但地域性强、国内关联度有限。",[24],{"name":10,"url":6},[26,27,28,29,30],"遥感监测","土地利用","地表温度","植被覆盖","水文响应",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,51,59,66],{"code":32,"score":45,"supported":46,"title":47,"abstract":49,"tags":50},11,true,[48],"remote sensing",[],[28,29,26],{"code":52,"score":53,"supported":46,"title":54,"abstract":55,"tags":58},"H2",6,[],[56,57],"土壤","soil",[],{"code":60,"score":53,"supported":46,"title":61,"abstract":62,"tags":65},"H3",[],[63,64],"蒸散发","evapotranspiration",[],{"code":67,"score":21,"supported":14,"title":68,"abstract":69,"tags":70},"H6",[],[],[27],[72,73],"Landsat 土地利用 植被覆盖 地表温度","土地利用 地表温度 植被覆盖 水文响应","Landsat土地利用植被覆盖地表温度-4678","10.14445\u002F23488352\u002Fijce-v13i9p115",{"doi":75,"openalex_id":77,"authors":78,"venue":10,"cited_by_count":89,"oa_url":90,"card":91,"direction":95,"ingested_from":97},"W7221352158",[79,81,83,86],{"name":80,"orcid":9},"Omar Taher Nafe'e",{"name":82,"orcid":9},"Dalia Shaker Mahdi",{"name":84,"orcid":85},"Lubna B. Mahmood","https:\u002F\u002Forcid.org\u002F0009-0000-4428-4891",{"name":87,"orcid":88},"Asmaa Abdul Jabbar Jamel","https:\u002F\u002Forcid.org\u002F0000-0001-7602-3426",0,"https:\u002F\u002Fwww.internationaljournalssrg.org\u002F..\u002FIJCE\u002F2026\u002FVolume13-Issue9\u002FIJCE-V13I9P115.pdf",{"tldr":92,"method":93,"finding":94,"direction":95,"opportunity":96},"基于Landsat 2017与2025年数据，分析伊拉克提克里特市LULC、NDVI与LST的耦合关","Landsat影像、4124个配对样点、NDVI与LST反演、相关与回归分析。","植被增加、裸土减少，LST均值稳定但空间分布显著变化，NDVI-LST正相关增强，主导热贡献由裸土转","农业遥感与作物表型","可结合土壤湿度与蒸散数据，探究NDVI-LST正相关机制及混合像元对城市农业水文过程的影响。","openalex","2026-10-11T23:30:30.165387Z",{"total":53,"page":21,"page_size":53,"items":100},[101,155,230,287,345,418],{"id":102,"title":103,"url":104,"summary":105,"summary_zh":106,"content":9,"source_name":107,"source_url":104,"published_at":108,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":109,"score_detail":110,"sources":115,"tags":117,"primary_topic":120,"secondary_topics":121,"classification":122,"search_phrases":139,"slug":142,"view_count":131,"doi":143,"paper":144,"created_at":154},4094,"Cambios en el uso y cobertura de la tierra y su relación con la temperatura superficial terrestre en la cuenca del río Rocha, Bolivia, 1992–2022","https:\u002F\u002Fdoi.org\u002F10.23881\u002Fidupbo.026.1-4i","This study analyzes land use and land cover changes and their relationship with land surface temperature (LST) in the Rocha River basin, Bolivia, during 1992–2022. Landsat imagery from six dates was used to classify seven land use and land cover categories, estimate LST using remote sensing techniques, and statistically evaluate thermal differences among categories. Land cover changes were analyzed using annual change rates and a transition matrix, while LST differences were assessed with Welch's test and Games–Howell post hoc comparisons, and linear regression models were fitted for each date. Between 1992 and 2022, urban area increased by 66.99 km² and agriculture by 56.80 km², whereas grassland decreased by 104.76 km². Agricultural dynamics were not uniform, showing negative rates until 2004–2010 and positive rates thereafter. Land use and land cover categories showed statistically significant differences in LST on all six dates. In 2022, the highest mean LST values occurred in agriculture (21.79 °C), shrubland (20.40 °C), bare soil (20.22 °C), and urban area (19.76 °C), whereas the lowest values occurred in water bodies (15.46 °C), grassland (17.46 °C), and forest (17.57 °C). The regression models yielded R² values between 0.2699 and 0.5256. The results indicate a statistical association between land use and land cover categories and LST, but do not establish causal effects or long-term climatic trends.","本研究分析了1992—2022年玻利维亚罗查河流域土地利用与土地覆盖变化及其与地表温度（LST）的关系。研究使用六个日期的Landsat影像，对七类土地利用与土地覆盖进行分类，利用遥感技术估算地表温度，并对各类别之间的热差异进行统计评估。土地覆盖变化采用年变化率和转移矩阵进行分析，地表温度差异则通过Welch检验和Games–Howell事后比较进行评估，并针对每个日期拟合线性回归模型。1992—2022年间，城市面积增加66.99 km²，农业面积增加56.80 km²，而草地面积减少104.76 km²。农业动态并不均匀，2004—2010年前呈负增长速率，此后转为正增长速率。六个日期上，土地利用与土地覆盖类别之间的地表温度均存在统计学显著差异。2022年，地表温度均值最高出现在农业（21.79 °C）、灌丛（20.40 °C）、裸土（20.22 °C）和城市区域（19.76 °C），最低值出现在水体（15.46 °C）、草地（17.46 °C）和林地（17.57 °C）。回归模型的R²值介于0.2699至0.5256之间。结果表明，土地利用与土地覆盖类别同地表温度之间存在统计关联，但并未确立因果效应或长期气候趋势。","Revista Investigación & Desarrollo","2026-10-01T00:00:00Z",67,{"impact":17,"substance":111,"depth":112,"authority":20,"freshness":113,"relevant":21,"comment":114},21,16,9,"基于Landsat遥感定量分析玻利维亚Rocha河流域土地利用与地表温度关系，方法规范、数据翔实，但属区域案例研究，对国内三农信息化参考价值有限。",[116],{"name":107,"url":104},[26,27,28,118,119],"流域治理","玻利维亚",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":123},{"candidates":124,"agricultural_evidence":46},[125,130,135],{"code":32,"score":17,"supported":46,"title":126,"abstract":127,"tags":129},[],[128,48],"遥感",[28,26],{"code":52,"score":131,"supported":46,"title":132,"abstract":133,"tags":134},3,[],[57],[],{"code":67,"score":21,"supported":14,"title":136,"abstract":137,"tags":138},[],[],[27],[140,141],"土地利用 地表温度 流域治理 玻利维亚","土地利用 地表温度","土地利用地表温度流域治理玻利维亚-4094","10.23881\u002Fidupbo.026.1-4i",{"doi":143,"openalex_id":145,"authors":146,"venue":107,"cited_by_count":89,"oa_url":104,"card":149,"direction":95,"ingested_from":97},"W7216167048",[147],{"name":148,"orcid":9},"Benjamin Gossweiler Herrera",{"tldr":150,"method":151,"finding":152,"direction":95,"opportunity":153},"分析玻利维亚罗查河流域1992-2022年土地利用变化与地表温度的关系。","Landsat影像分类七类地物，遥感反演LST，Welch检验与线性回归。","城市和农业扩张、草地减少；农业、灌木、裸地LST最高，水体、草地、林地最低。","可结合多源遥感与因果推断，量化不同农业扩张模式对地表温度的贡献，支撑流域热环境调控。","2026-10-03T23:30:35.454291Z",{"id":156,"title":157,"url":158,"summary":159,"summary_zh":160,"content":9,"source_name":161,"source_url":162,"published_at":163,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":164,"score_detail":165,"sources":169,"tags":171,"primary_topic":174,"secondary_topics":175,"classification":181,"search_phrases":210,"slug":213,"view_count":214,"doi":215,"paper":216,"created_at":229},3187,"Spatio-temporal analysis of Land Use and Land Cover (LULC) change using high resolution satellite data: A case study of Nagaon, Assam","https:\u002F\u002Fdoi.org\u002F10.31018\u002Fjans.v18i3.7774","Geographic information systems (GIS) coupled with satellite remote sensing (RS) have had a significant impact on the assessment and mapping of land surface dynamics, specifically the analysis of land-use land-cover (LULC) change. This study uses high-resolution multispectral LISS-IV (Linear Imaging Self-Scanning Sensor-IV) imagery with a 5.8-meter resolution to evaluate LULC trends in the Nagaon district of Assam between 2015 and 2024. Land use classes in a variety of categories, including vegetation, water bodies, agricultural land, built-up areas, scrubland, sandbars, tea plantations, and trees outside forests (TOF), were identified applying the maximum likelihood classification algorithm. Overall, The accuracy was 85.7% in 2015 and 90.3% in 2024, with respective Kappa Coefficients of 0.836 and 0.889, respectively. The results showed that between 2015 and 2024, the areas of tea plantations, natural vegetation, scrubland, and agricultural land fell by 0.26%, 6.14%, 0.26%, and 9.83%, respectively. Conversely, the waterbody, sandbar, built-up, and TOF have all increased by 0.29%, 0.91%, 0.82%, and 14.46%, respectively. This noticeable shift from conventional agricultural and natural vegetation landscapes toward tree-based systems and urban expansion on the study area, emphasize on matters concerning climate stress, declining soil fertility, economic benefits, policy support, and the need for resilient livelihoods.","地理信息系统（GIS）与卫星遥感（RS）相结合，对地表动态的评估与制图产生了显著影响，尤其是土地利用与土地覆盖（LULC）变化分析。本研究利用分辨率为5.8米的高分辨率多光谱LISS-IV（线性成像自扫描传感器-IV）影像，评估了阿萨姆邦纳冈县2015年至2024年间的LULC变化趋势。采用最大似然分类算法，识别了植被、水体、农地、建设用地、灌丛地、沙洲、茶园及林外树木（TOF）等多种土地利用类别。总体而言，2015年分类精度为85.7%，2024年为90.3%，Kappa系数分别为0.836和0.889。结果表明，2015年至2024年间，茶园、自然植被、灌丛地和农地面积分别减少了0.26%、6.14%、0.26%和9.83%。相反，水体、沙洲、建设用地和TOF分别增加了0.29%、0.91%、0.82%和14.46%。研究区从传统农业和自然植被景观向林基系统和城市扩张的显著转变，凸显了气候胁迫、土壤肥力下降、经济效益、政策支持以及韧性生计需求等相关问题。","Journal of Applied and Natural Science","https:\u002F\u002Fjournals.ansfoundation.org\u002Findex.php\u002Fjans\u002Farticle\u002Fview\u002F7774","2026-09-20T00:00:00Z",62,{"impact":17,"substance":166,"depth":167,"authority":20,"freshness":17,"relevant":21,"comment":168},18,15,"基于高分辨率遥感的区域土地利用变化实证研究，方法规范、数据翔实，对农业遥感监测有参考价值，但属地方性案例，公共影响有限。",[170],{"name":161,"url":162},[172,26,27,173,29],"农业遥感","印度农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[176],{"code":177,"slug":178,"name":179,"path":180,"parent_code":36},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis",{"status":39,"locked":14,"version":40,"method":41,"evidence":182},{"candidates":183,"agricultural_evidence":46},[184,190,197,201,205],{"code":32,"score":185,"supported":46,"title":186,"abstract":187,"tags":189},12,[],[128,48,188],"multispectral",[172,29,26],{"code":177,"score":113,"supported":46,"title":191,"abstract":192,"tags":196},[],[193,194,195],"地理信息","GIS","geographic information",[],{"code":52,"score":53,"supported":46,"title":198,"abstract":199,"tags":200},[],[56,57],[],{"code":67,"score":21,"supported":14,"title":202,"abstract":203,"tags":204},[],[],[27],{"code":206,"score":21,"supported":14,"title":207,"abstract":208,"tags":209},"J3",[],[],[173],[211,212],"Nagaon Assam LULC 遥感","LISS-IV 土地利用变化","NagaonAssamLULC遥感-3187",5,"10.31018\u002Fjans.v18i3.7774",{"doi":215,"openalex_id":217,"authors":218,"venue":161,"cited_by_count":89,"oa_url":162,"card":224,"direction":95,"ingested_from":97},"W7213942371",[219,221],{"name":220,"orcid":9},"J. C. Das",{"name":222,"orcid":223},"Prodyut Bhattacharya","https:\u002F\u002Forcid.org\u002F0000-0002-4294-5585",{"tldr":225,"method":226,"finding":227,"direction":95,"opportunity":228},"利用高分辨率卫星影像分析印度阿萨姆邦纳冈地区2015-2024年土地利用\u002F覆盖变化。","LISS-IV 5.8米多光谱影像，最大似然分类，精度与Kappa系数评估。","农业用地和自然植被分别减少9.83%和6.14%，而林外树木和建设用地分别增加14.46%和0.82","可结合时序高分辨率影像与农户调查，探究林外树木扩张对农业韧性和碳汇的驱动机制。","2026-09-22T23:30:25.539323Z",{"id":231,"title":232,"url":233,"summary":234,"summary_zh":235,"content":9,"source_name":236,"source_url":233,"published_at":163,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":237,"score_detail":238,"sources":241,"tags":243,"primary_topic":246,"secondary_topics":247,"classification":248,"search_phrases":270,"slug":273,"view_count":53,"doi":274,"paper":275,"created_at":286},3183,"Integrated Remote Sensing and Time Series Analysis for Long-Term Assessment of Vegetation Resilience: Synthesizing Climatic Variables and Land-Use\u002FLand-Cover Trajectories in Al-Ahsa Oasis, Saudi Arabia","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fland15091758","Continuous monitoring of land-use\u002Fland-cover (LULC) change is essential in the Al-Ahsa Oasis, an arid region characterized by a sensitive and fragile environment. This study is the first to integrate vegetation, climate, and land-use frameworks by combining vegetation indicators, climatic variables, and LULC trajectory classification over a 41-year period (1985–2025). Data from three Landsat sensors (Landsat 5-TM, 7-ETM+, and 8-OLI) were processed to derive vegetation indicators and an LULC trajectory classification, while ERA5-Land and CHIRPS data provided surface temperature and rainfall information, respectively. LULC trajectory classification was implemented using a random forest classifier, generating six LULC trajectory classes: stable barren, stable urban, stable water, urban expansion, transition lands, and stable vegetation. Pearson correlation analysis was used to assess the relationships between the vegetation indicators (normalized difference vegetation index [NDVI] and soil-adjusted vegetation index [SAVI]) and climatic variables (temperature and rainfall) at different time lags (0–3 years) and after detrending the time series. The detrending analysis showed no statistically significant associations between the vegetation indicators (NDVI and SAVI) and the climatic variables (temperature and rainfall) across the four examined lags, whereas the original, non-detrended time series showed positive associations that were mainly attributable to long-term trends rather than to interannual climate–vegetation covariation. The accuracy of LULC trajectory classification was high, with an overall accuracy of 0.939 and a kappa coefficient of 0.924, indicating robust mapping performance. Overall vegetation cover improved over the study period. The degradation occurred in the central part of the oasis (stable urban, urban expansion, and stable water classes, accounting for 4.506%, 5.179%, and 41.773% of each trajectory class, respectively), whereas the recovery was observed in the northern, southern, and eastern parts (stable vegetation and transition lands, accounting for 37.656% and 52.891% of each trajectory class, respectively). These findings provide long-term insights into vegetation resilience in the Al-Ahsa Oasis over 41 years, supporting sustainable urban planning and vegetation and agricultural management.","在环境敏感而脆弱的干旱区——哈萨绿洲，持续监测土地利用\u002F土地覆盖（LULC）变化至关重要。本研究首次在41年（1985—2025年）时间跨度内，通过整合植被指标、气候变量与LULC轨迹分类，构建了植被、气候与土地利用的综合框架。研究处理了三颗Landsat传感器（Landsat 5-TM、7-ETM+和8-OLI）的数据，以提取植被指标并进行LULC轨迹分类，同时分别利用ERA5-Land和CHIRPS数据获取地表温度和降雨信息。LULC轨迹分类采用随机森林分类器实现，生成了六类LULC轨迹：稳定裸地、稳定城市、稳定水体、城市扩张、过渡土地和稳定植被。采用Pearson相关分析评估植被指标（归一化差异植被指数[NDVI]和土壤调节植被指数[SAVI]）与气候变量（温度和降雨）在不同时间滞后（0—3年）及时间序列去趋势后的关系。去趋势分析表明，在四个考察滞后下，植被指标（NDVI和SAVI）与气候变量（温度和降雨）之间均无统计学显著关联，而原始未去趋势时间序列则显示出正相关，这主要归因于长期趋势而非年际气候—植被协变。LULC轨迹分类精度较高，总体精度为0.939，kappa系数为0.924，表明制图性能稳健。研究期间整体植被覆盖有所改善。退化发生在绿洲中部（稳定城市、城市扩张和稳定水体类别，分别占各轨迹类别的4.506%、5.179%和41.773%），而恢复则出现在北部、南部和东部（稳定植被和过渡土地，分别占各轨迹类别的37.656%和52.891%）。这些发现为哈萨绿洲41年来的植被恢复力提供了长期见解，可支持可持续城市规划以及植被与农业管理。","Land",73,{"impact":185,"substance":239,"depth":166,"authority":20,"freshness":17,"relevant":21,"comment":240},22,"41年长时序遥感与气候变量整合分析，方法扎实、结论可靠，对干旱区绿洲农业可持续管理有参考价值，但属区域性案例研究，公共影响有限。",[242],{"name":236,"url":233},[244,26,27,29,245],"气候变化","绿洲农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":249},{"candidates":250,"agricultural_evidence":46},[251,255,259,266],{"code":32,"score":13,"supported":46,"title":252,"abstract":253,"tags":254},[48],[],[29,26],{"code":52,"score":53,"supported":46,"title":256,"abstract":257,"tags":258},[],[56,57],[],{"code":260,"score":261,"supported":46,"title":262,"abstract":263,"tags":265},"H7",4,[],[264],"干旱",[244],{"code":67,"score":21,"supported":14,"title":267,"abstract":268,"tags":269},[],[],[27],[271,272],"Al-Ahsa Oasis 遥感 植被","Landsat NDVI 土地利用变化","Al-AhsaOasis遥感植被-3183","10.3390\u002Fland15091758",{"doi":274,"openalex_id":276,"authors":277,"venue":236,"cited_by_count":89,"oa_url":233,"card":281,"direction":95,"ingested_from":97},"W7213862324",[278],{"name":279,"orcid":280},"Amal H. Aljaddani","https:\u002F\u002Forcid.org\u002F0000-0003-1171-8416",{"tldr":282,"method":283,"finding":284,"direction":95,"opportunity":285},"整合41年Landsat植被指数、气候变量与LULC轨迹，评估沙特Al-Ahsa绿洲植被恢复力。","Landsat 5\u002F7\u002F8时序、ERA5-Land与CHIRPS气候数据、随机森","去趋势后植被与气候无显著相关，绿洲整体植被改善，中部退化、南北东恢复。","可引入非线性\u002F因果推断与高分辨率数据，区分灌溉、城市化与气候对干旱区绿洲植被恢复力的驱动。","2026-09-22T23:30:25.304168Z",{"id":288,"title":289,"url":290,"summary":291,"summary_zh":292,"content":9,"source_name":293,"source_url":290,"published_at":294,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":295,"score_detail":296,"sources":299,"tags":301,"primary_topic":304,"secondary_topics":305,"classification":306,"search_phrases":321,"slug":324,"view_count":89,"doi":325,"paper":326,"created_at":344},1311,"Land Cover and Land Surface Temperature Dynamics in West Kotawaringin (2005-2025) Based on Remote Sensing and Random Forest Classification","https:\u002F\u002Fdoi.org\u002F10.32734\u002Fjsi.v9i02.25534","Land cover changes can influence surface temperatures and environmental conditions; therefore, spatial and temporal monitoring is crucial for regional management and climate-change mitigation. This study analyzes land-cover and Land Surface Temperature (LST) dynamics in West Kotawaringin Regency in 2005, 2015, and 2025 using Google Earth Engine, Landsat 7, Landsat 8, and Landsat 9 imagery, Random Forest classification, accuracy assessment, and LST extraction. Forest area decreased by 228,930 ha, from 598,649 ha (63.37%) in 2005 to 369,719 ha (39.14%) in 2025, while agricultural land increased by 172,131 ha, from 207,659 ha (21.98%) to 379,790 ha (40.20%). The classification yielded an Overall Accuracy of 0.93 and Kappa coefficients of 0.89-0.90. Mean LST increased from 19.50°C to 22.31°C in forest areas and from 24.58°C to 26.20°C in settlements. The spatial pattern consistently shows lower mean LST in forested areas than in built-up and other non-forest surfaces. Scientifically, the study integrates multi-temporal land-cover and LST analysis at the regency scale to support spatial planning, environmental management, and climate-change mitigation.","土地覆盖变化能够影响地表温度和环境条件，因此，对其进行时空监测对于区域管理和减缓气候变化至关重要。本研究利用谷歌地球引擎、Landsat 7、Landsat 8和Landsat 9影像、随机森林分类、精度评估及地表温度提取方法，分析了西科塔瓦林金县2005年、2015年和2025年的土地覆盖与地表温度动态变化。森林面积减少了228,930公顷，从2005年的598,649公顷（占63.37%）降至2025年的369,719公顷（占39.14%），而农业用地增加了172,131公顷，从207,659公顷（占21.98%）增至379,790公顷（占40.20%）。分类结果的总体精度为0.93，Kappa系数为0.89-0.90。森林地区的平均地表温度从19.50°C升至22.31°C，居民区的平均地表温度从24.58°C升至26.20°C。空间格局一致显示，森林地区的平均地表温度低于建成区及其他非森林地表。科学上，本研究在县级尺度上整合了多时相土地覆盖与地表温度分析，以支持空间规划、环境管理和减缓气候变化。","Journal of Sylva Indonesiana","2026-08-31T00:00:00Z",64,{"impact":185,"substance":18,"depth":166,"authority":185,"freshness":297,"relevant":21,"comment":298},2,"基于遥感与随机森林的长时间序列土地利用与地表温度分析，数据详实，对区域气候调节与农业规划有参考价值。",[300],{"name":293,"url":290},[26,27,28,302,303],"森林变化","农业扩张",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":307},{"candidates":308,"agricultural_evidence":46},[309,313,317],{"code":32,"score":13,"supported":46,"title":310,"abstract":311,"tags":312},[48],[],[28,26],{"code":260,"score":131,"supported":46,"title":314,"abstract":315,"tags":316},[],[244],[],{"code":67,"score":21,"supported":14,"title":318,"abstract":319,"tags":320},[],[],[27],[322,323],"农业扩张 土地利用 地表温度 森林变化","农业扩张 土地利用","农业扩张土地利用地表温度森林变化-1311","10.32734\u002Fjsi.v9i02.25534",{"doi":325,"openalex_id":327,"authors":328,"venue":293,"cited_by_count":89,"oa_url":290,"card":339,"direction":95,"ingested_from":97},"W7204775314",[329,331,334,337],{"name":330,"orcid":9},"Nazla Paradisa",{"name":332,"orcid":333},"Beni Iskandar","https:\u002F\u002Forcid.org\u002F0000-0001-9530-8419",{"name":335,"orcid":336},"Sari Marlina","https:\u002F\u002Forcid.org\u002F0000-0003-2948-2157",{"name":338,"orcid":9},"Ahmad Jauhari",{"tldr":340,"method":341,"finding":342,"direction":95,"opportunity":343},"利用遥感与随机森林分析西科塔瓦林金2005-2025年土地覆盖与地表温度动态。","GEE平台，Landsat影像，随机森林分类，LST提取，精度评估。","森林减少22.9万公顷，农业增加17.2万公顷，森林区LST低于建成区。","可延伸研究森林减少对农业区微气候的影响，或结合作物模型评估土地利用变化对产量的长期效应。","2026-09-01T23:30:20.045578Z",{"id":346,"title":347,"url":348,"summary":349,"summary_zh":350,"content":9,"source_name":351,"source_url":348,"published_at":352,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":89,"score_detail":353,"sources":355,"tags":357,"primary_topic":360,"secondary_topics":361,"classification":362,"search_phrases":384,"slug":387,"view_count":89,"doi":388,"paper":389,"created_at":417},5390,"Land use and socio-economic changes caused by riverbank erosion - case study: Obrenovac municipality, Serbia","https:\u002F\u002Fdoi.org\u002F10.59954\u002Fstnv.797","Lateral bank erosion of meandering rivers represents a significant geomorphological process in the lower part of the Kolubara River Basin in Serbia. This process directly impacts land-use and agricultural productivity and lead to broader environmental, socioeconomic, and demographic changes. Historically, the Kolubara riverbanks have been intensively used for agriculture. Today, lateral channel migration and riverbank erosion, driven by the interaction between natural process and human activities, directly threaten traditionally active land plots along the river. This study investigates the long-term dynamics of riverbank erosion along the four active meanders of the Kolubara River in Obrenovac Municipality over a 97-year period (1930–2026). Main tasks include quantification of lateral channel migration and land loss rates, analysis of land-use changes within the endangered plots, and an investigation of socioeconomic consequences and demographic dynamics in affected settlements. The methodological framework integrates cadastral maps analysis, remote sensing techniques (UAVs), and GIS software, with analysis of demographic and land-use data. The results indicate that maximum lateral channel migration reached 259.3 m during the observed period, while the total land loss amounted to 17.6 ha, consisting mostly of arable land. This reduction has directly affected the local agricultural sector, resulting in an estimated land loss value of approximately 24,122 USD. Demographic analysis reveals population decline exceeding 40% in the analysed settlements (Draževac, Konatice and Poljane) between 1961 and 2022, from over 90% of the economically active population in 1961 to less than 2% in 2022. Ultimately, by highlighting the socioeconomic impacts of riverbank erosion such as irreversible agricultural land loss and rural livelihood disruption, these findings offer valuable insights for spatial planning and sustainable land management.","蜿蜒河流的侧向河岸侵蚀是塞尔维亚科卢巴拉河（Kolubara River）流域下游一个重要的地貌过程。该过程直接影响土地利用和农业生产力，并引发更广泛的环境、社会经济和人口变化。历史上，科卢巴拉河岸曾被密集用于农业生产。如今，在自然过程与人类活动相互作用驱动下的侧向河道迁移和河岸侵蚀，直接威胁着沿河传统上活跃的地块。本研究考察了奥布雷诺瓦茨市（Obrenovac Municipality）科卢巴拉河四个活跃曲流段在97年期间（1930—2026年）河岸侵蚀的长期动态。主要任务包括：量化侧向河道迁移和土地流失速率，分析受威胁地块内的土地利用变化，以及调查受影响居民点的社会经济后果和人口动态。方法框架整合了地籍图分析、遥感技术（无人机，UAVs）和GIS软件，并结合人口与土地利用数据分析。结果表明，在观测期内侧向河道迁移最大距离达259.3 m，土地流失总量为17.6 ha，其中大部分为耕地。这一减少直接影响了当地农业部门，估计土地流失价值约为24,122美元。人口分析显示，1961年至2022年间，所分析居民点（Draževac、Konatice和Poljane）的人口下降幅度超过40%，经济活动人口比例从1961年的超过90%降至2022年的不足2%。最终，通过突出河岸侵蚀的社会经济影响，如不可逆的农业土地流失和农村生计破坏，这些发现为空间规划和可持续土地管理提供了有价值的见解。","Stanovnistvo","2026-10-19T00:00:00Z",{"impact":89,"substance":89,"depth":89,"authority":89,"freshness":89,"relevant":89,"comment":354},"塞尔维亚河岸侵蚀案例研究，属地理与土地利用领域，与三农及农业信息化主题关联弱，不建议进入每日精选。",[356],{"name":351,"url":348},[26,27,358,359],"土壤侵蚀","乡村人口",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":363},{"candidates":364,"agricultural_evidence":46},[365,370,374,380],{"code":32,"score":366,"supported":46,"title":367,"abstract":368,"tags":369},7,[],[128,48],[26],{"code":177,"score":131,"supported":46,"title":371,"abstract":372,"tags":373},[],[194],[],{"code":375,"score":131,"supported":46,"title":376,"abstract":377,"tags":379},"I7",[],[378],"methodological framework",[],{"code":67,"score":21,"supported":14,"title":381,"abstract":382,"tags":383},[],[],[27],[385,386],"Kolubara 河岸侵蚀","Obrenovac 土地利用","Kolubara河岸侵蚀-5390","10.59954\u002Fstnv.797",{"doi":388,"openalex_id":390,"authors":391,"venue":351,"cited_by_count":89,"oa_url":348,"card":411,"direction":95,"ingested_from":97},"W7222945959",[392,395,398,400,403,406,409],{"name":393,"orcid":394},"Slavoljub Dragićević","https:\u002F\u002Forcid.org\u002F0000-0002-1417-5405",{"name":396,"orcid":397},"Marko Langović","https:\u002F\u002Forcid.org\u002F0000-0002-4614-7265",{"name":399,"orcid":9},"Милан Радовић",{"name":401,"orcid":402},"Radislav Tošić","https:\u002F\u002Forcid.org\u002F0000-0002-3994-125X",{"name":404,"orcid":405},"Milica Langović","https:\u002F\u002Forcid.org\u002F0000-0002-6979-377X",{"name":407,"orcid":408},"Novica Lovrić","https:\u002F\u002Forcid.org\u002F0009-0006-0838-4370",{"name":410,"orcid":9},"Manojlović Stefan",{"tldr":412,"method":413,"finding":414,"direction":415,"opportunity":416},"研究塞尔维亚Kolubara河岸侵蚀97年间的河道迁移、耕地损失及社会经济影响。","结合地籍图、UAV遥感、GIS与人口土地利用数据分析四条曲流。","最大侧向迁移259.3米，损失17.6公顷耕地约2.4万美元，村落人口降超40%。","其他","可将河岸侵蚀遥感监测与农户生计、土地价值评估耦合，构建侵蚀风险预警与补偿决策模型。","2026-10-20T23:30:18.982943Z",{"id":419,"title":420,"url":421,"summary":422,"summary_zh":423,"content":9,"source_name":424,"source_url":421,"published_at":425,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":89,"score_detail":426,"sources":428,"tags":430,"primary_topic":433,"secondary_topics":434,"classification":435,"search_phrases":442,"slug":445,"view_count":89,"doi":446,"paper":447,"created_at":462},5244,"Diurnal and Seasonal Surface Urban Heat Island Dynamics and Thermal Field Variance in Faridabad District, India: A MODIS-Based Assessment (2001–2025)","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fajgr\u002F2026\u002Fv9i4489","Aims: To examine the spatial and temporal dynamics of land surface temperature (LST), urban–rural biophysical indices (BUI and NDVI), daily Surface Urban Heat Island Intensity (SUHII), and the Urban Thermal Field Variance Index (UTFVI) on a diurnal and seasonal basis in Faridabad District of northern India. Study Design: Multi-temporal geospatial remote sensing and statistical modelling study. Place and Duration of Study: Faridabad District (Urban Core and Rural Hinterland), Haryana, India; Summer and Winter Seasons Analysed through Six Benchmark Periods (2001, 2005, 2010, 2015, 2020, and 2025). Methodology: MODIS optical (MOD09A1) and thermal infrared (MOD11A2) composite data were analysed using Google Earth Engine at the daytime (10:30 am) and night-time (10:30 pm) overpasses. LST values were grouped into UTFVI (Urban Thermal Field Variance Index) classes. Multivariable OLS regressions and empirical biophysical sensitivities such as Vegetation Cooling Efficiency (VCE) and Impervious Heating Effect (IHE) were evaluated in Python using a stratified random grid (N = 2,500 sampling locations; 235 n 872 pixels). Results: Over the 25-year study period, the built-up gradient for winter (BUI) increased from +0.096 to +0.233 in association with agricultural changes and urban development in the region, while the vegetative deficit for winter (NDVI) increased from -0.061 to -0.136. In terms of temperature, Faridabad showed a SUHI regime during summer (ranging from to ), where the urban core nocturnal LST increased from in 2001 to in 2025, together with regional warming and compression of the urban DTR. The pre-monsoon diurnal regimes showed the SUCI phenomenon (as low as in 2005) owing to the effects of sensible heating in the desiccated fallow rural lands after harvest season. Urban Core thermal field variance showed that moderate thermal stress (UTFVI Class 3) expanded from to , while severe stress tiers (Classes 4–6) concentrated within industrial estates. Daytime vegetation provided consistent cooling (VCE up to per ), whereas nocturnal VCE exhibited temporal variability and diminished transpirational cooling following stomatal closure. Conclusion: Urban greening offers a strong mechanism for daytime heat mitigation but is insufficient to address independently nocturnal heat trapping resulting from the high thermal inertia of construction materials. The sustainable heat-mitigation strategy in industrial nodes entails a combination of urban greening and reflective cool coatings on industrial sheds and impervious surfaces.","目的：考察印度北部法里达巴德县地表温度（LST）、城乡生物物理指数（BUI和NDVI）、日间地表城市热岛强度（SUHII）以及城市热场方差指数（UTFVI）在昼夜和季节尺度上的时空动态。研究设计：多时相地理空间遥感与统计建模研究。研究地点与时长：印度哈里亚纳邦法里达巴德县（城市核心区与乡村腹地）；通过六个基准时段（2001、2005、2010、2015、2020和2025年）分析夏季与冬季。方法：利用Google Earth Engine分析MODIS光学（MOD09A1）和热红外（MOD11A2）合成数据，分别对应白天（上午10：30）和夜间（晚上10：30）过境时刻。LST值按UTFVI（城市热场方差指数）类别分组。在Python中采用分层随机网格（N=2，500个采样点；235 n 872像素）评估多变量OLS回归及经验生物物理敏感性指标，如植被冷却效率（VCE）和不透水面增温效应（IHE）。结果：在25年研究期内，冬季建成区梯度（BUI）从+0.096增至+0.233，与该地区农业变化和城市发展相关；冬季植被亏缺（NDVI）从-0.061增至-0.136。温度方面，法里达巴德在夏季呈现SUHI态势（范围为至），城市核心区夜间LST从2001年的增至2025年的，同时伴随区域增暖和城市日较差（DTR）压缩。季风前昼夜态势因收获季后干燥休耕乡村土地的感热加热效应而呈现SUCI现象（2005年低至）。城市核心区热场方差显示，中度热胁迫（UTFVI第3类）从扩大至，而严重胁迫层级（第4—6类）集中于工业园区。白天植被提供持续冷却（VCE最高达每），而夜间VCE呈现时间变异性，且气孔关闭后蒸腾冷却减弱。结论：城市绿化是白天热缓解的有力机制，但不足以独立应对建筑材料高热惯性导致的夜间热量滞留。工业节点的可持续热缓解策略需要将城市绿化与反射性","Asian Journal of Geographical Research","2026-10-17T00:00:00Z",{"impact":89,"substance":89,"depth":89,"authority":89,"freshness":89,"relevant":89,"comment":427},"印度城市热岛遥感研究，属城市气候与环境领域，与三农、农业信息化、智慧农业无直接关联，不建议进入每日精选。",[429],{"name":424,"url":421},[26,28,431,432],"城市热岛","MODIS",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":436},{"candidates":437,"agricultural_evidence":46},[438],{"code":32,"score":17,"supported":46,"title":439,"abstract":440,"tags":441},[],[128,48],[28,26],[443,444],"Faridabad 城市热岛","MODIS 地表温度 遥感","Faridabad城市热岛-5244","10.9734\u002Fajgr\u002F2026\u002Fv9i4489",{"doi":446,"openalex_id":448,"authors":449,"venue":424,"cited_by_count":89,"oa_url":421,"card":457,"direction":95,"ingested_from":97},"W7222794736",[450,453,455],{"name":451,"orcid":452},"Abhishek Malik","https:\u002F\u002Forcid.org\u002F0009-0009-4878-0871",{"name":454,"orcid":9},"Shubham Mor",{"name":456,"orcid":9},"Gaurav Kalotra",{"tldr":458,"method":459,"finding":460,"direction":95,"opportunity":461},"基于MODIS分析印度Faridabad 2001–2025年昼夜与季节地表城市热岛及热场差异演变。","MODIS光学与热红外数据、Google Earth Engine、OLS回归及","白天绿化降温显著，但夜间建筑热惯性导致的热滞留难以单独缓解。","可结合城乡梯度与作物休耕期感热效应，研究农业用地变化对昼夜热岛的非对称贡献。","2026-10-18T23:30:31.211684Z"]