Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-de...Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.展开更多
适应城市化进程加速与气候变化,提高抵御洪涝灾害的能力是可持续发展的必由之路。从韧性视角出发,构建基于“自然-经济-社会-基础设施”的洪涝韧性评估框架,运用组合赋权-逼近理想解排序模型(Technique for Order Preference by Similar...适应城市化进程加速与气候变化,提高抵御洪涝灾害的能力是可持续发展的必由之路。从韧性视角出发,构建基于“自然-经济-社会-基础设施”的洪涝韧性评估框架,运用组合赋权-逼近理想解排序模型(Technique for Order Preference by Similarity to the Ideal Solution,TOPSIS)评估2007—2022年南京都市圈城市洪涝韧性水平,并利用障碍度模型诊断抑制洪涝韧性提升的主要因素。结果表明:(1)都市圈城市洪涝韧性呈上升趋势,从较低水平转变为中等水平;(2)洪涝韧性空间分布呈现以南京为核心、向四周辐射递减的“中心-外围”特征;(3)研究时段末南京都市圈洪涝韧性的关键限制因素有河流调蓄能力、人口脆弱度、政府财政情况,植被覆盖率为部分城市潜在障碍因素。研究可为南京都市圈完善洪涝灾害防治体系、提升洪涝韧性提供参考。展开更多
针对黑河流域大尺度环境下水体提取难度大、演变规律尚不明晰等问题,基于谷歌地球引擎(Google Earth Engine,GEE)处理黑河流域1986—2024年Landsat影像,采集7.8×10^(4)个水体/非水体样本并构建逐年样本数据集,通过将多波段水体指数...针对黑河流域大尺度环境下水体提取难度大、演变规律尚不明晰等问题,基于谷歌地球引擎(Google Earth Engine,GEE)处理黑河流域1986—2024年Landsat影像,采集7.8×10^(4)个水体/非水体样本并构建逐年样本数据集,通过将多波段水体指数(Multi band water index,MBWI)、增强型水体指数(Enhanced water index,EWI)、改进归一化差异水体指数(Modified normalized difference water index,MNDWI)与光谱波段进行单独与统一组合,构建并筛选出最佳融合水体指数的随机森林(Random forest,RF)水体提取方法,提取了研究区39个时相的逐年地表水体影像,采用曼-肯德尔(Mann-Kendall,M-K)法揭示了黑河流域逐年地表水体面积变化特征,基于主成分与敏感性分析探究了影响地表水体演变的主要驱动因素。结果表明:融合3种水体指数(MBWI、EWI、MNDWI)的随机森林水体提取方法对黑河流域Landsat影像的水体提取效果最佳,平均总体精度(Overall accuracy,OA)为96.16%,平均Kappa系数为0.9128;经M-K法检验,黑河流域1986—2024年地表水体面积呈波动减少态势;年降水量、人口、年蒸散量为黑河流域地表水体演变的最主要驱动因素。研究结果可为全流域地表水体的快速准确提取提供理论支持。展开更多
基金Projects(41601424,41171351)supported by the National Natural Science Foundation of ChinaProject(2012CB719906)supported by the National Basic Research Program of China(973 Program)+2 种基金Project(14JJ1007)supported by the Hunan Natural Science Fund for Distinguished Young Scholars,ChinaProject(2017M610486)supported by the China Postdoctoral Science FoundationProjects(2017YFB0503700,2017YFB0503601)supported by the National Key Research and Development Foundation of China
文摘Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.
文摘适应城市化进程加速与气候变化,提高抵御洪涝灾害的能力是可持续发展的必由之路。从韧性视角出发,构建基于“自然-经济-社会-基础设施”的洪涝韧性评估框架,运用组合赋权-逼近理想解排序模型(Technique for Order Preference by Similarity to the Ideal Solution,TOPSIS)评估2007—2022年南京都市圈城市洪涝韧性水平,并利用障碍度模型诊断抑制洪涝韧性提升的主要因素。结果表明:(1)都市圈城市洪涝韧性呈上升趋势,从较低水平转变为中等水平;(2)洪涝韧性空间分布呈现以南京为核心、向四周辐射递减的“中心-外围”特征;(3)研究时段末南京都市圈洪涝韧性的关键限制因素有河流调蓄能力、人口脆弱度、政府财政情况,植被覆盖率为部分城市潜在障碍因素。研究可为南京都市圈完善洪涝灾害防治体系、提升洪涝韧性提供参考。
文摘针对黑河流域大尺度环境下水体提取难度大、演变规律尚不明晰等问题,基于谷歌地球引擎(Google Earth Engine,GEE)处理黑河流域1986—2024年Landsat影像,采集7.8×10^(4)个水体/非水体样本并构建逐年样本数据集,通过将多波段水体指数(Multi band water index,MBWI)、增强型水体指数(Enhanced water index,EWI)、改进归一化差异水体指数(Modified normalized difference water index,MNDWI)与光谱波段进行单独与统一组合,构建并筛选出最佳融合水体指数的随机森林(Random forest,RF)水体提取方法,提取了研究区39个时相的逐年地表水体影像,采用曼-肯德尔(Mann-Kendall,M-K)法揭示了黑河流域逐年地表水体面积变化特征,基于主成分与敏感性分析探究了影响地表水体演变的主要驱动因素。结果表明:融合3种水体指数(MBWI、EWI、MNDWI)的随机森林水体提取方法对黑河流域Landsat影像的水体提取效果最佳,平均总体精度(Overall accuracy,OA)为96.16%,平均Kappa系数为0.9128;经M-K法检验,黑河流域1986—2024年地表水体面积呈波动减少态势;年降水量、人口、年蒸散量为黑河流域地表水体演变的最主要驱动因素。研究结果可为全流域地表水体的快速准确提取提供理论支持。
