Flood disasters can have a serious impact on people's production and lives, and can cause hugelosses in lives and property security. Based on multi-source remote sensing data, this study establisheddecision tree c...Flood disasters can have a serious impact on people's production and lives, and can cause hugelosses in lives and property security. Based on multi-source remote sensing data, this study establisheddecision tree classification rules through multi-source and multi-temporal feature fusion, classified groundobjects before the disaster and extracted flood information in the disaster area based on optical imagesduring the disaster, so as to achieve rapid acquisition of the disaster situation of each disaster bearing object.In the case of Qianliang Lake, which suffered from flooding in 2020, the results show that decision treeclassification algorithms based on multi-temporal features can effectively integrate multi-temporal and multispectralinformation to overcome the shortcomings of single-temporal image classification and achieveground-truth object classification.展开更多
目的为探究大气污染物与植被生长状况之间的相互影响,方法基于美国国家航空航天局(national aeronautics and space adminidtration,NASA)提供的归一化植被指数(normalized difference vegetation index,NDVI)与空气质量在线监测分析平...目的为探究大气污染物与植被生长状况之间的相互影响,方法基于美国国家航空航天局(national aeronautics and space adminidtration,NASA)提供的归一化植被指数(normalized difference vegetation index,NDVI)与空气质量在线监测分析平台提供的空气质量指数(air quality index,AQI),采用Kriging插值、一元线性回归和相关性分析等方法,对黄河中下游地区的河南省、山东省、山西省、陕西省,海河流域的河北省和重要城市(北京市和天津市)的AQI与NDVI时空分布特征进行解释,并分析其相关性。结果结果表明:(1)2014—2016年,AQI年均值呈显著下降趋势,每年AQI数值冬季最高,春秋相对较低,夏季最低,且呈现明显的区域差异性,出现中间高两侧低的“中心-外围”结构;2017年后,夏季AQI反而高于春秋季的。(2)2014—2020年,NDVI波动上升,上升斜率为0.0041/a。总体上,NDVI上升的面积占研究区总面积的93.76%,且极显著和显著上升趋势的面积分别占16.32%和12.09%。结论黄河中下游地区和海河流域AQI与NDVI时空格局及相关分析结果可以为气候变化对环境的影响研究提供理论基础。展开更多
文摘Flood disasters can have a serious impact on people's production and lives, and can cause hugelosses in lives and property security. Based on multi-source remote sensing data, this study establisheddecision tree classification rules through multi-source and multi-temporal feature fusion, classified groundobjects before the disaster and extracted flood information in the disaster area based on optical imagesduring the disaster, so as to achieve rapid acquisition of the disaster situation of each disaster bearing object.In the case of Qianliang Lake, which suffered from flooding in 2020, the results show that decision treeclassification algorithms based on multi-temporal features can effectively integrate multi-temporal and multispectralinformation to overcome the shortcomings of single-temporal image classification and achieveground-truth object classification.
文摘目的为探究大气污染物与植被生长状况之间的相互影响,方法基于美国国家航空航天局(national aeronautics and space adminidtration,NASA)提供的归一化植被指数(normalized difference vegetation index,NDVI)与空气质量在线监测分析平台提供的空气质量指数(air quality index,AQI),采用Kriging插值、一元线性回归和相关性分析等方法,对黄河中下游地区的河南省、山东省、山西省、陕西省,海河流域的河北省和重要城市(北京市和天津市)的AQI与NDVI时空分布特征进行解释,并分析其相关性。结果结果表明:(1)2014—2016年,AQI年均值呈显著下降趋势,每年AQI数值冬季最高,春秋相对较低,夏季最低,且呈现明显的区域差异性,出现中间高两侧低的“中心-外围”结构;2017年后,夏季AQI反而高于春秋季的。(2)2014—2020年,NDVI波动上升,上升斜率为0.0041/a。总体上,NDVI上升的面积占研究区总面积的93.76%,且极显著和显著上升趋势的面积分别占16.32%和12.09%。结论黄河中下游地区和海河流域AQI与NDVI时空格局及相关分析结果可以为气候变化对环境的影响研究提供理论基础。
