It is crucial to investigate the urban agglomerations spatio-temporal evolution patterns and driving factors for analyzing the urban spatial structure-functional division and promoting the coordinated development of u...It is crucial to investigate the urban agglomerations spatio-temporal evolution patterns and driving factors for analyzing the urban spatial structure-functional division and promoting the coordinated development of urban agglomerations.In this study,a novel vegetation-building-nighttime light-adjusted index(VBNAI)was established for rapid and effective mapping of urban construction land(UCL)in Central Plains Urban Agglomeration(CPUA),China during 2000–2020 based on Google Earth Engine(GEE)platform.Compared with traditional indices,VBNAI can significantly decrease the blooming effect,Normalized Difference Vegetation Index(NDVI)saturation,and soil background of nighttime light data.In addition,the urban expansion indices and standard deviation ellipse model were synthetically adopted to analyze the spatio-temporal evolution pattern of urban expansion.The gravity model and the geographically weighted regression model were employed to determine the spatial interaction forces and drivers of urban expansion,respectively.The results showed that the VBNAI index has obvious advantages in efficiency and accuracy to extract UCL with the overall accuracy of more than 91%.The UCL of CPUA had increased by 4489.84 km2 during 2000–2020 with the gravity center moving towards southeast continuously.From 2000 to 2010,the urban expansion was in a‘center-hinterland’pattern which had benefit from the favorable effect of the traffic shaft belt.During 2010–2020,the urban network structure had basically established.Urban expansion had been influenced by a variety of socio-economic and demographic factors,and the impact degree varied from region to region.This study could provide scientific references for facilitating the intensive utilization of urban resources and optimizing the spatial development pattern of urban agglomeration.展开更多
围绕如何在浩瀚的中文网页中找到用户感兴趣的内容,提出了基于UCL(Uniform Content Locator)的“二阶过滤法”.它将媒体空间中的信息用UCL语义格(Semantic Cases based on UCL,SCU)表示,通过语义向量空间模型(Semantic Vector Space Mod...围绕如何在浩瀚的中文网页中找到用户感兴趣的内容,提出了基于UCL(Uniform Content Locator)的“二阶过滤法”.它将媒体空间中的信息用UCL语义格(Semantic Cases based on UCL,SCU)表示,通过语义向量空间模型(Semantic Vector Space Model,SVSM)对网页的语义矩阵进行分析计算,粗略筛选出用户感兴趣的网页;再借助精细语义逐句解读其内容,提取用户所关注的信息.根据用户的阅读行为动态了解用户的兴趣变化,建立用户兴趣的本体模型,并分析和定义了用户兴趣度的度量.实验验证了上述过滤方法的有效性,其测试结果同向量空间模型(Vector SpaceModel,VSM)进行了比较,性能明显优于VSM.展开更多
基金Under the auspices of Social Science and Humanity on Young Fund of the Ministry of Education of China(No.21YJCZH100)the Scientific Research Project on Outstanding Young of the Fujian Agriculture and Forestry University(No.XJQ201920)+1 种基金the Science and Technology Innovation Special Fund Project of Fujian Agriculture and Forestry University(No.CXZX2021032)the Forestry Peak Discipline Construction Project of Fujian Agriculture and Forestry University(No.72202200205)。
文摘It is crucial to investigate the urban agglomerations spatio-temporal evolution patterns and driving factors for analyzing the urban spatial structure-functional division and promoting the coordinated development of urban agglomerations.In this study,a novel vegetation-building-nighttime light-adjusted index(VBNAI)was established for rapid and effective mapping of urban construction land(UCL)in Central Plains Urban Agglomeration(CPUA),China during 2000–2020 based on Google Earth Engine(GEE)platform.Compared with traditional indices,VBNAI can significantly decrease the blooming effect,Normalized Difference Vegetation Index(NDVI)saturation,and soil background of nighttime light data.In addition,the urban expansion indices and standard deviation ellipse model were synthetically adopted to analyze the spatio-temporal evolution pattern of urban expansion.The gravity model and the geographically weighted regression model were employed to determine the spatial interaction forces and drivers of urban expansion,respectively.The results showed that the VBNAI index has obvious advantages in efficiency and accuracy to extract UCL with the overall accuracy of more than 91%.The UCL of CPUA had increased by 4489.84 km2 during 2000–2020 with the gravity center moving towards southeast continuously.From 2000 to 2010,the urban expansion was in a‘center-hinterland’pattern which had benefit from the favorable effect of the traffic shaft belt.During 2010–2020,the urban network structure had basically established.Urban expansion had been influenced by a variety of socio-economic and demographic factors,and the impact degree varied from region to region.This study could provide scientific references for facilitating the intensive utilization of urban resources and optimizing the spatial development pattern of urban agglomeration.
文摘围绕如何在浩瀚的中文网页中找到用户感兴趣的内容,提出了基于UCL(Uniform Content Locator)的“二阶过滤法”.它将媒体空间中的信息用UCL语义格(Semantic Cases based on UCL,SCU)表示,通过语义向量空间模型(Semantic Vector Space Model,SVSM)对网页的语义矩阵进行分析计算,粗略筛选出用户感兴趣的网页;再借助精细语义逐句解读其内容,提取用户所关注的信息.根据用户的阅读行为动态了解用户的兴趣变化,建立用户兴趣的本体模型,并分析和定义了用户兴趣度的度量.实验验证了上述过滤方法的有效性,其测试结果同向量空间模型(Vector SpaceModel,VSM)进行了比较,性能明显优于VSM.
