城市空间POI点的分布模式、分布密度在基础设施规划、城市空间分析中具有重要意义,表达该特征的核密度法(kernel density estimation)由于顾及了地理学第一定律的区位影响,比其他密度表达方法(如样方密度、基于Voronoi图密度)占优。然而...城市空间POI点的分布模式、分布密度在基础设施规划、城市空间分析中具有重要意义,表达该特征的核密度法(kernel density estimation)由于顾及了地理学第一定律的区位影响,比其他密度表达方法(如样方密度、基于Voronoi图密度)占优。然而,传统的核密度计算方法往往基于二维延展的欧氏空间,忽略了城市网络空间中设施点的服务功能及相互联系发生于网络路径距离而非欧氏距离的事实。本研究针对该缺陷,给出了网络空间核密度计算模型,分析了核密度方法在置入网络结构中受多种约束条件的扩展模式,讨论了衰减阈值及高度极值对核密度特征表达的影响。通过实际多种POI点分布模式(随机型、稀疏型、区域密集型、线状密集型)下的核密度分析试验,讨论了POI基础设施在城市区域中的分布特征、影响因素、服务功能。展开更多
数字经济时代POI大数据为城市及城市群商业空间结构及变化研究提供了新思路。基于2015年和2021年POI大数据,采用空间核密度、Theil指数等方法从区县层面对粤港澳大湾区商业总体及购物、休闲、餐饮三类业态的空间布局演变特征、区域差异...数字经济时代POI大数据为城市及城市群商业空间结构及变化研究提供了新思路。基于2015年和2021年POI大数据,采用空间核密度、Theil指数等方法从区县层面对粤港澳大湾区商业总体及购物、休闲、餐饮三类业态的空间布局演变特征、区域差异进行研究。结果表明:1) 2015~2021年间粤港澳大湾区多中心商业空间一体化发展格局进一步强化,形成显著的多中心多等级都市圈商业空间格局;2) Theil指数表明商业网点总体及三大细分业态POI数量的区域差异均呈现扩大态势,组内差距明显大于组间差距;相对于城市尺度下的区域差异,区县尺度下的组内差异有所下降但组间差距明显增大;3) 不同商业中心区的演变趋势存在差异,高密度商圈主要分布于广州、深圳、香港三大一线城市,商业网点密度最高等级从2015年的968个/km2增加到2021年1904个/km2;4) 购物服务类、餐饮服务类、休闲娱乐POI增长幅度均超过50%,空间集聚和连片化特征明显加强;5) 不同商业业态网点规模结构发生动态调整,超市、专卖店、便利店等业态网点增长较快,大型购物中心下降态势明显,不同业态的空间变化特征有明显差异。POI big data provides new ideas for research on spatial structure and changes of commercial space in cities and urban agglomerations in digital economy era. Based on the two periods of POI big data in 2015 and 2021, the paper used method called spatial kernel density and Theil’s Index to study evolution characteristics of spatial layout of the overall business and three types of business formats in the Guangdong-Hong Kong-Macao Greater Bay Area from perspective of county-level regions. The results showed that: 1) During the period from 2015 to 2021, the integrated development pattern of multi-center commercial space in Guangdong-Hong Kong-Macao Greater Bay Area was further strengthened, forming a significant multi-center and multi-level metropolitan commercial space pattern;2) Theil’s index showed that the regional differences of POI quantity in all commercial network and three sub-formats were enlarged, and the intra-group differences were obviously larger than the inter-group differences. Relative to regional differences at the city scale, intra-group differences at county scale declined but inter-group gaps increased significantly. 3) There were differences in the evolution trends of different commercial central areas. The high-density business districts were mainly distributed in three first-tier cities including Guangzhou, Shenzhen, and Hong Kong. The highest level of commercial network density increased from 968 per km2 in 2015 to 1904 per km2 in 2021;4) The growth rate of shopping service, catering service, and leisure entertainment POIs exceeded 50%, and the characteristics of spatial agglomeration and contiguousness were significantly strengthened;5) The scale structure of outlets for different business formats underwent dynamic adjustments. Supermarkets, specialty stores, convenience stores, and other business formats had rapid growth. Large shopping malls showed a significant downward trend. There were significant differences in the spatial variation characteristics of different formats.展开更多
为了促进区域经济发展、改善黄河流域生态环境质量,基于景区兴趣点(point of interest,POI)数据,采用核密度估计、标准差椭圆、地理联系率和空间叠加分析等方法,探究黄河流域中游170个3A级及以上(以下简称“3A级以上”)山地景区的空间...为了促进区域经济发展、改善黄河流域生态环境质量,基于景区兴趣点(point of interest,POI)数据,采用核密度估计、标准差椭圆、地理联系率和空间叠加分析等方法,探究黄河流域中游170个3A级及以上(以下简称“3A级以上”)山地景区的空间分布特点及影响因素.结果表明:①黄河流域中游3A级以上山地景区集中分布在晋、陕、豫三省,景区密度大.3A级山地景区高密度区主要分布在豫北、豫南、晋东南;4A级山地景区呈向右旋转90°的“Y”型分布;5A级山地景区主要集中在晋、陕、豫交界处,组团状分布,由东北向西南展布.②自然地理环境方面,3A级以上山地景区主要分布在海拔300~1200 m处,坡度为15°~45°,偏南坡.河流水系、植被指数、空气质量对景区分布的影响效果显著.③社会经济环境方面,交通区位、固定资产投资、旅游收入和文化遗产禀赋是景区发展的重要影响因素.展开更多
文摘城市空间POI点的分布模式、分布密度在基础设施规划、城市空间分析中具有重要意义,表达该特征的核密度法(kernel density estimation)由于顾及了地理学第一定律的区位影响,比其他密度表达方法(如样方密度、基于Voronoi图密度)占优。然而,传统的核密度计算方法往往基于二维延展的欧氏空间,忽略了城市网络空间中设施点的服务功能及相互联系发生于网络路径距离而非欧氏距离的事实。本研究针对该缺陷,给出了网络空间核密度计算模型,分析了核密度方法在置入网络结构中受多种约束条件的扩展模式,讨论了衰减阈值及高度极值对核密度特征表达的影响。通过实际多种POI点分布模式(随机型、稀疏型、区域密集型、线状密集型)下的核密度分析试验,讨论了POI基础设施在城市区域中的分布特征、影响因素、服务功能。
文摘数字经济时代POI大数据为城市及城市群商业空间结构及变化研究提供了新思路。基于2015年和2021年POI大数据,采用空间核密度、Theil指数等方法从区县层面对粤港澳大湾区商业总体及购物、休闲、餐饮三类业态的空间布局演变特征、区域差异进行研究。结果表明:1) 2015~2021年间粤港澳大湾区多中心商业空间一体化发展格局进一步强化,形成显著的多中心多等级都市圈商业空间格局;2) Theil指数表明商业网点总体及三大细分业态POI数量的区域差异均呈现扩大态势,组内差距明显大于组间差距;相对于城市尺度下的区域差异,区县尺度下的组内差异有所下降但组间差距明显增大;3) 不同商业中心区的演变趋势存在差异,高密度商圈主要分布于广州、深圳、香港三大一线城市,商业网点密度最高等级从2015年的968个/km2增加到2021年1904个/km2;4) 购物服务类、餐饮服务类、休闲娱乐POI增长幅度均超过50%,空间集聚和连片化特征明显加强;5) 不同商业业态网点规模结构发生动态调整,超市、专卖店、便利店等业态网点增长较快,大型购物中心下降态势明显,不同业态的空间变化特征有明显差异。POI big data provides new ideas for research on spatial structure and changes of commercial space in cities and urban agglomerations in digital economy era. Based on the two periods of POI big data in 2015 and 2021, the paper used method called spatial kernel density and Theil’s Index to study evolution characteristics of spatial layout of the overall business and three types of business formats in the Guangdong-Hong Kong-Macao Greater Bay Area from perspective of county-level regions. The results showed that: 1) During the period from 2015 to 2021, the integrated development pattern of multi-center commercial space in Guangdong-Hong Kong-Macao Greater Bay Area was further strengthened, forming a significant multi-center and multi-level metropolitan commercial space pattern;2) Theil’s index showed that the regional differences of POI quantity in all commercial network and three sub-formats were enlarged, and the intra-group differences were obviously larger than the inter-group differences. Relative to regional differences at the city scale, intra-group differences at county scale declined but inter-group gaps increased significantly. 3) There were differences in the evolution trends of different commercial central areas. The high-density business districts were mainly distributed in three first-tier cities including Guangzhou, Shenzhen, and Hong Kong. The highest level of commercial network density increased from 968 per km2 in 2015 to 1904 per km2 in 2021;4) The growth rate of shopping service, catering service, and leisure entertainment POIs exceeded 50%, and the characteristics of spatial agglomeration and contiguousness were significantly strengthened;5) The scale structure of outlets for different business formats underwent dynamic adjustments. Supermarkets, specialty stores, convenience stores, and other business formats had rapid growth. Large shopping malls showed a significant downward trend. There were significant differences in the spatial variation characteristics of different formats.
文摘为了促进区域经济发展、改善黄河流域生态环境质量,基于景区兴趣点(point of interest,POI)数据,采用核密度估计、标准差椭圆、地理联系率和空间叠加分析等方法,探究黄河流域中游170个3A级及以上(以下简称“3A级以上”)山地景区的空间分布特点及影响因素.结果表明:①黄河流域中游3A级以上山地景区集中分布在晋、陕、豫三省,景区密度大.3A级山地景区高密度区主要分布在豫北、豫南、晋东南;4A级山地景区呈向右旋转90°的“Y”型分布;5A级山地景区主要集中在晋、陕、豫交界处,组团状分布,由东北向西南展布.②自然地理环境方面,3A级以上山地景区主要分布在海拔300~1200 m处,坡度为15°~45°,偏南坡.河流水系、植被指数、空气质量对景区分布的影响效果显著.③社会经济环境方面,交通区位、固定资产投资、旅游收入和文化遗产禀赋是景区发展的重要影响因素.
