With the continuous development of urbanization in China,the country’s growing population brings great challenges to urban development.By mastering the refined population spatial distribution in administrative units,...With the continuous development of urbanization in China,the country’s growing population brings great challenges to urban development.By mastering the refined population spatial distribution in administrative units,the quantity and agglomeration of population distribution can be estimated and visualized.It will provide a basis for a more rational urban planning.This paper takes Beijing as the research area and uses a new Luojia1-01 nighttime light image with high resolution,land use type data,Points of Interest(POI)data,and other data to construct the population spatial index system,establishing the index weight based on the principal component analysis.The comprehensive weight value of population distribution in the study area was then used to calculate the street population distribution of Beijing in 2018.Then the population spatial distribution was visualize using GIS technology.After accuracy assessments by comparing the result with the WorldPop data,the accuracy has reached 0.74.The proposed method was validated as a qualified method to generate population spatial maps.By contrast of local areas,Luojia 1-01 data is more suitable for population distribution estimation than the NPP/VIIRS(Net Primary Productivity/Visible infrared Imaging Radiometer)nighttime light data.More geospatial big data and mathematical models can be combined to create more accurate population maps in the future.展开更多
The Tibetan Plateau(TP)is undergoing rapid urbanization.To improve urban sustainability and construct eco-logical security barriers,it is essential to quantify the spatial patterns of urbanization level on the TP,but ...The Tibetan Plateau(TP)is undergoing rapid urbanization.To improve urban sustainability and construct eco-logical security barriers,it is essential to quantify the spatial patterns of urbanization level on the TP,but the existing studies on the topic have been limited by the lack of socioeconomic data.This study aims to quantify the urbanization level on the TP in 2018 with Luojia1-01(LJ1-01)high-resolution nighttime light(NTL)data.Specifically,the compounded night light index is used to quantify spatial patterns of urbanization level at mul-tiple scales.The results showed that the TP had a low overall urbanization level with a large internal difference.The urbanization level in the northeast,southeast and south of the TP was relatively high,forming three hotspots centered in Xining City,Lhasa City and Shangri-La City,while the urbanization level in the central and western regions was relatively low.The analysis of influencing factors,based on the random forest model,showed that transportation and topography were the main factors affecting the TP’s spatial patterns of urbanization level.The comparison analysis with socioeconomic statistics and traditional NTL data showed that LJ1-01 NTL data can be used to more effectively quantify the urbanization level since it is more advantageous for reflecting the spatial extent of urban land and describing the spatial structure of socioeconomic activities within urban areas.These advantages are attributed to the high spatial resolution of the data,appropriate imaging time and unaf-fected by saturation phenomena.Thus,the proposed LJ1-01 NTL-based urbanization level measurement method has the potential for wide applications around the world,especially in less-developed regions lacking statistical data.Using this method,we refined the measurement of the TP’s urbanization level in 2018 for multiple scales including the region,basin,prefecture and county levels,which provides basic information for the further urban sustainability research on the TP.展开更多
探究功能多样性如何影响商圈活力,可为城市用地功能结构优化调整和商圈功能改造提供理论支撑,进而促进城市混合功能有序开发、提升城市活力。已有关于功能多样性与活力的研究,大多集中在城市、街道活力等方面,对于商圈活力研究很少涉及...探究功能多样性如何影响商圈活力,可为城市用地功能结构优化调整和商圈功能改造提供理论支撑,进而促进城市混合功能有序开发、提升城市活力。已有关于功能多样性与活力的研究,大多集中在城市、街道活力等方面,对于商圈活力研究很少涉及,且大多利用单一的熵指数反映功能多样性。在利用夜光数据对活力的研究中,大多选取城市或更大区域尺度作为研究单元,无法精准地从多角度、多层面理解功能多样性与城市内部活力的关系。因此,本文以广州市主城区为例,以商圈作为基本研究单元,融合城市设施兴趣点(Point of Interest,POI)和珞珈一号夜间灯光数据,利用希尔数模型从多维视角测度商圈功能多样性特征,并以此来探究其与商圈活力的定量化关系。主要结论如下:①仅用熵指数来反映多样性是不足的,其与商圈活力在0.1的显著性水平下无相关性,需结合希尔数多样性指数从多视角度量商圈功能多样性,以弥补单一熵指数测度方法的不足;②广州商圈功能丰富度指数与其活力净相关系数为0.382,提高功能丰富度以增加商圈各功能间互补性、异质性或混合性,从而具备足够的功能多样性,促进各类功能间的协同与竞争,形成良好的兼容性混合,以更好的满足多数人的消费需求,激发商圈活力;③广州商圈规模效应与其活力净相关系数为0.507,对比大于集聚效应的0.371,表明广州商圈发展遵循新经济地理学的规模报酬递增规律,即商圈规模越大对于提升商圈活力的效用越大,而商圈功能集聚度对于提升商圈活力的效用相对较小。展开更多
基金Under the auspices of Natural Science Foundation of China(No.42071342,31870713)Beijing Natural Science Foundation Program(No.8182038)Fundamental Research Funds for the Central Universities(No.2015ZCQ-LX-01,2018ZY06)。
文摘With the continuous development of urbanization in China,the country’s growing population brings great challenges to urban development.By mastering the refined population spatial distribution in administrative units,the quantity and agglomeration of population distribution can be estimated and visualized.It will provide a basis for a more rational urban planning.This paper takes Beijing as the research area and uses a new Luojia1-01 nighttime light image with high resolution,land use type data,Points of Interest(POI)data,and other data to construct the population spatial index system,establishing the index weight based on the principal component analysis.The comprehensive weight value of population distribution in the study area was then used to calculate the street population distribution of Beijing in 2018.Then the population spatial distribution was visualize using GIS technology.After accuracy assessments by comparing the result with the WorldPop data,the accuracy has reached 0.74.The proposed method was validated as a qualified method to generate population spatial maps.By contrast of local areas,Luojia 1-01 data is more suitable for population distribution estimation than the NPP/VIIRS(Net Primary Productivity/Visible infrared Imaging Radiometer)nighttime light data.More geospatial big data and mathematical models can be combined to create more accurate population maps in the future.
基金the Second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0405)the National Natural Science Foundation of China(Grant No.41871185&41971270)。
文摘The Tibetan Plateau(TP)is undergoing rapid urbanization.To improve urban sustainability and construct eco-logical security barriers,it is essential to quantify the spatial patterns of urbanization level on the TP,but the existing studies on the topic have been limited by the lack of socioeconomic data.This study aims to quantify the urbanization level on the TP in 2018 with Luojia1-01(LJ1-01)high-resolution nighttime light(NTL)data.Specifically,the compounded night light index is used to quantify spatial patterns of urbanization level at mul-tiple scales.The results showed that the TP had a low overall urbanization level with a large internal difference.The urbanization level in the northeast,southeast and south of the TP was relatively high,forming three hotspots centered in Xining City,Lhasa City and Shangri-La City,while the urbanization level in the central and western regions was relatively low.The analysis of influencing factors,based on the random forest model,showed that transportation and topography were the main factors affecting the TP’s spatial patterns of urbanization level.The comparison analysis with socioeconomic statistics and traditional NTL data showed that LJ1-01 NTL data can be used to more effectively quantify the urbanization level since it is more advantageous for reflecting the spatial extent of urban land and describing the spatial structure of socioeconomic activities within urban areas.These advantages are attributed to the high spatial resolution of the data,appropriate imaging time and unaf-fected by saturation phenomena.Thus,the proposed LJ1-01 NTL-based urbanization level measurement method has the potential for wide applications around the world,especially in less-developed regions lacking statistical data.Using this method,we refined the measurement of the TP’s urbanization level in 2018 for multiple scales including the region,basin,prefecture and county levels,which provides basic information for the further urban sustainability research on the TP.
文摘探究功能多样性如何影响商圈活力,可为城市用地功能结构优化调整和商圈功能改造提供理论支撑,进而促进城市混合功能有序开发、提升城市活力。已有关于功能多样性与活力的研究,大多集中在城市、街道活力等方面,对于商圈活力研究很少涉及,且大多利用单一的熵指数反映功能多样性。在利用夜光数据对活力的研究中,大多选取城市或更大区域尺度作为研究单元,无法精准地从多角度、多层面理解功能多样性与城市内部活力的关系。因此,本文以广州市主城区为例,以商圈作为基本研究单元,融合城市设施兴趣点(Point of Interest,POI)和珞珈一号夜间灯光数据,利用希尔数模型从多维视角测度商圈功能多样性特征,并以此来探究其与商圈活力的定量化关系。主要结论如下:①仅用熵指数来反映多样性是不足的,其与商圈活力在0.1的显著性水平下无相关性,需结合希尔数多样性指数从多视角度量商圈功能多样性,以弥补单一熵指数测度方法的不足;②广州商圈功能丰富度指数与其活力净相关系数为0.382,提高功能丰富度以增加商圈各功能间互补性、异质性或混合性,从而具备足够的功能多样性,促进各类功能间的协同与竞争,形成良好的兼容性混合,以更好的满足多数人的消费需求,激发商圈活力;③广州商圈规模效应与其活力净相关系数为0.507,对比大于集聚效应的0.371,表明广州商圈发展遵循新经济地理学的规模报酬递增规律,即商圈规模越大对于提升商圈活力的效用越大,而商圈功能集聚度对于提升商圈活力的效用相对较小。
