Dynamic Development Characteristics and Driving Factors of High Quality Development Level in China’s Five Major Urban Agglomerations

High-quality development is the primary task of comprehensively building a socialist,modern country,as well as the primary task of building urban agglomerations in China.Based on the five development concepts,this paper used the entropy method to measure the High Quality Development Index(HQDI)of the five major urban agglomerations.The results showed that the HQDI of the five major urban agglomerations shows a fluctuating upward trend.First,using the Dagum Gini coefficient to explore the sources of HQDI development differences in urban agglomerations,we found that the main source of HQDI differences in urban agglomerations was inter-regional differences,while intra-regional differences were not important.Second,kernel density estimation was used to test the dynamic evolution trend of HQDI within urban agglomerations.There was a polarisation phenomenon in the HQDI of urban agglomerations,such as the Pearl River Delta urban agglomeration and the Chengdu-Chongqing urban agglomeration.But overall,the degree of imbalance had decreased.Third,using geographic detectors to examine the driving factors of HQDI in urban agglomerations,we found that the main driving forces for improving HQDI in urban agglomerations were economic growth,artificial intelligence technology and fiscal decentralisation.All the interaction factors had greater explanatory power for the spatial differentiation of HQDI,which can be divided into two types:two-factor improvement and non-linear improvement.This study is conducive to improving and enriching the theoretical system for evaluating the high quality development of urban agglomerations,and provides policy references for promoting the high quality development of urban agglomerations.

Analysis of Urban Agglomeration Network Structure Based on Baidu Migration Data: A Case Study of the Guangdong-Hong Kong-Macao Greater Bay Urban Agglomeration

The inter-city linkage heat data provided by Baidu Migration is employed as a characterization of inter-city linkages in order to facilitate the study of the network linkage characteristics and hierarchical structure of urban agglomeration in the Greater Bay Area through the use of social network analysis method.This is the inaugural application of big data based on location services in the study of urban agglomeration network structure,which represents a novel research perspective on this topic.The study reveals that the density of network linkages in the Greater Bay Area urban agglomeration has reached 100%,indicating a mature network-like spatial structure.This structure has given rise to three distinct communities:Shenzhen-Dongguan-Huizhou,Guangzhou-Foshan-Zhaoqing,and Zhuhai-Zhongshan-Jiangmen.Additionally,cities within the Greater Bay Area urban agglomeration play different roles,suggesting that varying development strategies may be necessary to achieve staggered development.The study demonstrates that large datasets represented by LBS can offer novel insights and methodologies for the examination of urban agglomeration network structures,contingent on the appropriate mining and processing of the data.

Spatially Heterogeneous Response of Carbon Storage to Land Use Changes in Pearl River Delta Urban Agglomeration, China

Carbon storage of terrestrial ecosystems plays a vital role in advancing carbon neutrality. Better understanding of how land use changes affect carbon storage in urban agglomeration will provide valuable guidance for policymakers in developing effective regional conservation policies. Taking the Pearl River Delta Urban Agglomeration(PRDUA) in China as an example, we examined the heterogeneous response of carbon storage to land use changes in 1990–2018 from a combined view of administrative units and physical entities. The results indicate that the primary change in land use was due to the expansion of construction land(5897.16 km2). The carbon storage in PRDUA decreased from 767.34 Tg C in 1990 to 725.42 Tg C in 2018 with a spatial pattern of high wings and the low middle. The carbon storage loss was largely attributed to construction land expansion(55.74%), followed by forest degradation(54.81%). Changes in carbon storage showed significant divergences in different sized cities and hierarchical boundaries. The coefficients of geographically weighted regression(GWR) reveal that the alteration in carbon storage in Guangzhou City was more responsive to changes in construction land(-0.11) compared to other cities, while that in Shenzhen was mainly affected by the dynamics of forest land(8.32). The change in carbon storage was primarily influenced by the conversion of farmland within urban extent(5.05) and the degradation of forest land in rural areas(5.82). Carbon storage changes were less sensitive to the expansion of construction land in the urban center, urban built-up area, and ex-urban built-up area, with the corresponding GWR coefficients of 0.19, 0.04, and 0.02. This study necessitates the differentiated protection strategies of carbon storage in urban agglomerations.

Multi-scenario Simulation for 2060 and Driving Factors of the Eco-spatial Carbon Sink in the Beibu Gulf Urban Agglomeration, China

Since China announced its goal of becoming carbon-neutral by 2060, carbon neutrality has become a major target in the development of China's urban agglomerations. This study applied the Future Land Use Simulation(FLUS) model to predict the land use pattern of the ecological space of the Beibu Gulf urban agglomeration, in 2060 under ecological priority, agricultural priority and urbanized priority scenarios. The Integrated Valuation of Ecosystem Services and Trade-offs(In VEST) model was employed to analyse the spatial changes in ecological space carbon storage in each scenario from 2020 to 2060. Then, this study used a Geographically Weighted Regression(GWR) model to determine the main driving factors that influence the changes in land carbon sinking capacity. The results of the study can be summarised as follows: firstly, the agricultural and ecological priority scenarios will achieve balanced urban expansion and environmental protection of resources in an ecological space. The urbanized priority scenario will reduce the carbon sinking capacity. Among the simulation scenarios for 2060, carbon storage in the urbanized priority scenario will decrease by 112.26 × 10^(6) t compared with that for 2020 and the average carbon density will decrease by 0.96 kg/m^(2) compared with that for 2020. Carbon storage in the agricultural priority scenario will increase by 84.11 × 10^(6) t, and the average carbon density will decrease by 0.72 kg/m^(2). Carbon storage in the ecological priority scenario will increase by 3.03 × 10^(6) t, and the average carbon density will increase by 0.03 kg/m^(2). Under the premise that the population of the town will increases continuously, the ecological priority development approach may be a wise choice.Secondly, slope, distance to river and elevation are the most important factors that influence the carbon sink pattern of the ecological space in the Beibu Gulf urban agglomeration, followed by GDP, population density, slope direction and distance to traffic infrastructure.At the same time, urban space expansion is the main cause of the changes of this natural factors. Thirdly, the decreasing trend of ecological space is difficult to reverse, so reasonable land use policy to curb the spatial expansion of cities need to be made.

Urban Agglomerations in China: Characteristics and Influencing Factors of Population Agglomeration

Urban agglomeration(UA)is an advanced spatial economic form formed and developed in the process of rapid industrialization and urbanization,and an important carrier of urbanization and economic development.The economy has developed rapidly in the recent decades of China,and the UAs have also developed rapidly.However,as a large population country,the population distribution and changes of UAs in China has unique characteristics.Using the fifth,sixth and seventh population census data,spatial auto-correlation and spatial econometric models,we analyzed the spatial-temporal evolution characteristics and influencing factors of population agglomeration in China’s UAs.Results revealed that:1)from 2000 to 2020,the population gradually converged into UAs,and the characteristics of population agglomeration in different development degree of UAs differ.The higher the development degree of UA,the higher the population agglomeration degree.Besides,UAs are the main area with the most significant population agglomeration degree,and the spatial autocorrelation show that the cities with similar degree tend to be concentrated in space.The urban population gathering in UAs has a certain positive spillover effect on population size of neighboring cities.2)Economic development and social conditions factors are important factors affecting population agglomeration degree in UAs.The main factors of population gather into UAs are similar with the outside UAs,but the positive promotion of urbanization rate and proportion of tertiary industry in GDP on population agglomeration of UAs in China are enhancing from 2000 to 2020.Meanwhile,the other factors,such as high-quality public services,good urban living environment conditions,high-quality medical and educational resources,are also important factors to promote urban population gather into UAs.This study provides a basis for formulating the development planning of UAs in China,and enriches the relevant theoretical research of population evolution and influencing factors of UAs.

Spatial Distribution and Influencing Factors of Urban Shrinkage from the Perspective of Factor Flow - A Case Study of National Urban Agglomerations

This paper examines national urban agglomerations by taking factor flows as the focal point as the research subject.By dividing the stages of urban agglomeration development,a comprehensive framework of urban shrinkage is constructed,encompassing economic,population,and social shrinkage.The study explores the spatial distribution characteristics of urban shrinkage during different stages of urban agglomeration and investigates the influencing factors using a geographic detector model.The findings reveal that urban shrinkage within urban agglomerations is widely spread,predominantly in peripheral areas.During the diffusion stage,urban shrinkage is scattered,with population shrinkage concentrated in peripheral regions,economic shrinkage concentrated on old industrial cities,and social shrinkage concentrated on the northeast.The outcomes of the geographic detector model indicate that traffic flow,capital flow,information flow,node importance,network connectivity,government investment,openness,and environmental regulations all play significant roles in shaping the spatial distribution of urban shrinkage.

The Effect of Urban Agglomeration Expansion on PM_(2.5) Concentrations: Evidence from a Quasi-natural Experiment

This study constructs a quasi-natural experiment based on the expansion of the Yangtze River Delta urban agglomeration(YRDUA) of China in 2010 to investigate the impact and inner mechanism of urban agglomeration expansion on fine particulate matter(PM_(2.5)) concentrations through propensity scores in difference-in-differences models(PSM-DID) using panel data from 286 prefecturelevel cities in China from 2003 to 2016. The results show that 1) urban agglomeration expansion contributes to an overall decrease in PM_(2.5)concentration, which is mainly achieved from the original cities. For the new cities, on the other hand, the expansion significantly increases the local PM_(2.5)concentration. 2) In the long term, the significant influence of urban agglomeration expansion on PM_(2.5)concentration lasts for three years and gradually decreases. A series of robustness tests confirm the applicability of the PSM-DID model.3) Cities with weaker government regulation, a better educated population and higher per capita income present stronger PM_(2.5)reduction effects. 4) Urban agglomeration expansion affects the PM_(2.5)concentration mainly through industrial transfer and population migration, which cause a decrease in the PM_(2.5)concentration in the original cities and an increase in the PM_(2.5)concentration in the new cities.Corresponding policy suggestions are proposed based on the conclusions.

Spatio-temporal Evolution of Urban Expansion Based on a Novel Adjusted Index and GEE: A Case Study of Central Plains Urban Agglomeration, China

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.

Surface Regional Heat(Cool) Island Effect and Its Diurnal Differences in Arid and Semiarid Resource-based Urban Agglomerations

With the rapid development of urban agglomerations in northwest arid and semiarid regions of China, the scope of the urban heat island(UHI) effect has gradually expanded and gradually connected, and has formed a regional heat island(RHI) with a larger range of impact to the regional environment. However, there are few studies on the heat island effect of urban agglomerations in arid and semiarid regions, so this paper selects the urban agglomeration of Hohhot, Baotou and Ordos(HBO) of Inner Mongolia, China as the study area. Based on the 8-day composite Moderate-resolution Imaging Spectroradiometer(MODIS) surface temperature data(156scenes in all) and land use maps for 2005, 2010, and 2015, we analyze the spatiotemporal distributions of regional heat(cool) islands(RH(C)I) and the responses of surface temperatures to land-use changes in the diurnal and interannual surface cities. The results showed that: 1) from 2005 to 2015, urban areas showed the cold island effect during the day, with the area of the cold island showing a shrinking feature;at night, they showed the heat island effect, with the area of the heat island showing a first decrease and then an increase.2) From 2005 to 2015, the land development(unutilized land to building land) brings the greatest temperature increase(ΔT = 1.36°C)during the day, while the greatest temperature change at night corresponds to the conversion of cultivated land to building land(ΔT =0.78°C) exhibited the largest changes at night. From 2010 to 2015, the land development(grassland to building land) bring the greatest temperature increase(ΔT = 0.85°C) during the day, while the great temperature change at night corresponds to the conversion of water areas to building land(ΔT = 1.38°C) exhibited the largest changes at night. Exploring the spatial and temporal evolution of surface urban heat(cool) islands in urban agglomerations in arid and semiarid regions will help to understand the urbanization characteristics of urban agglomerations and provide a reference for the formulation of policies for the coordinated and healthy development of the region and co-governance of regional environmental problems.

NDVI characteristics and precipitation sensitivity of urban agglomeration in Central Shanxi Basin

The overall NDVI characteristics and precipitation sensitivity in the study area from 2000 to 2018 were investigated using NDVI images of urban agglomeration in central Shanxi basin in 2000,2005,2010,and 2018 as well as the climate data of China’s surface cumulative annual value data set(1981-2010)in accordance with the method such as the geographically weighted regression model.As can be seen from the results,first,the overall NDVI pattern of urban agglomeration in central Shanxi basin,China has been changed and distributed along the topography in the shape of strip.Second,the spatial evolution of NDVI in the study area is varied significantly with the trend of expansion as a whole and a shrinking trend in some areas.Third,the overall precipitation in the study area presents a declining trend from the west to the east,while the NDVI precipitation sensitivity shows a decreasing trend from west to east.To be specific,the west and the east have a positive value of 1.3129 with strong sensitivity and a negative value of-1.0908 with weak sensitivity,respectively.The study results are expected to provide a scientific basis for restoring vegetation and formulating disaster prevention policies for urban agglomeration in Central Shanxi Basin.

Spatial Pattern Evolution and Casual Analysis of County Level Economy in Changsha-Zhuzhou-Xiangtan Urban Agglomeration, China

In order to evaluate whether or not the county units′ economy in the Changsha-Zhuzhou-Xiangtan(Chang-Zhu-Tan) Urban Agglomeration was growing as expected, this study analyzed the spatial economy pattern at county-level by using the Exploratory Spatial Data Analysis(ESDA) method. In this process, the global Moran′s I and local Getis-Ord G*i indexes were employed to analyze indicators including per capita GDP and three industrials(i.e. primary, secondary and tertiary industry) from 2000 to 2010. The results show that: 1) the county units′ economy in the Chang-Zhu-Tan Urban Agglomeration has exhibited a strong spatial autocorrelation and an accelerated integration trend since 2008(Moran′ s I increased from 0.26 to 0.56); 2) there is a significant difference in economy development between the northern and southern county units in the Chang-Zhu-Tan Urban Agglomeration: the hotspot zone with high economic level was formed among the northern county units whereas the coldspot zone with low economic level was located in the southern areas. This difference was caused primarily by the increasingly prominent economic radiation effect of Changsha ′upheaval′; 3) town density, secondary industry, and the integration policy are the major contributors driving the evolution of the spatial economy pattern in the Chang-Zhu-Tan Urban Agglomeration.

Exploring Smart Growth Boundaries of Urban Agglomeration with Land Use Spatial Optimization:A Case Study of Changsha-Zhuzhou-Xiangtan City Group,China

Urban agglomeration is the main spatial organization mode used by the Chinese government to promote the policy of new urbanization strategy.Hence,a better understanding of the urban growth boundary(UGB)has profound theoretical and practical significance regarding sustainable urban development.This study devised a raster-based land use spatial optimization(LUSO)framework,and utilized ant colony optimization(ACO)algorithm to delimit the smart growth boundaries of the Changsha-Zhuzhou-Xiangtan city group(CZTCG)in China.The aim of this study is to design a LUSO model to explore an optimal pattern of urban agglomeration for sustainable growth.Multi growth scenario including a single development center,multipolar development and balanced development patterns are generated by the LUSO model for the year of 2050,and the optimum spatial pattern is chosen based on objectives comparison and the present stage of economic and social development in CZTCG.The main results are listed as the following.1)It is feasible to identify the growth boundaries of the urban agglomeration using the land use spatial optimization model,and the optimal form of the spatial pattern can be defined.2)With the growth trend of the urban agglomeration gradually spreads from a single center to multi-centers and even small towns,the total optimization target performance gradually increases,which means that the traditional pie-shaped development does not meet the maximum comprehensive benefit of the city group.3)Subject to the regional social and economic development stage,absolute fair development or simply developing the central city is not conducive to promoting the coordinated development of the urban agglomeration.Gradient equalization and gradual advancement are the best choice for UGB delineation of urban agglomeration.The findings of this study would be useful to identify the UGB in CZTCG for more sustainable urban development in the future.

The Land Management Pattern in " Green Heart" Area——A Case Study of Changsha-Zhuzhou-Xiangtan Urban Agglomeration

By analyzing the status quo of land resources in " green heart" area of Changsha-Zhuzhou-Xiangtan urban agglomeration,and problems existing in land management,this article puts forward some countermeasures and proposals as follows:establish new land management mechanism in " green heart" area;based on land planning," green heart" overall planning and policies and regulations,manage land and promote the protection of urban ecological environment.

Study on Spatial Structure of Rural Tourism in Wuhan Urban Agglomerations

Spatial structure of rural tourism in the urban agglomerations of Wuhan was analyzed by comprehensively studying relevant documents about rural tourism,and reviewing previous researches on the concept and spatial structure of rural tourism.Through investigating rural tourist resources in the study area,resource advantages and characteristics of 9 cities were introduced,and the Gini Coefficient was taken to quantitatively analyze spatial patterns of its rural tourist villages,the obviously imbalanced concentration of these villages was pointed out.By measuring connectivity and accessibility of regional spaces in the study area,its traffic connectivity was proved moderate,and accessibility of each tourist village and town was fine.Then an optimized spatial structure was proposed for the rural tourism development in Wuhan Urban Agglomerations,that is,"one core,one belt and three districts".

Spatiotemporal Variations and Regional Transport of Air Pollutants in Two Urban Agglomerations in Northeast China Plain

Characteristics of air pollution in Northeast China(NEC) received less research attention in the past comparing to other heavily polluted regions in China.Spatiotemporal variations of six criteria air pollutants(PM10, PM2.5, SO2, NO2, O3 and CO) in Central Liaoning Urban Agglomeration(CLUA) and Harbin-Changchun Urban Agglomeration(HCUA) in NEC Plain were analyzed in this study based on three-year hourly observations of air pollutants and meteorological variables from 2015 to 2017.The results indicated that the annual mean concentrations of air pollutants are generally higher in the middle and southern regions in NEC Plain and lower in the northern region.Megacities such as Shenyang, Harbin and Changchun experience severe air pollution, with a three-year averaged air quality index(AQI) larger than 80, far exceeding the daily AQI standard at the first-level of 50 in China.The annual mean PM and SO2 concentrations decrease most significantly in NEC urban agglomerations from 2015 to 2017, followed by CO and NO2, while O3 shows a slight increasing trend.All the six pollutants exhibit obvious seasonal and diurnal variations, and these variations are dictated by local emission and meteorological conditions.PM2.5 and O3 concentrations in NEC urban agglomerations strongly depend on wind conditions.High O3 concentrations at different cities usually occur in presence of strong winds but are independent on wind direction(WD), while high PM2.5 is usually accompanied by weak winds and poor dispersion condition, and sometimes also occur when the northerly or southerly winds are strong.Regional transport of air pollutants between NEC urban agglomerations is common.A severe haze event on November 1–4, 2017 is examined to demonstrate the role of regional transport on pollution.

Impact of Anthropogenic Heat Release on Regional Climate in Three Vast Urban Agglomerations in China

We simulated the impact of anthropogenic heat release （AHR） on the regional climate in three vast city agglomerations in China using the Weather Research and Forecasting model with nested high-resolution modeling.Based on energy consumption and high-quality land use data,we designed two scenarios to represent no-AHR and current-AHR conditions.By comparing the results of the two numerical experiments,changes of surface air temperature and precipitation due to AHR were quantified and analyzed.We concluded that AHR increases the temperature in these urbanized areas by about 0.5℃-1℃,and this increase is more pronounced in winter than in other seasons.The inclusion of AHR enhances the convergence of water vapor over urbanized areas.Together with the warming of the lower troposphere and the enhancement of ascending motions caused by AHR,the average convective available potential energy in urbanized areas is increased.Rainfall amounts in summer over urbanized areas are likely to increase and regional precipitation patterns to be altered to some extent.

Reductions of PM_(2.5) in Beijing-Tianjin-Hebei Urban Agglomerations during the 2008 Olympic Games

The Atmospheric Environmental Monitoring Network successfully undertook the task of monitoring the atmospheric quality of Beijing and its surrounding area during the 2008 Olympics. The results of this monitoring show that high concentrations of PM2.5 pollution exhibited a regional pattern during the monitoring period （1 June-30 October 2008）. The PM2.5 mass concentrations were 53 μg m-3, 66 p.g m-3, and 82 μg m-3 at the background site, in Beijing, and in the Beijing-Tianjin-Hebei urban agglomerations, respectively. The PM2.5 levels were lowest during the 2008 Olympic Games （8-24 August）： 35μg m-3 at the background site, 42 μg m-3 in Beijing and 57 μg m-3 in the region. These levels represent decreases of 49%, 48% and 56%, respectively, compared to the prophase mean concentration before the Olympic Games. Emission control measures contributed 62% 82% of the declines observed in Beijing, and meteorological conditions represented 18%-38%. The concentration of fine particles met the goals set for a ＂Green Olympics.＂

Optimization Transmission Theory and Technical Pathways that Describe Multiscale Urban Agglomeration Spaces

Urban agglomerations are spatial entities that promote the development of ‘new urbanization' processes within China. In this context, the concept of ‘multiscale urban agglomeration spaces' encompasses three linked levels: macroscale urban agglomerations, mesoscale cities, and microscale urban centers. Applying a series of multidisciplinary integrated research methods drawn from geography, urban planning, and architecture, this paper reveals two intensive utilization laws that can be generalized to apply to multiscale urban agglomeration spaces, top-to-bottom ‘positive transmission' linkage and inside-to-outside ‘negative transmission' movement. This paper also proposes optimization transmission theory and policy decision technical pathways that can be applied to these three urban agglomeration spatial scales. Specific technical pathways of transmission include intensive expansion and simulated decision-making in macroscale urban agglomerations, ecology, production, and living space intensive layout and dynamic decision-making in mesoscale cities, and four cores(i.e., ‘single, ring, axis, and pole core') progressive linkage and intensive optimization decision-making in microscale urban centers. The theory and technical pathways proposed in this paper solve the technical problem of optimization and provide intensive methods that can be applied not only at the individual level but also at multiple scales in urban agglomeration spaces. This study also advances a series of comprehensive technical solutions that can be applied to both compact and smart growth cities as well as to urban agglomerations. Solid theoretical support is provided for the optimization of Chinese land development, urbanization, agricultural development, and ecological security.

Environmental influence of Wuhan urban agglomeration development and strategies of environmental protection

In Wuhan urban agglomeration （WUA）, the population growth and concentration, the industrial development and urban sprawl have been affecting the environment ftmdamentally. Comparing with Yangtze delta metropolitan region, the level of urbanization and industrialization of WUA has lagged behind for about 10 years; but the problems in environmental protection and rehabilitation are commonly serious. In the future, WUA should avoid unnecessary mistakes and seek a win-win strategy for economy and environment in its large-scale development stage. Based on the analysis of the changing of main environmental pollutants and the coupled curves in past decades, the paper discussed the important links among the urban environmental pollutions, industry growth and urban sprawl in WUA. It is concluded that the integration of economic and environmental policies in urban development is more required and significant at the large urban agglomeration region. Four proactive and long-term strategies need to be adopted to provide prior guidance and better protection for the development of WUA.

Using ecosystem service supply and ecosystem sensitivity to identify landscape ecology security patterns in the Lanzhou-Xining urban agglomeration, China

The construction of an ecological security pattern(ESP)is an important way to ensure regional ecological security and to achieve sustainable regional development.It is also one of the hotspot topics of landscape ecology research.This paper identifies the ecological source through the evaluation of the ecosystem service and ecosystem sensitivity of the Lanzhou-Xining(Lan-Xi)urban agglomeration.The minimum cumulative resistance(MCR)model modified by night light data NPP/VIIRS(National Polar-orbiting Operational Environmental Satellite System Preparatory Project/Visible Infrared Imaging Radiometer Suite)was used to measure the relative resistance of the materials and energy circulation between the source areas,and to establish the resistance surface of the ecological source area expansion.Then ecological corridors were identified based on ecological sources and resistance surface.The ecological strategic node is the ecological fragile point in the ecological corridors.The ecological strategic node is identified with hydrological module by superimposing the"ridge line"of cumulative ecological resistance with the ecological corridor.Combined with ecological sources,corridors and strategic nodes,the ESP of the Lan-Xi urban agglomeration can be constructed.The ecological source of the Lan-Xi urban agglomeration accounts for 28.42%of the total area,most of which is distributed within Qinghai Province.The nature reserves in the area are all located within the ecological source area.A total of 41 potential ecological corridors have been identified in the study area.The total length of the potential corridors is 1201.03 km,comprising 23 source corridors and 18 radiation corridors.There are 30 strategic nodes identified in the Lan-Xi urban agglomeration.These locations are the most vulnerable areas of the ecological corridors.Ecological engineering should be applied in the construction of corridors.Affected by the ecological source,the potential ecological corridor extends from the northwest to the southeast,which is basically consistent with the direction trend of the mountains in the region.