Wuhan Urban Agglomeration Research Articles

Mapping seasonal impervious surface dynamics in Wuhan urban agglomeration, China from 2000 to 2016

Numerous methods have been successfully applied to estimate the regional impervious surface dynamics based on spectral or spatial information from remote sensing imagery. However, previous methods mainly focused on mapping impervious surfaces at annual or decadal time scales. Few studies have attempted to map impervious surface dynamics at finer time scales, such as on a seasonal time scale using temporal information. This study aims to map regional impervious surface dynamics on a seasonal time scale by using time series Landsat data. The semi-supervised support vector machine (SVM) algorithm was employed for classifying impervious surfaces based on temporal characteristics, which were derived from seasonal time series biophysical composition index (BCI) and seasonal time series modified normalized difference impervious surface index (NDISI). The proposed method was validated over the Wuhan urban agglomeration (WUA) in China from 2000 to 2016. The results showed that impervious surfaces in the Wuhan urban agglomeration increased from 903.24 km2 in 2000 to 3989.49 km2 in 2016, with an annual growth rate of 20.10%. Additionally, the proposed method yielded reasonable average overall classification accuracy (up to 88%). Our results demonstrated that the proposed method could accurately map seasonal impervious surface dynamics based on temporal characteristics. This study could enable the monitoring of time-intensive impervious surfaces at a regional scale using remote sensing data.

Modeling Urban Collaborative Growth Dynamics Using a Multiscale Simulation Model for the Wuhan Urban Agglomeration Area, China

Urban agglomeration has become the predominant form of urbanization in China. In this process, spatial interaction evidently played a significant role in promoting the collaborative development of these correlated cities. The traditional urban model’s focus on individual cities should be transformed to an urban system model. In this study, a multi-scale simulation model has been proposed to simulate the agglomeration development process of the Wuhan urban agglomeration area by embedding the multi-scale spatial interaction into the transition rule system of cellular automata (CA). A system dynamic model was used to predict the demand for new urban land at an aggregated urban agglomeration area scale. A data field approach was adopted to measuring the interaction of intercity at city scale. Neighborhood interaction was interpreted with a logistic regression method at the land parcel scale. Land use data from 1995, 2005, and 2015 were used to calibrate and evaluate the model. The simulation results show that there has been continuing urban growth in the Wuhan urban agglomeration area from 1995 to 2020. Although extension-sprawl was the predominant pattern of urban spatial expansion, the trend of extensive growth to intensive growth is clear during the entire period. The spatial interaction among these cities has been reinforced, which guided the collaborative development and formed the regional urban system network.

REAL-TIME AND SEAMLESS MONITORING OF GROUND-LEVEL PM2.5 USING SATELLITE REMOTE SENSING

Abstract. Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM2.5. However, the satellite-based monitoring of ground-level PM2.5 is still challenging. First, the previously used polar-orbiting satellite observations, which can be usually acquired only once per day, are hard to monitor PM2.5 in real time. Second, many data gaps exist in satellitederived PM2.5 due to the cloud contamination. In this paper, the hourly geostationary satellite (i.e., Harawari-8) observations were adopted for the real-time monitoring of PM2.5 in a deep learning architecture. On this basis, the satellite-derived PM2.5 in conjunction with ground PM2.5 measurements are incorporated into a spatio-temporal fusion model to fill the data gaps. Using Wuhan Urban Agglomeration as an example, we have successfully derived the real-time and seamless PM2.5 distributions. The results demonstrate that Harawari-8 satellite-based deep learning model achieves a satisfactory performance (out-of-sample cross-validation R2 = 0.80, RMSE = 17.49 μg/m3) for the estimation of PM2.5. The missing data in satellite-derive PM2.5 are accurately recovered, with R2 between recoveries and ground measurements of 0.75. Overall, this study has inherently provided an effective strategy for the realtime and seamless monitoring of ground-level PM2.5.

Simulating Urban Cooperative Expansion in a Single-Core Metropolitan Region Based on Improved CA Model Integrated Information Flow: Case Study of Wuhan Urban Agglomeration in China

AbstractWith the expansion of regional urbanization, urban agglomeration has become the most striking area of China’s urbanization process. Simulation of the urban growth of metropolitan regions is...

Patterns of CO2 emissions in 18 central Chinese cities from 2000 to 2014

With the Rise of Central China Plan, the central region has had a great opportunity to develop its economy and improve its original industrial structure. However, this region is also under pressure to protect its environment, keep its development sustainable and reduce carbon emissions. Therefore, accurately estimating the temporal and spatial dynamics of CO2 emissions and analysing the factors influencing these emissions are especially important. This paper estimates the CO2 emissions derived from the fossil fuel combustion and industrial processes of 18 central cities in China between 2000 and 2014. The results indicate that these 18 cities, which contain an average of 6.57% of the population and 7.91% of the GDP, contribute 13% of China's total CO2 emissions. The highest cumulative CO2 emissions from 2000 to 2014 were from Taiyuan and Wuhan, with values of 2268.57 and 1847.59 million tons, accounting for 19.21% and 15.64% of the total among these cities, respectively. Therefore, the CO2 emissions in the Taiyuan urban agglomeration and Wuhan urban agglomeration represented 28.53% and 20.14% of the total CO2 emissions from the 18 cities, respectively. The three cities in the Zhongyuan urban agglomeration also accounted for a second highest proportion of emissions at 23.51%. With the proposal and implementation of the Rise of Central China Plan in 2004, the annual average growth rate of total CO2 emissions gradually decreased and was lower in the periods from 2005 to 2010 (5.44%) and 2010 to 2014 (5.61%) compared with the rate prior to 2005 (12.23%). When the 47 socioeconomic sectors were classified into 12 categories, “power generation” contributed the most to the total cumulative CO2 emissions at 36.51%, followed by the “non-metal and metal industry”, “petroleum and chemical industry”, and “mining” sectors, representing emissions proportions of 29.81%, 14.79%, and 9.62%, respectively. Coal remains the primary fuel in central China, accounting for an average of 80.59% of the total CO2 emissions. Industrial processes also played a critical role in determining the CO2 emissions, with an average value of 7.3%. The average CO2 emissions per capita across the 18 cities increased from 6.14 metric tons in 2000 to 15.87 metric tons in 2014, corresponding to a 158.69% expansion. However, the average CO2 emission intensity decreased from 0.8 metric tons/1000 Yuan in 2000 to 0.52 metric tons/1000 Yuan in 2014 with some fluctuations. The changes in and industry contributions of carbon emissions were city specific, and the effects of population and economic development on CO2 emissions varied. Therefore, long-term climate change mitigation strategies should be adjusted for each city.

Study on the Layout of Intercity Rail Transit Network Based on Traffic Location

The concept of a high-speed passenger traffic location line is proposed by analyzing intercity rail traffic location and network evolution characteristics to improve the effectiveness of intercity rail transit network layout planning. Then, a multilevel intercity rail transit network planning and optimization model is constructed. The model is divided into two levels, namely, the backbone network and the preliminary network. The backbone network optimization model is the minimum spanning tree model, which uses the reciprocal of economical relation intensity as its weight. The preliminary network model is a multi-objective function, which maximizes economical relation intensity and connectivity and minimizes the total length of rail transit lines. The optimization model provides a new method for intercity rail transit network planning. Finally, the rationality and effectiveness of the network layout are verified using the line network within the Wuhan urban agglomeration area as an example.

Spectral-spatial multi-feature classification of remote sensing big data based on a random forest classifier for land cover mapping

Supplementary information, such as multi-temporal spectral data and textural features, has the potential to improve land cover classification accuracy. However, given the larger volumes of remote sensing data, it is difficult to utilize all the features of remote sensing big data having different times and spatial resolutions. Inefficiency is also a large problem when dealing with large area land cover mapping. In this study, a new mode of incorporating spatial and temporal dependencies in a complex region employing the random forests (RFs) classifier was utilized. To map land covers, spring and autumn spectral images and their spectral indexes, textural features obtained from Landsat 5 were selected, and an importance measure variable was used to reduce the data’s dimension. In addition to randomly selecting the variable, we used random sampling to furthest decrease the generalization error in RF. The results showed that utilizing random sampling, multi-temporal spectral image and texture features, the classification of the Wuhan urban agglomeration, China, using RF performed well. The RF algorithm yielded an overall accuracy of 89.2% and a Kappa statistic of 0.8522, indicating high model performance. In addition, the variable importance measures demonstrated that the type of textural features was extremely important for intra-class separability. The RF model has transitivity. The algorithm can be extended by choosing a set of appropriate features for signature extension over large areas or in time-series of Landsat imagery. Land cover mapping might be more economical and efficient if no-cost imagery is used.

A Map Spectrum-Based Spatiotemporal Clustering Method for GDP Variation Pattern Analysis Using Nighttime Light Images of the Wuhan Urban Agglomeration

Estimates of gross domestic product (GDP) play a significant role in evaluating the economic performance of a country or region. Understanding the spatiotemporal process of GDP growth is important for estimating or monitoring the economic state of a region. Various GDP studies have been reported, and several studies have focused on spatiotemporal GDP variations. This study presents a map spectrum-based clustering approach to analyze the spatiotemporal variation patterns of GDP growth. First, a sequence of nighttime light images (from the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS)) is used to support the spatial distribution of statistical GDP data. Subsequently, the time spectrum of each spatial unit is generated using a time series of dasymetric GDP maps, and then the spatial units with similar time spectra are clustered into one class. Each category has a similar spatiotemporal GDP variation pattern. Finally, the proposed approach is applied to analyze the spatiotemporal patterns of GDP growth in the Wuhan urban agglomeration. The experimental results illustrated regional discrepancies of GDP growth existed in the study area.

Measuring urban spatial interaction in Wuhan Urban Agglomeration, Central China: A spatially explicit approach

In the context of globalization and integration, urban agglomeration gradually becomes the basic unit of regional competitions. In addition to urban agglomeration system, spatial interaction has become a popular topic and a key element for sustainable urban development. This paper investigates the typical agglomeration area in Central China-Wuhan Urban Agglomeration (WUA) and uses a spatially explicit approach based on the data field to analyze urban spatial interaction inside the region. Four years of cross-section data are used as case studies to analyze the spatial structure of urban interactions and the dynamic interaction variations. The results indicate that the spatial patterns of “one nucleus and multitude weak” and “the east is stronger than the west” exist in the study area. Spatial interactions among non-core cities were small during the study period. Due to the “Rise of Central China” strategy and integrated construction in the WUA, spatial interactions have increased since 2006. Notably, spatial interactions have become more integrated, and the narrow trend of interaction differences has been represented. Regional spatial interaction gradually develops in a positive direction and leads the urban development into a sustainable way.

Spatio-Temporal Change of Lake Water Extent in Wuhan Urban Agglomeration Based on Landsat Images from 1987 to 2015

Urban lakes play an important role in urban development and environmental protection for the Wuhan urban agglomeration. Under the impacts of urbanization and climate change, understanding urban lake-water extent dynamics is significant. However, few studies on the lake-water extent changes for the Wuhan urban agglomeration exist. This research employed 1375 seasonally continuous Landsat TM/ETM+/OLI data scenes to evaluate the lake-water extent changes from 1987 to 2015. The random forest model was used to extract water bodies based on eleven feature variables, including six remote-sensing spectral bands and five spectral indices. An accuracy assessment yielded a mean classification accuracy of 93.11%, with a standard deviation of 2.26%. The calculated results revealed the following: (1) The average maximum lake-water area of the Wuhan urban agglomeration was 2262.17 km2 from 1987 to 2002, and it decreased to 2020.78 km2 from 2005 to 2015, with a loss of 241.39 km2 (10.67%). (2) The lake-water areas of loss of Wuhan, Huanggang, Xianning, and Xiaogan cities, were 114.83 km2, 44.40 km2, 45.39 km2, and 31.18 km2, respectively, with percentages of loss of 14.30%, 11.83%, 13.16%, and 23.05%, respectively. (3) The lake-water areas in the Wuhan urban agglomeration were 226.29 km2, 322.71 km2, 460.35 km2, 400.79 km2, 535.51 km2, and 635.42 km2 under water inundation frequencies of 5%–10%, 10%–20%, 20%–40%, 40%–60%, 60%–80%, and 80%–100%, respectively. The Wuhan urban agglomeration was approved as the pilot area for national comprehensive reform, for promoting resource-saving and environmentally friendly developments. This study could be used as guidance for lake protection and water resource management.

Spatial-Temporal Features of Wuhan Urban Agglomeration Regional Development Pattern—Based on DMSP/OLS Night Light Data

Based on the night light data, urban area data, and economic data of Wuhan Urban Agglomeration from 2009 to 2015, we use spatial correlation dimension, spatial self-correlation analysis and weighted standard deviation ellipse to identify the general characteristics and dynamic evolution characteristics of urban spatial pattern and economic disparity pattern. The research results prove that: between 2009 and 2013, Wuhan Urban Agglomeration expanded gradually from northwest to southeast and presented the dynamic evolution features of “along the river and the road”. The spatial structure is obvious, forming the pattern of “core-periphery”. The development of Wuhan Urban Agglomeration has obvious imbalance in economic geography space, presenting the development tendency of “One prominent, stronger in the west and weaker in the east”. The contract within Wuhan Urban Agglomeration is gradually decreased. Wuhan city and its surrounding areas have stronger economic growth strength as well as the cities along The Yangtze River. However, the relative development rate of Wuhan city area is still far higher than other cities and counties.

Study on Spatial Structure Dynamic Evolution of Tourism Economic Zone along Wuhan-Guangzhou HSR

Wuhan-Guangzhou HSR is a passenger line, communication with Wuhan Urban Agglomeration, Changsha-Zhuzhou-Xiangtan Urban Agglomeration and the Pearl River Delta Urban Agglomeration. Wuhan-Guangzhou HSR achieves a bus-based operation, shortens the distance between cities, conducive to economic development, regional tourism. Applying Point Axis theory and Spatial Structure theory, this paper analyzes and contrasts regional economy and society, analyzing the dynamic change of regional tourism economy along Wuhan-Guangzhou HSR with its operation for the past five years, revealing high-speed transportation on the impact of regional tourism space, proposes that Tourism Economic Zone along Wuhan-Guangzhou HSR is divided into core tourism economic zone, compact tourism economic zone and radiant tourism economic zone, and makes recommendations, promoting regional tourism economy healthy and rapid development.

Analyzing the Effects of Spatial Interaction among City Clusters on Urban Growth—Case of Wuhan Urban Agglomeration

For the past two decades, China’s urbanization has attracted increasing attention from scholars around the world. Numerous insightful studies have attempted to determine the socioeconomic causes of the rapid urban growth in Chinese cities. However, most of these studies regarded each city as a single entity, with few considering inter-city relationships. The present study uses a gravity-based model to measure the spatial interaction among city clusters in the Wuhan urban agglomeration (WUA), which is one of China’s most rapidly urbanizing regions. The effects of spatial interaction on urban growth area were also analyzed. Empirical results indicate that, similar to urban population or employment in secondary and tertiary industries in the WUA from 2000 to 2005, the spatial interaction among city clusters is one of the main drivers of urban growth. In fact, this study finds the effects of spatial interaction as the only socioeconomic factor that affected the spatial expansion from 2005 to 2010. This finding suggests that population migration and information and commodity flows showed greater influence than the socioeconomic drivers of each city did on promoting urbanization in the WUA during this period. We thus argue that spatial interaction among city clusters should be a consideration in future regional planning.

Urbanization and administrative restructuring: A case study on the Wuhan urban agglomeration

Urbanization in China has been closely associated with urban sprawl, rural migration and the role of government has been more direct and powerful in setting it in motion. In 2014, the New Urbanization Planning in China has been released in which the development of urban agglomeration and small-medium cities has been highlighted. In this context, we decompose urbanization into population-oriented and land-centered archetypes and devise spatial models in multiple strategies embedded with different spatial relations to unfold the underlying driving forces using Wuhan agglomeration as the case. In addition to the identification of major driving forces which are gross domestic product (GDP), income, fixed asset investment and the transportation construction, the major contributions of our study lie in the gauge on administrative influence, to be more specific, the status of urban district, city-level county and county, through incorporating different spatial weight matrix in different scenarios in spatial modeling. It found out that 1) both non-agricultural population and urban land exhibit significant spatial autocorrelation and the superiority in the city center is evident; 2) socio-economic development and transportation construction significantly influence urbanization whereas the personal income and fixed asset investment accounting for a large proportion being the most powerful factors; 3) different administrative status at the county level is an unneglectable factor and urban area has higher probability to expand when urban district is adjacent to county-level city; 4) the magnitude of this administrative status influence generally grows to a certain level and then reaches to a plateau. These findings provide theoretical basis for understanding the administrative dimension in new urbanization and have important policy implications on administrative adjustment and urban agglomeration.

Region-based urbanization and mechanism of Wuhan urban agglomeration

Region-based urbanization and mechanism of Wuhan urban agglomeration

Study on Urbanization Development Strategy along Wuhan to Xianning Intercity Rail

As the development of two-oriented society in Wuhan urban agglomeration, the intercity railway will be an important way of driving the development of urbanization in Wuhan urban agglomeration. Intercity railway shortens the time in traffic between surrounding cities of Wuhan and it brings a lot of people, materials and information. It has also brought opportunities and challenges to the areas along intercity railway. The question is how to seize the development opportunities and coordinate the contradiction between development and environmental protection, and taking a new type urbanization. The paper, studying on the areas along Wuhan to Xianning intercity railway, made a summary of the objective law of urbanization and the influence to the along areas by the intercity railway, meanwhile, had experienced from the developed areas which along the intercity railway both in China and abroad. Then the paper proposed the urbanization development strategy from the aspect of land use, industry, population and transportation on the basis of analysis to be economic base and development conditions of the areas.

Urban growth and its determinants across the Wuhan urban agglomeration, central China

China has witnessed rapid urban growth over the past two decades, which has resulted in vast ecological and environmental issues, both in urban and peri-urban areas. It is therefore extremely important to explore the driving factors, and thus gain an insight into the process of urban growth, to be able to provide help for urban planning and policy making. This paper examines the features and spatial determinants of urban growth in the Wuhan urban agglomeration (WUA) from 1988 to 2011. Four landscape metrics (patch density, landscape shape index, aggregation index, and total area) were selected to characterize the urban landscape features at two scales (5 km and 10 km grid sizes). Spatial regression models were then used to explore the relationships between urban landscape change and its spatial determinants. The results showed that the urban area of the WUA increased from 4.19 × 104 ha in 1988 to 49.29 × 104 ha in 2011, with an annual growth rate of 46.75% over the past two decades. The WUA landscape has also become more fragmented and irregular. Spatial autocorrelations were common in the urban growth changes at the two different scales. Both physical and proximity factors have significantly influenced the urban landscape changes, and they have varied with time and scale. Among these variables, all the levels of road network have had a considerable effect on the shape and density changes of the urban landscape, while distance to railway and highway did not show obvious effects on the total area change of the urban growth. In addition, city center has had an increasing effect on patch density, and a decreasing impact on the total area of the urban landscape. The different land-use policies should be compromised and reconciled so that the objectives of promoting socioeconomic development and farmland protection can be balanced. These results could help us to better understand the process of urban growth, and thus have important implications for urban management and policy making in metropolitan areas in developing countries.

Spatio-Temporal Patterns and Policy Implications of Urban Land Expansion in Metropolitan Areas: A Case Study of Wuhan Urban Agglomeration, Central China

Relatively little attention has been paid to examining the spatial expansion features of cities at various tiers at the regional level in China, especially those located in central and western regions of the country. Based on Landsat satellite imagery from four years—1980, 1990, 2000, and 2010, this paper investigates the spatio-temporal pattern of urban land expansion and its influencing factors in the Wuhan Urban Agglomeration (WUA) in central China. The research found that the total area of urban land expanded from 203.66 km2 in 1980 to 1370.07 km2 in 2010, and that urban land areas increased by 423.82, 167.42, and 574.93 km2 in the periods 1980–1990, 1990–2000, and 2000–2010 respectively, exhibiting significant fluctuation between the different periods studied. Geographically, this spatial expansion pattern was characterised by conspicuous concentrations and regional imbalances across the overall study period. Whilst these spatio-temporal differences were found to be closely related to industrialisation, urban population growth, land-use policies, urbanisation guidelines (governmental plans and regulations addressing urbanisation), and national development strategy, the dominant mechanisms driving those differences varied over time. In response, the paper presents an urban-rural and regional integration strategy, with the aim of avoiding economic gaps and the inefficient utilisation of various resources in the urban agglomeration areas.

Comprehensive Evaluation and Study on Regional Economic Development of Huangshi City

Under the background of “Two-oriented Society”, it was one of the important content of promoting the construction and development of Wuhan urban agglomeration to achieve the rapid development of the deputy center city (Huangshi). In this study, statistical data, the principal component analysis and K-means clustering algorithm are integrated to assess and analyze the economic development of Huangshi City in Wuhan urban agglomeration in 2010. Finally this analysis is applied to real data, it is demonstrated that the result are clear and realizable, which shows that proposed evaluation method can provide enough instructions for the real cases.

Evaluation of water security: an integrated approach applied in Wuhan urban agglomeration, China

To evaluate water security, the Water Resources Sustainability Evaluation Model has been developed. The model employs four criteria (economic development, flood control security, water supply security, and water environment security) and has 22 indicators, integrating them using their relative weights. The model is applied to evaluate the water security of Wuhan urban agglomeration, China. The values of the indicators are normalized using the exponential efficacy functions based on the law of diminishing marginal utility. The evaluation results show that, overall, the state of water security in Wuhan urban agglomeration is good, which is in good agreement with the true situation. The comparison between the results of the model and other three evaluation methods by the Spearman coefficient of rank correlation verifies the science and reliability of the developed model. Consequently, it is concluded that the model can be an effective tool for evaluating the states of water security and provide a basis on which to create policies for improving inadequacies in water security.