Distribution Of Urban Land Research Articles

Spatial utilization of historical topographic map and its application in land reconstruction of ancient Chinese urban land use

The historical topographic map preserves rich geographic information and can provide direct assistance for the reconstruction of various geographic elements. Based on the historical data of cities throughout the Qing Dynasty, the land use scale data of cities across the country was obtained using GIS and urban perimeter conversion models. This study combines city information and city circumference records from the historical maps and archives of the late Qing Dynasty to quantitatively reconstruct the use patterns of ancient China’s urban land at a spatial resolution of 1° × 1°. Uncertainty analysis of the reconstruction results was conducted using modern remote sensing image data as the validation data set. The results showed the following. (1) During the late Qing Dynasty, the total area of urban land in the various provinces and regions was 1456.015 km2. The maximum value was 208.691 km2 in Beijing-Tianjin-Hebei, the minimum value was 1.713 km2 in Qinghai, and the average value was 56.001 km2. (2) The results of grid reconstruction show that among the 398 grids with urban land distribution, the maximum value is 64.099 km2/grid, the minimum value is 0.013 km2/grid, and the average value is 3.658 km2/grid. (3) Of all the grids with urban land, the urban land grid to the west of the Hu Line accounts for 12.5% and the east to 87.5%. (4) During the late Qing Dynasty, urban land use in China was primarily concentrated in agriculturally developed areas such as the North China Plain, the Central Plains, Jiangnan, and the Sichuan-Chongqing region. (6) The results of a kernel density estimation showed that there were obviously three core areas of urban land agglomeration in China during the late Qing Dynasty: the North China Plain-Central Plains, the Jiangsu-Shanghai-Zhejiang-Anhui area, and the Sichuan-Chongqing urban core area. This study provides basic data for urban land use during historical periods and provides a basis for the quantitative reconstruction of relevant urban land data for historical archives.

Urbanization and weather dynamics co-dominated the spatial-temporal variation in pCO2 and CO2 fluxes in small montanic rivers draining diverse landscapes

Rivers have been widely reported as important CO2 emitters to the atmosphere. Rapid urbanization has a profound impact on the carbon biogeochemical cycle of rivers, leading to enhanced riverine CO2 evasions. However, it is still unclear whether the spatial–temporal patterns of CO2 emissions in the rivers draining diverse landscapes dominated by urbanization were stable, especially in mountainous areas. This study carried out a two-year investigation of water environmental hydrochemistry in three small mountainous rivers draining urban, suburban and rural landscapes in southwestern China, and CO2 partial pressure (pCO2) and fluxes (fCO2) in surface water were measured using headspace equilibrium method and classical thin boundary layer model. The average pCO2 and fCO2 in the highly urbanized river were of 4783.6 μatm and 700.0 mmol m−2 d−1, conspicuously higher than those in the rural river (1525.9 μatm and 123.2 mmol m−2 d−1), and the suburban river presented a moderate level (3114.2 μatm and 261.2 mmol m−2 d−1). It provided even clearer evidence that watershed urbanization could remarkably enhance riverine CO2 emissions. More importantly, the three rivers presented different longitudinal variations in pCO2, implying diversified spatial patterns of riverine CO2 emissions as a result of urbanization. The urban land can explain 49.6–69.1% of the total spatial variation in pCO2 at the reach scale, indicating that urban land distribution indirectly dominated the longitudinal pattern of riverine pCO2 and fCO2. pCO2 and fCO2 in the three rivers showed similar temporal variability with higher warm-rainy seasons and lower dry seasons, which are significantly controlled by weather dynamics, including monthly temperature and precipitation, but seem to be impervious to watershed urbanization. High temperature-stimulated microorganisms metabolism and riched-CO2 runoff input lead much higher pCO2 in warm-rainy seasons. However, it showed more sensitivity of pCO2 to monthly weather dynamics in urbanized rivers than that in rural rivers, and warm-rainy seasons showed hot moments of CO2 evasion for urban rivers. TOC, DOC, TN, pH and DO were the main controls on pCO2 in the urban and suburban rivers, while only pH and DO were connected with pCO2 in the rural rivers. This indicated differential controls and regulatory processes of pCO2 in the rivers draining diverse landscapes. Furthermore, it suggested that pCO2 calculated by the pH-total alkalinity method would obviously overestimate pCO2 in urban polluted rivers due to the inevitable influence of non-carbonate alkalinity, and thus, a relatively conservative headspace method should be recommended. We highlighted that urbanization and weather dynamics co-dominated the multiformity and uncertainty in spatial–temporal patterns of riverine CO2 evasions, which should be considered when modeling CO2 dynamics in urbanized rivers.

Who owns the city? Neoliberal urbanism and land purchases in Gurgaon, India

Increasing purchases of valuable real estate for storing capital have contributed to the soaring prices of modest housing in many global cities and in several South Asian cities such as Mumbai, Delhi and Bangalore. Saskia Sassen has drawn attention to the phenomenon of underutilisation of purchased properties existing alongside the acute demand for housing by low- and moderate-income households in the same cities. Despite the gravity of this issue, empirical analyses of urban land transactions remain rare, especially because such purchases often tend to be piecemeal and obscure, involving a multitude of smaller land deals and a variety of actors. This paper examines corporate purchases of urban land in Gurgaon, a city adjacent to New Delhi that has embraced neoliberal economic policies. By creating a land database for the upcoming sectors in the city, the study makes sharply visible: (1) the radical changes in property ownership patterns from agricultural land to luxury gated communities, (2) the growing corporate investments, extreme concentration of land ownership and deeply unequal distribution of urban land and (3) the use of various illicit practices by market-leading companies in land banking.

Triple Spatial Effects of the Administrative Hierarchy on Urban Built-Up Areas in Fujian Province, China: Heterogeneity, Radiation, and Segmentation

The expansion of urban built-up areas is one of the most prominent characteristics of land use change in China. A growing body of literature has emphasized the triple spatial effects of the administrative hierarchy on urban built-up areas expansion, including heterogeneity, radiation, and segmentation. However, the existing studies have mainly focused on the administrative hierarchy at the prefectural level and above and have primarily concentrated on one single effect; few have integrated the triple effects as a whole. Based on high-resolution land use data and taking Fujian province as a study case, this study proposes an integrated theoretical framework and modeling approach and investigates the triple spatial effects of administrative hierarchy on built-up areas at the prefectural level and below. Descriptive statistics show the following: (1) Built-up areas of municipal districts are significantly larger than those of county-level units, showing the heterogeneity characteristics of urban land distribution across different levels of administrative hierarchy; (2) The county-level units adjacent to municipal districts exploit more built-up areas than other county-level units, indicating the radiation effects of municipal districts; (3) The radiation effects tend to be reduced if a municipal district and its adjacent county-level units are not located in the same prefectural city, revealing the segmentation effects among the different prefectural cities. Using the spatial econometric model with regimes, we further find the following: (1) The strengths of driving forces of built-up areas are heterogeneous between municipal districts and county-level units, and there are significant spatial interactions among administrative units; (2) The spatial interactions between municipal districts and county-level units are stronger than those between two county-level units, but the strength is restricted by the prefectural boundary, reflecting the radiation effects of municipal districts and the segmentation effects of the prefectural boundary, respectively. By investigating the triple spatial effects of the administrative hierarchy on urban built-up areas, we conclude that comprehensively considering these triple effects as a whole will result in a fuller understanding of the rapid built-up areas expansion in China, especially at the prefectural level and below.

Optimizing distribution of urban land on the basis of urban land use intensity at prefectural city scale in mainland China

Urban land use intensity (ULUI) reflects the utilization status of urban land use. However, few studies have allocated urban land distribution across provinces or cities based on the ULUI. We propose an optimization method to allocate the urban land based on ULUI to make it effective and decrease the loss of ecosystem services. Using mainland China as the research area, we first estimated ULUI at the prefectural city level in 2015 and evaluated its spatial heterogeneity; urban land distribution in 2030 was then optimized by coupling the estimated ULUI and the LAND System Cellular Automata model for Potential Effects (LANDSCAPE). Specifically, we generated two scenarios: ULUI, and quota (QT). Results showed the following: (1) ULUI demonstrated a spatially heterogenous distribution in 2015. Cities with high ULUI were mainly centralized around urban agglomerations; those with low ULUI were distributed in the northwest and northeast of the research area, where there were economically undeveloped regions. (2) Using optimization, the total economic benefits (EBs) increased and the loss of ecosystem service value (ESV) decreased. Many prefectural cities increased economic output, and reduced ecological losses, even in some rapidly cities. Our research highlights that optimizing urban land based on ULUI is a reasonable method to increase EBs and reduce ESV loss.

Continuous Simulation of Highly Urbanized Watershed to Quantify Nutrients’ Loadings

The United States has witnessed various extreme land use changes over the years. These changes led to alterations in watersheds’ characteristics, impacting their water quality and quantity. To quantify this impact in highly urbanized watersheds such as the Chicago Metropolitan Area, it is crucial to examine the characteristics and imperviousness distribution of urban land uses and available point and non-point sources. In this paper, the effect of urban runoff and nutrient loadings to water bodies in the Chicago River Watershed resulting from level (III) detailed urban land uses is investigated. A watershed scale hydrologic and water quality simulation using BASINS/HSPF model was developed for the highly urbanized watershed. Appropriate considerations were given to the effective impervious area (EIA). The results from the five-year calibrated water quality simulation were reasonably reflected with observed data in the study area and nutrient loadings of both point and non-point sources for 44 different land uses were found. The export coefficients (EC) values obtained are site-specific depending on conditions and variables at the watershed level such as physical characteristics, land use management practices, hydro-meteorological and topographical data, while using a continuous simulation approach and watershed perspective analysis. This is the first attempt to measure and model nutrients’ loadings using detailed land use types in the Chicago River Watershed. The proposed continuous calibrated and validated model can be used in the investigation and analysis of different scenarios and possible future conditions and land utilization.

How will innovation-driven development policy affect sustainable urban land use: Evidence from 230 Chinese cities

Government policy has a significant effect on rural–urban land conversion, ultimately affecting sustainable urban land use. Unlike most studies that have centred on the effects of local land-use policies, such as regulations and taxes, the present study investigates the effect of the innovation-driven development policy initialised recently by China on urban land growth at the national level. Although the geography of innovation, high-tech agglomeration and sectoral restructuring are place-based activities, existing evidence shows several links between urban innovation and urban land growth. However, only a few empirical studies have examined their relationships to date. Thus, we aim to determine the effect of urban innovation on the size and the spatial distribution of urban land using a statistical dataset from 2007 to 2015 and a spatial data source at two-time points for 230 Chinese cities. We employ three fixed effects models to control for the possible correlation between independent variables and unobservable city-level effects. Our results indicate that urban innovation has indeed driven urban land growth but does not make the urban landscape more scattered than before. Further examinations suggest that the urban innovation effect varies across the whole country, and the innovation-urban land growth connection relies on the geographic location rather than the economy size.

An Optimized Approach for Extracting Urban Land Based on Log-Transformed DMSP-OLS Nighttime Light, NDVI, and NDWI

Quantitative and accurate urban land information on regional and global scales is urgently required for studying socioeconomic and eco-environmental problems. The spatial distribution of urban land is a significant part of urban development planning, which is vital for optimizing land use patterns and promoting sustainable urban development. Composite nighttime light (NTL) data from the Defense Meteorological Program Operational Line-Scan System (DMSP-OLS) have been proven to be effective for extracting urban land. However, the saturation and blooming within the DMSP-OLS NTL hinder its capacity to provide accurate urban information. This paper proposes an optimized approach that combines NTL with multiple index data to overcome the limitations of extracting urban land based only on NTL data. We combined three sources of data, the DMSP-OLS, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI), to establish a novel approach called the vegetation–water-adjusted NTL urban index (VWANUI), which is used to rapidly extract urban land areas on regional and global scales. The results show that the proposed approach reduces the saturation of DMSP-OLS and essentially eliminates blooming effects. Next, we developed regression models based on the normalized DMSP-OLS, the human settlement index (HSI), the vegetation-adjusted NTL urban index (VANUI), and the VWANUI to analyze and estimate urban land areas. The results show that the VWANUI regression model provides the highest performance of all the models tested. To summarize, the VWANUI reduces saturation and blooming, and improves the accuracy with which urban areas are extracted, thereby providing valuable support and decision-making references for designing sustainable urban development.

Spatial optimization of urban land and cropland based on land production capacity to balance cropland protection and ecological conservation

Cropland protection strategies have provided a strong contribution to limit cropland transformation worldwide. However, it negatively affects ecological land (e.g., forest, grassland, and wetland). Identifying a win-win approach for cropland protection and ecological conservation is important. Land use optimization plays a vital role in solving conflicts among land uses. Thus, in this research, taking China (mainland) as the study area, we optimized the spatial distribution of urban land and cropland to balance the requirement of cropland protection strategies and their negative effects on ecological land according to the spatial heterogeneity of land agricultural production capacity by using the LAND System Cellular Automata model for Potential Effects (LANDSCAPE). Specifically, we developed three optimization scenarios from compensational, occupancy, and occupancy and compensational sectors. We also developed one non-optimization scenario to remain comparable. Results show that compared with the non-optimization scenario, the reduced loss of ecological land in compensational, occupancy, and occupancy and compensational optimization scenario is 7180, 247, and 7277 km2, respectively. Our research indicates that we should prioritize the quality of compensated cropland when developing cropland protection strategies and planning, considering the low efficiency of the occupancy optimization and the cost of policymaking and implementing.

Spatial Evolution of Urban Expansion in the Beijing–Tianjin–Hebei Coordinated Development Region

Against the background of coordinated development of the Beijing–Tianjin–Hebei region (BTH), it is of great significance to quantitatively reveal spatiotemporal dynamics of urban expansion for optimizing the layout of urban land across regions. However, the urban expansion characteristics, types and trends, and spatial coevolution (including urban land, GDP, and population) have not been well investigated in the existing research studies. This study presents a new spatial measure that describes the difference of the main trend direction. In addition, we also introduce a new method to classify an urban expansion type based on other scholars. The results show the following: (1) The annual urban expansion area (UEA) in Beijing and Tianjin has been ahead of that in Hebei; the annual urban expansion rate (UER) gradually shifted from the highest in megacities to the highest in counties; the high–high clusters of the UEA presented an evolution from a “seesaw” pattern to a “dumbbell” pattern, while that of the UER moved first from Beijing to Tianjin and eventually to Hebei. (2) Double high speed for both UEA and UER was the main extension type; most cities presented a U-shaped trend. (3) Qinhuangdao has the largest difference between the main trend direction of spatial distribution of urban land, GDP and population; the spatial distribution of GDP is closer to that of urban land than population. (4) The area and proportion of land occupied by urban expansion varied greatly across districts/counties. BTH experienced dramatic urban expansion and has a profound impact on land use. These research results can provide a data basis and empirical reference for territorial spatial planning.

Coupled controls of climate, lithology and land use on dissolved trace elements in a karst river system

As an important factor affecting water quality, dissolved trace element (DTE) is not well studied in the karst region. Here, eighteen DTEs were analyzed to investigate their contents, seasonal-spatial variations, sources and controlling factors, and to evaluate water quality and health risks in a karst river system (Chishui River, southwestern China). The results showed that dissolved trace element concentrations (DTECs) in this river were at a relatively low level compared with other Chinese rivers. Except for Cr, Ni, Sr and U, other DTEs had a higher median concentration in the wet period than in the dry period. Water quality and health risk assessments indicated that the water quality in this river had no extensive heavy metal pollution, and the DTECs were below the hazard level. Correlation analysis and principal component analysis identified that Al, Co, Cu, Li, Mn, Ni, U, Mo, Sb and Sr were mainly derived from natural sources, while As, Ba, Cr, Ga, Pb, Rb, V and Zn were dominated by anthropogenic sources. Carbonate and urban land distributions control the DTECs of river waters, indicated by correlations of DTECs with coverage of carbonate and urban land within the draining area. Further analyses found that for mono-lithological sub-catchments with low urban land coverage, the water samples from carbonate catchments had a higher concentration of Co, Cr, Ni, U, Mo, Li and Sr and a lower concentration of Ga, Pb, Sb, Cu, As, Rb, V, Mn, Zn, Al and Ba than the water samples from silicate catchments. These differences would be changed with the increasing of urban land coverage in mono-lithological sub-catchments, suggesting that the impacts of urban land on DTEs are not limited to As and Rb indicated by correlation analyses. Seasonal changes in contents of DTEs and in their correlations with analyzed factors reflect the regulations of seasonal hydrologic conditions. This study highlights that the DTECs of river waters in the Chishui River basin, a region with low level of urbanization, are significantly related to urban land distribution. Future urban planning and watershed management need consider the impacts of urbanization on the DTEs and water quality in rivers in karst areas.

Land Use Simulation of Guangzhou Based on Nighttime Light Data and Planning Policies

With the implementation processes of strategies such as Guangdong-Hong Kong-Macau Greater Bay Area’s coordinated development and “Belt and Road Initiative” initiative, the planning policies had produced a significant influence on land use distributions in Guangzhou. In this paper, we employ nighttime light (NTL) information as a proxy indicator of gross domestic product(GDP), and a future land use simulation model (FLUS) to simulate the land use patterns in Guangzhou from 2015 to 2018 and 2018 to 2035 by incorporating planning policies. The results show that: (1) the accuracy of simulation result from 2015 to 2018 based on National Polar-orbiting Partnership, Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) is higher than that based on GDP; (2) by incorporating planning policies into the model can better identify the potential spatial distribution of urban land and make the simulated results more consistent with the actual urban land development trajectory. This study demonstrates that NTL is a suitable and feasible proxy indicator of GDP for the land use simulations, providing a scientific basis for the development of urban planning and construction policy.

Annual large-scale urban land mapping based on Landsat time series in Google Earth Engine and OpenStreetMap data: A case study in the middle Yangtze River basin

Long time series (e.g. 30 years) urban land observations from remote sensing images are important for urban growth modeling as well as for the goal of sustainable urban development. However, updates to regional and even global maps are infrequent due to the cost and difficulty of collecting representative training data and the requirement for high-performance computation in processing large amounts of images. In this study, a semi-automatic large-scale and long time series (LSLTS) urban land mapping framework is demonstrated by integrating the crowdsourced OpenStreetMap (OSM) data with free Landsat images (~13,218 scenes) to generate annual urban land maps in the 317,000 km2 middle Yangtze River basin (MYRB) from 1987 to 2017 facilitated by Google Earth Engine (GEE). Random training samples for latest year were generated based on the updated OSM land use data after a manual topological conflict processing and uploaded to GEE for automatic image classification. For each historical year, training samples were obtained with a proposed transferring schema by which only the unchanged were selected through a change detection analysis. The annual spectral indices and texture feature maps acquired from the surface reflectance dataset were also added to the original bands. Finally, the classified maps were downloaded from GEE and a spatial-temporal consistency checking was further performed. Based on independent samples, the overall accuracies and kappa coefficients of all years ranged from 98% to 99% and 0.65 to 0.85, respectively. Our product when compared with current 30 m land-cover products showed similar accuracies but more spatial details. The characteristics of pattern, traces, and hotspots of urban expansion were further explored. This study provides a more convenient procedure for LSLTS urban land mapping especially for areas where large-scale field sample-collection is difficult and little historical crowdsourced datasets are available. The resultant dataset is expected to provide consistent details about the spatial distribution of urban land in MYRB. We highlight the potential use of this proposed framework to be applied and validated to other parts of the world to help better understand and quantify various aspects of urban-related problems.

Simulation and prediction of Shanghai urban spatial change based on random forest and CA-Markov model

Abstract. In the context of rapid urbanization, accurate assessment of urban expansion has become increasingly important for urban sustainable development, and smart growth theory has been put forward to avoid urban sprawl. Previous studies about urban expansion simulation focused only on ecological constrain which prevent urban growth from developing in specific regions. However, government decision-making and urban planning greatly influence urban development and limit the disorderly expansion of the urban. In this paper, we consider planning policies into urban simulation and uses the ecological protection red line, farmland protection red line and cultural protection control line as limiting factors for future urban simulation. Choosing Shanghai as the study area, we integrated Random Forests Algorithm (RFA), Markov chain and Cellular Automata (CA) to simulate urban expansion in 2015, and further predict the urban expansion in 2020, 2025 and 2030. The results show that the overall accuracy of urban land use simulation in 2015 is 93.86%, and the kappa coefficient is 0.8577. The model has a good simulation effect. Furthermore, the predicted results in 2020, 2025 and 2030 show that the urban land area in Shanghai is still increasing, and the spatial distribution of urban land has obvious circle structure and regional differences. The urban areas within 10km from the city center are growing slowly, and the region within 30km from the city center is growing faster, and there are more new urban points from 2025 to 2030. But in the area 30km away from the city center, different administrative areas show different urban growth phenomena. Among them, there are a large number of new urban points in the junction area between Songjiang District and Jinshan District, which may be the focus of future urban development planning in Shanghai. The proposed model and the results can help planners study the evolution of urban patterns and develop further urban planning.

Beyond the urban-rural dichotomy: Towards a more nuanced analysis of changes in built-up land

Urban land and rural land are typically represented as homogenous and mutually exclusive classes in land change analyses. As a result, differences in urban land use intensity, as well as mosaic landscapes combining urban and rural land uses are not represented. In this study we explore the distribution of urban land and urban land use intensity in Europe and the changes therein. Specifically, we analyze the distribution of built-up land within pixels of 1 km2. At that resolution we find that most built-up land is distributed over predominantly non-built-up pixels. Consistently, we find that most urban land use changes between 2000 and 2014 come in small incremental changes, rather than sudden large-scale conversions from rural to urban land. Using urban population densities, we find that urban land use intensity varies strongly across 1 km2 pixels in Europe, as illustrated by a coefficient of variation of 85%. We found a similarly high variation between urban population densities for most individual countries and within areas with the same share of built-up land. Population changes have led to different combinations of urban land expansion and urban intensity changes in different study periods (1975–1990, 1990–2000, and 2000–2015) and countries. These findings suggest that land use change models could be improved by more nuanced representations of urban land, including mosaic classes and different urban land use intensities.

The border effect on urban land expansion in China: The case of Beijing-Tianjin-Hebei region

Since the seminal contribution of McCallum (1995), border study has been introduced to broader fields. However, it’s still a puzzle that how administrative boundaries affect the process of urban land expansion. In this study, we develop the Stage Model of Border Effect on urban land expansion based on Core-Periphery Theory and divide the evolutive process of border effect into four stages: the invisibility stage of administrative boundaries, the differentiation stage of administrative boundaries, the channelization stage of administrative boundaries and the evaporation stage of administrative boundaries. In the model, urban land distribution of different cities in urban agglomeration is in high-level balance after the evolution which is from low-level equilibrium to none-equilibrium state during the invisibility stage and the evaporation stage. Then, Beijing-Tianjin-Hebei region is fully studied based on conditionalβconvergence analysis. Research results show that the model is well adapted to empirical study and evolutive process of border effect on urban land expansion in the region experienced the invisibility stage of administrative boundaries, the differentiation stage of administrative boundaries and the channelization stage of administrative boundaries from 1990 to 2010. We also find that the wider the gap between cities of different administrative ranks is, the larger the border effect tends to be. When border effects of different cities are equal and measure results are “1″, process of urban land expansion enter the evaporation stage of administrative boundaries. Additionally, impact of boundaries on urban land expansion is a long-term and cumulative process. The longer the research period is, the more significant the border effect tends to be. These findings can serve as basis of theoretical support and policy recommendations in breaking restriction of boundaries, delimiting the urban growth boundary and contributing to the rational expansion of urban land.

Estimating changes in urban land and urban population using refined areal interpolation techniques

Abstract. The analysis of changes in urban land and population is important because the majority of future population growth will take place in urban areas. U.S. Census historically classifies urban land using population density and various land-use criteria. This study analyzes the reliability of census-defined urban lands for delineating the spatial distribution of urban population and estimating its changes over time. To overcome the problem of incompatible enumeration units between censuses, regular areal interpolation methods including Areal Weighting (AW) and Target Density Weighting (TDW), with and without spatial refinement, are implemented. The goal in this study is to estimate urban population in Massachusetts in 1990 and 2000 (source zones), within tract boundaries of the 2010 census (target zones), respectively, to create a consistent time series of comparable urban population estimates from 1990 to 2010. Spatial refinement is done using ancillary variables such as census-defined urban areas, the National Land Cover Database (NLCD) and the Global Human Settlement Layer (GHSL) as well as different combinations of them. The study results suggest that census-defined urban areas alone are not necessarily the most meaningful delineation of urban land. Instead, it appears that alternative combinations of the above-mentioned ancillary variables can better depict the spatial distribution of urban land, and thus make it possible to reduce the estimation error in transferring the urban population from source zones to target zones when running spatially-refined temporal areal interpolation.

Modelling urban expansion guided by land ecological suitability: A case study of Changzhou City, China

Rapid urban expansion usually leads to the change of land use pattern and poses a severe threat to land resources with high ecological value, it is necessary to model the impact of urban development on surrounding environment. The aim of our study is to construct an effective model of simulating urban expansion with protecting ecological land, which could provide a decision-making reference for sustainable development of the city and promote the rational distribution of land resources. In this paper, we proposed an urban expansion model based on land ecological suitability (LES). The proposed model involves using the minimum cumulative resistance (MCR) method to evaluate and visualize the land ecological suitability of the study area. Next, the random forest (RF) algorithm and cellular automaton (CA) are combined to construct an RF–CA to simulate future growth of urban land. As a case study, the RF–CA was used to simulate the distribution of urban land in Changzhou City, eastern China in 2020. The LES evaluation results were then used as the basis of optimizing urban expansion and restrained the excessive sprawl of the city, which could reduce encroachment on land resources such as waterbody and farmland, thereby increasing the ecosystem services value (ESV) by 50.24 million RMB(1 RMB = 0.15 US dollar). It was observed that our model could reduce the spatial conflict between urban expansion and ecological land protection effectively. Therefore, we believe that the results of our case study can contribute to more reasonable urban planning.

Temporal and Spatial Effects of Urban Center on Housing Price — A Case Study on Hangzhou, China

<em>With the acceleration of urbanization and the rapid development of real estate, people pay more and more attention to the change of urban housing prices. Over time, the change of city center will inevitably affect the urban land or housing prices, which is reflected in the spatial distribution of urban land or housing prices. Therefore, this article attempts to explore the impact of urban center on housing prices from the perspective of multi-center city and study separately from two aspects of time and space. This paper takes the six main urban districts of Hangzhou as the research scope. At the time level, we select the residential data from 2007 to 2015 to construct models respectively based on the hedonic price theory and find that the influence of different urban center on housing price shows a certain change with time. On the spatial level, this paper choses the residential data in 2012 to construct geographic weighted regression model and the result shows that the impact of three centers on housing prices shows a certain degree of spatial heterogeneity.</em>

SPATIAL PATTERNS OF ECONOMIC RENTS: DEVELOPING SUVARNABHUMI INTERNATIONAL AIRPORT, THAILAND

With the rise of the importance of air transportation in the 21st century, the role of economics in airport planning and decision-making has become crucial to the urban structure and land values. This paper examines the relationship between an airport and its impact on the distribution of urban land uses and land values by applying the Alonso’s bid-rent model. Using Suvarnabhumi International Airport as a case study, the analysis was made over three different time periods of airport development. The statistical results confirm that: (i) Alonso’s model can be used to explain the impacts of the airport only for the northeast quadrant of the airport; (ii) proximity to the airport shows an inverse relationship with the land value of all six types of land use activities through three periods of time; and (iii) the land value for commercial land use is the most sensitive to the location of the airport compared to other types of land use activities.