Modeling urban growth with GIS based cellular automata and least squares SVM rules: a case study in Qingpu–Songjiang area of Shanghai,China

A critical issue in urban cellular automata (CA) modeling concerns the identification of transition rules that generate realistic urban land use patterns. Recent studies have demonstrated that linear methods cannot sufficiently delineate the extraordinary complex boundaries between urban and non-urban areas and as most urban CA models simulate transitions across these boundaries, there is an urgent need for good methods to facilitate such delineations. This paper presents a machine learning CA model (termed MachCA) with nonlinear transition rules based on least squares support vector machines (LS-SVM) to simulate such urban growth. By projecting the input dataset into a high dimensional space using the LS-SVM method, an optimal hyper-plane is constructed to separate the complex boundaries between urban and nonurban land, thus enabling the retrieval of nonlinear CA transition rules. In the MachCA model, the transition rules are yes–no decisions on whether a cell changes its state or not, the rules being dynamically updated for each iteration of the model implementation. The application of the MachCA for simulating urban growth in the Shanghai Qingpu–Songjiang area in China reveals that the spatial configurations of rural–urban patterns can be modeled. A comparison of the MachCA model with a conventional CA model fitted by logarithmic regression (termed LogCA) shows that the MachCA model produces more hits and less misses and false alarms due to its capability for capturing the spatial complexity of urban dynamics. This results in improved simulation accuracies, although with only less than 1 % deviation between the overall errors produced by the MachCA and LogCA models. Nevertheless, the way MachCA model use in retrieving the transition rules provides a new method for simulating the dynamic process of urban growth.     

Modeling determinants of urban growth in Dongguan,China: a spatial logistic approach

This paper examines spatial variations of urban growth patterns in Chinese cities through a case study of Dongguan, a rapidly industrializing city characterized by a bottom-up pattern of development based on townships. We have employed both non-spatial and spatial logistic regression models to analyze urban land conversion. The non-spatial logistic regression has found the significance of accessibility, neighborhood conditions and socioeconomic factors for urban development. The logistic regression with spatially expanded coefficients significantly improves the orthodoxy logistic regression with lower levels of spatial autocorrelation of residuals and better goodness-of-fit. More importantly, the spatial logistic model reveals the spatially varying relationship between urban growth and its underlying factors, particularly the local influence of environment protection and urban development policies. The results of the spatial logistic model also provide clear clues for assessing environmental risks to take the local contexts into account.     

Urban land expansion and arable land loss of the major cities in China in the 1990s

China is a country with vast population and scarce arable land per capita. China’s population is more than 1.2 billion, about one-fifth of the world’s total, while the arable land area is only 0.106 hm2 per capita, less than half of the world’s average of 0.23 hm2[1]. Arable land conservation/food security has been acknowl- edged as one of the main factors affecting the sustain- able socio-economic development in China[2], which catches the special attention of many scholars at home and abr…     

Discovery of transition rules for geographical cellular automata by using ant colony optimization

A new intelligent algorithm of geographical cellular automata (CA) based on ant colony optimization (ACO) is proposed in this paper. CA is capable of simulating the evolution of complex geographical phenomena, and the core of CA models is how to define transition rules. However, most of the transition rules are defined by mathematical equations, and are hence not explicit. When the study area is complicated, it is much more difficult to extract parameters for geographical CA. As a result, ACO is applied to geographical CA to automatically and intelligently obtain transition rules in this paper. The transition rules extracted by ACO are defined as logical expressions rather than implicit mathematical equations to describe the complex relationships of the nature, and easy for people to understand. The ACO-CA model was applied to simulating rural-urban land conversions in Guangzhou City, China, and appropriate simulation results were generated. Compared with See5.0 decision tree model, ACO-CA is more suitable to discovering transition rules for geographical CA.     

Developing land use scenario dynamics model by the integration of system dynamics model and cellular automata model

Models of land use change are useful tools for un-derstanding the analysis of the cause and conse-quences of land use changes, assessing the impacts of land use system on ecological system and supporting land use planning and policy[1,2]. Modeling land use scenario changes and its potential impacts on the structure and function of the ecosystem in the typical regions are regarded as one of the good ways to un-derstand the interactive mechanism between land use system and ecological system[3―10…     

Multi-agent systems for simulating spatial decision behaviors and land-use dynamics

A new method to simulate urban land-use dynamics is proposed based on multi-agent systems (MAS). The model consists of a series of environmental layers and multi-agent layers, which can interact with each other. It attempts to explore the interactions between different players or agents, such as residents, property developers, and governments, and between these players and the envi- ronment. These interactions can give rise to urban macro-spatial patterns. This model is used to simulate the land-use dynamics of the Haizhu district of Guangzhou City in 1995―2004. Cellular automata (CA) were also used for the simulation of land use changes as a comparison. The study indicates that MAS has better performance for simulating complex cities than CA.     

A gravity-spatial entropy model for the measurement of urban sprawl

Since the mid-twentieth century, most cities worldwide have undergone a rapid expansion in urban land use. Along with the expansion, several problems, such as excessive loss of prime agricultural land and increasing traffic congestion have arisen. Thus, understanding and measurements of the expansion scale and its speed are crucial to planners and officials during urban planning and management processes. To measure such geographic phenomena, Shannon first devised entropy theory, and then Batty developed it into spatial entropy. The recently developed spatial entropy model, which was used to measure urban sprawl, introduced area to represent spatial asymmetry. However, most models did not consider spatial discretization, particularly the impact of distance. This study attempted to construct an integrated gravity-spatial entropy model to delineate distance and spatial diffusion impacts on population distribution. Then, we tested the model using Shanghai’s temporal land use and community statistical data. Application results for the new gravity-spatial model show that it is a useful tool for identifying spatial and temporal variations of urban sprawl.     

Performance of WASMOD and SWAT on hydrological simulation in Yingluoxia watershed in northwest of China

Two hydrological models with different structures and spatial capabilities are selected to simulate the runoff and actual evapotranspiration (AET) in Yingluoxia watershed, the upper reaches of Heihe River basin in northwest of China, to validate their performances in simulating hydrological processes. They are calibrated against the observed runoff at the watershed outlet (Yingluoxia station) for the period from 1990 to 1996 and validated for the period from 1997 to 2000. Results show that in terms of the simulated hydrograph against observations and the two selected objective functions, the conceptual, lumped Water And Snow balance MODeling system (WASMOD) with simple model structure could give the same, even better results than the semi‐distributed Soil and Water Assessment Tool (SWAT) with complex structure. Compared with other model applications to the watershed, simulation for monthly runoff made in this study seems better. With regard to AET, results calculated from both models are comparable as well. Both WASMOD and SWAT are proved to be suitable and satisfactory tools in simulating hydrological processes in the study area, although both of them have strengths and limitations in applications. WASMOD model may be one of the promising alternatives in hydrological modelling. Copyright © 2010 John Wiley & Sons, Ltd.     

Integration of principal components analysis and cellular automata for spatial decisionmaking and urban simulation

This paper discusses the issues about the correlation of spatial variables during spatial decisionmaking using multicriteria evaluation (MCE) and cellular automata (CA). The correlation of spatial variables can cause the malfunction of MCE. In urban simulation, spatial factors often exhibit a high degree of correlation which is considered as an undesirable property for MCE. This study uses principal components analysis (PCA) to remove data redundancy among a large set of spatial variables and determine ‘ideal points’ for land development. PCA is integrated with cellular automata and geographical information systems (GIS) for the simulation of idealized urban forms for planning purposes.     

The relative impact of climate change and urban expansion on peak flows: a case study in central Belgium

An essential part of hydrological research focuses on hydrological extremes, such as river peak flows and associated floods, because of their large impact on economy, environment, and human life. These extremes can be affected by potential future environmental change, including global climate change and land cover change. In this paper, the relative impact of both climate change and urban expansion on the peak flows and flood extent is investigated for a small‐scale suburban catchment in Belgium. A rainfall‐runoff model was coupled to a hydrodynamic model in order to simulate the present‐day and future river streamflow. The coupled model was calibrated based on a series of measured water depths and, after model validation, fed with different climate change and urban expansion scenarios in order to evaluate the relative impact of both driving factors on the peak flows and flood extent. The three climate change scenarios that were used (dry, wet winter, wet summer) were based on a statistical downscaling of 58 different RCM and GCM scenario runs. The urban expansion scenarios were based on three different urban growth rates (low, medium, high urban expansion) that were set up by means of an extrapolation of the observed trend of urban expansion. The results suggest that possible future climate change is the main source of uncertainty affecting changes in peak flow and flood extent. The urban expansion scenarios show a more consistent trend. The potential damage related to a flood is, however, mainly influenced by land cover changes that occur in the floodplain. Copyright © 2011 John Wiley & Sons, Ltd.     

A method characterizing urban expansion based on land cover map at 30 m resolution

Based on the global land cover data at 30 m resolution (GlobeLand30) in the year 2000 and 2010, the urban expansion process of 320 cities in China was analyzed using lognormal regression, and the expansion model were established. Three metrics were presented for the models, including the peak position, the full width at half maximum, and the skewness. It was found that the three metrics could reveal different patterns of the urban expansion process of cities with different sizes. Specifically, cities with larger size tend to expand outward strongly, and their expansion intensity and influence are likely to be higher. Moreover, most cities’ expansion occurs around the urban core with spatially limited influence. In addition, it was also found that the city’s expansion intensity is related to the city size. These results showed that the lognormal regression model could describe the distribution of urban expansion with effectiveness and robustness.     

The influence of land use patterns on water quality at multiple spatial scales in a river system

The influence of land use patterns on water quality in a river system is scale‐dependent. In this study, a four‐order hierarchical arrangement method was used to select water sampling sites and to delineate sub‐basins in the Daliao River Basin, China. The 20 sub‐basins were classified into four spatial scales that represented four different stream orders. Pearson correlation analysis was used to quantify relationships between land use composition and the river's physical‐chemical variables for all samples collected. This analysis showed that the presence of forest cover was associated with higher water quality at the scale of the whole basin. The scale effects of land use patterns on water quality were then examined using stepwise multiple regression analysis that compared different land use types with water quality variables. The results from this analysis showed that urban areas, as opposed to forest areas, became the most significant contributors of water pollutants when scale effects were considered. The influence of urban land cover on water pollution was significantly higher at larger scales. The lack of a significant regression correlation for the forest land use type at smaller scales revealed that forest located upstream of the Daliao River Basin did not provide a buffer for improved water quality. Further analysis showed that this result could be because of disproportionate spatial distributions for forest and urban land use types. The topographic characteristics of sub‐basins, such as average slope (S) and size (A), were determined to be secondary explanatory variables that affected land use impacts on stream water quality. Areas with steep slopes were associated with increased water oxygenation, whereas areas with flatter slopes were associated with higher concentrations of pollutants. These results are significant because they can provide a better understanding of the appropriate spatial scale required for effective river basin management in the future. Copyright © 2013 John Wiley & Sons, Ltd.     

Spatially explicit assessment of land ecological security with spatial variables and logistic regression modeling in Shanghai,China

Ecological security is a fundamental component of regional security that has drawn increased attention worldwide over the past two decades. This paper presents a novel approach to assess the status of land ecological security (LES) in Shanghai, China from 1992 to 2011 using spatial variables and a logistic regression model. The LES status of 1745 points within the study area in 1992, 2001 and 2011 was sampled systematically using a 2 × 2 km grid sample frame and evaluated based on an expert method with ten experts from five fields. A five-point Likert scale was used to score the LES status as very insecure, insecure, neutral, secure or very secure. We identified several explanatory factors to the LES status, including distance-based variables describing the proximities to urban center, developed areas and sources of pollution, as well as variables regarding the density of built-up areas and the mean value of normalized difference vegetation index. A logistic regression model was used to quantify the relationship between LES scores and the spatial variables at each of the three time points, resulting in a series of maps illustrating the LES patterns of Shanghai in 1992, 2001 and 2011. The results show that LES is either very insecure or insecure at the center of Shanghai and at its district centers, and the LES of the entire Shanghai municipality has deteriorated significantly from 1992 to 2011. This research contributes to an enhanced understanding of LES changes resulting from rapid urbanization and industrialization of the Shanghai municipality and provides a methodological framework to study LES elsewhere.     

Strategies to improve the explanatory power of a dynamic slope stability model by enhancing land cover parameterisation and model complexity

Despite the importance of land cover on landscape hydrology and slope stability, the representation of land cover dynamics in physically based models and their associated ecohydrological effects on slope stability is rather scarce. In this study, we assess the impact of different levels of complexity in land cover parameterisation on the explanatory power of a dynamic and process-based spatial slope stability model. Firstly, we present available and collected data sets and account for the stepwise parameterisation of the model. Secondly, we present approaches to simulate land cover: 1) a grassland landscape without forest coverage; 2) spatially static forest conditions, in which we assume limited knowledge about forest composition; 3) more detailed information of forested areas based on the computation of leaf area development and the implementation of vegetation-related processes; 4) similar to the third approach but with the additional consideration of the spatial expansion and vertical growth of vegetation. Lastly, the model is calibrated based on meteorological data sets and groundwater measurements. The model results are quantitatively validated for two landslide-triggering events that occurred in Western Austria. Predictive performances are estimated using the Area Under the receiver operating characteristic Curve (AUC). Our findings indicate that the performance of the slope stability model was strongly determined by model complexity and land cover parameterisation. The implementation of leaf area development and land cover dynamics further yield an acceptable predictive performance (AUC ~0.71-0.75) and a better conservativeness of the predicted unstable areas (FoC ~0.71). The consideration of dynamic land cover expansion provided better performances than the solely consideration of leaf area development. The results of this study highlight that an increase of effort in the land cover parameterisation of a dynamic slope stability model can increase the explanatory power of the model. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.     

Urban expansion in China and its effect on cultivated land before and after initiating “Reform and Open Policy”

Urbanization in China has expanded at an unprecedented speed since the declaration of "Reform and Open Policy"and presented many challenges. Unbalanced regional development, appearance of super megacities and concomitant problems,and conflicts between urbanization and cultivated land protection are three critical problems that Chinese urbanization has to face. To develop new plans for foreseeable future urbanization in China, it is critical to understand the evolving history of cities across China. This study maps urban expansion of 60 typical Chinese cities based on large amount of remote sensing data and the labor-intensive image interpretation method, in order to understand the history of urban expansion from the 1970 s to 2013.Results showed that area of cities expanded 5.23 times compared to their area in the 1970 s. Urban expansion in China accelerated three times(1988–1996, 1999–2006, and 2009–2011) and decelerated three times(1997–1998, 2007–2008, and 2012–2013) over the 40 years. The urban area of South China expanded most significantly 9.42 times, while the urban area in Northeast China expanded only 2.37 times. The disparity among different administrative ranks of cities was even greater than(3.81 times) the differences among different regions. Super megacities have been continuously expanding at a fast rate(8.60-fold), and have not shown obvious signs of slowing down. The proportion of cultivated land among the land sources for urban expansion decreased to a small extent in the 1990 s, but cultivated land continues to be the major land source for urban expansion. Effective future urbanization needs controlling the expansion scale of large cities and reasonably developing medium and small cities, as well as balancing regional development.     

Benchmarking land use change impacts on direct runoff in ungauged urban watersheds

This paper describes the results of benchmark testing of land use change impact on direct runoff using Soil Conservation Service-Curve Number (SCS-CN) model in two ungauged neighbouring urban watersheds (Çınar and Kadıyakuplu) in Istanbul, Turkey. To examine this impact, the model was applied to daily rainfall data using three different dated (1982, 1996 and 2012) hydrological soil groups and land use of the two ungauged urban watersheds. Finally, the impact of land use change and model performance were evaluated with the rainfall-runoff regression, the coefficient of determination and the NSE test using benchmark runoff data based on 1982 land use conditions. The results of the analysis indicate that the changing of land use types from natural surfaces to impervious surfaces has a significant impact on surface runoff. Additionally, remarkable spatial variations of the land use changes and their impact on the runoff in 1996 and 2012 were more detected in the Çınar watershed compared with the Kadıyakuplu watershed. The planning decision on land use of the watersheds, has vital role in these differences. The results of this research also reveal that change to intensive land use in urban watersheds has a significantly larger impact on runoff generation than those rainfall.     

Multi-agent based modeling of spatiotemporal dynamical urban growth in developing countries: simulating future scenarios of Lianyungang city,China

Urbanization is the most typical form of land use/cover change, and exploration of the driving mechanism of urban growth and the prediction of its future changes are very important for achieving urban sustainable development. In view of the ability of a multi-agent system to simulate a complex spatial system and from the perspective of combining macroscopic and microscopic decision-making behaviors of agents, a spatiotemporal dynamical urban growth simulation model based on the multi-agent systems has been developed. In this model, macroscopic land use planning behaviors implemented by macroagents and microscopic land use selection behaviors autonomously generated by microagents interact within two-dimensional spatial cells. Furthermore, the urbanization process is promoted through joint decision-making by macroagents and microagents. Considering the central region of the coastal industrial city Lianyungang as the study area, we developed three target scenarios on the basis of current trends, economic development priorities, and environmental protection priorities. Moreover, the corresponding urban growth scenarios were simulated and analyzed. The simulation results show that by combining the macroscopic and microscopic decision-making behaviors of agents to simulate spatiotemporal dynamical urban growth based on the multi-agent systems, the proposed model can provide a useful spatial exploratory tool for explaining the driving mechanism of urbanization and providing decision-making support for urban management.     

Current state of integrated earthquake simulation for earthquake hazard and disaster

This paper presents the current state of integrated simulation for earthquake hazard and disaster. This simulation takes advantage of the macro–micro analysis method; this method estimates an earthquake’s strong motion with high spatial and temporal resolution, using the bounding medium theory to obtain optimistic and pessimistic estimates of expected strong motion distribution and the singular perturbation expansion that results in an efficient multi-scale analysis. Integrated earthquake simulation calculates seismic responses for all structures in a target area, inputting simulated strong ground motion to a structure analysis method that is plugged into the system by means of a wrapper; a suitable method, linear or nonlinear, is chosen depending on the type of the structure. The results of all simulations are visualized so that residences and government officials can share a common recognition of earthquake hazard and disaster. Two examples of this integrated earthquake simulations are presented; one is made by plugging nonlinear structure analysis methods into the system, and the other is made for an actual city, the computer model of which is constructed with the help of available geographical information systems.     

An EcoCity model for regulating urban land cover structure and thermal environment: Taking Beijing as an example

Urban land-use/cover changes and their effects on the eco-environment have long been an active research topic in the urbanization field. However, the characteristics of urban inner spatial heterogeneity and its quantitative relationship with thermal environment are still poorly understood, resulting in ineffective application in urban ecological planning and management.Through the integration of "spatial structure theory" in urban geography and "surface energy balance" in urban climatology, we proposed a new concept of urban surface structure and thermal environment regulation to reveal the mechanism between urban spatial structure and surface thermal environment. We developed the EcoCity model for regulating urban land cover structure and thermal environment, and established the eco-regulation thresholds of urban surface thermal environments. Based on the comprehensive analysis of experimental observation, remotely sensed and meteorological data, we examined the spatial patterns of urban habitation, industrial, infrastructure service, and ecological spaces. We examined the impacts of internal land-cover components(e.g., urban impervious surfaces, greenness, and water) on surface radiation and heat flux. This research indicated that difference of thermal environments among urban functional areas is closely related to the proportions of the land-cover components.The highly dense impervious surface areas in commercial and residential zones significantly increased land surface temperature through increasing sensible heat flux, while greenness and water decrease land surface temperature through increasing latent heat flux. We also found that different functional zones due to various proportions of green spaces have various heat dissipation roles and ecological thresholds. Urban greening projects in highly dense impervious surfaces areas such as commercial, transportation, and residential zones are especially effective in promoting latent heat dissipation efficiency of vegetation, leading to strongly cooling effect of unit vegetation coverage. This research indicates that the EcoCity model provides the fundamentals to understand the coupled mechanism between urban land use structure and surface flux and the analysis of their spatiotemporal characteristics. This model provides a general computational model system for defining urban heat island mitigation, the greening ratio indexes, and their regulating thresholds for different functional zones.     

Expansion of Ürümqi urban area and its spatial differentiation

The expanded area and structure of urban lands and landscape features in Ürümqi City are analyzed using RS and GIS means based on the MSS image in 1975 and the TM images in 1990, 1999 and 2002, as well as other related maps. On which the scale, intensity and spatial differentiation of the expansion of the Ürümqi urban area during different periods are lucubrated. The results reveal that urban expansion was rapid during the periods of 1949–1965 and 1975–1990, and that it was stable after the 1990s. The urban expansion pattern was significantly different during different time periods: the urban area was expanded outwards based on old districts in a spanned development pattern during the period of 1949–1965; development was stagnant during the period of 1965–1975; urban expansion developed mainly in old districts in a grouped way during the period of 1975–1990. The trend of urban expansion along the traffic lines was obvious, and the direction of urban expansion was dominated by the south-north zonal expansion and supplemented by east-west axial expansion; urban expansion reached the development stage of “multiple centers and multiple districts” after the 1990s, and urban networks were developed more precisely after this time. The sources for urban expansion were mainly cultivated lands, grasslands and unused lands; during urban expansion, the land area devoted to traffic lines, residential areas, dispersive industrial and mineral areas, and garden plots was rapidly enlarged.