Using spatial heterogeneity to strengthen the neighbourhood effects of urban growth simulation models

2021 ◽  
pp. 1-19
Author(s):  
Shuting Zhai ◽  
Yongjiu Feng ◽  
Xinlei Yan ◽  
Yongliang Wei ◽  
Rong Wang ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Urban Growth ◽  
Simulation Models ◽  
Neighbourhood Effects ◽  
Growth Simulation

scholarly journals Monitoring of Urban Growth with Improved Model Accuracy by Statistical Methods

2019 ◽  
Vol 11 (20) ◽  
pp. 5579 ◽  
Author(s):  
Ayazli
Keyword(s):  
Urban Growth ◽  
Growth Models ◽  
Simulation Models ◽  
Growth Simulation ◽  
Urban Growth Model ◽  
Growth Properties ◽  
Force Calibration ◽  
Improved Model ◽  
Best Fit

While the rural population is decreasing day by day, the urban population is increasing rapidly. Urban growth, which occurs as a result of this increase, is sprawling toward natural and environmental areas in urban fringes, and constitutes the main source of many environmental, physical, social, and economic problems. In order to overcome these problems, the direction and rate of urban growth should be determined with simulation models. In this context, many urban growth models have been developed since the 1990s; the SLEUTH urban growth model is one of the most popular among them and has been used in many projects around the world. The brute force calibration process in which the best fit values of growth coefficients are determined is the most important stage of simulation models. The coefficient ranges are initially defined as being between 0 and 100 and are then narrowed in this step according to 13 separate regression scores, which are used to specify the characterization of urban growth. Consensus has not yet been reached as to which metrics should be used for calculating the best fit values, but the Lee–Sallee and Optimum SLEUTH Metric (OSM) methods have been mostly used in past studies. However, in rapidly growing study areas, these methods cannot truly explain urban growth properties. The main purpose of this paper is to precisely calibrate urban growth simulation models. Therefore, Exploratory Factor Analysis (EFA) was used to calculate the growth coefficients, as a new statistical approach for calibration, in this study. The district of Sancaktepe, Istanbul, which experienced population growth of 80% between 2008 and 2018, was selected as the study area in order to test the achievement of the EFA method, and two urban growth simulation models were generated for the years 2030 and 2050. According to the results, despite the fact that there is little effect of urban growth in the short term, more than 70% of forests and agricultural lands are at risk of urbanization by 2050.

scholarly journals INVESTIGATION OF URBAN GROWTH EFFECTS ON FOREST AREA BY CREATING DIFFERENT SIMULATION SCENARIOS

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 87-92
Author(s):  
I. E. Ayazli ◽  
S. Baslik ◽  
A. E. Yakup ◽  
F. Kilic Gul ◽  
D. Kotay ◽  
...  
Keyword(s):  
Land Cover ◽  
Urban Growth ◽  
Simulation Models ◽  
Urban Life ◽  
Background Information ◽  
Urban Management ◽  
Growth Simulation ◽  
Cadastral Maps ◽  
Land Cover Data

<p><strong>Abstract.</strong> It is necessary to keep urban growth under control according to the understanding of sustainable urban management in rapidly growing cities. In other words, sustainable urban management requires estimating how the land cover will change and in which direction the urbanization will be in the coming years, as well as knowing the current structures of the cities. Therefore, simulation models are frequently used for monitoring urban growth. The results of simulation models help to obtain background information that will be the basis for the formation of a “sustainable urban life” by allowing the determination of the natural areas that can face the threat of urbanization. The cadastral structure is one of the basic variables affecting the growth of a city. Therefore, the purpose of the study is to investigate urban growth by producing cadastral parcel-based simulation models. The land cover data required to create a simulation model were generated from cadastral maps and land registry data, in four different time periods. Within the scope of the study, cellular automata-based urban growth simulation models for the years 2030, 2050 and 2070 were produced, and the land cover changes that occurred in Sancaktepe were investigated.</p>

scholarly journals Optimization of a Novel Urban Growth Simulation Model Integrating an Artificial Fish Swarm Algorithm and Cellular Automata for a Smart City

2021 ◽  
Vol 13 (4) ◽  
pp. 2338
Author(s):  
Xinxin Huang ◽  
Gang Xu ◽  
Fengtao Xiao
Keyword(s):  
Land Use ◽  
Sustainable Development ◽  
Urban Growth ◽  
Smart City ◽  
Urban Land ◽  
Urban Land Use ◽  
Growth Simulation ◽  
Artificial Fish Swarm Algorithm ◽  
Artificial Fish Swarm ◽  
Ca Model

As one of the 17 Sustainable Development Goals, it is sensible to analysis historical urban land use characteristics and project the potentials of urban sustainable development for a smart city. The cellular automaton (CA) model is the widely applied in simulating urban growth, but the optimum parameters of variables driving urban growth in the model remains to be continued to improve. We propose a novel model integrating an artificial fish swarm algorithm (AFSA) and CA for optimizing parameters of variables in the urban growth model and make a comparison between AFSA-CA and other five models, which is used to study a 40-year urban land growth of Wuhan. We found that the urban growth types from 1995 to 2015 appeared relatively consistent, mainly including infilling, edge-expansion and distant-leap types in Wuhan, which a certain range of urban land growth on the periphery of the central area. Additionally, although the genetic algorithms (GA)-CA model and the AFSA-CA model among the six models due to the distance variables, the parameter value of the GA-CA model is −15.5409 according to the fact that the population (POP) variable should be positively. As a result, the AFSA-CA model regardless of the initial parameter setting is superior to the GA-CA model and the GA-CA model is superior to all the other models. Finally, it is projected that the potentials of urban growth in Wuhan for 2025 and 2035 under three scenarios (natural urban land growth without any restrictions (NULG), sustainable urban land growth with cropland protection and ecological security (SULG), and economic urban land growth with sustainable development and economic development in the core area (EULG)) focus mainly on existing urban land and some new town centers based on AFSA-CA urban growth simulation model. An increasingly precise simulation can determine the potential increase area and quantity of urban land, providing a basis to judge the layout of urban land use for urban planners.

scholarly journals Transpiration-use efficiency of young cactus pear plants (Opuntia ficus-indica L.)

2021 ◽  
Vol 48 (2) ◽  
pp. 115-124
Author(s):  
Cristian Kremer ◽  
◽  
Carlos Faúndez ◽  
Víctor Beyá-Marshall ◽  
Nicolas Franck ◽  
...  
Keyword(s):  
Vapor Pressure Deficit ◽  
Simulation Models ◽  
Arid Zones ◽  
Opuntia Ficus Indica ◽  
Growth Simulation ◽  
First Approximation ◽  
Potential Development ◽  
Dependent Parameter ◽  
Use Efficiency ◽  
Crop Growth Simulation

Opuntia ficus-indica is a versatile crop that is resilient to drought, making it perfect for semiarid to arid zones. However, the lack of knowledge associated with its benefits and the lack of simple crop growth simulation models to determine its potential development, among others, has prevented its expansion. Transpiration-use efficiency (w) has been used to evaluate crop performance under different water supplies; however, the lack of consistency in w values under different environmental conditions has impeded its use as a transferable parameter. To overcome this problem, w is estimated through the normalized water-use efficiency (kDa) and the vapor pressure deficit (Da) as w = kDa Da-1, where kDa is a crop-dependent parameter. Therefore, the goals of this research were (i) to determine w and kDa in young plants of Opuntia ficus-indica and (ii) to compare the obtained parameters with values from other species. The w and kDa results were 18.57 (g kg-1) and 6.48 (g kPa kg-1), respectively. Here, w was more than two to six times the value for traditional cereals (maize, rice, wheat), while kDa was larger than that of most C3 crops and fell in the range for C4 and CAM crops. This is the first study that explicitly determines kDa for Opuntia ficus-indica; hence, more research should be carried out on its estimation, including under different agroclimatic conditions and in later stages of development. As a first approximation, the parameters obtained here can be used as a simple model to estimate yield projections of Opuntia ficus-indica.

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