scholarly journals A Spatial-Temporal Analysis of Urban Parkland Expansion in China and Practical Implications to Enhance Urban Sustainability

2018 ◽  
Vol 11 (1) ◽  
pp. 138
Author(s):  
Wenbin Luo ◽  
Mingming Su
Keyword(s):  
Urban Development ◽  
Urban Expansion ◽  
Urban Sustainability ◽  
Recent Decade ◽  
Temporal Analysis ◽  
Influential Factors ◽  
Urban Land Use ◽  
National Standards ◽  
Cultural Challenges ◽  
Spatial Temporal Analysis

In response to serious environmental and socio-cultural challenges brought about by fast urbanization, the concept of a sustainable city emphasizes the quality of life of urban residents, assuring the importance of parkland provision in urban development. Despite China’s fast urban expansion in recent decades, scant attention has been paid to the development pattern of urban parkland in China and its implications toward urban sustainability. Engaging official data from government sources, this study conducted a spatial-temporal analysis of urban parkland in China. Results support the overall fast increase of urban parkland provision in China with a clear regional disparity. Moreover, the shift of development momentum from the east to the west has been identified in the recent decade. The status of economic development, the progress of urbanization, and the level of urban development investments are identified as key influential factors influencing the temporal changes of urban parkland in China. With the increasing demand for urban parkland and its important role in ensuring urban sustainability, recommendations to improve urban park development in China are proposed, including integrating urban parkland in urban land use management with specific planning guidelines, establishing a dynamic urban parkland monitoring system, incorporating both national and regional policy frameworks catering for both national standards and regional preferences, and shifting urban development investments with more emphasis on urban maintenance expenditure.

scholarly journals Dynamic simulation of urban expansion based on cellular automata and logistic regression model: Case study of Hyrcanian region of Iran

2016 ◽  
Author(s):  
Meisam Jafari ◽  
Seyed Masoud Monavari ◽  
Hamid Majedi ◽  
Ali Asghar Alesheikh ◽  
Mirmasoud Kheirkhah Zarkesh
Keyword(s):  
Land Use ◽  
Logistic Regression ◽  
Cellular Automata ◽  
Urban Development ◽  
Rural Areas ◽  
Urban Expansion ◽  
Urban Land ◽  
Urban Land Use ◽  
High Rate ◽  
Hyrcanian Forests

Although, promotion of urbanization culture in recent decades has made inevitable development of cities in the world, however, the development can be guided in a direction that leave, to the extent possible, minimum socioeconomic and environmental impacts. For this, it is required to first forecast auto-spreading orientation of cities and suburbs in rural areas over time and then avoid shapeless growth of cities. This paper is an attempt to develop a dynamic hybrid model based on logistic regression (LR), Markov chain (MC), and cellular automata (CA) for prediction of future urban sprawl in fast-growing cities. The model was developed using 12 widely-used urban development criteria, whose significant coefficient was determined by logistic regression, and validated by relative operating characteristic (ROC) analysis. The validated model was run in Guilan, a tourist province in northern Iran with a very high rate of urban development. For this, changes in the area of urban land use were detected over the period of 1989 to 2013 and then, future sprawl of the province was forecasted by the years 2025 and 2037. The analysis results revealed that the area of urban land use was increased by more than 1.7 % from 36012.5 ha in 1989 to 59754.8 ha in 2013, and the area of Caspian Hyrcanian forestland was reduced by 31628 ha. The results also predicted an alarming increase in the rate of urban development in the province by the years 2025 and 2037, during which urban land use is predicted to develop 0.9 % and 1.38 %, respectively. The development pattern is expected to be uneven and scattered, without following any particular direction. The development will occur close to the existing or newly-formed urban basements as well as around major roads and commercial areas. This development, if not controlled, will lead to the loss of 13863 ha of Hyrcanian forests and if the trend continues, 21013 ha of Hyrcanian forests and 20208 ha of Barren/open lands are expected to be destroyed by the year 2037. In general, the proposed model is an efficient tool for the support of urban planning decisions and facilitates the process of sustainable development of cities by providing decision-makers with an overview on future development of cities where the growth rate is very fast.

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

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Xuewei Dang ◽  
Liang Zhou ◽  
Xiaoen Li ◽  
Haowei Mu ◽  
Lei Che ◽  
...  
Keyword(s):  
Urban Planning ◽  
Urban Development ◽  
Urban Growth ◽  
Urban Expansion ◽  
Urban Land ◽  
Urban Land Use ◽  
City Center ◽  
Urban Simulation ◽  
The City ◽  
Red Line

<p><strong>Abstract.</strong> 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.</p>

scholarly journals Urban growth dynamics based on surface Albedo changes in Petrolina, Brazil

2020 ◽  
Vol 42 ◽  
pp. e46270
Author(s):  
Michele Laurentino de Oliveira ◽  
Iana Alexandra Alves Rufino ◽  
John Elton de Brito Leite Cunha ◽  
Rochele Sheila Vasconcelos ◽  
Higor Costa de Brito
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Growth ◽  
Land Use Planning ◽  
Quantitative Methods ◽  
Surface Albedo ◽  
Urban Expansion ◽  
Temporal Analysis ◽  
Urban Land ◽  
Urban Land Use

Cities keep growing, and in most of the cases this expansion process is hard to model and describe for planning actions. Quantitative methods are increasingly used to help planning, monitoring, and regulating urban land-use processes. Remote sensing images series are making possible different types of spatial-temporal analysis of the Earth surface. Surface albedo is a remote sensing product acquired in a long series of satellite images such as Landsat (more than 40 years of observation). Those analyses allow measuring waterproofed areas for urban drainage studies, as well as monitoring urban spreading patterns, growth vectors, and issues related to comfort and environmental quality, as well as about land use and land-use planning (directives for master plans) among others. This article shows the direct applicability of surface albedo changes as an indicator of urban land-cover changes. The current study analyzed the urban area of Petrolina County (PE) in the following periods: 2001 and 2006, 2006 and 2011, and 2011 and 2017. Such analysis uses the surface albedo variation along the time and results showed a strong correlation between increased surface albedo and urban expansion. Besides, it enabled to observe the relation between the high urban growth in the 2011-2017 period and the urban spot expansion by 14% (approximately 590 thousand square meters of territorial extension). The Urban development stood out in the Northern and Southwestern regions of Petrolina County.

scholarly journals Assessment and Spatial-Temporal Evolution Analysis of Urban Land Use Efficiency under Green Development Orientation: Case of the Yangtze River Delta Urban Agglomerations

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 715
Author(s):  
Yingkai Tang ◽  
Kun Wang ◽  
Xuanming Ji ◽  
He Xu ◽  
Yangqing Xiao
Keyword(s):  
Land Use ◽  
Urban Development ◽  
Evaluation System ◽  
Yangtze River Delta ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Efficiency ◽  
Green Development ◽  
Use Efficiency ◽  
Development Orientation

Rapid urbanization has provided a strong impetus for the economic growth of China, but it has also caused many problems such as inefficient urban land use and environmental pollution. With the popularization of the concept of green and sustainable development, the Environmental-Social-Governance (ESG) assessment concept is widely accepted. The government and residents are paying more and more attention to environmental issues in urban development, and environmental protection has formed an important part of urban development. In this context, this study takes 26 cities in the Yangtze River Delta as examples to build an evaluation system for urban land-use efficiency under green development orientation. The evaluation system takes into account the inputs of land, capital, labor, and energy factors in the process of urban development. Based on emphasizing economic output, the social benefits and undesired outputs brought about by urban development are taken into account. This paper measures urban land use efficiency by the super-efficiency SBM model, and on this basis, analyses the spatial-temporal evolution characteristics of urban land-use efficiency. Further, this paper measures urban land use efficiency without considering undesired outputs and compares the two evaluation methods. Again, the comparison illustrates the rationality of urban land use efficiency evaluation system under green development orientation.

scholarly journals Current and Future Land Use Characters of a National Central City in Eco-Fragile Region—A Case Study in Xi’an City Based on FLUS Model

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 286
Author(s):  
Dingrao Feng ◽  
Wenkai Bao ◽  
Meichen Fu ◽  
Min Zhang ◽  
Yiyu Sun
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Urban Development ◽  
Urban Expansion ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Pattern Change ◽  
Land Use Dynamics ◽  
The Future ◽  
Xi’An City

Land use change plays a key role in terrestrial systems and drives the process of ecological pattern change. It is important to investigate the process of land use change, predict land use patterns, and reveal the characteristics of land use dynamics. In this study, we adopted the Markov model and future land use (FLUS) model to predict the future land use conditions in Xi’an city. Furthermore, we investigated the characteristics of land use change from a novel perspective, i.e., via establishment of a complex network model. This model captured the characteristics of the land use system during different periods. The results indicated that urban expansion and cropland loss played an important role in land use pattern change. The future gravity center of urban development moved along the opposite direction to that from 2000 to 2015 in Xi’an city. Although the rate of urban expansion declined in the future, urban expansion remained the primary driver of land use change. The primary urban development directions were east-southeast (ENE), north-northeast (NNE) and west-southwest (WSW) from 1990 to 2000, 2000 to 2015, and 2015 to 2030, respectively. In fact, cropland played a vital role in land use dynamics regarding all land use types, and the stability of the land use system decreased in the future. Our study provides future land use patterns and a novel perspective to better understand land use change.

scholarly journals Recession, Local Fertility, and Urban Sustainability: Results of a Quasi-Experiment in Greece, 1991–2018

2021 ◽  
Vol 13 (3) ◽  
pp. 1052
Author(s):  
Rares Halbac-Cotoara-Zamfir ◽  
Gianluca Egidi ◽  
Rosanna Salvia ◽  
Luca Salvati ◽  
Adele Sateriano ◽  
...  
Keyword(s):  
Urban Expansion ◽  
Urban Sustainability ◽  
Low Fertility ◽  
Fertility Rates ◽  
Economic Expansion ◽  
Metropolitan Regions ◽  
Advanced Economies ◽  
Macro Scale ◽  
Economic Downturns ◽  
Quasi Experiment

Fertility is a spatially non-stationary property of regional demographic systems. Despite the wealth of quantitative (micro–macro) information delineating short-term population dynamics in advanced economies, the contribution of economic downturns to local fertility has still been under-investigated along urban–rural gradients, especially in low-fertility contexts. Recent studies have assumed suburban fertility rates as systematically higher than urban and rural fertility rates. This assumption (hereafter known as the “suburban fertility hypothesis”) has been grounded on stylized facts and spatial regularities in advanced economies that reflect a significant role of both macro (contextual) and micro (behavioral) factors that positively influence fertility in suburban locations. To test the suburban fertility hypothesis at the macro-scale, the present study compares gross fertility rates from seven regional units of the Athens metropolitan area between 1991 and 2018. A refined spatial analysis of gross fertility rates during an economic expansion (1999–2008) and recession (2009–2018) was carried out in 115 urban, suburban, and rural municipalities of the same area. Experiencing sequential waves of economic expansion and recession, Athens’ socio-demographic dynamics were considered a sort of “quasi-experiment” for Southern Europe, linking late suburbanization with the multiple impacts of (rapid) economic downturns. Compared with both urban and rural locations, a higher fertility rate in suburban municipalities (15–20 km away from downtown Athens) was observed during the study period. However, a subtle distinction was observed during the economic expansion versus the recession. In the first period, the highest birth rates were recorded in industrial locations west of Athens, hosting economically disadvantaged communities with a relatively young population structure. With the recession, the highest fertility was associated with residential and service-specialized (wealthier) locations east of Athens, attracting resident population from neighboring areas, and better responding to crisis. The results of our study document how recent urban expansion and economic downturns have intrinsically shaped fertility dynamics, with implications for urban sustainability and social cohesion of metropolitan regions.

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