scholarly journals ANALYZING AND MODELING THE SPATIOTEMPORAL DYNAMICS OF URBAN EXPANSION: A CASE STUDY OF HANGZHOU CITY, CHINA

2019 ◽  
Vol 27 (4) ◽  
pp. 228-241
Author(s):  
Jie Zhao ◽  
Wenfu Yang ◽  
Junhuan Peng ◽  
Cheng Li ◽  
Zhen Li ◽  
...  
Keyword(s):  
Urban Development ◽  
Spatial Pattern ◽  
Urban Expansion ◽  
Urban Land ◽  
Spatiotemporal Dynamics ◽  
Sustainable Urban Development ◽  
Spatial Metrics ◽  
Spatiotemporal Characteristics ◽  
Ca Model ◽  
Coordination Development

Understanding the spatiotemporal characteristics of urban expansion is increasingly important for assisting the decision making related to sustainable urban development. By integrating remote sensing (RS), spatial metrics, and the cellular automata (CA) model, this study explored the spatiotemporal dynamics of urban expansion and simulated future scenarios for Hangzhou City, China. The land cover maps (2002, 2008, and 2013) were derived from Landsat images. Moreover, the spatial metrics were applied to characterize the spatial pattern of urban land. The CA model was developed to simulate three scenarios (Business-As-Usual (BAU), Environmental Protection (EP), and Coordination Development (CD)) based on the various strategies. In addition, the scenarios were further evaluated and compared. The results indicated that Hangzhou City has experienced significant urban expansion, and the urban area has increased by 698.59 km2. Meanwhile, the spatial pattern of urban land has become more fragmented and complex. Hangzhou City will face unprecedented pressure on land use efficiency and coordination development if this historical trend continues. The CD scenario was regarded as the optimized scenario for achieving sustainable development. The findings revealed the spatiotemporal characteristics of urban expansion and provide a support for future urban development.

scholarly journals Spatial differences and pattern evolution of Multi-scale Urban Land between China and India

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Qinke Sun ◽  
Liang Zhou ◽  
Xuewei Dang ◽  
Bowei Hu ◽  
Haowei Mu
Keyword(s):  
Urban Development ◽  
Spatial Pattern ◽  
Regional Development ◽  
Urban Expansion ◽  
Urban Land ◽  
Expansion Rate ◽  
Low Level ◽  
Multi Scale ◽  
China And India ◽  
High Level

<p><strong>Abstract.</strong> “The dragon and the elephant” between China and India is an important manifestation of global multipolarization in the 21st century. As an engine of global economic growth, China and India have similar development processes, different development models as well as differences in urban development, which have attracted widespread attention from scholars. Based on the 1992&amp;ndash;2012 consecutive annual nighttime lighting data (DMSP-OLS), this paper uses the Gini coefficient, the Getis-Ord Gi* index and the Compounded Night Light Index (CNLI) to conduct a multi-scale comparative analysis of the differences in urban development between China and India from the perspective of geospatial. The results show that: (1) The space of urban land in the two countries expanded rapidly, with an average annual expansion rate of 5.24% and 3.85% respectively. China's urban land expansion rate is 1.36 times that of India. Among them, the arid resource towns in northwest China and the resource towns in central India have recently developed rapidly. (2) India’s imbalance in development is more prominent than China’s. China's regional and provincial imbalances are narrowing, while the regional differences in India are gradually widening. (3) The spatial pattern of land use in both countries shows a certain degree of coastal and inland differences. The main spatial pattern of China's regional development is the difference between East-Central-West, while the spatial pattern of regional development in India is North-South difference. (4) The strength of the expansion of the core cities of the two countries is quite different. From 1997 to 2007, China's core urban expansion intensity remained at a relatively high level while India was at a relatively low level. But from 2007 to 2012, India's core cities expanded at a relatively high level while China was at a relatively low level.</p>

scholarly journals Comparison on Multi-Scale Urban Expansion Derived from Nightlight Imagery between China and India

2019 ◽  
Vol 11 (16) ◽  
pp. 4509 ◽  
Author(s):  
Liang Zhou ◽  
Qinke Sun ◽  
Xuewei Dang ◽  
Shaohua Wang
Keyword(s):  
Urban Development ◽  
Spatial Pattern ◽  
Regional Development ◽  
Urban Expansion ◽  
Central India ◽  
Urban Land ◽  
Expansion Rate ◽  
Multi Scale ◽  
China And India ◽  
The Difference

“The Dragon and the Elephant” between China and India is an important manifestation of global multipolarization in the 21st century. As engines of global economic growth, the two rising powers have followed similar courses of development but possess important differences in modes of development and urban development, which have attracted the widespread attention of scholars. From a geospatial perspective, and based on continuous annual night light data (Defense Meteorological Satellite Program-Operational Linescan System, DMSP-OLS) from 1992 to 2012, this paper conducts a multi-scale comparative analysis of urban development differences between China and India by employing various approaches such as the Gini coefficient, Getis–Ord Gi* index, and the Urban Expansion Intensity Index (UEII). The results show that: (1) The urban land space of the two countries expand rapidly, with the average annual expansion rate of China and India being 5.24% and 3.85%, respectively. The urban land expansion rate in China is 1.36 times faster than that in India. Resource-typed towns in arid northwest China and the resource-typed towns in central India have developed rapidly in recent years. (2) The unbalanced development in India is more prominent than in China; and the regional and provincial development imbalances in China are shrinking, while India’s imbalances are improving slowly and its regional differences are gradually widening. (3) The spatial pattern of land use in both countries shows significant coastal and inland differences. The difference between the east, the central regions, and the west is the main spatial pattern of China’s regional development, while the difference between the north and the south is the spatial pattern of India’s regional development. (4) There are obvious differences in the expansion intensity of core cities between the two countries. From 1997 to 2007, the expansion intensity of core cities in China was relatively higher than that in India, while that in India was relatively higher than that in China from 2007 to 2012.

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

2021 ◽  
Vol 13 (4) ◽  
pp. 766
Author(s):  
Yuanmao Zheng ◽  
Qiang Zhou ◽  
Yuanrong He ◽  
Cuiping Wang ◽  
Xiaorong Wang ◽  
...  
Keyword(s):  
Urban Development ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Development Planning ◽  
Urban Land ◽  
Sustainable Urban Development ◽  
Land Use Patterns ◽  
Water Index ◽  
Nighttime Light

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.

scholarly journals Evaluating the Suitability of Urban Expansion Based on the Logic Minimum Cumulative Resistance Model: A Case Study from Leshan, China

2019 ◽  
Vol 8 (7) ◽  
pp. 291 ◽  
Author(s):  
Haijun Wang ◽  
Peihao Peng ◽  
Xiangdong Kong ◽  
Tingbin Zhang ◽  
Guihua Yi
Keyword(s):  
Urban Development ◽  
Evaluation System ◽  
Urban Expansion ◽  
Ecological Impacts ◽  
Sustainable Urban Development ◽  
Expansion Process ◽  
Mountain Areas ◽  
Resistance Factors ◽  
Ecological Barriers

This paper focuses on the suitability of urban expansion in mountain areas against the background of accelerated urban development. Urbanization is accompanied by conflict and intense transformations of various landscapes, and is accompanied by social, economic, and ecological impacts. Evaluating the suitability of urban expansion (UE) and determining an appropriate scale is vital to solving urban environmental issues and realizing sustainable urban development. In mountain areas, the natural and social environments are different from those in the plains; the former is characterized by fragile ecology and proneness to geological disasters. Therefore, when evaluating the expansion of a mountain city, more factors need to be considered. Moreover, we need to follow the principle of harmony between nature and society according to the characteristics of mountain cities. Thus, when we evaluate the expansion of a mountain city, the key procedure is to establish a scientific evaluation system and explore the relationship between each evaluation factor and the urban expansion process. Taking Leshan (LS), China—a typical mountain city in the upper Yangtze River which has undergone rapid growth—as a case study, the logic minimum cumulative resistance (LMCR) model was applied to evaluate the suitability of UE and to simulate its direction and scale. The results revealed that: An evaluation system of resistance factors (ESRFs) was established according to the principle of natural and social harmony; the logic resistance surface (LRS) scientifically integrated multiple resistance factors based on the ESRF and a logic regression analysis. LRS objectively and effectively reflected the contribution and impact of each resistance factor to urban expansion. We found that landscape, geological hazards and GDP have had a great impact on urban expansion in LS. The expansion space of the mountain city is limited; the area of suitable expansion is only 23.5%, while the area which is unsuitable for expansion is 39.3%. In addition, it was found that setting up ecological barriers is an effective way to control unreasonable urban expansion in mountain cities. There is an obvious scale (grid size) effect in the evaluation of urban expansion in mountain cities; an evaluation of the suitable scale yielded the result of 90 m × 90 m. On this scale, taking the central district as the center, the urban expansion process will extend to the neighboring towns of Mianzhu, Suji, Juzi and Mouzi. Urban expansion should be controlled in terms of scale, especially in mountain cities. The most suitable urban size of LS is 132 km2.This would allow for high connectivity of urban-rural areas with the occupation of relatively few green spaces.

scholarly journals SPATIAL PATTERN OF SUSTAINABLE URBAN DEVELOPMENT INDICATOR FOR THE MONTREAL URBAN COMMUNITY

2015 ◽  
Vol 39 (4) ◽  
pp. 220-231 ◽  
Author(s):  
Shohel Reza Amin ◽  
Umma Tamima
Keyword(s):  
Sustainable Development ◽  
Urban Development ◽  
Spatial Pattern ◽  
Spatial Data ◽  
Urban Community ◽  
Spatial Data Analysis ◽  
Sustainable Urban Development ◽  
Development Indicator ◽  
Development Plans ◽  
The City

The City of Montreal initiated a First Strategic Plan for Sustainable Development in 2005 followed by a Community and Corporate Sustainable Development Plan in 2010–2015. This study proposes a sustainable urban development indicator (SUDI) for each Montreal Urban Community (MUC) to evaluate the achievements of sustainable development plans. This study identifies thirty-two variables as the attributes of sustainable urban development. The multivariate technique and Exploratory Spatial Data Analysis are applied to determine the spatial pattern of SUDI for each MUC. The spatial pattern of SUDI identifies that Ville Marie, Verdun, Sud-Ouest, Mercier-Hochelaga-Maisonneuve and Plateau Mont-Royal have strong sustainable development. The findings of this study help the City of Montreal to understand the improvement of the sustainable development plans for Montreal city and to distribute the municipal budget for the community benefits accordingly.

scholarly journals MCR-Modified CA–Markov Model for the Simulation of Urban Expansion

2018 ◽  
Vol 10 (9) ◽  
pp. 3116 ◽  
Author(s):  
Xiuquan Li ◽  
Meizhen Wang ◽  
Xuejun Liu ◽  
Zhuan Chen ◽  
Xiaojian Wei ◽  
...  
Keyword(s):  
Land Use ◽  
Markov Model ◽  
Metropolitan Area ◽  
Urban Expansion ◽  
Ecological Factors ◽  
Sustainable Urban Development ◽  
Ecological Regions ◽  
Ca Model ◽  
Wuhan Metropolitan Area ◽  
Mcr Model

Ecosystem balance is an important factor that affects healthy and sustainable urban development. The traditional cellular automata (CA) model considers only a few ecological factors, however, the MCR model can account for ecological factors. In previous studies, few ecological factors were added to the CA model. Thus, the minimal cumulative resistance (MCR) model is combined with the CA and Markov models for the simulation of urban expansion. To verify the reliability of the method, the Wuhan metropolitan area was selected as a representative urban area, and its expansion in the past and future was simulated. Firstly, seven influential factors were selected from the perspective of location theory. The transformation rules of the comprehensive resistance surface followed by the modified CA–Markov model were constructed on the basis of the MCR model. The expansion of the Wuhan metropolitan area in 2013 was simulated on the basis of the 1996 and 2006 maps of land-use status, and the kappa coefficient was used as an index to evaluate the accuracy of the proposed method. Then, the expansion of the Wuhan metropolitan area in 2020 was simulated. Finally, the simulation results obtained with and without the MCR model were compared and analysed from the macro- and micro levels. Results show that the prediction accuracy of the two models differed for ecological regions, such as woodlands and water bodies. The similarities between the regions that were overestimated and underestimated by the MCR-modified CA–Markov model and non-MCR model may be attributed to solution of the land-use transfer matrix with the Markov model. The accuracy of the MCR-modified CA–Markov model for predicting forests, water and other ecological regions was higher than that of the Markov model. Therefore, the proposed MCR-modified CA–Markov model has potential applications in environmentally-conscious urban expansion.

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 Big Science, Ethics, and the Scalar Effects of Urban Planning

2020 ◽  
Vol 5 (4) ◽  
pp. 217-226
Author(s):  
Sandra Kopljar
Keyword(s):  
Land Use ◽  
Urban Development ◽  
Large Scale ◽  
Agricultural Land ◽  
Materials Science ◽  
Urban Expansion ◽  
Sustainable Urban Development ◽  
Planning Strategy ◽  
Urban Level ◽  
Research Facilities

The urban expansion currently under development around the two materials science facilities MAX IV and European Spallation Source in Lund, Sweden, surrounds two meticulously designed research facilities steered by global demands. The new urban area, together with the research facilities dedicated to science and the development of knowledge, expands the city of Lund onto high-quality agricultural land. In doing so, the municipal planning is attempting to align contemporary ideas of sustainable urban development with large-scale scientific infrastructure. This actualizes an ethical dilemma as the urban expansion onto productive agricultural land overrides previous decisions taken by the municipality regarding land use. It can also be understood as going against national land use policy which states that development on productive agricultural land should be avoided. As the planning stands today, the research facilities heavily push local urban development into the area while the intended research outcomes primarily relate to a global research community tied to international scientific demands for materials science. Although the Brunnshög area is realized through a neutralizing planning strategy, thought to balance and compensate for the development on farmland, the effects of the counterbalancing acts are primarily played out at a local urban level in terms of diverse, exciting, and locally sustainable neighbourhoods. The land use protection policies meant to secure national food production rather operates on a national scale. The argument made in this text is that sustainable development, and the intended balancing acts it involves, ought to be carefully considered in terms of scalar effects. Sustainable planning<em> </em>effects’ <em>scalar extent</em> should be taken into account through careful assessment of the step between good intentions and expected outcomes.

scholarly journals Past and Future Trajectories of Farmland Loss Due to Rapid Urbanization Using Landsat Imagery and the Markov-CA Model: A Case Study of Delhi, India

2019 ◽  
Vol 11 (2) ◽  
pp. 180 ◽  
Author(s):  
Junmei Tang ◽  
Liping Di
Keyword(s):  
Transition Probabilities ◽  
Urban Expansion ◽  
Sustainable Urban Development ◽  
Landsat Images ◽  
Rapid Urbanization ◽  
The Past ◽  
Farmland Loss ◽  
Rate Of Increase ◽  
Multi Temporal ◽  
Ca Model

This study integrated multi-temporal Landsat images, the Markov-Cellular Automation (CA) model, and socioeconomic factors to analyze the historical and future farmland loss in the Delhi metropolitan area, one of the most rapidly urbanized areas in the world. Accordingly, the major objectives of this study were: (1) to classify the land use and land cover (LULC) map using multi-temporal Landsat images from 1994 to 2014; (2) to develop and calibrate the Markov-CA model based on the Markov transition probabilities of LULC classes, the CA diffusion factor, and other ancillary factors; and (3) to analyze and compare the past loss of farmland and predict the future loss of farmland in relation to rapid urban expansion from the year 1995 to 2030. The predicted results indicated the high accuracy of the Markov-CA model, with an overall accuracy of 0.75 and Kappa value of 0.59. The predicted results showed that urban expansion is likely to continue to the year of 2030, though the rate of increase will slow down from the year 2020. The area of farmland has decreased and will continue to decrease at a relatively stable rate. The Markov-CA model provided a better understanding of the past, current, and future trends of LULC change, with farmland loss being a typical change in this region. The predicted result will help planners to develop suitable government policies to guide sustainable urban development in Delhi, India.

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