Delineation of urban growth boundary based on FLUS model under the perspective of land use evaluation in hilly mountainous areas

With rapid economic development,the size of urban land in China is expanding dramatically.The Urban Growth Boundary(UGB)is an expandable spatial boundary for urban construction in a certain period in order to control the urban sprawl.Reasonable delineation of UGB can inhibit the disorderly spread of urban space and guide the normal development of the city.It is of practical significance for the construction of green urban space.The study utilizes GIS technology to establish a land construction suitability evaluation system for Nankang city,which is experiencing rapid urban expansion,and outlines the preliminary UGB under the future land use simulation(FLUS)model.At the same time,considering the coupled coordination of"Production-Living-Ecological Space",and based on the suitability evaluation,we revised the preliminary UGB by combining the advantages of the patch-generating land use simulation(PLUS)model and the convex hull model to delineate the final UGB.The results show that:1)the comprehensive score of the evaluation of the suitability of the construction of land from high to low shows the distribution of the center of the city to the surrounding circle type spread,the center of the city has the highest suitability score.The results of convex hull model show that the urban expansion type of Nankang is epitaxial.In the future,the urban expansion will mainly occur in the northern part of the city.The PLUS model predicts an increase of 3359.97 hm^(2)of construction land in Nankang by 2035,of which 2022.97 hm^(2)is urban construction land.2)The FLUS model has a prediction accuracy of 86.3%and delineates a preliminary UGB area of 9215.07 hm^(2).3)We used the results of the construction suitability evaluation,PLUS model simulation results,and convex hull model predictions to revise the originally delineated UGB.The final delineated UGB area is 8895.67 hm^(2)and it is capable of meeting the future development of the study area.The results of the delineation can promote sustainable urban development,and the delineation methodology can provide a reference basis for the preparation of territorial spatial planning.

URBAN GROWTH, TRANSPORTATION SYSTEM AND COMMERCIALNETWORK OF BEIJING

In this afticle, three uopt problems on the developlnent and plabong of Beijing metropolis are expounded (1) Having analyzed the process of urbanlzation dunng 45 years, the autihor divides it into three Stages :city expansion, qrban sprawl and fonmation of centnpotal urban nngr. Then a rank-number-size law is pLif fotward to predict the development and allocation of satellite towns (2) Having looked back on the change of urban transpoftation nforork, the atlthor points out its merits and demerits.According to the increases of traffic flow, improving measures for the urban road systems are demonstrated. (3) Having reviewed the llistory of commercial distnbution and referred to previous lnodels, the author roprds the spatial structure of business as a combined network from central place and idealized stnucture of lnetropolitan area. The trade and service orgaluzation in n1ain urban area and peripheral zone can be planned with defferent ways. The atlthor predicts a rational network of commerce and service of Beijing with a strong BCD Which is accepted by some trade authorities

THE RESEARCH ON MAXIMUM TURBIDITY OF YANGTZE RIVER ESTUARY AND URBAN GROWTH OF SHANGHAI USING TM CCT DATA

Based on the research on the diffusion of suspended sediments discharged outside of Yangtze River estuary and the landuse of Shanghai using Landsat MSS images in several years, the authors analysed the characteristics of TM CCT data of Shanghai scene, pointed out concrete range of maximum turbidity and growth of urban boundary of Shanghai through the information extraction.The feature vector combination method is used in the research process. The result is getting nice.

Urban Growth Modeling Using Neural Network Simulation: A Case Study of Dongguan City, China

Dongguan is an important industrial city, located in the Pearl River Delta, South China. Recently, Dongguan city experienced a rapid urban growth with the locational advantage by transforming from traditional agricultural region to modern manufacturing metropolis. The urban transformation became the usual change in China under the background of urbanization which belongs to one trend of globalization in the 21st century. This paper tries to analyze urban growth simulation based on remotely sensed data of previous years and the related physical and socio-economic factors and predict future urban growth in 2024. The study examined and compared the land use/cover (LUC) changes over time based on produced maps of 2004, 2009, and 2014. The results showed that water and forest area decreased since the past years. In contrast, the urban land increased from 2004 to 2014, and this increasing trend will continue to the future years through the urbanization process. Having understood the spatiotemporal trends of urban growth, the study simulated the urban growth of Dongguan city for 2024 using neural network simulation technique. Further, the figure of merit (FoM) of simulated map of 2014 map was 8.86%, which can be accepted in the simulation and used in the prediction process. Based on the consideration of water body and forest, the newly growth area is located in the west, northeast, and southeast regions of Dongguan city. The finding can help us to understand which areas are going to be considered in the future urban planning and policy by the local government.

Satellite remote sensing for urban growth assessment in Shaoxing City, Zhejiang Province

Urban growth represents specific response to economic, demographic and environmental conditions. Rapid urbanization and industrializations have resulted in sharp land cover changes. The present investigation was carried out from Shaoxing City to quantify satellite-derived estimates of urban growth using a three-epoch time series Landsat TM data for the years 1984, 1997 and ETM 2000. The methodology used was based on post classification comparison. The use of GIS allowed spatial analysis of the data derived from remotely sensed images. Results showed that the built-up area surrounding Shaoxing City has expanded at an annual average of 7 km2. Analysis of the classified map showed that the physical growth of urban area is upsetting the other land cover classes such as farming, water resources, etc. The study conclusion mainly emphasized the need for sustainable urban capacity.

Ecological suitability evaluation for urban growth boundary in red soil hilly areas based on fuzzy theory

The fuzziness exists in spatial distribution of geographic data of land suitability evaluation processes,which makes it difficult to quantify land boundaries by using traditional binary logic-based overlay model.Aiming at this limitation,an ecological suitability evaluation analysis model was presented based on fuzzy theory and a research on urban growth boundary(UGB) of the Great-Hexi Leading District(GHLD) of Changsha was conducted.With the support of GIS,RS and MATLAB,slope,elevation,vegetation,soil productivity,soil permeability,water body and land use are selected as the input of model according to the characteristic properties of soil and terrain in red soil hilly areas.The running result of this model indicates that the ratios of highly suitable land,suitable land,moderately suitable land and unsuitable land in GHLD are 18.75%,10.31%,64.16%,6.78%,respectively.This result accords with spatial structure worked out by Space Development Strategy Planning of GHLD,Based on this result,several suggestions are made to guide UGB developments in future.

Remote Sensing Data and SLEUTH Urban Growth Model:As Decision Support Tools for Urban Planning

Sri Lanka is experiencing speedy urbanization by converting the agriculture land and other natural land cover into built-up land. The urban population of Sri Lanka is expected to reach to 60% by 2030 from 14% in 2010. The rapid growth in urban population and urban areas in Sri Lanka may cause serious socioeconomic disparities, if they are not handled properly. Thus, planners in Sri Lanka are in need of information about past and future urban growth patterns to plan a better and sustainable urban future for Sri Lanka. In this paper, we analyzed the characteristics of past land use and land cover trends in Matara City of Sri Lanka from 1980 to 2010 to assess the historic urban dynamics. The land use change detection analysis based on remote sensing datasets reveal that the conversion of homestead/garden and paddy into urban land is evident in Matara City. The historic urban trends are projected into the near future by using SLEUTH urban growth model to identify the hot spots of future urbanization and as well as the urban growth patterns in Matara City up to the basic administrative level, i.e., Grama Niladari Divisions(GND). The urban growth simulations for the year 2030 reveal that 29 GNDs out of 66 GNDs in Matara City will be totally converted into urban land. Whereas, 28 GNDs will have urban land cover from 75% to 99% by 2030. The urban growth simulations are further analyzed with respect to the proposed Matara city development plan by the Urban Development Authority(UDA) of Sri Lanka. The results show that the UDA's city development plan of Matara will soon be outpaced by rapid urbanization. Based on the calibration and validation results, the SLEUTH model proved to be a useful planning tool to understand the near future urbanization of Sri Lankan cities.

A Spatially Heterogeneous Expert Based (SHEB) Urban Growth Model using Model Regionalization

Urbanization changes have been widely examined and numerous urban growth models have been proposed. We introduce an alternative urban growth model specifically designed to incorporate spatial heterogeneity in urban growth models. Instead of applying a single method to the entire study area, we segment the study area into different regions and apply targeted algorithms in each subregion. The working hypothesis is that the integration of appropriately selected region-specific models will outperform a globally applied model as it will incorporate further spatial heterogeneity. We examine urban land use changes in Denver, Colorado. Two land use maps from different time snapshots (1977 and 1997) are used to detect the urban land use changes, and 23 explanatory factors are produced to model urbanization. The proposed Spatially Heterogeneous Expert Based (SHEB) model tested decision trees as the underlying modeling algorithm, applying them in different subregions. In this paper the segmentation tested is the division of the entire area into interior and exterior urban areas. Interior urban areas are those situated within dense urbanized structures, while exterior urban areas are outside of these structures. Obtained results on this model regionalization technique indicate that targeted local models produce improved results in terms of Kappa, accuracy percentage and multi-scale performance. The model superiority is also confirmed by model pairwise comparisons using t-tests. The segmentation criterion of interior/exterior selection may not only capture specific characteristics on spatial and morphological properties, but also socioeconomic factors which may implicitly be present in these spatial representations. The usage of interior and exterior subregions in the present study acts as a proof of concept. Other spatial heterogeneity indicators, for example landscape, socioeconomic and political boundaries could act as the basis for improved local segmentations.

GIS and Remote Sensing to Investigate Urban Growth in Mafraq City/Jordan between 1987 and 2010

The spatial, temporal and spectral characteristics of the remote sensing data are effectively used in land use and land cover change mapping, hence helping in decision making for sustainable land resource management. The aim of the study is to map urbanization growth using satellite imagery, Google imagery and GIS in Mafraq city/North Jordan. Landsat imageries of 1987, 2005 and Google Earth (GeoEye-1) imagery of 2010 were used in GIS environment to map the change in the urbanization at Mafraq city. Maximum likelihood algorithm of supervised classification was used to delineate two land use and land cover classes for the study area, namely: populated areas and non-populated areas from 1987 and 2005 imageries. On-Screen digitizing was adopted on Google Earth (GeoEye-1) imagery of 2010 to map the populated areas. The main change observed for the time period of 1987-2010 was that the urbanized areas have increased approximately by 7.14 km2 (approximately 23% of the study area). The population density within the study area has increased from approximately 965 inhabitants per sq.km in 1987 to 1808 inhabitants per sq·km in 2005 and reached 2146 inhabitants per sq·km in 2010. The increase in the populated area within Mafraq city has impacted the surface hydrology runoff which leads to diverting some Wadis to avoid passing through the city centre. Also, the increase in urbanization in Mafraq city has put more pressures on the waste water treatment plant and solid waste dumpsite that serve Mafraq city.

A Century of Monitoring Urban Growth in Menofya Governorate, Egypt, Using Remote Sensing and Geographic Information Analysis

Urban growth is a global phenomenon mainly driven by the overpopulation growth particularly in developing countries like Egypt. Pattern and extent of urban growth could be monitored and modelled on a spatial and temporal dimension. GIS and remote sensing data along with other thematic maps were used to analyze the urban growth, pattern and extent in the last century in one of the biggest governorates at the heart of the Nile Delta of Egypt. Both spatial and temporal analyses enabled to identify the pattern of urban growth and subsequently project the nature of future growth. However, the overall urban growth in the last century was 12 times the original built up areas in 1910;the third stage from 1950 to 1972 was the highest stage of urban growth with 124% increase of the built-up area. The dominant pattern of urban growth was linear along highways and railways with majority to the North, North East and North West directions. The study developed a spatial model to project urban growth by 2027, indicating that urban growth in the Menofya Governorate would be continued at the same directions with the same pattern with an estimated increase of 33%. The study provided an understanding of the controlling factors which drove the urban growth along this long time.

GIS Integrated Spatio-Temporal Urban Growth Modelling: Colombo Urban Fringe, Sri Lanka

Urban growth is a continuous spatial expansion, and happens as a spatial-temporal process. This physical process influenced by various driving factors on the sub-systems within the main urban system. Analysing this spatial-temporal process and the influencing factors behind it is a substantial and essential task as it facilitates the local planning process. Previous studies were concerned with the individual effect of each driver on the main urban system rather than with the interactions between the drivers in the different sub-systems. This research aims to model urban growth and to consider the effect of the driving factors separately on the socio-economic, physical and environmental sub-systems. GIS based logistic regression modelling is used to model the fringe growth to find out the relationship between urban growth and its driving factors. These findings highlighted the positive and negative influencing factors in terms of, “where the growth should go?” and “how much of it should go?”. The factors in the socio-economic, physical, and environmental sub-systems can exert their influence in a positive or negative manner. The cumulative results of the various influences caused a unique pattern of growth in the Colombo urban fringe that is quite distinct from the pattern witnessed in other Asian countries.

THE ROLE OF RAILROAD IN THE DEVELOPMENT OF THE AMERICAN WEST—Railroad,Migration and Urban Growth

This paper explores the role of geographical expansion of railroads,one of the most important Fransporta-tion vehicles,in the history of American west development,analyses its implication on the unprecedented mi gration move-ment and the resulted urbanization i n the west and concludes with the fact that the appropriate interference b y the governm-net,especially in the early period,is vital to regional development pra ctice,because of market failure at t he initial stage,infrastructure constructio n conducted by the government always plays as the first impetus to any regional develop-ment process.Only through this brid ge,can some physical factors,such a s population,be attracted to feed th e back-ward area.As a result,cities grow fa st and the region develops well.The e xperience can be shared by all countr ies.Be-sides reviewing the history of west development in America,focusing on t he relationship between railroads e xpansion and urban growth,which was realized thr ough population migration.Acomparison on the particular pattern of regional develop-ment between U.S and China is made as well at the end.It is noted that despite of the common first impetus,govern-ment subsidies and the common final r esult,urbanization,the path for th e America is bottom-up,whereas that for China is top down,that is to say,developme nt should originate from big cities,then to towns,and finally radiate in to rural ar-eas.

Towards a Remote Sensing and GIS-Based Technique to Study Population and Urban Growth: A Case Study of Multan

In recent decades, the migration rates of the large cities of Punjab have been risen up to a considerable level due to the lack of employment opportunities as well as lack of facilities in the rural areas of the province. It has caused an unprecedented and unplanned urbanization across the urban areas of the province. This study has been undertaken to perform fractal analysis about the sprawl in rapidly growing city. GIS and remote sensing data have been used in this study as an emerging technology which is cost effective as well as accurate at the same time. Landsat images have been taken for the study and the sprawl has been calculated with the analysis of the data of each decade for past more than 40 years. It has been observed that the built up area is 47.8 to 141.12 Sq. Km whereas the pattern of urban settlement has been classified as clustered and linear, following the roads network. The temporal population growth also seconded these results. The population growth rate and population density increase, are based on the pixel based extraction of the data from satellite imagery for the period of 2000 to 2014, which is taken as a decision support tool. In 2000, the population of the district increased from 2,071,694 (1981 census) to 2,939,907 and then in 2013, it became 4,384,191 at a rate to 2.93% upturn per annum. Moreover, the study also reveals the extent of the growth of other land uses as well which may be taken as a reference that in an agricultural country like Pakistan, the natural resources are being wasted (by urbanization of the fertile land). There must be some master planning to avoid such things in the other cities as well.

Spatial Effects of Varying Model Coefficients in Urban Growth Modeling in Nairobi, Kenya

Urban land-use modeling has gained increased attention as a research topic over the last decade. This has been attributed to advances in remote sensing and computing technology that now can process several models simultaneously at regional and local levels. In this research we implemented a cellular automata (CA) urban growth model (UGM) integrated in the XULU modeling frame-work (eXtendable Unified Land Use Modeling Platform). We used multi-temporal Landsat satellite image sets for 1986, 2000 and 2010 to map urban land-use in Nairobi. We also tested the spatial effects of varying model coefficients. This approach improved model performance and aided in understanding the particular urban land-use system dynamics operating in our Nairobi study area. The UGM was calibrated for Nairobi and predicted development was derived for the city for the year 2030 when Kenya plans to attain Vision 2030. Observed land-use changes in urban areas were compared to the results of UGM modeling for the year 2010. The results indicate that varying the UGM model coefficients simulates urban growth in different directions and magnitudes. This approach is useful to planners and policy makers because the model outputs can identify specific areas within the urban complex which will require infrastructure and amenities in order to realize sustainable development.

Urban Growth Prediction Modelling Using Fractals and Theory of Chaos

Urban growth prediction has acquired an important consideration in urban sustainability. An effective approach of urban prediction can be a valuable tool in urban decision making and planning. A large urban development has been occurred during last decade in the touristic village of Pogonia Etoloakarnanias, Greece, where an urban growth of 57.5% has been recorded from 2003 to 2011. The prediction of new urban settlements was achieved using fractals and theory of chaos. More specifically, it was found that the urban growth is taken place within a Sierpinski carpet. Several shapes of Sierpinski carpets were tested in order to find the most appropriate, which produced an accuracy percentage of 70.6% for training set and 81.8% for validation set. This prediction method can be effectively applied in urban growth modelling, once cities are fractals and urban complexity can be successfully described through a Sierpinski tessellation.

Urban Growth Modelling Using Determinism and Stochasticity in a Touristic Village in Western Greece

Urban development has acquired an important magnitude in touristic places in Greece. Many villages, especially in seaside areas have adapted to touristic requirements by the necessary infrastructures and activities. Pogonia, located in Vonitsa Etoloakarnanias, is a village which has welcomed the opportunity of touristic development. As a result, the house settlements increased 57.5% during the last 8 years. Urban growth modelling using Artificial Neural Networks (ANNs) was applied in order to simulate the urban development in Pogonia village using two methods: determinism and stochasticity. The variables used for deterministic simulation were: distances to roads, urban areas and coastline, slope and elevation. It was found that urban development can be better described using the network of distances between all urban settlements (stochastic approach) rather than using determinism. This can be explained by the importance of the neighbourhood relationships and the interaction between urban settlements, occurred within the interconnected network of the self-organized urban system.

The Mechanism Behind Urban Population Growth and Shrinkage from the Perspective of Urban Network Externalities

Urban shrinkage is a global phenomenon,and it will coexist with urban growth for many years.At the same time,the network connection between cities continuously improved due to the construction of the transportation and information networks.However,the relationship between urban network externalities and urban population growth/shrinkage remains unclear.Therefore,based on high-speed railway(HSR)flow data,a spatial econometric model is used to explore the mechanism behind urban population growth and shrinkage from the perspective of network externalities in China.The results indicate that:1)the urban network experiences a certain clubbing effect.Growing cities that are strongly connected are concentrated along China’s main railway lines and the southeastern coastal areas,while shrinking cities that are weakly connected are distributed at the periphery of the network.2)Moreover,the network externality disregards spatial distance and together with the agglomeration externality influences the growth and shrinking of cities.3)Urban economic development still promotes the development of Chinese cities.However,the improvement of the urban economy has a negative cross-regional spillover effect on neighboring cities due to urban competition.4)Lastly,Local spillovers of urban network externalities are positive,while cross-regional ones are negative.Consequently,the government needs to promote the construction of multi-dimensional network connections between cities to promote cities’sustainable development.This study reveals the relationship between urban network externalities and urban development,enriches the theories of network externalities and urban growth/shrinkage,and provides a reference for regional coordinated development.

Urban growth dynamics and expansion forms in 11 Tanzanian cities from 1990 to 2020

With rapid urban expansion across Tanzania,there is a need to institute steps to address factors and forms as well as impacts and challenges associated with the observed trend.This study’s aim is to use spatial urban landscape indices to analyze the spatial changes in urban forms,patterns,and rates across 11 urban centers in Tanzania over a 30-year study period(1990–2020).During the past three decades,urban lands of 11 cities and town in Tanzania have grown by a total of 480 km2.Leapfrog growth was found as the most dominant form of urban expansion in Tanzania while Dodoma,the capital city of Tanzania,had the highest rate of urban expansion when compared to all other individual cities.The most robust and significant interaction of the AWMLEI and MLEI was found in Kigoma,Arusha,Mtwara,Mafinga,and Tunduma cities.In contrast,Mbeya agricultural city,Arusha the tourist city,Tabora,and Geita Lake zone areas did show their own peculiarities revealing an interesting spatial temporal variation in rate and form of expansion.The outcome of this study reveals that the influence and management of economic and socio-cultural opportunities will be an effective tool for the determination of the rapidly expanding cities and towns of Tanzania.

Does innovative city pilot policy promote urban green growth in China?An analysis of green total factor productivity,2005-2020

The innovative city pilot policy(ICPP)is an essential manifestation of China’s construction of an innovative and green-driven development country.We incorporated urban green total factor productivity(GTFP)growth into the evaluation of ICPP.Based on the panel data of 223 cities in China from 2005 to 2020,we used the difference-in-differences model to empirically assess the influence and mechanism of the ICPP on urban GTFP growth.The main results show that(i)The ICPP has maintained an effectively fluctuating promotion on urban GTFP growth,mainly manifested in the urban green technological progress improvement.(ii)The ICPP has urban heterogeneity in promoting GTFP growth in pilot cities,mainly affecting key cities such as provincial capitals.(iii)The interaction between the agglomeration of producer services and the ICPP inhibits GTFP growth in pilot cities.