Abstract. The alarming rate of urbanization poses immediate problems to water resources management, mainly, but not limited to water supply, flood risk management, wastewater treatment and water quality control. Ideally, strategic planning of water systems should be fully aware of the prospects of future urban growth in order to maintain high reliability of services provided and satisfy customers in the long term. Typically, urban growth is handled in a static manner via the development of future scenarios based on previous urban planning studies. Generally, these scenarios focus solely on population increase and ignore the spatial allocation dynamics. Modern urban water strategic thinking needs to incorporate robust tools and methodologies in management practices, able to predict and quantify the outcome possibility of future urban growth. To cope with the aforementioned challenge, this study proposes a novel cellular automata urban growth model as well as, a supplementary remote sensing methodology to preprocess input data.
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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 Ex- pert Based (SHEB) model tested decision trees as the underlying modeling algorithm, applying them in dif- ferent subregions. In this paper the segmentation tested is the division of the entire area into interior and ex- terior 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 spa- tial representations. The usage of interior and exterior subregions in the present study acts as a proof of con- cept. Other spatial heterogeneity indicators, for example landscape, socioeconomic and political boundaries could act as the basis for improved local segmentations.
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coefficient and the transportation accessibility in the exclusion/attraction layer allows the model to capture the highly accessible urban growth areas. Meanwhile, incorporating planned urban development areas into the initial urban extent layer also helps predict the future urban structure and the new city construction pattern in the study area (Region C in Figs. 9 and 10). Basically, the embryonic form of the new city in the study area is emerging in the first five-year plan, and the new city will be completely constructed within the next two or three five-year plans. In this scenario, the plan and expectations of the new city center around the western high-speed railway are reflected more accurately than in the other two scenarios. However, edge proliferation still dominates the simulated growth in this area rather than the development of new urban centers, indicating that it is difficult for the model to capture this feature based on the historical data.
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a spatial data management tool which has been used in data pre-process, process and post-process stages. It can be considered as a pre-processor by generating input data derived from a variety of sources; also at each stage of analysis as a data management tool; and finally as a post- processor for data visualization and planning (Kumar et al. 2013). In this condition, remote sensing imageries are a reliable and accurate data sources which are valu- able for the analysis and modeling of urban status (Jensen and Cowen 1999; Batty and Howes 2001; Donnay et al. 2001; Herold et al. 2001; Clarke et al. 2002). Temporal fre- quency, availability of free to less expensive data sources of satellite imagery and image processing techniques have greatly enhanced the potential for monitoring and mapping urban growth and monitoring urban land use change (Goodchild 2000; Im et al. 2008), urban land use dynamics (Herold et al. 2003), landscape pattern analy- sis (Li and Yeh 2004), and urbanization (Weng 2007). Remote sensing data used in this research, comes from three satellite imageries in 1987, 2000 and 2006 from Landsat TM and ETM + (Fig. 4) with pixel sizes of 28.5
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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 imple- mented 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 ur- ban 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 mag- nitudes. 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.
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Abstract: Urban growth modelling cellular automata has blossomed due to the advancement in geographic information systems (GIS), remote sensing and computer technology. Among such urban growth models, our urban growth model (UGM), was modified from SLEUTH (Slope Land-use Transport Hill-shade) model. UGM has been integrated in the XULU modeling frame-work (eXtendable Unified Land Use Modelling Platform). In this research we evaluated a modified UGM whose transition rules were modified. In order to arrive at urban growth modelling, we used multi-temporal Landsat satellite image sets for 1987 and 2010 to map urban land-use in Nyeri. We compared our results with a normal UGM simulation. Thus, we arrived at two urban growth simulations for Nyeri in order to get a better glimpse of land-use system dynamics. Both models were calibrated and urban growth simulated until the year 2030 when Kenya plans to attain Vision 2030. Observed land-use changes in urban areas were compared to the results of both UGM models for the year 2010. The results indicate that the two models resulted in urban growth in different directions and magnitudes. This approach is useful to planners as it gives the scenarios of using different transition rules of a cellular automata model in urban growth modelling.
There has been growing need for accurate assessment of urban growth so as to foster sustainable urban devel- opment strategy (Han, Hayashi, Cao, & Imura, 2009). This has resulted to development of urban growth models which are able to spatio-temporal simulate urban dynamics. Such models incorporate socio-economic and physical components at different scales so as to address challenges in urban planning and promote plausible ur- ban development paths. Our urban growth model (UGM) was implemented in the modelling platform XULU (Extendable Unified Land Use Modelling Platform) in a modified way (Goetzke & Judex, 2011). UGM uses cellular automata (CA) technique. CA serves as a paradigm for thinking about complex spatio-temporal phe- nomena and an experimental laboratory for testing ideas (Itami, 1994).
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due to the lack of time-series data that these facts have not received as much attention as has classical business cycle behavior. However, the type of lags assumed in the model and their duration are not easily ascertained. It seems that there exists here a new field for research in urban economics that could lead to a different view of available data and different answers to current urban problems. It seems reasonable to simulate, urban
To interact with urban growth model, the human involvement simulation should be capa- ble of responding with the landowners’ decisions while retrieving sufficient information for both the internal(landowner) and the external(environment) properties. With more information considered, a simulating module could always generate better predictions. In our design of the agent-based model, we fully considered the heterogeneity of the model, each agent on the map is an autonomous individual [ Zha16 ] . The system level behaviors emerge from the micro-level interactions of the agents. Therefore, it could depict the whole simulation procedure with the details of different levels, specifically reasoning how and when a decision is made by the landowners. Also, ABM aggregates all the information of its constituent elements and measure the outcomes in the system level over time.
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The study of land use change simulated with the CA-Markov approach, on remote sensing data was used to evaluate changing land use in developing areas. Even though the accuracy of the overall area is not good, the results for a small area, such as a dense residential area, are satisfactory. However, this study represents other factors, such as the government policy needed as an essential element in the analysis of an urban area. The pattern of urban expansion by transportation, along with the government development policy in 2016, has been the most effective. In the future, there will be more policies to develop other areas, such as an economic one-stop service center , so that the pattern of urban development will be different, especially economically.
It is important here to avoid viewing exchange value as an abstract or predetermined economic relation. Rather, the growth machine thesis posits exchange value as a product of concerted activities on the part of various actors to make money off real estate. Since land property, like labor, is not produced but something existing in finite amount, the market for land is intrinsically monopolistic. One parcel of land does not usually perfectly substitute for another. But by working to change the content of their property (e.g. by influencing zoning), and ensuring certain qualities or conditions exist in relation to it (e.g. transport, services, policing, the uses of surrounding properties), land owners commodify place and therefore enhance the possible rent they can derive from their particular slice of the property market. It is this exchange- seeking activity that designates a particular type of actor hypothesized to be at the core of place commodification: the place entrepreneur.
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For 4 and 8-state codes, it can be observed that, whatever the number of receiver antennas, the TCM- UGM/STBC and TCM/STBC present approximately the same performance in sense of BER (see fig. 5 and fig. 6), and a little advantage for TCM-UGM in sense of FER (see fig. 7 and fig. 8). For 16 and 32-state codes, it can be observed that TCM-UGM/STBC presents better performance in sense of BER and FER. The most remarkable result is realized using 16-state TCM-UGM encoder, where its performance outperforms that of 32- state TCM; e.g., in fig. 7, a gain of 0.5 dB can be obtained at FER of 2.10 -3 .
In the contemporary cities that are always subject to changes and developments, unmethodical expansion, and constant addition of components the form too, faces new challenges and problems. In this connection Dr. Nasr writes: “Our traditional architecture and urban development were seriously damaged by imitating European architecture and urban planning. Almost all of the new constructions are ugly. The majority of the new buildings are terrible as far as Indian traditional culture and aesthetics, social and human relations that Islam has publicized, and their impacts on natural environment are concerned” (Nasr, 1995).
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Today, obstacles such as air pollution, traffic congestion, and high transport expenses, etc. have led to lower quality of life in cities, especially in metropolitan areasand struggle to accommodate more growth and development though the city has its own potential for growth. For this reason, it has been many years to come up with solutions to improve this situation by the experts of urban authorities.One of the ways which can solve this issue is the use of public transport with transit- oriented development.The goal of this paper is to consider the challenges of the use of public transport with transit-oriented development (TOD) specifically with the emphasis on the use of bus and rail transportusing a descriptive-analytical method.The main question is, whether TOD can be used as a good solution to the current problems of the cities? The hypothesis is, whether using TOD can improve the current situation of cities to some extent or not?The result is that both methods have advantages and disadvantages.For instance, the use of Bus and BRT is suitable for smaller population size lower population density areas and less costly for implementation and operation. But successful implementation of TOD based on the bus is more difficult for longer cities than an implementation of TOD based on rail. Also, the cost of implementing rail transport during the implementation the project costishigh, but fora longtime, this will be beneficial for the city.Hence, this paper attempted to create a dynamic, energetic, and vibrant central business district in urban areas through integration with other land use and transport-oriented development.
Most Indian literature (Sridhar, 2010; Mathur, 2005; Mills and Becker, 1986; Narayana, 2009) have mainly focused on finding the determinants of urban population concentration and seeing whether urban concentration has declined or increased over the period, in different class of cities. Also some studies (Lall and Mengistae, 2005; Lall and Rodrigo, 2001; Lall et al., 2004) explore the determinants of urban agglomeration and urban economic development in India through the indices of industrialization. Sridhar (2010) analyzes and estimates determinants of city growth and output at the district level as well as city level in India. In city level analysis, the study finds that proximity to a large city, or turning away from agriculture towards manufacturing by its populace encourages a city to become larger. In addition, the author finds that existence of urban land ceiling act deters city growth by artificially creating scarcity of urban land.
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them to afford "quality" care at prohibitive costs. With more than a dozen taxa with proven medicinal properties (Mangifera indica, Spondias mombin, Annona muricata, Ceiba pentandra, Dacryodes edulis, Senna siamea, Terminalia superba, Persea americana, Ficus vogeliana, Elaeis guineensis, Millettia laurentii, Millettia versicolor), urban floriculture is a rampart against disease [3, 38]. Indeed, the many tangible signs of anthropogenic debarking confirm the perception and expectations of populations [11-12]. However, this activity, which is beneficial to human well-being, affects the tree population by disrupting their metabolism and exposing internal organs to pathogenic microorganisms and boring insects [11-12].
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Parking: A park is a piece of land or terminal where public passenger vehicles or other vehicles may be parked. Faulks (1980) defines parking lot as outdoor lot for parking automobiles. But in the study area, parking is mostly along the roads or streets, of the study area. It has been observed that lack of proper parking facilities could lead to congestion; it is one of the many problems confronting a lot of people in the urban areas, as vehicle owners require space to park their vehicles but when this space is not available, they seem to park any how or anywhere. This causes obstruction and congestion which leads to delays in journey movement. People who go into shops or supermarkets are asked to park their vehicles on nearby lanes. Most office buildings or premises do not allow parking of vehicles in their buildings except one has an office there, all these result in on-street parking. Most times, drivers are asked to park on one side of the road, but the Table 5 shows location of public parks in Owerri
After processing the model, we obtain the parameters of best coefficient data and fit coefficient data which can be seen in Table 3. From this table we can see the urban expansion in Yilan City is a mixture of spread and road gravity expansion. The urban expansion of Luodong is mainly by spread, but is resisted by slope. The reason for the urban expansion of these two cities is probably due to the government using both as centers for local development. The function of Yilan city is as an administrative center and a center for culture. Luodong is a center for light industry such as logging, and therefore attracts workers from the surrounding countryside. By contrast, the expansion of Suao is by breed and road gravity expansion, but strongly resisted by slope.
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Extra details could also be included in an improved transport-based model, such as different modal weights w for different regions of the study area, or transport networks evolving over time. The functionality to introduce changes to the network at specified time steps during a simulation is already implemented, but has not been used due to a lack of data. Since Belgium already has a dense network, there are likely to be few additions to the network, but a growing population and increased congestion could reduce travel speeds in the future, and road characteristics could change. Congestion scenarios of transport models can therefore provide useful input for the model. It would be an interesting exercise to couple our activity based CA model directly to a transport model in order to get simultaneous predictions of activities, land uses and transport for the future. On the other hand, we fear that a direct coupling would increase the computation time drastically.
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Abstract: In view of urban sprawl brought about by urbanization development, this paper establishes a weighted comprehensive evaluation model to measure the city’s smart growth status. Bordeaux is selected as the research object, and relevant data are collected and processed. The data is then substituted into the established model to solve the problem. The results show that some indicators in the city are still at a poor level. Combining the indicators with higher weights and lower scores in the evaluation results, a better urban smart growth plan was proposed. Finally, the ARIMA forecasting model is used to predict the indicators in the future more than ten years. The results verify the effectiveness of the urban smart growth plan and the potential of the plans.