Measurements of POI-based mixed use and their relationships with neighbourhood vibrancy

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An intelligent solution support system for spatial modelling and decision support

‘Modelling inside GIS’ has been widely researched over the years. This paper argues that such approach lacks appropriate model reusing and management functions because it is often domain-dependent. In this paper, we propose a ‘modelling outside GIS’ approach to design a model management module that can be incorporated with GIS and other systems to perform flexible model retrieval and development. As a first step, an intelligent solution support system (subsystem) that can assist users to select and construct appropriate models for their particular application domains is developed. Some essential mechanisms and procedures involved in the developing this system are proposed and demonstrated.published_or_final_versio

China’s Post-Reform Urbanization: Trends and Policies

Since the adoption of economic reform policy in 1978, several trends are changing the Chinese society. Chief among these is the rapid transition to an urbanized country. Not only is more than 1/3 the country’s population now living in cities and towns but the remaining is becoming increasingly dependent on cities and towns for its economic survival and livelihood. Chinese experts predict that by 2050, urban population is likely to reach 1.0-1.1 billion with urbanization level soaring up to over 75 percent and urban sector contributing to over 95 percent of the national economy. Accordingly, more than 600 million Chinese people will shift from rural areas to urban districts by 2050. Furthermore, projections shows that by 2050, there are likely to be 50 ultra-large cities with population of more than two million, some 150 big cities, 500 medium-sized cities and 1,500 small cities. While these figures are predictable, other forces such as globalization and regional integration will reinforced the role of cities as centers of production, consumption and social and political change. This chapter aims to unravel such changes and to examine issues related to these developments.postprintThe IIED‐UNFPA Research Workshop on Population and Urbanization Issues, London, 9-10 September 2009, IIED code: G0256

City repositioning and competitiveness building in regional development: New development strategies in Guangzhou, China

Competition among cities for mobile capital in the twenty-first century has intensified. The urban hierarchy of regions is undergoing transformation, causing economic fortunes to vary markedly among different localities. In China, these global forces and regional restructuring have caused a relative economic decline in some historically powerful cities, and have also brought about the emergence of new economic centers. In response to these forces, many Chinese cities have been driven into adopting a series of new competitive strategies, which seek to win back and build up their leading positions and competitiveness. To translate these strategies into concrete actions, local governments have promoted high-profile and face-lifting projects and investments. The extensive new urban development in Guangzhou is a particularly interesting case. As the provincial capital of the Guangdong Province, and a historically central city in the Pearl River Delta region, Guangzhou's importance has recently declined. This article attempts to reveal the general strategies and specific projects initiated in Guangzhou as important promotion devices in its revitalization program, and to examine the rationales behind them. The ambitious new strategies are most likely to occur under the 'soft budget constraint' syndrome in China, and these strategies could be risky. Although the extent to which these strategies actually do stimulate business and lure investment is yet to be seen, the citizens are immediately and directly benefiting from them and consequently they have gained much popularity and support. However, the competitiveness building in Chinese cities has called into question the legitimacy of local state governance, and the validity of large projects that lack financial discipline, social objectives and accountability for unsuccessful investments. © Joint Editors and Blackwell Publishing Ltd 2005.postprin

Interjurisdictional Cooperation through Bargaining: The Case of the Guangzhou–Zhuhai Railway in the Pearl River Delta, China

Interjurisdictional cooperation has emerged as a major recent trend in China in response to challenges from market reforms and globalization. However, given that cities are in fierce competition with one another, interjurisdictional cooperation presents many difficulties for policy making. This paper attempts to examine how cooperative partnerships can be developed, sustained, or even resisted. It uses the Guangzhou-Zhuhai Railway as a case study to explore the institutional configuration of such a practice and to understand how the historical contingencies and path-dependencies in a transitional society interact with intensive bargaining to influence partnership building. It argues that the lack of a formal institutional framework to facilitate horizontal networking forces actors to opt for ad hoc collaborative arrangements. With the objective of making joint projects workable, commitments for cooperation have to be negotiated on a case-by-case basis through extensive bargaining. Although this creates much flexibility in consensus building, it does not guarantee success: success depends on the interplay of inter-ministry politics, interscalar relations, intercity politics and state-market relations. To a certain extent, the Chinese state can go beyond economic logic and shore up its legitimacy by prioritizing development. The post-reform path-dependencies can provide current political leaders with more rather than fewer instruments with which to negotiate interjurisdictional projects, and thus have greater influence over urban and regional economic governance. © 2013 The China Quarterly.published_or_final_versio

Modeling of traffic data characteristics by Dirichlet Process Mixtures

Conference Theme: Green Automation Toward a Sustainable SocietyThis paper presents a statistical method for modeling large volume of traffic data by Dirichlet Process Mixtures (DPM). Traffic signals are in general defined by their spatial-temporal characteristics, of which some can be common or similar across a set of signals, while a minority of these signals may have characteristics inconsistent with the majority. These are termed outliers. Outlier detection aims to segment and eliminate them in order to improve signal quality. It is accepted that the problem of outlier detection is non-trivial. As traffic signals generally share a high degree of spatial-temporal similarities within the signal and between different types of traffic signals, traditional modeling approaches are ineffective in distinguishing these similarities and discerning their differences. In regard to modeling the traffic data characteristics by DPM, this paper conveys three contributions. First, a new generic statistical model for traffic data is proposed based on DPM. Second, this model achieves an outlier detection rate of 96.74% based on a database of 764,027 vehicles. Third, the proposed model is scalable to the entire road network. © 2012 IEEE.published_or_final_versio

利用主成分分析改善土地利用變化的遙感監測精度: 以珠江三角洲城市用地擴張為例

近年來,珠江三角洲由于經濟的快速發展,城市用地急劇增加。利用多時相的遙感圖象,可以定量地監測這種城市化的現象。但是,由一般的遙感動態監測方法所得的結果往往夸大變化的程度,以及獲得一些不合理的結論。該文提出利用主成分分析的方法來改善遙感動態監測的精度。將該方法應用于珠江三角洲發展最快的東莞市,獲得了較滿意的結果。The Pearl River Delta is experiencing a fast urban growth in recent years which is responsible for rapid loss of the valuable agricultural land in the region. There is a great need to monitor the urban expansion using remote sensing for urban planning and management purposes. However, it has been well recognized that there is significant over-estimation of land use change inusing multitemporal images in change detection. The problem is due to inadequate creation of classification signatures in the classification of remote sensing images. This paper presents an improved method using principal components analysis of stacked multi-temporal images. It is found that this method can reduce the errors in land use change detection and provide a very useful method in monitoring land use changes in the Pearl River Dalta

Role of the Built Environment in the Recovery From COVID-19: Evidence From a GIS-Based Natural Experiment on the City Blocks in Wuhan, China

The built environment closely relates to the development of COVID-19 and post-disaster recovery. Nevertheless, few studies examine its impacts on the recovery stage and corresponding urban development strategies. This study examines the built environment’s role in Wuhan’s recovery at the city block level through a natural experiment. We first aggregated eight built environmental characteristics (BECs) of 192 city blocks from the perspectives of density, infrastructure supply, and socioeconomic environment; then, the BECs were associated with the recovery rates at the same city blocks, based on the public “COVID-19-free” reports of about 7,100 communities over the recovery stages. The results showed that three BECs, i.e., “number of nearby designated hospitals,” “green ratio,” and “housing price” had significant associations with Wuhan’s recovery when the strict control measures were implemented. At the first time of reporting, more significant associations were also found with “average building age,” “neighborhood facility development level,” and “facility management level.” In contrast, no associations were found for “controlled residential land-use intensity” and “plot ratio” throughout the stages. The findings from Wuhan’s recovery pinpointing evidence with implications in future smart and resilient urban development are as follows: the accessibility of hospitals should be comprehensive in general; and the average housing price of a city block can reflect its post-disaster recoverability compared to that of the other blocks

Radius and chirality dependent conformation of polymer molecule at nanotube interface

Temperature dependent conformations of linear polymer molecules adsorbed at carbon nanotube (CNT) interfaces are investigated through molecule dynamics simulations. Model polyethylene (PE) molecules are shown to have selective conformations on CNT surface, controlled by atomic structures of CNT lattice and geometric coiling energy. PE molecules form entropy driven assembly domains, and their preferred wrapping angles around large radius CNT (40, 40) reflect the molecule configurations with energy minimums on a graphite plane. While PE molecules prefer wrapping on small radius armchair CNT (5, 5) predominantly at low temperatures, their configurations are shifted to larger wrapping angle ones on a similar radius zigzag CNT (10, 0). A nematic transformation around 280 K is identified through Landau-deGennes theory, with molecule aligning along tube axis in extended conformationsComment: 19 pages, 7 figure2, submitted to journa

Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: the case of Sana'a metropolitan city, Yemen.

An effective and efficient planning of an urban growth and land use changes and its impact on the environment requires information about growth trends and patterns amongst other important information. Over the years, many urban growth models have been developed and used in the developed countries for forecasting growth patterns. In the developing countries however, there exist a very few studies showing the application of these models and their performances. In this study two models such as cellular automata (CA) and the SLEUTH models are applied in a geographical information system (GIS) to simulate and predict the urban growth and land use change for the City of Sana’a (Yemen) for the period 2004–2020. GIS based maps were generated for the urban growth pattern of the city which was further analyzed using geo-statistical techniques. During the models calibration process, a total of 35 years of time series dataset such as historical topographical maps, aerial photographs and satellite imageries was used to identify the parameters that influenced the urban growth. The validation result showed an overall accuracy of 99.6 %; with the producer’s accuracy of 83.3 % and the user’s accuracy 83.6 %. The SLEUTH model used the best fit growth rule parameters during the calibration to forecasting future urban growth pattern and generated various probability maps in which the individual grid cells are urbanized assuming unique “urban growth signatures”. The models generated future urban growth pattern and land use changes from the period 2004–2020. Both models proved effective in forecasting growth pattern that will be useful in planning and decision making. In comparison, the CA model growth pattern showed high density development, in which growth edges were filled and clusters were merged together to form a compact built-up area wherein less agricultural lands were included. On the contrary, the SLEUTH model growth pattern showed more urban sprawl and low-density development that included substantial areas of agricultural lands