A new perspective on the temporal pattern of human activities in cities: The case of Shanghai

Time is a fundamental characteristic for understanding human activities. When analysing temporal pattern of a group of activities, most researchers tend to utilise one temporal attribute when representing time use of activities. Thus, temporal pattern of activities is usually visualised and understood as a profile of various observations listed sequentially over time. This paper aims to investigate the temporal pattern of activities in urban areas from a new perspective. Temporal pattern is visualised and analysed as the distribution of activity points in a two-dimensional temporal plane defined by the start and end time of activities as x and y axes. Kernel density estimation is used as a typical method to observe the temporal pattern of activities in Shanghai based on a one-week smart card dataset generated in the Shanghai's metro system. The results show that the proposed perspective can reveal considerably more information regarding the temporal pattern than a conventional one can.     

A relational exploratory study of business incubation and smart cities - Findings from Europe

This is a pioneering research linking two areas of knowledge which attract great attention from academia, industry, and governments: business incubation and smart cities. It is a quantitative exploratory study, whose purpose is to investigate the relationship between incubation mechanisms and local urban development according to the concept of Smart City. Methodologically, canonical correlation analysis was applied between two sets of elements: variables associated to business incubation and variables related to smart city characteristics. The research was concentrated on 157 medium- and large-sized cities from 25 European countries. Based on the findings, clusters analysis was also performed. The article presents, among the main results: (1) evidence of correlation between business incubation and smart urban development, and (2) visual classification of these cities into four clusters, according to their urban development and incubation activity.     

An agent-based procedure with an embedded agent learning model for residential land growth simulation: The case study of Nanjing,China

The agent-based modelling (ABM) is commonly used to simulate urban land growth. A key challenge of ABM for the simulation of urban land-use dynamics in support of sustainable urban management is to understand and model how human individuals make and develop their location decisions that then shape urban land-use patterns. To investigate this issue, we focus on modelling the agent learning process in residential location decision-making process, to represent individuals' personal and interpersonal experience learning during their decision-making. We have constructed an extended reinforcement learning model to represent the human agents' learning when they make location decisions. Consequently, we propose and have developed a new agent-based procedure for residential land growth simulation that incorporates an agent learning model, an agent decision-making model, a land use conversion model, and the impacts of urban land zoning and the developers' desires. The proposed procedure was first tested by using hypothetical data. Then the model was used for a simulation of the urban residential land growth in the city of Nanjing, China. By validating the model against empirical data, the results showed that adding agent learning model contributed to the representation of the agent's adaptive location decision-making and the improvement of the model's simulation power to a certain extent. The agent-based procedure with the agent learning model embedded is applicable to studying the formulation of urban development policies and testing the responses of individuals to these policies.     

Migration of As, and H/He ages, in groundwater from West Bengal: Implications for monitoring

From 2002 to 2010 inclusive we monitored concentrations of arsenic (As) and major ions (Ca, Mg, Sr, Na, K, Fe, Mn, Cl, and SO₄) in groundwater from 14 domestic wells and three piezometer nests in a shallow aquifer (<60 m depth), and 3 wells in a deep aquifer (>70 m depth), in southern West Bengal, India. In the deep aquifer, concentrations of As did not change over time despite increases in the concentration of Fe in two wells. The shallow aquifer occurs in two sedimentological settings: palaeo-channel and palaeo-interfluve. At the top of the shallow aquifer of the palaeo-channel, decreases in all constituent concentrations with time, and an ³H/³He age of 1.4 years, proves that the aquifer is beginning to be flushed of pollutants. In As-polluted groundwater (>50 μg/L As) tapped from deeper grey sands of the shallow, palaeo-channel, aquifer, concentrations of As were mostly stable over time, but both increases and decreases occurred with time in response to downward migration of the chemically-stratified water column. In groundwater tapped from Pleistocene brown sands, the concentration of As remained either low and stable (<2 μg/L As), or increased at rates up to 34 μg/L per year. The increases were caused by the flow of As-rich groundwater either downward into brown sand at the base of palaeo-channels, or laterally into a confined, unpolluted, palaeo-interfluvial, aquifer of brown sand that lies regionally beneath a palaeosol.Under the present pumping regime, the prognosis for As-pollution in the shallow aquifer is complex. Wells in brown sand may become polluted over timescales of as little as 2 years, whilst some wells tapping As-polluted groundwater from grey sand will become fit for potable use (<50 μg/L) within a few decades. The evidence of flushing, and of declining As in some of the groundwater from palaeo-channels, which are conduits for recharge of the confined, As-free, palaeo-interfluve aquifer, and probably also the deeper aquifer, offers hopes that the spread of As-pollution will be limited.     

Multiscale analysis of the urbanization pattern of the Phoenix metropolitan landscape of USA: Time,space and thematic resolution

Investigating the ecological consequences of urbanization require knowledge of land-cover dynamics. Quantification of land-use/land-cover change in Phoenix, Arizona during the period of 1985–2005 using landscape metrics computed from Landsat-derived maps revealed temporal patterns of landscape composition and configuration. With accelerated urbanization the landscape as a whole became more fragmented ecologically and more complex compositionally and geometrically. However, the majority of individual patches became more compact in shape. Urban land covers, especially xeric residential, increased substantially and the desert decreased by 20%. Spatial and thematic resolution of data was shown to have large effects on the analysis of land-cover pattern. Our results, while agreeing in general with previously reported scaling relations with respect to changing spatial grain and extent, showed that scaling relations are also robust and consistent across thematic resolutions and time periods. Some metrics behaved unpredictably and some exhibited scale-free behavior. Compositional metrics, such as patch density, diversity, evenness, and largest patch index, were well correlated with vegetative cover, its spatial variation, and population density. Many of these correlations exhibited hump-shaped patterns with respect to increasing grain size, indicating a characteristic scale at approximately 500–1000 m. By simultaneously manipulating spatial and thematic resolutions, the importance of the Modifiable Area Unit Problem in relating landscape patterns to vegetation and socio-economic variables was also demonstrated. Additionally, highly variable desert vegetation due to precipitation variability poses a challenge for accurately quantifying urbanization pattern in arid environments. Choosing appropriate spatial, temporal and thematic resolutions is essential in meeting this challenge.     

Detection of haze and its intensity based on visibility and relative humidity estimated from MODIS data

Over recent years, air pollution has become a serious environmental problem with frequent occurrence of hazy days in many Chinese cities. In this study, a satellite-based method was developed to detect haze and its intensity for the Chinese city of Nanjing. This detection was based on the joint consideration of two indices, visibility, and relative humidity. They were determined from the Moderate Resolution Imaging Spectroradiometer-derived aerosol optical thickness, surface temperature, and precipitable water vapour data. Evaluated against the in situ measured results, haze and its intensity were found to be detected at a maximum accuracy of 81.7% and 60%, respectively. Of the two indices, visibility plays a more important role than relative humidity in affecting the detection accuracy. It is concluded that it is feasible to detect haze and its intensity from satellite data.     

基于SketchUp和ArcGIS的三维场景构建技术研究

三维可视化是GIS研究的新趋势之一。提出一种基于SketchUp和ArcGIS的三维场景构建方法,详细介绍此方法的流程与步骤。     

Impact of consumers' personal characteristics on hedonic prices of energy-conserving durables

Since the oil crisis of 1973, American consumers have made progress conserving energy, but the average home remains far short of its potential thermal efficiency. An incentive for investing in energy-conserving home improvements is the potential increment they make to the home sale price. Our purpose was to determine whether the addition that energy-conserving improvements made to home sale prices (hedonic price) varied with the demographic characteristics of the buyers. Nonpooled regression analysis was used to estimate the hedonic prices of the housing attributes for each group of consumers. The focus was on wall and ceiling insulation, as well as wood or vinyl window frames. The hedonic prices of these features tended to vary with consumers' ages, levels of education and per capita incomes, but not with household size.