Urban Local Areas Research Articles

Occurrence and spatial variation of antibiotic resistance genes (ARGs) in the Hetao Irrigation District, China

The prevalence and proliferation of antibiotic resistance genes (ARGs) has been identified as an emerging contaminant of concern and a crucial threat to public health worldwide. To determine the occurrence and distribution of ARGs in artificial agricultural irrigation systems, we designed eight sample sites of farmland drainage in the Hetao Irrigation District, Inner Mongolia, China. Results indicated that the distribution of ARGs in sub-drainage canals is influenced by the local urban area, agriculture, and animal husbandry structure. The blaTEM gene was predominant in the water samples (up to 8.98 ARG copies/16S rRNA genes). The average ARG abundance in drainage channel sampling sites was significantly higher than the influent water from the Yellow River, which means that the artificial agricultural irrigation system enhances the abundance of resistance genes in the study area. Moreover, the effluent water of the whole irrigation system presented a lower abundance of ARGs than the influent water. This demonstrates that the Wuliangsuhai watershed ecosystem plays an important role in regulating the abundance of ARGs in the area. In our study, the mobile gene elements correlated with trB, emrD, mexF, and vanC (P < 0.001) in the irrigation system. Additionally, different correlations exist between other special subtypes of ARGs. These findings provided deeper insights into mitigating the propagation of ARGs and the associated risks to public health.

C-Sr-Pb isotopic characteristics of PM2.5 transported on the East-Asian continental outflows

This study investigated isotopic signatures of carbon (C), lead (Pb) and strontium (Sr) in PM2.5 samples collected from two paired sites (urban vs. rural/background) in northern Taiwan during the summer of 2015 and the spring of 2016, respectively. Significant seasonality was revealed in the isotopic signatures of C and Pb, whereas no seasonal difference was observed in 87Sr/86Sr ratio. The values of δ13C, 206Pb/207Pb, and 208Pb/207Pb were more diverse and exhibited local features in summer. However, during the episodes of continental pollution outbreaks in springtime, the δ13C and Pb isotope ratios of PM2.5 shifted and converged consistently toward the documented characteristics of particulate matters in northern China. Moreover, the results showed that the differences in the Pb and Sr isotopic characteristics between the paired urban and rural sites were statistically insignificant, whereas marginally lower δ13C values were observed at the urban site. It was inferred accordingly that a substantial amount of gaseous hydrocarbons emitted in local urban areas could have been converted to secondary organic aerosols with lower δ13C. On the contrary, the consistency in the spatial and temporal variations of mass concentration and isotope ratios of Pb at the two sites suggested that East-Asian continental pollution outbreak was the major source of Pb-containing particles in the northern Taiwan during springtime. It is noteworthy that there was neither seasonal nor spatial differences in the 87Sr/86Sr ratio observed in this study, which suggested that the Sr-containing particles collected in this study could be originating from a common mixture of sources, including not only natural dust but also the anthropogenic emissions, coal-combustion for instance. This investigation upon the C-Pb-Sr isotopic features evidenced the substantial impacts of the continental pollution outbreaks on the aerosol composition and air quality in the downwind areas of the East-Asian winter monsoons.

Urban and rural measurements of atmospheric potential gradient

Atmospheric potential gradient was measured at three sites within the Bristol area of the UK between 19th May and 24th June 2016. Two sites were on rooftops within the city of Bristol, 800 m apart from each other, while the third was in a rural location 17 km to the south. Potential gradient measurements at the two rooftop urban sites showed great temporal similarity, implying that a rooftop measurement may be assumed to represent the local urban area. Frequency domain analysis indicated a half-day cycle in the urban sites that was not observed in the rural site, consistent with other studies showing the effect of traffic aerosol on potential gradient measurements. The correlation between the two urban sites was not affected by an increase in aerosol concentration. Removal of data during rainfall, as well as one hour before and after rain, removed some of the larger changes in potential gradient typical of disturbed weather. However, large changes of potential gradient still existed, showing that rainfall alone should not be relied upon as an indicator of a non-fair weather potential gradient.

Is Uber Helping or Hurting Mass Transit? An Empirical Investigation

Sharing economy reshapes the distribution of unused or underutilized asset through digital platforms to individuals who are willing to pay for the services. The new economy model has introduced dramatic impact on the traditional industries by matching the demand and supply in real time. In this paper, we examine how the entry of Uber, a ride-sharing services digital platform, influences the demand of public transportation. Significant debate has surrounded whether the new ride-sharing model siphoned riders from public transit, or made transit feasible for more riders. However, limited empirical research has been done to uncover whether Uber is helping or hurting public transportation systems. Leveraging a natural experiment setting, the entry of Uber, with a difference-in-differences approach, we find a significant drop in the number of passenger trips with bus. Further, our results suggest that the effect of Uber is not uniform – the reduction in bus passenger trips is mitigated when the proportion of old age people in a local urban area is large; the decrease is amplified when the populations of disable people, including with language difficulty, and self-employed people are large. However, the moderating effect of poverty is mixed. We discuss the implications for research and practice.

Assessing Current Local Capacity for Agrifood Production To Meet Household Demand: Analyzing Select Food Commodities across 377 U.S. Metropolitan Areas.

Increasing food production in local urban and peri-urban areas is articulated as a potential way for local governments to achieve multiple sustainability outcomes (environmental, social, and human health). However, scientific judgements on localization are difficult to make because the degree of current food localization has not been systematically measured or defined across large numbers of cities. We develop new methods to quantify current local capacity for food production to meet total household agrifood demand, harmonizing bottom-up and top-down approaches to assess direct-plus-embodied agrifood demand of both fresh and processed foods. We find unique patterns of localization for different agrifoods, with 21% of U.S. metropolitan statistical areas (MSAs) currently capable of local self-sufficiency for eggs and milk equivalents embodied in diet, versus 12% and 16% of MSAs self-sufficient in fruits and vegetables, respectively. Focusing only on the direct fresh food demand, increased current local capacity (e.g., 45% MSAs self-sufficient in direct fluid milk), which also increases with production distances around cities.Overall, significant agricultural production is found to already occur in and around U.S. MSAs for these items.Multivariable analysis finds that state policies that promote urban agriculture may influence greater localization, which, interestingly, is independent of population density. Such spatial demand-production analysis is the first step in informing sustainable city or regional food policies and envisioning spatial food supply chains to urban areas.

Long-run urban dynamics: understanding local housing market change in London

Recently, a literature has emerged using empirical techniques to study the evolution of international cities over many centuries; however, few studies examine long-run change within cities. Conventional models and concepts are not always appropriate and data issues make long-run neighbourhood analysis particularly problematic. This paper addresses some of these points. First, it discusses why the analysis of long-run urban change is important for modern urban policy and considers the most important concepts. Second, it constructs a novel data set at the micro level, which allows consistent comparisons of London neighbourhoods in 1881 and 2001. Third, the paper models some of the key factors that affected long-run change, including the role of housing. There is evidence that the relative social positions of local urban areas persist over time but, nevertheless, at fine spatial scales, local areas still exhibit change, arising from aggregate population dynamics, from advances in technology, and also from the effects of shocks, such as wars. In general, where small areas are considered, long-run changes are likely to be greater, because individuals are more mobile over short than long distances. Finally, the paper considers the implications for policy.

Use of Bayesian inference method to model vehicular air pollution in local urban areas

Traffic Related Air Pollution (TRAP) studies are usually investigated using different categories such as air pollution exposure for health impacts, urban transportation network design to mitigate pollution, environmental impacts of pollution, etc. All of these subfields often rely on a robust air pollution model, which also necessitates an accurate prediction of future pollutants. As is widely accepted by the heath authorities, TRAP is considered to be the major health issue in urban areas, and it is difficult to keep pollution at harmless levels if the time sequenced dynamic pollution and traffic parameters are not identified and modelled efficiently. In our work here, artificial intelligence techniques, such as Bayesian Networks with an optimized configuration, are used to deliver a probabilistic traffic data analysis and predictive modelling for air pollution (SO2, NO2 and CO) at very local scale of an urban region with up to 85% accuracy. The main challenge for traditional data analysis is a lack of capability to reveal the hidden links between distant data attributes (e.g. pollution sources, dynamic traffic parameters, etc.), whereas some subtle effects of these parameters or events may play an important role in pollution on a long-term basis. This study focuses on the optimisation of Bayesian Networks to unveil hidden links and to increase the prediction accuracy of TRAP considering its further association with a predictive GIS system.

The Roles of Foundations and Universities in Redevelopment Planning

Laurie A. Walker, the 2017 recipient of the Ernest A. Lynton Award for the Scholarship of Engagement, is an Associate Professor in the School of Social Work at the University of Montana. Together with her co-author, Dr. Jean F. East, Professor in the Graduate School of Social Work at the University of Denver, they have raised, in this piece, an important and insightful critical lens on the implications of higher education institutions’ “engagement” with their local communities. It looks deeply into the implications of the “blind spot” identified by Baldwin (2017), which “comes largely from the assumption that higher education, while hypnotized by corporate power, is still an inherent public good, most clearly marked by its tax-exempt status for providing services that would otherwise come from the government.” They examine how campuses may be deeply involved in the local urban area and also advancing a self-interest that may not be a public interest – through gentrification, and through what Baldwin calls “noneducational investments in real estate, policing, and labor” that “can carry negative consequences for neighborhoods of color.” Walker and East are asking us to more closely examine how campuses can get so involved in the cities of which they are a part as to be a dominant force that does not advance the public good, but the good of the campus. This is a dilemma and a question that many of the CUMU member campuses have already faced or may face in the coming years, and goes to the heart of the public good of higher education in a neoliberal age. —John Saltmarsh, University of Massachusetts, Boston

Local variation of outdoor thermal comfort in different urban green spaces in Guangzhou, a subtropical city in South China

To understand the influence of different urban green spaces on outdoor thermal comfort, researchers have focused on developing a thermal comfort range and estimating neutral and preferred temperatures through questionnaire surveys and microclimatic measurements. The simultaneity of investigation among different sites is often neglected, which decreases the accuracy and reliability of the outcomes. To fill this gap and to better address the local variation of outdoor thermal comfort in different urban green spaces, both surveys and measurements were performed simultaneously at three sites, “central grassland,” “pond-side garden” and “grove” in a subtropical urban local area in warm and cool periods. Remarkable differences in microclimatic conditions, thermal sensations, thermal comfort, and both neutral temperatures and preferred temperatures were observed among the three sites and in the two periods. Preferred temperatures were lower than neutral temperatures among different sites in each period or both periods combined, indicating the instinctive preference of people from relatively hot regions for a cooler thermal state. The grove yielded the best cooling capability but was perceived as the hottest and most uncomfortable site in the warm period. The central grassland with the highest air temperature, conversely, was perceived as the most comfortable site. The subjective perceptions were also reflected by lower neutral and preferred temperatures in the grove than those in the central grassland in the warm period. In particular, for preferred temperatures, up to 8.8 °C operative temperature (Top) and 4.3 °C physiological equivalent temperature (PET) differences between these two sites were observed. Hence, a high density of trees does not necessarily result in better outdoor thermal comfort. Future urban planning and management, therefore, should emphasize the types and structures of different urban green spaces. To further comprehensively explore the roles of different urban green spaces in outdoor thermal comfort, high synchronicity among sites during investigation is important.

UAV Remote Sensing for delineation of Urban Vegetation using Object Based Image Analysis

Remote sensing technology has rapidly advanced during the last few decades and the number of remote sensing platforms has increased. The development of Unmanned Aerial Vehicles (UAV) image acquisition systems has radically changed the aerial Photogrammetric mapping due to its low cost, high spatial resolution and high accuracy and provide a great potential for vegetation mapping in urban areas. Urban environment planning becomes a challenging task for urban planners due to fast urbanization processes and growth of population. Urban land use is a crucial information for planning authorities and there is a growing demand for urban land cover maps for decision-making procedures in urban planning. In this article, we demonstrate a rule sets knowledge-based classification method, in object oriented classification which is a fully automated and highly accurate engineering approach for demarcation of urban vegetation with the use of eCognition software. DJI Phantom 4, consumer grade drone was used to acquire high resolution aerial photos as an input dataset in the study. In this study, vegetation mapping was done using the textural and contextual information acquired from the RGB image (Orthophoto) without using any Near Infrared (NIR) information and a Digital Surface Model (DSM) which was developed using Pix4D software, used as an ancillary data in the classification process in order to obtain the elevation information. The extraction of tree canopy and the buildings in a coastal urban environment has used to illustrate the analysis. The DSM was validated using ground control points observed by field measurements. The resultant urban vegetation map was validated with the digitized land use layer and an overall accuracy of 90.15% was obtained. This study indicates that low cost drones compared to the survey grade drones, also can provide high accurate and high resolution products suitable for many urban local area planning studies. Keywords: Photogrammetry, Object oriented classification, DSM, Orthophoto, Urban planning

Vegetation role in controlling the ecoenvironmental conditions for sustainable urban environments: a comparison of Beijing and Islamabad

The rapid increase in urbanization due to population growth leads to the degradation of vegetation in major cities. This study investigated the spatial patterns of the ecoenvironmental conditions of inhabitants of two distinct Asian capital cities, Beijing of China and Islamabad of Pakistan, by utilizing Earth observation data products. The significance of urban vegetation for the cooling effect was studied in local climate zones, i.e., urban, suburban, and rural areas within 1-km2 quantiles. Landsat-8 (OLI) and Gaofen-1 satellite imagery were used to assess vegetation cover and land surface temperature, while population datasets were used to evaluate environmental impact. Comparatively, a higher cooling effect of vegetation presence was observed in rural and suburban zones of Beijing as compared to Islamabad, while the urban zone of Islamabad was found comparatively cooler than Beijing’s urban zone. The urban thermal field variance index calculated from satellite imagery was ranked into the ecological evaluation index. The worst ecoenvironmental conditions were found in urban zones of both cities where the fraction of vegetation is very low. Meanwhile, this condition is more serious in Beijing, as more than 90% of the total population is living under the worst ecoenvironment conditions, while only 7% of the population is enjoying comfortable conditions. Ecoenvironmental conditions of Islamabad are comparatively better than Beijing where ∼61% of the total population live under the worst ecoenvironmental conditions, and ∼24% are living under good conditions. Thus, Islamabad at this early growth stage can learn from Beijing’s ecoenvironmental conditions to improve the quality of living by controlling the associated factors in the future.

An algorithm for search automation of lighting sources optimal arrangement in urban environment

The paper presents research results on the optimal lighting arrangement using the potential of space and geometry in an urban environment. A local urban area such as a city block is selected as an object of research. In the process of the block geometry analysis the required number of light sources and their position with the given characteristics of the sources are calculated. The proposed algorithm is based on the concept of the isovist from the theory of spatial syntax and consists of two stages: visibility map creation and the optimal arrangement of lighting sources. The result of the algorithm operation is an illumination matrix with the optimal arrangement of light sources and a list of their coordinates. The presented algorithm can be used to estimate an urban light demand. The algorithm presented in the paper can be used for design of schematic urban lighting. In particular, it can be used in the early stages of design to assess the project’s potential.

Identification and Prediction of Urban Traffic Congestion via Cyber-Physical Link Optimization

In this paper, to accurately predict and evaluate the traffic states in local urban areas, an effective as well as efficient algorithm combined with leakage integral echo state network (LiESN) and Pearson correlation analysis is presented. First, aiming at the parameter optimization of LiESN, the differential evolution algorithm is used to calibrate the key parameters. Second, the road weight allocation is carried out by Pearson correlation analysis considering the specific topology characteristics of local road nets. On this basis, the corresponding flow-frameworks are designed. Finally, the congestion delay data of local road nets in Chongqing Nan’an district, acquired from AutoNavi, are used to verify the validity and rationality of our method. Experimental results indicate that the proposed identification and prediction mechanism relates the congestion indicators to actual traffic operating mechanism in a more reasonable way.

Constraining the Deforestation History of Europe: Evaluation of Historical Land Use Scenarios with Pollen-Based Land Cover Reconstructions

Anthropogenic land cover change (ALCC) is the most important transformation of the Earth system that occurred in the preindustrial Holocene, with implications for carbon, water and sediment cycles, biodiversity and the provision of ecosystem services and regional and global climate. For example, anthropogenic deforestation in preindustrial Eurasia may have led to feedbacks to the climate system: both biogeophysical, regionally amplifying winter cold and summer warm temperatures, and biogeochemical, stabilizing atmospheric CO 2 concentrations and thus influencing global climate. Quantification of these effects is difficult, however, because scenarios of anthropogenic land cover change over the Holocene vary widely, with increasing disagreement back in time. Because land cover change had such widespread ramifications for the Earth system, it is essential to assess current ALCC scenarios in light of observations and provide guidance on which models are most realistic. Here, we perform a systematic evaluation of two widely-used ALCC scenarios (KK10 and HYDE3.1) in northern and part of central Europe using an independent, pollen-based reconstruction of Holocene land cover (REVEALS). Considering that ALCC in Europe primarily resulted in deforestation, we compare modeled land use with the cover of non-forest vegetation inferred from the pollen data. Though neither land cover change scenario matches the pollen-based reconstructions precisely, KK10 correlates well with REVEALS at the country scale, while HYDE systematically underestimates land use with increasing magnitude with time in the past. Discrepancies between modeled and reconstructed land use are caused by a number of factors, including assumptions of per-capita land use and socio-cultural factors that cannot be predicted on the basis of the characteristics of the physical environment, including dietary preferences, long-distance trade, the location of urban areas and social organization.

Faktor Internal Lemahnya Penguasaan Bahasa Jawa Krama pada Generasi Muda

This research has purpose to find the internal factor causing the weakness of mastery of krama lexicon in young generation of Java in Semarang City. The low treasury of krama lexicon affects the use of Javanese krama. Research location in urban area of Semarang: Banyumanik and Tlogosari housing. Data were collected using method:observation, note, record and method: participant, interview. Data were analyzed using quantitative and comparative descriptive method. The research findings that the treasury krama lexicon on the young generation of Java City Semarang are in very weak classification (score 20.8% - 24.4%). Three internal factors cause weakness of mastery of Javanese krama: (1) pattern of formation of lexicon krama: krama andhap and krama inggil. (2) The placement of lexicon krama in starata fine speech: krama lugu, wredha krama, mudha krama. (3) Changes in morphemes (affix) in the process of formation of lexicon krama.

IDENTIFIKASI KARAKTERISTIK ANAK PUTUS SEKOLAH DI JAWA BARAT DENGAN REGRESI LOGISTIK

School dropouts are the problem in education which is the condition of children who do not have the opportunity to complete their education that they couldnt obtain degree certificate due to certain factors. Based on SUSENAS 2013, there is 2.15% of children aged 7-15 years old in West Java who dropped out of school. Three aspects that have great potential on the incidence of school dropouts are characteristic of social, economy, and demography. This study uses logistic regression analysis to determine the effect of school dropouts by the three aspects. The results of logistic regression analysis at 5% significance level indicates that the characteristics of social, economy, and demography that have significant effect on the incidence of school dropouts are the low education of household head, more than four household members, less than the poverty line household expenditure per capita, residence location in urban areas, and boys. The resulting model is sufficientfor estimation with the sensitivity value of 70.20% and the area under the ROC curve of 76.42%.&#x0D; Keywords: logistic regression, ROC curve, school children, sensitivity.

Assessing the ecosystem services provided by urban green spaces along urban center-edge gradients

Urban green spaces provide various ecosystem services, especially cultural services. Previous assessment methods depend either on hypothetic payments for ecosystems or real payments not directly related to ecosystems. In this paper, we established a method for assessing the cultural ecosystem services in any location in urban area using only two variables, green space (ecosystem) and land rent (real payment). We integrated the cultural and the regulating services into the total ecosystem services because urban green spaces provide almost no provisioning services. Results showed that the same area of green spaces near the center provided much higher cultural services than that near the urban edge; the regulating services accounted for 5% to 40% of the total ecosystem services from the center to the edge of urban area; along the center-edge gradient, there was a threshold out which the ecosystem services were lower than the maintenance cost of green spaces.

PERENCANAAN JARINGAN EVOLUTION DATA OPTIMIZED (EVDO) PADA TELKOM FLEXI AREA JAKARTA

Abstract The development of high-speed data connection and internet in mobile phones technologies is rapidly growing lately. Certain technology that support the growth of mobile data communication is EVDO system. EVDO offers wireless internet technology for data optimization and internet access with high speed data rate and large capacity. This technology also provides a solution for wireless mobile internet with high performance. EVDO can achieve peak data rates up to 2.45 Mbps on the forward link with the use of 1.25 MHz wide spectrum. This paper discusses Network Evolution Data Optimized (EVDO) plan at Telkom Flexi Jakarta. The area of discussion includes traffic prediction, and coverage area to existing BTS CDMA 2000 1x. Based on the prediction, the number of customers in 2015 for the dense urban areas in Central Jakarta will be 150,000 customers, while in the urban area of West Jakarta will reach 60,000 customers and the local urban areas in North Jakarta will have 60,000 subscribers. The offered traffic in dense urban area North Jakarta is 15,170 Kbps/km2, while in urban area of West Jakarta is 17,455 Kbps/km2, and for the urban area in North Jakarta is 13,473 Kbps/km2. Keywords: EVDO, wireless network, internet access.

Spatial Analysis to Identify Urban Areas with Higher Potential for Social Investment

There has been great interest on the part of public and private initiatives in knowing the location of urban areas with potential for investments in social resources. The aim of the present article is to propose a methodology to identify such areas, using the city of São Paulo (Brazil) as a case study. This approach, supported by The Geographic Information System (GIS), is based on multicriteria analysis and quantification of spatial data. The results, presented spatially in a synthesis map, made possible to identify promissory areas for social investment in São Paulo. The method allows us to analyze data at different spatial scales from the GIS base, enabling a systematization to find out areas with higher potential for investment in social equipment, services and facilities. Furthermore, it gives possibility of modeling several variables, thus being adaptable to different geographic areas.

Observations on the occurrence and phenology of the invasive elm defoliator Aproceros leucopoda (Hymenoptera: Argidae) in the Czech Republic

Aproceros leucopoda has been found at nine locations in urban areas and in forests in the Czech Republic. Aproceros leucopoda was first reported at a location 700m a.s.l. in the northern part of the country in 2011. The other locations range in elevation from 150 to 460m a.s.l. In the current study, A. leucopoda was studied in four plots, where larvae and their zigzag feeding tracks were observed on 10 Ulmus trees located south of Lanžhot (southeastern Czech Republic) in 2014 and 2015. In 2014, feeding tracks and larvae were detected in late May, from 22 June to 13 July, and from 9 August to 6 September, suggesting the occurrence of three generations per year in the southeastern Czech Republic. The southern Czech Republic has been colonized much earlier than other parts of the country because of its proximity to localities with A. leucopoda in Slovakia and Austria. The presence of larvae or evidence of larval feeding was detected on only 2.84% of monitored leaves. We suggest that A. leucopoda endangers solitary elms in urban greening areas more than elms in forests.