Understanding the Spatiotemporal Variation of High-Efficiency Ride-Hailing Orders: A Case Study of Haikou, China

Understanding the spatiotemporal variation of high-efficiency ride-hailing orders (HROs) is helpful for transportation network companies (TNCs) to balance the income of drivers through reasonable order dispatch, and to alleviate the imbalance between supply and demand by improving the pricing mechanism, so as to promote the sustainable and healthy development of the ride-hailing industry and urban transportation. From the perspective of TNCs for order management, this study investigates the spatiotemporal variation of HROs and common ride-hailing orders (CROs) for ride-hailing services using the trip data of Didi Chuxing in Haikou, China. Ordinary least squares (OLS) and geographically weighted regression (GWR) models are established to examine the factors that affect the densities of HROs and CROs during different time periods, such as morning, evening, afternoon and night, with considering various built environment variables. The OLS models show that factors including road density, average travel time rate, companies and enterprises and transportation facilities have significant impacts on HROs and CROs for most periods. The results of the GWR models are consistent with the global regression results and show the local effects of the built environment on HROs and CROs in different regions.

Association between leisure-time physical activity and the built environment in China: Empirical evidence from an accelerometer and GPS-based fitness app

To reexamine the relationship between leisure-time physical activity (LTPA) and the built environment (BE), this paper takes advantage of the massive amount of data collected by an accelerometer and GPS-based fitness mobile app. Massive LTPA data from more than 3 million users were recorded by Codoon in 500m by 500m grid cells and aggregated to 742 natural cities in mainland China. Six BE indicators were quantified using GIS at the city scale. Robust regression analysis was used to estimate the correlation between LTPA and BE. Five of six BE indicators—connectivity, road density, land use mix, points of interest density, and density of parks and squares—were significantly, positively, independently, and linearly related to LTPA in the regression analysis. The study obtains findings that are consistent with the previous literature but also provides novel insights into the important role of POI density in encouraging LTPA, as well as how the relationship between LTPA and BE varies by time of day. The study also sheds light on the embrace of new technology and new data in public health and urban studies.

Predicting the response of the lung function in patients with chronic obstructive pulmonary disease under the influence of climate-technogenic factors

Introduction. Lung function plays an important role in the adaptation to environmental conditions. Therefore, the study of the processes of influence of climatic and technogenic factors on the human respiratory organs is an urgent problem of our time.Aim. To predict the dynamics of lung function indicators in patients with chronic obstructive pulmonary disease (COPD) under the influence of changes in the qualitative state of the climatic and technogenic environment of Vladivostok.Materials and methods. 177 people were examined: of them 45 patients with mild COPD, 50 with moderate COPD, 45 with severe COPD, 37 healthy volunteers were included in the control group. The study of the lung function was carried out by the spirometry. For the analysis, we used regression models that assess the activity and intensity of the compensatory and pathogenic response of the lung function indicators to the impact of 28 climatic and technogenic factors of the urban environment.Results. As a result of calculations, Rfunc (at p<0.05) was selected for the impact of 11 trigger factors of the environment. The search for the optimal multiple regression model (Rregr=0.69; F=7.1; p=0.001), which characterized the response of the indicator Yi (FEV1) to the action of Xi (“road density”) and X2 (“air temperature“), was carried out. Substitution of the values Xi, X2 made it possible to form a nomogram of the calculated data (Yi).Conclusion. The difference in the response of lung function to the technogenic and climatic environment made it possible to assess the impact of external factors from the standpoint of its pathogenicity and sanogenic power. According to the obtained regression model, it was found that in Vladivostok, the most favorable external loads are observed at temperatures >5ºC (FEV1>80%), however, at the maximum “road density”, the indicator falls (FEV1≤60%). The resulting nomogram makes it possible to predict the dynamics of the FEV1 in the patients with COPD living in different environmental conditions, depending on the change in air temperature. Timely implementation of medical and preventive measures will reduce the risk of COPD progression in an urban environment.

The Effect of Urban Form on PM2.5 Concentration: Evidence from China’s 340 Prefecture-Level Cities

Exploring how urban form affects the Particulate Matter 2.5 (PM2.5) concentration could help to find environmentally friendly urbanization. According to the definition of geography, this paper constructs a comprehensive urban form evaluation index system applicable to many aspects. Four urban form metrics, as well as road density and five control variables are selected. Based on 2015 data on China’s 340 prefecture-level cities, the spatial regression model and geographically weighted regression model were used to explore the relationship between the urban form evaluation index system and PM2.5 pollution. The main results show that the spatial distribution of PM2.5 in China follows an increasing trend from northwest to southeast. Urban form indicators such as AI, LPI, PLAND, LSI and road density were all significantly related to PM2.5 concentrations. More compact urban construction, lower fragmentation of urban land, and lower density of the road network are conducive factors for improving air quality conditions. In addition, affected by seasonal changes, the correlation between urban form and PM2.5 concentration in spring and winter is higher than that in summer and winter. This study confirmed that a reasonable urban planning strategies are very important for improving air quality.

Methodology for mapping the probability of fire occurrence in the Brazilian cerrado biome based on the danger of fire propagation variables

The area covered by the Brazilian cerrado biome has been greatly reduced in recent years due to the expansion of agricultural land and the increased number of fire outbreaks. The objective of this paper is to propose a methodology based on geospatial analysis and logistic regression analysis (LRA) for mapping the probability of fire occurrence in Brazilian cerrado conservation units. This model was applied in the Serra da Canastra National Park (SCNP) in the Southeast of Brazil. The methodology uses the maps of the following environmental variables, which are related to the danger of fire propagation: wind effect (WIN), terrain convexity (CVX), slope (SLO), drainage density (DRD), altitude (ELV), vegetation index (NDVI), and road density (ROD). The results of the LRA showed that the variables SLO, ELV, NDVI, ROD (p<0.0001), DRD (p=0.0005) and WIN (p=0.0007) contributed significantly to the occurrence of fire outbreaks. The model correctly classified 94.26% of cases. We conclude that this methodology can be used to inform the planning of firefighting actions in the Brazilian cerrado biome.

Porcine Reproductive and Respiratory Syndrome (PRRS) Epidemiology in an Integrated Pig Company of Northern Italy: A Multilevel Threat Requiring Multilevel Interventions

Porcine reproductive and respiratory syndrome (PRRS) is probably the most relevant viral disease affecting pig farming. Despite the remarkable efforts paid in terms of vaccination administration and biosecurity, eradication and long-term control have often been frustrated. Unfortunately, few studies are currently available that objectively link, using a formal statistical approach, viral molecular epidemiology to the risk factors determining the observed scenario. The purpose of the present study is to contribute to filling this knowledge gap taking advantage of the advancements in the field of phylodynamics. Approximately one-thousand ORF7 sequences were obtained from strains collected between 2004 and 2021 from the largest Italian pig company, which implements strict compartmentalization among independent three-sites (i.e., sow herds, nurseries and finishing units) pig flows. The history and dynamics of the viral population and its evolution over time were reconstructed and linked to managerial choices. The viral fluxes within and among independent pig flows were evaluated, and the contribution of other integrated pig companies and rurally risen pigs in mediating such spreading was investigated. Moreover, viral circulation in Northern Italy was reconstructed using a continuous phylogeographic approach, and the impact of several environmental features on PRRSV strain persistence and spreading velocity was assessed. The results demonstrate that PRRSV epidemiology is shaped by a multitude of factors, including pig herd management (e.g., immunization strategy), implementation of strict-independent pig flows, and environmental features (e.g., climate, altitude, pig density, road density, etc.) among the others. Small farms and rurally raised animals also emerged as a potential threat for larger, integrated companies. These pieces of evidence suggest that none of the implemented measures can be considered effective alone, and a multidimensional approach, ranging from individual herd management to collaboration and information sharing among different companies, is mandatory for effective infection control.

A GIS-Based Methodology to Determine Effect of Vehicular Pollution at Ward Level: Case Study of Jaipur City

To determine appropriate measures to reduce air pollution in any urban city, the first essential requirement is to estimate the spatial distribution of air pollution parameters in that area. In absence of air monitoring stations, alternative methods are required for the same. In the present work, a GIS-based methodology is presented to estimate the level of NO2 based on the road density of the road network of different categories of roads. Road network GIS layer and measured levels of the average value of NO2 for the year 2019 at 12 air pollution monitoring stations of Jaipur city are used to develop a large number of possible linear regression models for estimation of NO2 values based on road density values. Akaike Information Criterion (AIC) and adjusted r2 values are used to evaluate and arrive at the best-fitted model. Values from the cities of Jodhpur and Kota are used to validate the model. Using this model, NO2 levels are determined at 91 wards of Jaipur city and the output is compared with the similar map derived based on interpolation of NO2 values at the 12 monitoring stations. It is concluded that the methodology developed in this study generates better estimates of NO2 at the ward levels.

ITLCS Based on OpenCV Image Processing Technology

With the rapid growth of the number of motor vehicles in the city, traffic congestion is more serious every day, part of it is caused by the coding delay with the red light on, not real traffic jams, now we need a control system that can really change the traffic flow. In this paper, ITLCS (intelligent traffic signal control system) based on OpenCV image processing technology is proposed to adjust the timing of traffic signal according to road density, instead of setting a level that is balanced with other lanes, so that high-load traffic lanes can be used for a long time. The camera facing the roadway in the system takes pictures of the driving route, then takes pictures of the driving density of pedestrians and vehicles, and compares each image through processing technology, after the system is processed, the traffic light signal timing can be adjusted immediately, which greatly reduces the time spent on the inactive green light and can effectively deal with the traffic congestion problem.

Economic Competitiveness and Availability of Road Infrastructure

The level of road infrastructure development brings about several benefits, such as shorter travel times, reduced transport costs, or improved road safety. Undoubtedly, it is also a factor that has had a beneficial impact on the growth of certain regions. This is particularly important for the entire economy (in the macroeconomic context), for regions (on the meso-regional level) and for business enterprises (the macroeconomic aspect). The aim of this study has been to evaluate the effect of the availability of road infrastructure on the economic competitiveness of Polish voivodeships. To this end, the Regional Competitiveness Index (RCI) was compared with the ratio of the density of hard-surface roads per 100 km2. The analysis showed that the highest regional competitiveness and simultaneously the highest road density ratio were in the voivodeships: śląskie, małopolskie and mazowieckie. However, the majority of regions in Poland are composed of voivodeships with both of these indicators scoring below zero. These are regions in the eastern part of Poland; as well as the lubuskie and zachodniopomorskie voivodeships.

Variability in Human Mobility during the Third Wave of COVID-19 in Japan

Understanding factors regarding individual variability in human mobility during the COVID-19 pandemic would help inform future political and medical decisions. Particularly, understanding environmental factors would provide effective evidence for future urban development and the construction of a mobility service. Given the limited related evidence thus far, we investigated inter-individual variability in human mobility regarding life space during COVID-19 in Japan. We conducted an online survey to assess human mobility, demographics, and personality, and city structure surveys for objective environmental factors. Human mobility was assessed using the Life Space Assessment (LSA) questionnaire. Result revealed that the total LSA score was significantly higher in people who were men, middle-aged, working, living with their children, public transportation users, bicycle users, and car drivers, and those having a higher score for extraversion and ego resiliency and a lower score for conscientiousness. People living in the city with high traffic on the roads between plains and mountains had a higher LSA score, and had a lower score where there were many plains with a consistent road density, revealing diverse individual and environmental factors associated with human mobility during the pandemic. Thus, political decisions for urban development should consider these characteristics, the pandemic, and individual convenience.