Dense Road Network Research Articles

Long-term impact of road salt (NaCl) on soil and urban trees in Edmonton, Canada

The application of de-icing salts for winter road maintenance is recognized as a major contributor to the decline of urban trees. We conducted a long-term monitoring program across several locations in the City of Edmonton (Alberta, Canada) to evaluate the impact of roadway salt application on tree species widely planted in boulevards and right-of-ways: Ulmus americana, Fraxinus pennsylvanica, Pinus contorta, and Picea glauca. Soil and leaf samples were collected from a total of 16 sites over six years. There were four sites selected for each tree species: three mid- to high- traffic roadside sites that received regular winter maintenance and one non-serviced site (control). Sampling was performed three times per year from late spring to late summer. Airborne salinity was assessed in four locations at different distances from the road. In 50% of the roadside sites, soil electrical conductivity (EC) values exceeded 2dSm−1. Soil pH in all of the roadside sites was also significantly higher than in the control sites, with values ranging from 7.6 to 8.5. In all four species, trees growing in sites with high soil EC had increased leaf Na concentrations and reduced leaf chlorophyll concentrations. Among the airborne monitoring sites, Na deposition in high traffic locations was over four-fold higher than those measured in the control location. Furthermore, Na levels remained relatively high at 20–50m from the main road. Our data suggest that while soil salinity is among the main stressors affecting roadside trees in Edmonton, salt spray deposition may also have a significant impact on trees located close to high vehicle traffic areas and dense road networks. Our study highlights the importance of collecting data over several years and from multiple locations to account for the spatial and temporal heterogeneity of the urban environments in order to better evaluate the impact of road salt application on urban trees.

Implementation of generic algorithm in map-matching model

This paper proposed a novelty map-matching method based on multi-criteria genetic algorithm. In addition, the new ideas are introduced, such as incorporation of dynamic time wrapping method and dynamic programming technique. Dynamic time wrapping is used to evaluate the geometric similarity between recorded trajectory and observed route, while dynamic programming is used to accelerate the calculations of fitness functions in genetic algorithm. Model is tested on real data collected from the street network, which yielded good results with regard to accuracy and running time. Furthermore, it is shown that proposed model is capable to process the GPS data, recorded on dense street network with negligible amount of errors, which is the most challenging task for majority of map-matching algorithms. Therefore, the main impact of this research is observed through the development of better and more precise global map-matching algorithm. This is really important for expert and intelligent transport systems, which are based on input data collected by floating car data systems. This type of system relies on high quality post-processing map-matching model, which should provide accurate results in order to ensure that intelligent transport system makes more precise estimations and predictions of traffic conditions.

How is habitat connectivity affected by settlement and road network configurations? Results from simulating coupled habitat and human networks

Habitat connectivity is important for species’ survival and can be maintained in landscapes with well-connected habitat networks. The integrity of these habitat networks, however, is often threatened by “human networks” consisting of settlements connected by roads with traffic. Both settlement and road network changes can decrease habitat connectivity, either directly or indirectly through changes in traffic flows. Due to these complex interactions, it remains unclear how habitat connectivity in habitat networks is affected by settlement or road network configurations in human networks. To address this issue we develop a new spatially explicit simulation model coupling habitat and human networks. In binary landscape rasters, consisting of settlement patches surrounded by a continuous matrix through which animals could move, we varied the number, the size and the proportion of settlements. Settlements were connected with either dense or sparse road networks. On all roads connecting settlements, we estimated traffic volume based on settlement sizes and topology. Traffic volumes were then used to parameterize landscape resistance networks that quantify the probability of movement for animals throughout the landscape. From these resistance networks, we calculated average habitat connectivity for several animal species (i.e. tree frog, hedgehog and badger). In this innovative model setup, habitat connectivity was thus influenced by a combination of settlement patterns and traffic volumes. For all species, we found a negative correlation between habitat connectivity and the number of settlement patches. Furthermore, in landscapes with a high proportion of settlement, highest habitat connectivity was found when most settlement cells were concentrated in large patches. Surprisingly, in some cases, we found higher habitat connectivity for dense road networks than for sparse road networks. Results from this study can increase our understanding of habitat connectivity in heterogeneous landscapes and lead to recommendations for conservation planning. With this study we demonstrate the importance of considering interactions between spatial networks in ecological analyses.

Map‐matching algorithm applied to bicycle global positioning system traces in Bologna

A novel map-matching algorithm is proposed, implemented and applied to global positioning system (GPS) traces which have been recorded by cyclists in Bologna, a medium-sized city in the North of Italy. The algorithm has been developed to match geo-referenced traces to a sequence of edges of a given road network model. Map-matching for bike trips is particularly challenging as cyclists often use footpath or parks which are not necessarily represented by the road network model. The matching algorithm should smartly tolerate the lack of network information. The algorithm should also be fast and capable of processing thousands of GPS traces in a reasonable time. The proposed probability-based method, which also exploits information on various network attributes, allows a reliable and fast map matching, even in dense street networks and with interrupted GPS data streams. In fact, one serious issue is to find a reliability measure which allows to verify the matched routes, without the knowledge of the real routes, as the available cyclist traces are anonymous. In addition to the reliability check, a sensitivity analyses with respect to the most relevant parameters has been conducted. The advantages of the proposed map-matching algorithm are quantified through a direct comparison with a topology-based map-matching algorithm from literature.

Noise exposure of residential areas along LRT lines in a mountainous city

Light rapid transit (LRT) has been widely used in a number of Chinese cities in recent years. Different from plain cities, the urban areas in mountainous cities are featured with dense road networks and high density of buildings. The noise impact of urban LRT could be more complex and significant due to the special morphological conditions in mountainous cities. This paper aims to investigate the noise exposure of residential areas along LRT lines in a typical mountainous city, namely Chongqing in Southwest China, through a series of field measurements and questionnaire surveys. Eight typical spatial configurations were classified to represent the relationships between LRT lines and urban mountainous environment. Both the outdoor and indoor acoustic environment of residential areas along LRT lines largely exceeded the national standards by up to 15dBA, with dominant at low frequencies. The LRT noises tend to be more dominant on the ‘below track’ and ‘passing through’ rather than ‘above track’ areas or ‘facing towards’ locations. Good agreements were achieved between acoustic measurements and subjective evaluations from the local residents. Residents in the noisier areas tend to be more annoyed and influenced by the LRT noise, and 63.2% of interviewed residents once were awakened by the LRT noise. Among various urban noise sources, LRT noise resulted in the largest percentages of highly annoyed residents (30.9%), and acoustic environment was identified by 42.2% of the participants as the most urgent environmental factor to be improved. The preferred control strategies for LRT noise are possible but limited in practice. Moreover, noise sensitivity and age might significantly affect LRT noise annoyance and impact, whereas window glazing and residence time have no significant influence.

Environmental and land use determinants of grassland patch diversity in the western and eastern Alps under agro-pastoral abandonment

Agro-pastoral decline in European mountain areas has recently caused changes to traditional landscapes with negative consequences on semi-natural grassland conservation and the associated biodiversity and ecosystem services. In the Italian Alps, grassland patches enclosed in a forest matrix are progressively disappearing. Two alpine valleys (Pesio and Pejo), having similar land-use history, were chosen as representative of management conditions of western and eastern Italian Alps, respectively. This study aims at interpreting the effect of abandonment on grassland patch plant diversity, considering land cover changes of the last 60 years, and assessing the role of ecological, topographic, management and landscape configuration on current grassland species richness. The total area of grassland patches has declined by 54 and 91 % at Pesio and at Pejo, respectively. Actual grassland patch species richness was mostly influenced by ecological factors, such as quantity of light, soil moisture and reaction, then by topographic features, especially slope, and finally by management intensity. Landscape factors exerted a slightly significant effect on plant diversity. In the two valleys, differences on management practices were detected. Even though in the western valley the conservation of several grazing activities contributed to slow down the process of patch reduction, many species-rich grasslands were generally under-grazed. Conversely, in the eastern valley, despite a denser road network, the stronger decline of grassland patch extension was linked to the hay making decline. At the same time, overuse of grassland patches near farms reduced plant species richness. As a conclusion, plant species richness was weakly related to the area of grassland patches and current and historical landscape configuration were of relatively lower importance than ecological, topographic and management factors, when evaluated at patch-level.

Chloride Concentrations in Wetlands along a Rural to Urban Land Use Gradient

Relationships between anthropogenic sources of Cl− and wetland surface water Cl− concentrations have received little attention. Spatial and temporal patterns of Cl− concentration were investigated in 11 wetlands in the mid to late 1990s and in 2012–2013 along a rural to urban gradient. Chloride concentrations in wetlands located in forest watersheds were <3 mg/L. Small spring-fed swamps in relatively undeveloped rural areas had elevated Cl− concentrations ranging from 10 to 50 mg/L which originated from nearby house septic systems and salt application on secondary roads. Potassium fertilizer application on areas of intensive crop production was a major source of Cl− in riparian wetlands where surface water Cl− concentrations were 50–65 mg/L. The application of deicing salts caused the highest Cl− concentrations (100–730 mg/L) which were observed in depressional wetlands in a rapidly urbanizing landscape with a denser road network. Chloride contamination in the study wetlands occurred throughout the year and diffuse surface flow paths produced a widespread pattern of elevated surface water Cl concentrations which have increased considerably in the past 10–15 years in some of the wetlands. Wetland Cl− levels in the most developed landscapes reached or exceeded chronic water quality thresholds established in the USA and Canada for negative effects on aquatic biota.

A high-resolution map of direct and indirect connectivity of erosion risk areas to surface waters in Switzerland—A risk assessment tool for planning and policy-making

Off-site effects of soil erosion are becoming increasingly important, particularly the pollution of surface waters. In order to develop environmentally efficient and cost effective mitigation options it is essential to identify areas that bear both a high erosion risk and high connectivity to surface waters. This paper introduces a simple risk assessment tool that allows the delineation of potential critical source areas (CSA) of sediment input into surface waters concerning the agricultural areas of Switzerland. The basis are the erosion risk map with a 2m resolution (ERM2) and the drainage network, which is extended by drained roads, farm tracks, and slope depressions. The probability of hydrological and sedimentological connectivity is assessed by combining soil erosion risk and extended drainage network with flow distance calculation. A GIS-environment with multiple-flow accumulation algorithms is used for routing runoff generation and flow pathways. The result is a high resolution connectivity map of the agricultural area of Switzerland (888,050ha). Fifty-five percent of the computed agricultural area is potentially connected with surface waters, 45% is not connected. Surprisingly, the larger part of 34% (62% of the connected area) is indirectly connected with surface waters through drained roads, and only 21% are directly connected. The reason is the topographic complexity and patchiness of the landscape due to a dense road and drainage network. A total of 24% of the connected area and 13% of the computed agricultural area, respectively, are rated with a high connectivity probability. On these CSA an adapted land use is recommended, supported by vegetated buffer strips preventing sediment load. Even areas that are far away from open water bodies can be indirectly connected and need to be included in planning of mitigation measures. Thus, the connectivity map presented is an important decision-making tool for policy-makers and extension services. The map is published on the web and thus available for application.

Effects of Jobs–Residence Balance on Commuting Patterns

Jobs–residence balance is believed to be an important way to reduce commuting distance and related externalities. Although literature on jobs–residence balance is rich, relatively few studies investigate it in relation to employment industry sectors. However, consideration of the unique features of different industry sectors, such as workers’ ability and working hours, is necessary to gain useful knowledge. In addition, variability in commuting distance is an important factor often neglected in previous studies. Low variability implies a high potential for car sharing and for use of transportation services. This paper fills the voids of existing literature by investigating three employment industry sectors in relation to both averages and standard deviations of commuting distances. A seemingly unrelated regression model with spatial error was applied to examine the relationship between jobs–residence balance and commuting patterns. The investigation also considered the effects of urban forms, which had been found to be influential in commuting patterns. Two groups of cities, compact and sprawled, were used as the cases of different urban forms. Results showed that jobs–residence balance was more sensitive to the goods-producing sector and to compact regions. Meanwhile, an efficient commuting pattern was associated with a high jobs–residence ratio, clustered industry distribution, and dense road networks with few intersections.

What Makes Long Crime Trips Worth Undertaking? Balancing Costs and Benefits in Burglars’ Journey to Crime

This study taps into rational choice theory and scrutinizes the assumption that profit maximization and effort minimization govern decisions related to burglary behaviour and the journey to crime. It treats distance as one of the major costs in the burglary target selection process and uses community characteristics to gain insight into how the anticipation of particular benefits favours the incremental costs of long crime trips. 2,387 burglary trips were extracted from police records and analysed using negative binomial regression analysis. The journey-to-crime distance was found to increase when burglaries were committed in communities containing motorways, dense road networks, and being ethnically heterogeneous. The journey-to-crime distance was found to decrease when densely populated areas and communities with high clearance rates are targeted.

Network-level accident-mapping: Distance based pattern matching using artificial neural network

The objective of an accident-mapping algorithm is to snap traffic accidents onto the correct road segments. Assigning accidents onto the correct segments facilitate to robustly carry out some key analyses in accident research including the identification of accident hot-spots, network-level risk mapping and segment-level accident risk modelling. Existing risk mapping algorithms have some severe limitations: (i) they are not easily ‘transferable’ as the algorithms are specific to given accident datasets; (ii) they do not perform well in all road-network environments such as in areas of dense road network; and (iii) the methods used do not perform well in addressing inaccuracies inherent in and type of road environment. The purpose of this paper is to develop a new accident mapping algorithm based on the common variables observed in most accident databases (e.g. road name and type, direction of vehicle movement before the accident and recorded accident location). The challenges here are to: (i) develop a method that takes into account uncertainties inherent to the recorded traffic accident data and the underlying digital road network data, (ii) accurately determine the type and proportion of inaccuracies, and (iii) develop a robust algorithm that can be adapted for any accident set and road network of varying complexity. In order to overcome these challenges, a distance based pattern-matching approach is used to identify the correct road segment. This is based on vectors containing feature values that are common in the accident data and the network data. Since each feature does not contribute equally towards the identification of the correct road segments, an ANN approach using the single-layer perceptron is used to assist in “learning” the relative importance of each feature in the distance calculation and hence the correct link identification. The performance of the developed algorithm was evaluated based on a reference accident dataset from the UK confirming that the accuracy is much better than other methods.

English

Reducing connectivity, road networks may threaten the effectiveness of natural reserves, thus, representing a critical conservation matter. This work aims to: 1) evaluate the relationship between native vegetation cover and road distance; 2) evaluate the extent to which native vegetation and nature reserves are affected by roads. Our study area was a neotropical landscape in the state of São Paulo, Brazil. We divided the study area into 15 subregions to represent its high heterogeneity. First, we demarcated buffer zones of 10 different distances around each road, and quantified the density of roads and native vegetation cover. Second, we estimated the area ecologically affected by roads, the roadeffect zone, using buffers of increasing distances according to each road type. The most dense road network was found in the São Paulo Metropolitan area and the lowest was the Southern Coastline subregion, but this subregion showed the second highest expressway density. These two subregions had stronger positive relationships between native vegetation cover and road distance. Almost 10% of São Paulo state, about 6% of the remaining native vegetation, and more than 10% of the reserves were ecologically affected by roads. More than 50% of reserves were ecologically affected, and some have more than 60% of their territory affected. Threats related to proximity of roads, i.e. logging, may reduce effectiveness of more than 50% of natural reserves. Thus, we propose that identifying priority areas for integral conservation of pristine environments should include mostly remote areas, which are far from larger roads and under lower general road influence.

Safety assessment and remedial measures design for an extensive rockfall along the main road to Kimi, East Euboea, Greece

The steep morphology and the intense tectonic fragmentation of the mountainous areas of Greece combined with the dense road network create conditions favorable for the manifestation of rockfalls. Numerous events are recorded through the years, some of them causing injuries or even worse loss of lifes. The rockfall that took place along the Kimi – Platana – Paralia provincial road on August 2008, was studied in detail and is presented in the current paper. The rock detachment area was defined 200m away and at an altitude of 140m (130m higher from the road), while the rock pieces detached had a maximum volume of 4m3. The final consequences were two crashed cars and a heavily injured civilian. The causual factors as well as the proposed remedial measures, estimated by the use of RocFall by Rockscience Ltd., are described in detail. Furthermore, the temporary remedial measures applied by contractors are evaluated, pointing their defects.

Dynamic approach to the origin-destination matrix estimation in dense street networks

Dynamic approach to the origin-destination matrix estimation in dense street networks

When should exotic forest plantation tree species be considered as an invasive threat and how should we treat them?

The area of forests planted with exotic tree species is increasing worldwide in order to fulfill various economic and environmental demands. Numerous species currently used in forest plantations are considered to be invasive in many parts of the world. Exotic plantation tree species are endowed with a series of life-history traits that are characteristic of invasive species: easy establishment, fast growth, high propagule pressure, and low or intermediate shade tolerance. In addition, plantation forestry presents many features that increase ecosystem invasibility, including a regime of frequent and intensive canopy disturbances, a dense network of roads and trails with continuous traffic, and wide plantation areas. Exotic trees planted for production purposes have strong direct positive economic impacts on the local and national economies of many countries, often leading to notable conflicts of interest when the species becomes invasive, as well as to negative impacts on the ecosystem. Studies and management programs mainly focus on Pinus and Acacia, which are used as model species. Complementary management strategies have been established to control these species at different stages of the invasion process. Knowledge gained is useful to predict problems in other regions of the world with the same species and to guide research or management actions on other problematic but less studied tree species.

The opencast bauxite mining in N.E. Ghiona: Eco-environmental impacts and geomorphological changes (Central Greece)

It has been observed that certain anthropogenic interventions in the form of mining activities, such as opencast bauxite mining (large artificial cavities -pits-, voluminous piles of calcareous spoils -inert materials- derived from bauxite mining, dense road network constructed in order to get access to the mine location, etc), alter “critical” parameters of the natural environment and lead to destabilization of the environmental balance of forest ecosystems as well as cause changes in geomorphological processes. The way and methods used for the mining of bauxite until the end of the 20th century in the area of Northeastern Ghiona, in combination with the deforestation, forest fires, illegal logging- wood cutting, grazing-overgrazing in the forest, opening up new dense road network constructed in order to get access to the mine locations and the uncontrollable waste disposal, resulted in a significant burden to the natural environment, especially in the cases where it covered extended parts of forests, forest areas and grasslands as well as important geomorphological formations. All the aforementioned led to the occupation or the deforestation of forests and grasslands, the interruption of natural relief continuity and the change of natural geomorphologic processes and phenomena. Despite the existing strict relevant legal system that applies in the forest areas (Laws, 998/79, 1650/86, etc) in most cases, human activity in those areas does not take into account the necessary restrictions for the protection of the environment and this leads to unfavorable effects to the relevant areas which result in alterations as far as the extend and severity, depending on the type, the extend, the function and the location of the specific activity. The aim of this paper is: (a) To locate the main opencast bauxite mining activities as well as the existing or planned other human interventions and activities in the area of Northeastern Ghiona, and (b) The determination of the impacts to the natural environment and more specifically to the hydro-geomorphological characteristics and processes of Northeastern Ghiona, both during the time of the exploitation and after the ceasing of works as far as opencast bauxite mining is concerned in the numerous mines found in the area between Kaloskopi-Kastellia-Gravia-Variani (Northeastern Ghiona). Key words: Bauxite mining, environmental impact, geomorphology, Ghiona mountain, opencastmining.

Facilitated movement over major roads is required to minimise extinction risk in an urban metapopulation of a gliding mammal

Context Urbanisation is recognised as a primary cause of biodiversity loss. Roads are an inherent element of this, creating partial or complete barriers to animal movement. Urban landscapes of eastern Australia are typified by a dense road network interspersed with remnant patches of bushland. Inter-patch movement by tree-dependent gliding mammals may be halted and, consequently, population viability threatened, when canopy gaps over roads exceed gliding ability. Aims We test the notion that a metapopulation of the squirrel glider (Petaurus norfolcensis) in southern Brisbane can persist within a highly fragmented urban landscape with large road canopy gaps. Methods We used the population modelling software VORTEX to investigate the influence of inter-patch movement (dispersal) and wildfire on the probability of extinction. Wildfire is an inherent characteristic of this landscape. Key results Our modelling suggests that a lack of inter-patch movement as a result of road barriers, in tandem with wildfire, is associated with a high probability of local extinction. However, a small rate of inter-patch movement can substantially reduce the likelihood of extinction. Conclusions Road-crossing structures are the most plausible means available to link remnants to enable inter-patch movement for squirrel gliders in this landscape because of inadequate road-side tree height. Simulation studies such as the present study that test population viability are critical to convince land managers that action must be taken. Implications The need to conserve urban biodiversity will increase over time, so land managers must consider the likely benefits to population persistence conferred by installing wildlife crossing structures into existing roads.

Landscape disturbance causes small-scale functional homogenization, but limited taxonomic homogenization, in plant communities

Summary 1. Biotic homogenization (BH), a dominant process shaping the response of natural communities to human disturbance, reflects both the expansion of exotic species at large scales and other mechanisms that often operate at smaller scales. 2. Here, we examined the relationship between BH in plant communities and spatio-temporal landscape disturbance (habitat fragmentation and surrounding habitat conversion) at a local scale (1 km²), using data from a standardized monitoring programme in France. We quantified BH using both a spatial partitioning of taxonomic diversity and the average habitat specialization of communities, which informs on functional BH. 3. We observed a positive relationship between local taxonomic diversity and landscape fragmentation or instability. This increase in local taxonomic diversity was, however, paralleled by a decrease in average community specialization in more fragmented landscapes and in more unstable landscapes around forest sites. The decrease in average community specialization suggests that landscape disturbance causes functional BH, but there was limited evidence for concurrent taxonomic BH. 4. Synthesis. Our results show that landscape disturbance is partly responsible for functional BH at small scales via the extirpation of specialist species, with possible consequences for ecosystem functioning. However, this change in community composition is not systematically associated with taxonomic BH. This has direct relevance in designing biodiversity indicators: metrics incorporating species sensitivity to disturbance (such as species specialization to habitat) appear much more reliable than taxonomic diversity for documenting the response of communities to disturbance.

Development and evaluation of GRAL-C dispersion model, a hybrid Eulerian–Lagrangian approach capturing NO–NO2–O3 chemistry

Abstract Based on two recent publications using Lagrangian dispersion models to simulate NO–NO2–O3 chemistry for industrial plumes, a similar modified approach was implemented using GRAL-C (Graz Lagrangian Model with Chemistry) and tested on two urban applications. In the hybrid dispersion model GRAL-C, the transport and turbulent diffusion of primary species such as NO and NO2 are treated in a Lagrangian framework while those of O3 are treated in an Eulerian framework. GRAL-C was employed on a one year street canyon simulation in Berlin and on a four-day simulation during a winter season in Graz, the second biggest city in Austria. In contrast to Middleton D.R., Jones A.R., Redington A.L., Thomson D.J., Sokhi R.S., Luhana L., Fisher B.E.A. (2008. Lagrangian modelling of plume chemistry for secondary pollutants in large industrial plumes. Atmospheric Environment 42, 415–427) and Alessandrini S., Ferrero E. (2008. A Lagrangian model with chemical reactions: application in real atmosphere. Proceedings of the 12th Int. Conf. on Harmonization within atmospheric dispersion modelling for regulatory purposes. Croatian Meteorological Journal, 43, ISSN: 1330-0083, 235–239) the treatment of ozone was modified in order to facilitate urban scale simulations encompassing dense road networks. For the street canyon application, modelled daily mean NOx/NO2 concentrations deviated by +0.4%/−15% from observations, while the correlations for NOx and NO2 were 0.67 and 0.76 respectively. NO2 concentrations were underestimated in summer, but were captured well for other seasons. In Graz a fair agreement for NOx and NO2 was obtained between observed and modelled values for NOx and NO2. Simulated diurnal cycles of NO2 and O3 matched observations reasonably well, although O3 was underestimated during the day. A possible explanation here might lie in the non-consideration of volatile organic compounds (VOCs) chemistry.

Spatial disaggregation of carbon dioxide emissions from road traffic based on multiple linear regression model

Abstract Detailed estimates of carbon dioxide emissions at fine spatial scales are critical to both modelers and decision makers dealing with global warming and climate change. Globally, traffic-related emissions of carbon dioxide are growing rapidly. This paper presents a new method based on a multiple linear regression model to disaggregate traffic-related CO2 emission estimates from the parish-level scale to a 1 × 1 km grid scale. Considering the allocation factors (population density, urban area, income, road density) together, we used a correlation and regression analysis to determine the relationship between these factors and traffic-related CO2 emissions, and developed the best-fit model. The method was applied to downscale the traffic-related CO2 emission values by parish (i.e. county) for the State of Louisiana into 1-km2 grid cells. In the four highest parishes in traffic-related CO2 emissions, the biggest area that has above average CO2 emissions is found in East Baton Rouge, and the smallest area with no CO2 emissions is also in East Baton Rouge, but Orleans has the most CO2 emissions per unit area. The result reveals that high CO2 emissions are concentrated in dense road network of urban areas with high population density and low CO2 emissions are distributed in rural areas with low population density, sparse road network. The proposed method can be used to identify the emission “hot spots” at fine scale and is considered more accurate and less time-consuming than the previous methods.