Dense Road Network Research Articles

A-posteriori analysis of the performance of a rockfall susceptibility map

BackgroundRockfalls pose a serious threat along the main road network, representing a major hazard in mountainous territory and causing damage and victims. Currently, susceptibility mapping represents a starting point to identify areas more susceptible to rockfall occurrence, a key approach in land use planning and risk management. Despite the extensive use of these maps by decision makers and administrators, the usability of such maps over time and their reliability represent a poorly discussed and examined feature.MethodsHere, we proposed a-posteriori analysis of a three-year-old rockfall susceptibility map, generated along the main road network of the Aosta Valley, an alpine region of north-western Italy. To verify map consistency over time, we implemented a dual-analysis in GIS-environment and by text mining, to respectively analyse the geocoded data and textual information derivable from the regional landslide inventory. The first one allowed us to extract rockfall events occurred after the susceptibility map generation. By this way, we operated to spatially and temporally verify the map consistency. Jointly, the textual information reported in the Event Description Form, linked to each geocoded event, are being exploited. This allowed us to derive relevant information about occurred damage and their degree, presence of protective measures or secondary roads, i.e. involvement of, farm or forestry, road.ResultsThe implemented approach allowed us to prove the quality of the previous map in terms of reliability, robustness and degree of fitting respect to the succession of rockfall occurrence over time. After only three years as many as 198 rockfall events have been occurred and collected since the map was generated. Particularly, 80% of rockfall fit with “high” and “very high” susceptibility classes, and pointed out large involvement of main roads in rockfall occurrence, representing the most affected target with damage to road pavement and vehicles, as well as a relevant involvement of existing rockfall barriers and of the dense network of forestry roads and footpaths that characterize this alpine region.ResultsThe proposed approach representing a starting point in landslide susceptibility map verification and usability as valid instrument for a reliable land planning.

Active school travel in China: Unveiling multifaceted influences for sustainable mobility

This study examines multifaceted factors influencing active school travel (AST) in China, utilizing the social ecological model as an analytical framework. Leveraging data from the China Family Panel Survey (CFPS) spanning 2014–2018 and encompassing 5,522 individuals aged 5 to 18, binary logistic regression models were employed. A stark decline in AST prevalence among students was observed over this period. Factors influencing AST behavior were identified: a dense road network, lower distance from school, and moderate temperatures promoted AST, while higher family income, access to private vehicles, and smaller households deterred participation. Maternal education and belonging to the “Gen Y” demographic also impacted AST engagement, along with paternal education level. Notably, AST was more prevalent among boys, rural students, and older students. Subgroup analyses highlighted differing influencing factors between adolescents and children. This study provides a holistic understanding of AST behavior, vital for effective intervention strategies promoting sustainable mobility.

Evaluating the Spatial Heterogeneity and Driving Factors of Sustainable Development Level in Chengdu with Point of Interest Data and Geographic Detector Model

Over the past few decades, China has undergone the largest and fastest urbanization process in world history. By 2023, Chengdu’s urbanization rate had reached 80.5%, significantly higher than the national average of 66.16%. Studying the urbanization experience of Chengdu is of great significance for optimizing urban planning policies in Chengdu and other cities in China. Although much literature has explored the urbanization process from macro and micro perspectives, studies using a top-down approach to examine urban fringe expansion are relatively scarce. This study first applies the entropy weight method to analyze the spatial-temporal evolution trends of urban development, identifying areas of imbalanced development and prominent issues. Secondly, the K-means machine learning algorithm and nightlight data are used to reconstruct and classify urban regions, and a comparative analysis is conducted with administrative divisions to further identify unreasonable areas in urban spatial distribution and structure. Finally, POI data and the geographical detector method are used to analyze the micro-driving forces in areas of imbalanced development, identifying major limiting factors and solutions. The study found that the gap between urban and rural development in Chengdu is narrowing during the urbanization process, but there is severe differentiation in the second circle of Chengdu, where economic development is accelerating but residents’ happiness is declining. Moreover, analysis based on urban nightlight data and land-use data reveals that the expansion areas on the urban-rural fringe are mainly concentrated in the second circle of Chengdu. Micro-level driving factor analysis found that the western region of the second circle has many but small urban settlements, with a dense road network but scattered functional areas. The eastern region has inefficient and extensive use of construction land. Additionally, the mismatch between student status and household registration has resulted in relatively lagging educational resource development, and high entry barriers have hindered the progress of urbanization, leading to low per capita welfare expenditure. These reasons are the main factors causing the decline in residents’ happiness, and this impact shows significant differences at different temporal and spatial scales. Encouraging innovation in research and development or education can serve as a long-term and effective driving force for promoting sustainable urbanization. This study provides valuable insights for scientifically planning sustainable urban development and promoting the urbanization process.

Auf Rädern

Abstract The article outlines the basic lines of a phenomenology of driving. The starting point is the thesis that “driving” does not occur in nature and is therefore a form of movement reserved for humans, which is linked to the invention of the wheel. This invention expanded the possibilities of mobility in technical and social terms. We argue that, on the one hand, travelling on wheels strengthens individuality and the feeling of freedom, but on the other hand it has a strong socio-political component that is often ignored: Efficient driving requires a dense road network, and this only emerges as the achievement of a community. Referring back to Matthew B. Crawford’s philosophy of driving and Günther Anders’ philosophy of technology, the question of whether the “autonomous car” restricts or expands the freedom of drivers is discussed. Finally, it is shown that the concept of driving, as manifested above all in the automobile, has also had a significant influence on our concept of social progress. However, this concept has fallen into crisis due to the ecological collateral damage of combustion technology.

Таксационная характеристика особенностей лесного фонда Барнаульского лесничества Алтайского края

The study was conducted in order to identify forestry and taxation features of forest plantations in the Barnaul forestry of the Altai Territory, located in the suburban area of Barnaul. Areas of the forest fund were selected at different distances from the city of Barnaul: in the zone of a dense network of roads and settlements (0‑15 km) and in the zone of less intensive infrastructure (37 km). Using the methods of ecological profiles, variation statistics, comparative analysis, and forest taxation, the taxation materials of 32 forest quarters were processed, including data from 718 forest taxation allotments. Using two-factor analysis of variance, it was found that the individual studied indicators of forest plantations (average height, completeness, bonus class and reserve per 1 ha) depend on the type of forest. The taxation indicators of stands in the suburban area (except for the average stock per 1 ha) do not have a reliable dependence on the features of Barnaul. The analysiso f variance in relation to the natural renewal of the main breed showed that the average height and density depend on the type of forest, and the distance from the city limits affects only the average density. High vaul es of occurrence (65.4‑89.5%) of undergrowth were noted in fresh forest, lower in grass forest (15.5‑48.4%), but the occurrence increases with distance from the city in both types of forest. Ash-leaved maple finds its ecological niche mainly in the grass forest, displacing local plant species, preventing the natural renewal of pine. It has been previously established that the parameters of forest plantations in suburban pine forests of Barnaul depend on the type of forest, showing different structural and positional stability in relation to anthropogenic factors.

Reconstructing valley landscapes. GIS-analyses of past land use changes in three Flemish river valleys since the late 18th century

The restoration of riverine ecosystem services and floodplain landscapes has become an important tool in climate mitigation, however, it is often unclear what landscape a restoration is (or should be) referring to. Little is known moreover, about long-term transitions in historic valley land use or how they echo in contemporary perceptions of floodplain landscapes. Also in densely populated Flanders (in the north of Belgium), where floodplains are quickly losing their natural functions, policymakers are actively in pursuit of climate change adaptation strategies and sustainable valley management. We present the results of a GIS-based reconstruction of historical land use in three Flemish river valleys from 1771 to 2002 and compare them to changes in regional land use. We find that while grasslands initially and to a vast extent covered our selected floodplains, the latter were by the mid-19th century cultivated for agricultural production, in line with a global expansion of arable land and regional demographic growth. Also forest cover in the studied river valleys grew exponentially from the late 19th century, unmatched by regional forest cover. After the Second World War, a denser road network, more area that is built-up and forest plantations visually contributed to valley compartmentalisation and the perception of a closed landscape. Varying soil textures and drainage levels or the (in)ability to manage them properly accounted for different(ly) (timed) land use changes between the studied floodplain areas. Regional changes in historic land use were of lesser importance.

Influence of road network expansion on the landscape ecological risk in the Yangtze River Delta region over the past two decades

One of China's regions with the finest foundations for urbanization, the Yangtze River Delta (YRD), has experienced tremendous urbanization growth over the past 20 years. It is crucial to assess how the region's rapidly expanding road network may affect the landscape ecological risk (LER) by using landscape analysis, kernel density estimation and statistical analysis. The findings concluded that 1) The LER, which was significantly affected by the landscape pattern and topography was unevenly distributed throughout the YRD region, exhibiting obvious characteristics of high LER values in the north and low LER values in the south. From 2005 to 2020, the medium and sublow LER zones showed increasing trends, with increases of 7101 and 3186 km2, respectively. The decreased areas reached 5310, 2583, and 2394 km2 for the low, subhigh, and high LER zones, respectively. 2) There were obvious spatial differences in the impact of road networks on the LER’s geographical distribution in the YRD region. Significantly negative correlation areas were mainly distributed along and around the minimum spanning tree (MST) generated by the city centers of provinces, which had dense road networks. Significantly positive correlation areas were far away from the MST. 3) From 2005 to 2020, road network expansion in the YRD region impacted the interannual changes in both the LER index and each component index. As the road network expands, the fragmentation, splitting and disturbance indices of shrubs, grasslands and impervious land patches decrease, while those of croplands, forestlands, and water bodies increase. This study can serve as a scientific foundation and point of reference for planning the road network expansion and assessing the regional ecological risk in the YRD region.

জিআইএস এবং রিমোট সেন্সিং কৌশল ব্যবহার করে SDG লক্ষ্য এবং সূচক নিরূপন:

Among the Sustainable Development Goals, SDG-11 calls for a variety of initiatives to build sustainable cities for cities and their communities. The main agenda of SDG-11 is to make cities and human settlements more inclusive, safe, resilient and sustainable. The main objective of this study is to map the road network and road density of the Bil Baghil Basin using GIS and remote sensing (mainly satellite images) in urban areas and assess the accessibility of public transport to the public for sustainable development goal 11 (SDG-11) to assess and map the current status in order to achieving SDG indicator 11.2.1. SDG Indicator 11.2.1 strives to provide safe, affordable, accessible, and sustainable transportation networks for all, increase road safety, notably through the growth of public transportation, and respond to the needs of women, children, people with disabilities, and the elderly in crisis situations. In order to ensure a sustainable transportation system it is important to determine route designs and density. Here a very high resolution (30 cm) satellite image called WorldView-03 along with Bangladesh Bureau of Statistics is used to determine the road network pattern of the study area. As the Bil Baghil basin is a fully urbanized area which has already rapidly changed into an urban area resulting maximum amount of agricultural land, water bodies, forests and open areas in the region have all decreased. According to the research findings, the study area has three types of road networks- katca, pucca and semi-pucca, of which semi-pucca roads are the most and pucca roads are the least. Some areas have high population density as well as dense road network but no bus stops for transport accessibility. The percentage of overall transport accessibility for the study area is 35.68% and the percentage of inaccessible area is 64.22%. The survey area has very few areas with high transport accessibility and the percentage of population with high transport accessibility is also very low. The study area has only 10 bus stops which did not cover the entire study area. For higher transport accessibility it is necessary to build more bus stops in the study area. Which will make this place more convenient for the movement of its residents.

Soil heavy metals in tropical coastal interface of eastern Hainan Island in China: Distribution, sources and ecological risks

Coastal interface is the most active in the global element cycling, linking the terrestrial and ocean ecosystem. However, little attention is paid to the ecological risk of multiple heavy metals (HMs) residues in tropical coastal soil and its relationships with human activities. Here, 199 coastal topsoils were collected from the eastern Hainan Island of China in 2021. Furthermore, the pollution characteristics, spatial distribution, and ecological risk of eight HMs were evaluated. The results showed that the mean contents of eight HMs were in the order of Cr (47.96 mg·kg−1) > Zn (40.93 mg·kg−1) > Pb (21.28 mg·kg−1) > Cu (14.89 mg·kg−1) > Ni (8.67 mg·kg−1) > As (5.64 mg·kg−1) > Cd (0.06 mg·kg−1) > Hg (0.05 mg·kg−1). These HMs contents were larger than the soil background values of Hainan Province, indicating the accumulation risk. Based on the Nemerow integrated pollution index, the sample sites with moderate and severe pollution accounted for 28.5% and 28.0%, respectively. In contrast, the sum of sites with no and slight pollution was only 10%. The ecological risk assessment revealed that 25% and 5% of sites displayed moderate or extreme ecological risks with the mean RI value larger than 90, and As and Cd were the most dangerous HMs. Spatially, the pollution hotspots of Zn, Pb, Cd and Hg were distributed in the middle urban of the study area and the dense road network in the west, while that of Cr, Ni, and Cu were distributed in the woodland in the northeast and southwest. The pollution hotspots of As were distributed in northeast cropland. The PMF model further indicated that the largest contributor to Zn, Pb, and Cd were the combined sources of traffic and agricultural activities, accounting for 55.66%, 56.30%, and 55.36%, respectively. Soil parent materials contributed to the Cr, Ni, and Cu, accounting for 77.1%, 58.4%, and 38.2%, respectively. Coal combustion was the main source of Hg, accounting for 81.3%, while agricultural activities accounted for 80.8% of the As in the soils. Overall, anthropogenic activities (63.60%) were the main source for HMs residues in the studied coastal soils, but the contribution of soil parent materials (36.40%) could not be neglected.

Hybrid Search with Graph Neural Networks for Constraint-Based Navigation Planning [Extended Abstract

Route planning for autonomous vehicles is a challenging task, especially in dense road networks with multiple delivery points. Additional external constraints can quickly add overhead to this already-difficult problem that often requires prompt, on-the-fly decisions. This work introduces a hybrid method combining machine learning and Constraint Programming (CP) to improve search performance. A new message passing-based graph neural network tailored to constraint solving and global search is defined. Once trained, a single neural network inference is enough to guide CP search while ensuring solution optimality. Large-scale experiments using real road networks from cities worldwide are presented. The hybrid method is effective in solving complex routing problems, addressing larger problems than those used for model training.

Analysis of the injury severity of motor vehicle–pedestrian crashes at urban intersections using spatiotemporal logistic regression models

This paper conducted a comprehensive study on the injury severity of motor vehicle–pedestrian crashes at 489 urban intersections across a dense road network based on high-resolution accident data recorded by the police from 2010 to 2019 in Hong Kong. Given that accounting for the spatial and temporal correlations simultaneously among crash data can contribute to unbiased parameter estimations for exogenous variables and improved model performance, we developed spatiotemporal logistic regression models with various spatial formulations and temporal configurations. The results indicated that the model with the Leroux conditional autoregressive prior and random walk structure outperformed other alternatives in terms of goodness-of-fit and classification accuracy. According to the parameter estimates, pedestrian age, head injury, pedestrian location, pedestrian actions, driver maneuvers, vehicle type, first point of collision, and traffic congestion status significantly affected the severity of pedestrian injuries. On the basis of our analysis, a range of targeted countermeasures integrating safety education, traffic enforcement, road design, and intelligent traffic technologies were proposed to improve the safe mobility of pedestrians at urban intersections. The present study provides a rich and sound toolkit for safety analysts to deal with spatiotemporal correlations when modeling crashes aggregated at contiguous spatial units within multiple years.

A Study on the Impact of Roads on Grassland Degradation in Shangri-La City

Shangri-La is located in the eastern part of the Qinghai-Tibet Plateau, which has a fragile ecology. The plateau grassland has suffered from irreversible degradation under the influence of human activities. To address this issue, the Sentinel-2A data obtained is used in this study to calculate the RVI and build an inversion model of grassland degradation grade with GDI data, which was used to obtain the area and proportion of grassland degradation. Landscape indexes were then calculated for different degradation grades of grassland to examine the correlation between roads and degraded grassland in spatial distance and the spatial distribution characteristics of different degradation grades of grassland. The results show that the grassland area in Shangri-La was 2207.94 km2, of which the heavily degraded area reaches 824.03 km2, exceeding the undegraded grassland area by 172.62 km2, indicating that the grassland degradation is severe. From south to north, the proportion of heavily degraded and moderately degraded grassland in townships gradually decreased, while the proportion of lightly degraded and undegraded grassland gradually increased. The townships with high percentages of degraded grassland were predominantly located in the southern area, where there was a dense road network and well-developed transport networks, particularly along National Highway 214, which is the main road in Shangri-La. Conversely, townships with low percentages are generally located in the north with dispersed roads and sparse transport lines. The study’s outcomes are significant in providing a better understanding of the current status of grassland degradation and promoting the sustainable utilization of grassland resources in Shangri-La.

A Priori Knowledge Based Ground Moving Target Indication Technique Applied to Distributed Spaceborne SAR System

Through formation flying, the distributed spaceborne SAR(synthetic aperture radar) system can increase the number of spatial degree of freedoms (DOFs) and provide flexible multi-baselines for SAR-GMTI (ground moving target indication), which improves the system performance. This paper proposes an a priori knowledge-based adaptive clutter cancellation and moving target detection technique applied to the distributed spaceborne SAR-GMTI systems. Firstly, the adaptive clutter cancellation technique is exploited to suppress the ground clutter. A priori knowledge, such as road network information, is integrated to the adaptive clutter cancellation processor to reduce any moving target steering vector mismatch. Secondly, adaptive matched filter (AMF) and adaptive beamformer orthogonal rejection test (ABORT) are exploited as adaptive detection techniques for moving target detection. Due to the dense road network, the moving target steering vector estimation may be ambiguous for the different position and orientation of the roads. The multiple hypothesis testing (MHT) technique is proposed to detect the moving targets and resolve the potential ambiguities. A scheme is exploited to detect, classify, and relocate the moving targets. Finally, simulation experiments and performance analysis have demonstrated the effectiveness and robustness of the proposed technique.

Evidence of Multi-Source Data Fusion on the Relationship between the Specific Urban Built Environment and Urban Vitality in Shenzhen

Urban vitality is the key element of sustainable urban development. This paper aims to explore the relationship between urban vitality and the existing built-up environment of the city of Shenzhen. The regression models with multi-source geographic datasets from 2021–2022 were applied to assess Shenzhen in three dimensions: economic, social, and cultural. The results show that Shenzhen’s vitality originates from multiple popular centers. Dense road networks, abundant transportation, and commercial, recreational, entertainment, sports, and leisure facilities are positive indicators of vitality, while urban villages and residential areas have the opposite effect. The model can explain 59% of vitality changes. This paper proposes a quantifiable and replicable adaptation framework for urban villages that combines urban form with data vitality assessment in order to deepen our understanding of urban villages and offer theoretical justifications for long-term urban regeneration. The findings also suggest that spatial differences should be taken into account when formulating urban regeneration responses to make them more targeted. Overall, this paper provides valuable insights for urban planners, policymaker and researchers interested in promoting sustainable urban development through vitality-based urban regeneration.

Establishing a "dynamic two-step floating catchment area method" to assess the accessibility of urban green space in Shenyang based on dynamic population data and multiple modes of transportation

As an integral part of the urban environment, urban green space (UGS) is of great significance in maintaining urban ecosystem balance and biodiversity. Spatial accessibility is an important indicator of UGS distribution and can be calculated by the two-step floating catchment area method (2SFCA). However, problems exist in previous studies using 2SFCA: (1) the dynamics in population distributions are ignored when measuring UGS demand; and (2) travel costs are calculated for only a single mode of transportation. To address these problems, this study proposes a dynamic two-step floating catchment area method (D2SFCA) based on the Baidu heatmap and direction application programming interface and compares it with the traditional 2SFCA to investigate the characteristics of and differences in UGS accessibility in the first-ring built-up area of Shenyang, China. The results show the following: (1) the dynamic population distribution data calculated by the heatmap yielded the highest population density raster (581.0–1342.0 p/hm2) in areas with dense road networks and the lowest population density raster (2.0–91.0 p/hm2) in areas with railways and rivers, thereby more accurately reflecting reality and better quantifying the UGS demand than the static population distribution data; (2) the D2SFCA and 2SFCA findings had a slightly different distribution, and the D2SFCA assessment results more accurately reflected actual patterns, especially when the road data were inaccurate. In summary, the D2SFCA is more suitable for assessing accessibility and can identify specific areas that lack UGS. This study provides a scientific basis and methodological support for improving the services level and equity of UGS.

Environmental inequalities in the municipality of Lisbon: spatial analysis of combustion gases

Some inducing factors of climate change can be attributed to a set of pollution indicators, and the territorial distribution of pollution has repercussions on environmental inequalities. Based on the case study of Lisbon, we map some environmental inequalities and how they relate to the location of transport infrastructures, green spaces, and mobility practices. How is air pollution distributed inside Lisbon? What is the relationship between the distribution of air pollution and the location of transport infrastructure, and green spaces? The results show that there are environmental inequalities, air pollution is higher in zones with a dense road network and heavy traffic. Environmentally friendly mobility practices do not exclude an exposure to higher levels of air pollution due to combustion gases, representing a mismatch between the production of pollution and environmental exposure.

Sustainable mobility strategies and their impact: a case study using a multimodal activity based model

Nowadays, many cities are intending to reduce the use of private vehicles. Governments are incorporating new mobility services and are adapting their parking policies to promote a more sustainable mobility, as both strategies are believed to have the potential to reduce private vehicle use. To understand the effects of these strategies, one needs to be able to model complex travel behaviour up to a very high level of detail. Owing to their flexibility, robustness and ability to model travel activity behaviour on an individual level, activity based travel demand models (ABM) offer a highly suitable methodology for this purpose.In this paper, we employ this methodology to perform a case study in a metropolitan region in the Netherlands which surrounds and includes the cities of Rotterdam and The Hague. This region is of vital economic importance and has a very developed and dense road network. The population of this region is growing, which motivates the ambition to improve its accessibility and move towards sustainable mobility. Therefore, the findings of this study are important to similar regions seeking to do this as well. After setting up a suitable, calibrated ABM able to perform a comprehensive study on the effects of new mobility services and parking policy adaptations in the above-mentioned region, we design seven scenarios to give quantitative answers to policy-related questions on how altering features can reduce the extent to which private vehicles are used for travelling. These features include the availability of mobility hubs (hubs on neighbourhood level where sustainable travel modes are linked), the availability of car/bike sharing services, the availability of ‘Mobility as a Service’ (MaaS) subscriptions, the amount of parking capacity in the region and the parking costs. We also study what the impact would be of an improved public transport service with lowered public transport travel times to and from the city centers, and the impact of an improved cycling network infrastructure with significantly lowered travel times for bike and e-bike travellers.Based on the case study, we find that the introduction of mobility hubs alone has limited impact. However, combining this with making sharing services available to the public through MaaS subscriptions, there is a potential to reduce the number of car trips significantly, while the number of trips undertaken by a more sustainable (shared) e-bike increases as well as the number of so-called multi-modal mode trips (trips undertaken by a combination of various modes). Furthermore, improving the public transport service and micromobility network further increases the potential of mobility hubs in terms of making mobility more sustainable. The case study also shows that limiting parking capacity and increasing parking costs in the city centers is especially helpful for the reduction of vehicle use, leading to an improved car flow.

An Automatic Generalization Method for a Dense Road Network Area Considering Spatial Structural Features as Constraints

Road networks are the skeletal elements of topographic maps at different scales, and road selection is a prerequisite for implementing continuous multiscale spatial representations of road networks. The mesh-based approach is a common, advanced and powerful method for road selection in dense road areas in which small meshes are removed and road segments with the least importance in each mesh are eliminated. However, small meshes in a map can be classified into two types: aggregated small meshes and isolated small meshes. The number of the former is small, and that of the latter is large. Existing methods are generally applicable for the latter, and some or even most spatial characteristics will be lost when they are applied to the former; as a result, the road selection quality will be affected. Therefore, as a supplement to the mesh-based selection method, this paper proposed an automatic generalization method of dense road network areas (areas formed by aggregated small meshes) considering spatial structural features as constraints. First, the aggregated areas of small meshes were identified based on the number of adjoining small meshes, and the boundaries of aggregated areas are extracted and used as hard constraints during mesh elimination. Second, the starting meshes were redefined by simultaneously considering the edge features and mesh density of small meshes, and an ordinal elimination algorithm was proposed to eliminate the meshes in the stroke connection direction. Third, road selection was implemented by identifying the starting meshes and sequentially processing the related mesh pairs. This iterative process continued until all mesh densities of the newly formed meshes are beyond the threshold or the problem becomes a simple elimination problem involving two adjoining small meshes or one isolated small mesh. Finally, a 1:10,000 standard topographic road map for Jiangsu Province, China, was used for validation. The experimental results showed that in the aggregated areas with two small meshes, 31% of the areas obtained the same selection results by using the mesh-based method and the proposed method, and the remaining 69% obtained a more compact result with the proposed method. Moreover, for all aggregated areas with more than two small meshes, the spatial distribution structure of small meshes was preserved better by the proposed method.

Simulating platooned connected autonomous vehicle in a large scale urban scenario

This article is concerned with the performance evaluation of connected, autonomous vehicles (CAVs) in a realistic large-scale microsimulation scenario. In particular the question is: how much could a high diffusion of CAVs possibly change (1)~the average travel speeds (2)~the trip times of all traffic participants, including pedestrians, and (3)~the energy/fuel consumption? For this purpose, admittedly favourable assumptions are made: a 100\% diffusion of platooning-capable CAVs as substitution for private cars as well as a high maximum speed of platooned vehiclesin order to enable platoon formation. The morning rush hour scenario of the metropolitan area of Bologna, Italy has been selected for assessment. This scenario, which has been created and validated in previous works, represents an activity based demand model with travel plans for individual citizens, including all relevant transport modes. The microsimulation is performed by means of the SUMO simulator. The entire demand has been generated with the SUMOPy tool. For the platooning of CAVs, SUMO's SIMPLA module has been used, which controlls the vehicles via the interactive TRACI API. Results show an increased speed and reduced travel time for CAV vehicles, with respect to human driven cars, in particular in the periphery and less in the center with a dense road network. However, the reason for improved speeds and travel times is predominantly the higher maximum speed allowed for vehicles trying to catch up and join a platoon. Furthermore these higher speed would also be resposible for an increase in fuel consumption of approximately 5\%. In conclusion, CAVs alone are unlikely to reduce congestion in an urban area. To make the platooning concept work, additional technology and infrastructure is required in order to merge platoons effectively at freeways and at traffic lights. The latter could be simulated with GLOSA.

Urban green and blue space changes: A spatiotemporal evaluation of impacts on ecosystem service value in Bangladesh

The rapid decline in urban green (UGS) and blue space (UBS) in developing countries has led to a widespread degradation of available ecosystem services (ES). However, impacts of UGS and UBS changes on ES tend to vary over space and time, and to date these impacts have not been studied in sufficient detail in emerging economies. By comparing UGS and UBS change patterns with multitemporal Landsat data recorded during the past 30 years (1991–2021), this study has examined the impact of several factors on ES in some of the world's climate hotspots. Although obtaining relevant and accurate information on ES is difficult in many parts of the developing world, this work has developed baseline data suitable for assessing ES loss over five densely populated cities in Bangladesh – Dhaka, Chattogram, Khulna, Rajshahi, and Sylhet. ES loss was quantified in monetary terms using adjusted value coefficients. The topographic and anthropogenic factors driving spatial differences in ES degradation in these cities were analyzed with a geographical detector. The results indicated that the cities experienced a combined monetary loss of USD 628.58 million as a result of specific ES degradation, primarily due to the decline of UGS and UBS. The value of ES loss was notably higher in Dhaka and Chattogram than in the other cities due to marked differences in anthropogenic activities. Population growth, extensive urban sprawl, and the development of dense road networks were identified as the major causes of urban green and blue space loss and consequent reduction of ES. The findings of this study provide important insights which can be used to support the formulation of public policies and management plans aimed at restoring and maintaining sustainable urban ecosystems.