Road Edge Research Articles

Identification of restoration species for early roadcut slope regeneration using functional group approach

Current restoration protocols for roadside cut slopes in South Korea involve hydroseeding with exotic species to achieve early greening and soil stabilization. However, exotic species can negatively affect adjacent native ecosystems. This study investigated the functional traits of early colonizers in slope restoration and surrounding environments to inform restoration methods that generate similar communities as those of native ecosystems. Slope vegetation (species density, species cover, upperstory species, canopy cover) and environment (aspect, angle, soil properties) were surveyed from the road edge to the forest boundary, and were classified as three distinct zones: a hydroseeded slope, a transition zone, and the forest edge. Naturally occurring species were classified into functional groups to examine dominant traits during early colonization. Hemicryptophyte or geophyte forest species and forest interior woody species were well established and dominant in transition zones and cut slopes. Potential native species for slope restoration can be identified by examining functional group species in the adjacent forest. These native species can achieve restoration goals and block invasive species in the same functional group. Festuca arundinacea (tall fescue), which is reported as an invasive alien species, rapidly spread after introduction for restoration. Thus, continuous monitoring for impact on native communities is required after sowing invasive alien species. Future slope restoration should consider native woody species and perennial forest sedge species that develop rhizomes, and reconsider the use of tall fescue. This study indicates that cut slopes can be appropriately managed to enhance the quality of habitats for native species.

The Extraction of Street Curbs from Mobile Laser Scanning Data in Urban Areas

The demand for mobile laser scanning in urban areas has grown in recent years. Mobile-based light detection and ranging (LiDAR) technology can be used to collect high-precision digital information on city roads and building façades. However, due to the small size of curbs, the information that can be used for curb detection is limited. Moreover, occlusion may cause the extraction method unable to correctly capture the curb area. This paper presents the development of an algorithm for extracting street curbs from mobile-based LiDAR point cloud data to support city managers in street deformation monitoring and urban street reconstruction. The proposed method extracts curbs in three complex scenarios: vegetation covering the curbs, curved street curbs, and occlusion curbs by vehicles, pedestrians. This paper combined both spatial information and geometric information, using the spatial attributes of the road boundary. It can adapt to different heights and different road boundary structures. Analyses of real study sites show the rationality and applicability of this method for obtaining accurate results in curb-based street extraction from mobile-based LiDAR data. The overall performance of road curb extraction is fully discussed, and the results are shown to be promising. Both the completeness and correctness of the extracted left and right road edges are greater than 98%.

Calculation of the Roadside Clear Zone Width along Highways Based on the Safe Slope

International crash data indicate that roadside characteristics contribute to more than half of all roadside accidents involving serious injury or death. Therefore, research on roadside safety is urgently needed. Based on the vehicle departure speed, pavement height (i.e., the difference between pavement elevation and ground elevation), slope gradient, and horizontal curve radius, this study uses PC-Crash simulation software to carry out tests of trucks and cars exiting a road. A chi-squared automatic interaction detection (CHAID) decision tree is used to explore the causative mechanism of vehicle rollover, and the concept of a “safe slope” to ensure that vehicles do not roll over is proposed. Aiming at straight and curved sections, discriminant functions of vehicle rollover and nonrollover are fitted through Bayesian discriminant analysis, and safe slope calculation models for trucks and cars are then constructed. Based on the obtained safe slope models, calculation methods for the safe slope and the roadside clear zone width involving different traffic compositions are proposed by calibrating the lateral distance from the final position of nonrollover vehicles to the road edge. The results show that the factors affecting vehicle rollover are, in descending order of importance, the slope gradient, pavement height, vehicle type, departure speed, and horizontal curve radius. For a section with a large proportion of cars, the slope gradient should not be steeper than 1:3.5. The horizontal curve radius should not be less than 600 m for a section with a large proportion of trucks and a slope gradient steeper than 1:3.5 or shallower than 1:2.5. Additionally, for a section with a pavement higher than 0.5 m and a slope gradient steeper than 1:2.5, the operating speed limit should be lower than 60 km/h. These research results have theoretical value and practical significance to improve the driving safety level and reducing the risk of roadside accidents.

Road Edge Parking Management Strategy in Semarang City: Collaborative Governance Perspective

Roadside parking makes a large contribution to local revenue if managed properly. However, in its implementation, there have been many practices of "illegal parking" which have made the management very bad and caused losses to the parking users. Thus, government collaboration in parking management is important to involve all relevant stakeholders involved as a whole, forming cooperation, both in consensus and in decision making. This study focuses on-street parking management strategy from a collaborative governance perspective. This study used a descriptive qualitative method with the research location in the city of Semarang. Data collection was carried out through in-depth interviews with related agencies, apart from observing and documenting. From observations in the field, the researchers found that the Semarang City Government has not performed its function optimally as the main pillar in determining policies related to parking management. For this reason, a management strategy with a government collaboration concept approach that involves several stakeholders is needed to solve the parking problem collectively. With the concept of collaborative governance, it will reduce irregularities and monopolies in the implementation of parking management.

Potential of Sloped Solar Chimney for the Architectural Development of Sustainable Applied Technology Models for Passive Air Ventilation

This paper presents the result of research section for solar chimney (SC) model innovation as a passive cooling strategy. The research is motivated by sustainability issues, especially on the issue of environmental degradation due to uncontrolled use of air conditioning in urban environments. The vertical SC (VSC) model has been tested by the author et al., 2018. Although in general the presence of VSC has a significant effect on room temperature but it turns out that the VSC column height, that is assumed as the main determinant of performance, does not significantly influence [1]. The character of sun altitude in Indonesia is believed to cause the vertical chimney to be ineffective. For this reason, this study tested the Sloped Solar Chimney (SSC) model. The purpose of this study is to test whether: (1) SSC is better than VSC; (2) the sloping chimney thickness and internal chimney height give a difference in SC performance. The SSC model consists of three components: (1) internal vertical chimney inlet; (2) External 30â° slope and (3) external outlets. The test model is made from galvalum. Overall, the research method was carried out in two stages, namely: (1) testing the simulative models by using a software based on empirical data on the context of the urban housing environment being sampled; (2) testing the models in the field. However, only the result of the first stage is presented in this paper. The location of the urban environment of dense housing used as a case study was Jogoyudan, Yogyakarta. The empirical data input consists of 3 groups of houses: on the banks of the river, in the middle of a dense housing and on the edge of a neighborhood road. The modeling software used is CFD analysis. The analysis uses a comparative test statistic with a confidence level of 5%. From the results of the study it is found that SSC caused different thermal qualities in the test model room. The thickness of the sloping chimney also gives a difference in the thermal quality of space. However, this phase of the research has not been able to show significant effects due to the differences in height of the internal chimney.

A Real-Time Curb Detection Method for Vehicle by Using a 3D-LiDAR Sensor

<div class="section abstract"><div class="htmlview paragraph">Effectively detecting road boundaries in real time is critical to the applications of autonomous vehicles, such as vehicle localization, path planning and environmental understanding. To precisely extract the road boundaries from the 3D-LiDAR data, a dedicated algorithm consisting of four steps is proposed in this paper. The steps are as follows: Firstly, the 3D-LiDAR data is pre-processed by employing the RANSAC method, the ground points are quickly separated from the original 3D-LiDAR point cloud to reduce the disturbance from the obstacles on the road, this greatly decreases the size of the point cloud to be processed. Secondly, based on the principle of 3D-LiDAR scanning, the ground points are divided into scan layers. And the road boundary points of each scan layer are detected by using three spatial features based on sliding window. Thirdly, based on the improved beam model, the road type (straight road or curved road) where the vehicle is located is predicted, and then the edge points are subdivided into different areas by the road type. Finally, we use the distance filtering and RANSAC filtering to filter out false road boundary points caused by obstacles and obtain accurate road boundaries. Compared to other methods, we can effectively reduce the wrong classification of road edge points caused by obstacles by using the improved beam model. And the false points caused by obstacles are effectively reduced by using distance filtering and RANSAC filtering. The performance of the proposed method is verified through experiments with a vehicle driving on campus roads and extensive tests with the KITTI data set the experimental results demonstrate the accuracy and robustness of the proposed method.</div></div>

Open-Pit Mine Road Extraction From High-Resolution Remote Sensing Images Using RATT-UNet

With the further development of the construction of “smart mine,” the technology of mine unmanned truck has developed rapidly. Road data are an important prerequisite for the mature application of mining and transportation dispatching system and unmanned driving, so it is particularly important to extract the road in open-pit mines timely and accurately. Different from urban roads, mine roads have no clear road edge and more background interference. In view of the above problems, a convolutional neural network called RATT-UNet (R: residual connection; ATT: attention), which combines residual connection, attention mechanism, and U-Net, is proposed to extract mine road from high-resolution remote sensing images. The advantages of the proposed method are listed as follows: first, the well-designed RATT unit combining residual connection and attention mechanism is used to construct the proposed neural network, which improves the network’s perception ability of detailed features. Second, the abundant skip connections and residual connections can improve the information flow, allowing a better network to be designed with fewer parameters. Third, a composite loss function based on structural similarity is proposed, which effectively alleviates the noise and edge blurring phenomenon and improves segmentation quality. Finally, we perform postprocessing optimization operations on the road extraction results. Experimental results demonstrate that the proposed RATT-UNet outperforms all the comparing network models in terms of the quality of extraction results and evaluation indicators in the mining road extraction task.

Performance Evaluation Towards Automatic Building and Road Detection Technique for High-Resolution Remote Sensing Images

Building and road detection from the high-resolution remote sensing images has many applications in a wide range of areas including urban design, real-estate management, and disaster relief. Extracting buildings and roads from the remote sensing images have been performed by human experts manually, but it takes too much time and the cost of labor to build is also very high. So, an automated system that can emulate a human operator is desired. Our goal is to develop a system for automatically detecting buildings and roads directly from high-resolution satellite images. Therefore, we propose Internal Gray Variance (IGV) to detect the buildings and roads in the urban areas. First, the satellite images are enhanced by using morphological operators, which enhance the edges of the objects. Then multiseed-based clustering technique detects the building and road edges using the variance in the gray levels. To reduce the false alarm, tiny regions that are improbable to be buildings and roads are separated. Finally, by using the adaptive threshold-based segmentation technique, the buildings are segmented and the road network is extracted based on supervised directional homogeneity. Finally, we evaluate our system on a large-scale road and building detection data sets that are publicly available.

Using Different Types of Projectiles to Make Avalanches to Avoid Human Being Disasters and Properties Destruction

Some geological phenomena as landslides and the mobilization of the accumulated rocks or soil are discussed in this research by using projectiles that cause mobility and falling of these land masses which are present at the top of mountains and edges of roads and streets to avoid accidents and human disasters which will occur if they are left falling by effect of climate or vibrating factors that are produced by performing dams, bridges and reservoirs. According to the different divisions of land masses groups, primary and secondary, which depend on type of movement and material arrangement that form the mobile masses, this research had shown the effect of projectiles for every type of cannons on the mobility of every groups of these rocks masses by forming vibrations and earthquakes as a result of these different types of projectiles according to their power degrees.

Design of Road-Side Barriers to Mitigate Air Pollution near Roads

The effects of using solid barriers on the dispersion of air pollutants emitted from the traffic of vehicles on roads located over flat areas were quantified, aiming to identify the geometry that maximizes the mitigation effect of air pollution near the road at the lowest barrier cost. Toward that end, a near road Computational Fluid Dynamics (NR-CFD) model that simulates the dispersion phenomena occurring in the near-surface atmosphere (<250 m high) in a small computational domain (<1 km long), via Computational Fluid Dynamics (CFD) was used. Results from the NR-CFD model were highly correlated (R2 > 0.96) with the sulfur hexafluoride (SF6) concentrations measured by the US-National Oceanic and Atmospheric Administration (US-NOAA) in 2008 downwind a line source emission, for the case of a 6m near road solid straight barrier and for the case without any barrier. Then, the effects of different geometries, sizes, and locations were considered. Results showed that, under all barrier configurations, the normalized pollutant concentrations downwind the barrier are highly correlated (R2 > 0.86) to the concentrations observed without barrier. The best cost-effective configuration was observed with a quarter-ellipse barrier geometry with a height equivalent to 15% of the road width and located at the road edge, where the pollutant concentrations were 76% lower than the ones observed without any barrier.

The impacts of a logging road on the soil microbial communities, and carbon and nitrogen components in a Northern Zone Costa Rican forest

Logging road development is considered as potentially more damaging to a tropical forest than the felling of the actual trees. However, little work has been conducted to determine how logging road development impacts the soil microbial communities and associated C and N cycle activities in tropical forests. This study was conducted within an upland tropical forest in the Northern Zone of Costa Rica that had a 2-year abandoned logging road system (used for harvesting trees felled during a tornado) to determine how development of logging roads affected soil C and N cycle activities, efficiency of organic C use, and bacterial and fungal community compositions. Soil samples from a set of logging roads, the road edges, and adjacent primary forests were analyzed for C, N metrics, the Microbial Quotients, and DNA-based microbial taxonomic community compositions; which were tested for differences using multivariate statistical analyses. The logging road soils had significantly greater bulk density and clay, and lower levels of sand, TN, NO3−, NO3−/NH4+, TOC, C Biomass, and Microbial Quotients compared to the road edge and forest soils. The composition of the total bacterial genera of the road edge and forest soils were similar to one another and different from that of the logging road soils, and the composition of the total fungal genera was unique within each of the three areas sampled. The relative abundance of DNA sequences of N-cycle bacteria were greater, and lignin degrading bacteria and wood rot/lignin degrading fungi were less in the logging roads compared to the edge and forest soils. These results suggest that the rate of recovery of both the C and N cycle activities and associated microbial groups in the soils from the road edges is occurring more rapidly than in the abandoned logging road soils. Thus, we suggest that a new tropical forest management practice should include the movement of the slash and debris from the road edge regions onto the logging roads after abandonment, as it would enhance the rate of recovery of both the C and N cycle activities in the soils, and perhaps begin to address the concern that logging roads add an additional 10–15 years to tropical forest recovery following deforestation.

Impacts of multiple pollutants on pollinator activity in road verges

Abstract To tackle pollinator declines, there is a major need to increase the quantity of flower‐rich habitats. Road verges offer one such opportunity but are exposed to diverse forms of pollution from roads and road traffic. We carried out a broad initial assessment to establish if and how pollution affects the quality of road verges as pollinator foraging environments. We assessed the spatial distribution of pollution, flowers and pollinators in road verges, then used field experiments to simulate and measure the impacts of four ubiquitous and little studied forms of road pollution (noise, turbulence, dust and metals) on pollinator densities and foraging behaviour. We found that pollinators in road verges were exposed to noise, turbulence, dust and metal pollution, which decreased with distance from the road edge but, with the exception of turbulence, extended more than 8 m into road verges. Pollinator densities were lower closer to the road edge—particularly within first 2 m (55% lower than at 7–9 m)—where pollution is greatest. This was despite a similar density and species richness of flowers. Simulated turbulence deterred pollinators by causing intermittent disturbance (reducing visit duration by up to 54%), and some pollinator taxa preferentially avoided concentrations of metals that were more frequently found in flowers within 2 m of roads (resulting in up to 75% fewer visits), while noise and dust had no apparent effect. Synthesis and applications. Pollinators in road verges are exposed to many forms of pollution, and we found impacts of roadside‐realistic levels of turbulence and metals on pollinator densities and foraging behaviour. Although the findings suggest that road verges are largely suitable for pollinator conservation, management enhancements should prioritise areas more than 2 m from the road edge, and verges along roads with relatively lower traffic densities.

Snakes on a lane: Road type and edge habitat predict hotspots of snake road mortality

Roads constitute just 1% of the total land in the US, but their impacts on wildlife are significant and far-reaching. Snakes are particularly susceptible to road mortality because many species do not avoid crossing roads, may use the road’s surface to thermoregulate, or freeze when approached by a vehicle. We conducted opportunistic surveys to collect road mortality points for snakes in southeastern Ohio over 15 years (2003–2018). We used logistic regression to predict roadkill hotspots and evaluate variables that influence road mortality. The species most frequently found dead on roads were Black Ratsnakes (Pantherophis spiloides), Northern Black Racers (Coluber constrictor), Eastern Gartersnakes (Thamnophis sirtalis), and Rough Greensnakes (Opheodrys aestivus). Across the 14 snake species we recorded dead on roads, percent pasture within a 100 m buffer of the roadkill point, township route, county route, and state route were all negative predictors of road mortality. All surveys started in Athens, Ohio, and distance to roadkill locations was a positive predictor for road mortality. These results indicate that high-traffic roads pose a risk to snake populations, but that mortality also occurs on low-traffic roads as well. Our top model showed that low levels of pasture embedded in other land cover types was an important predictor of roadkill, suggesting that edge habitat contributes to snake road mortality. Because road mortality does not seem to be localized, road mortality mitigation structures such as underpasses and fences may have limited benefits for snake populations in our study area. The creation of edge habitat away from roads could provide snakes with necessary habitat without increasing their risk of mortality.

Effects of Natural Habitat Loss and Edge Effects on Wild Bees and Pollination Services in Remnant Prairies

Habitat loss and edge effects resulting from habitat fragmentation are key processes implicated in the decline of bee populations globally. Their effects on wild bees and their pollination services in natural ecosystems are poorly understood, particularly in North American prairies. Our objectives were to determine whether natural habitat loss and edge effects affect bee abundance and pollination services in the Northern Great Plains. We sampled bee abundance and pollination services along transects beginning at road or tree edges in grasslands located in Manitoba, Canada. We measured bee abundance using pan traps, and pollination services using seed-set of Brassica rapa (L.) (Brassicales: Brassicaceae) phytometers. We collected local-scale habitat data by measuring occurrence of flowering species, vegetation type, and vegetation structure, and we measured habitat amount at 1-km radii using GIS analysis of landscape cover. Increasing amounts of habitat loss resulted in declines in bee abundance, and sometimes in pollination services. Results varied with bee life-history: proximity to road edges negatively affected social bees, and litter depth had negative effects on below- ground-nesting bees. Surprisingly, few effects on bees led to corresponding impacts on pollination services. This suggests that conservation of intact natural habitat across the northern Great Plains is important for maintaining resilient and diverse bee communities, but that efforts to conserve bee populations cannot be assumed to also maintain all associated pollination services.

RoadEdgeNet: Road Edge Detection System Using Surround View Camera Images

Road Edge is defined as the borderline where there is a change from the road surface to the non-road surface. Most of the currently existing solutions for Road Edge Detection use only a single front camera to capture the input image; hence, the system’s performance and robustness suffer. Our efficient CNN trained on a very diverse dataset yields more than 98% semantic segmentation for the road surface, which is then used to obtain road edge segments for individual camera images. Afterward, the multi-cameras raw road edges are transformed into world coordinates, and RANSAC curve fitting is used to get the final road edges on both sides of the vehicle for driving assistance. The process of road edge extraction is also very computationally efficient as we can use the same generic road segmentation output, which is computed along with other semantic segmentation for driving assistance and autonomous driving. RoadEdgeNet algorithm is designed for automated driving in series production, and we discuss the various challenges and limitations of the current algorithm.

Annual weedy species of Erigeron in the northern Iberian Peninsula: a review

A revision of the alien Erigeron L. species formerly included in Conyza Less. found in the central-northern Iberian Peninsula is presented. A close examination of numerous specimens collected by the authors as well as voucher specimens preserved at several herbaria has helped clarify several aspects regarding this group. Four species have been recognised in the study area: Erigeron canadensis (=Conyza canadensis), E. bonariensis (=C. bonariensis), E. sumatrensis (=C. sumatrensis) and E. floribundus (=C. floribunda, including C. bilbaoana). They occupy anthropogenic habitats, such as road edges, abandoned fields, crops and waste ground, as well as natural and semi-natural communities, such as nitrophilous river bar communities and ruderal communities on coastal dunes subjected to substantial levels of anthropogenic disturbance. Erigeron sumatrensis and E. floribundus emerge as the two most frequent taxa. Erigeron canadensis, regarded in the past as the most widespread species of the group, is almost absent from the study area, especially from the Atlantic watershed. Furthermore, an important number of specimens previously identified as E. bonariensis do actually correspond to E. sumatrensis. No hybrids have been found. A detailed identification key highlighting the main features that help to separate the four Erigeron species is presented. Finally, as E. floribundus is the most controversial species in the group and the last to arrive, a study of its expansion across western Europe in the last century is included, where it has become a frequent alien especially along the Atlantic regions.

Soil properties limiting vegetation establishment along roadsides.

Roadside vegetation provides a multitude of ecosystem services, including pollutant remediation, runoff reduction, wildlife habitat, and aesthetic scenery. Establishment of permanent vegetation along paved roads after construction can be challenging, particularly within 1 m of the pavement. Adverse soil conditions could be one of the leading factors limiting roadside vegetation growth. In this study, we assessed soil physical and chemical properties along a transect perpendicular to the road at six microtopographic positions (road edge, shoulder, side slope, ditch, backslope, and field edge) along two highway segments near Beaver Crossing and Sargent, NE. At the Beaver Crossing site, Na concentration was 81 times, exchangeable Na 66 times, and cone index (compaction parameter) six times higher at the road-edge position (closest to the paved road and with sparse vegetation) compared to positions with abundant vegetation (ditch or field edge). At the Sargent site, Na concentration was 111 times, exchangeable Na 213 times, and cone index up to two times higher at the road-edge position compared with ditch or field-edge positions. Likewise, electrical conductivity was higher and macroaggregation and water infiltration were lower at the road edge than at the ditch or field-edge positions. Soil properties improved with increasing distance from the road. Exchangeable Na percentage and cone index at the road-edge position exceeded threshold levels for the growth of sensitive plants. Thus, high Na concentration and increased compaction at the road edge appear to be the leading soil properties limiting vegetation establishment along Nebraska highways.

Bird community structure and species responses to edges in laurel forest fragmented by narrow roads (Tenerife, Canary Islands)

We examined interacting effects of habitat structure, topographic landscape, road edge and vehicle traffic (density and noise), on bird species composition, abundance and diversity in the laurel forest of Tenerife (Canaries). We examined multivariate habitat and landscape factors determining bird community composition and structure, and modality of specific responses by comparing road edge vs interior zones. Abundance of breeding birds in laurel forest showed slight to no increases in response to roads. Two specialized taxa, the palaeoendemic pigeon Columba bollii and Regulus regulus, revealed neatest negative reductions in abundance near roads. Higher noise levels, vegetation density, lower canopy closure and wood selective extraction characterized roadsides. Most passerines showed moderate affinity for forest edges and did not evidence decreases due to road proximity. The topographic landscape in these mountainous areas strongly interacted with road edge effects to determine bird community structure. Narrow road disturbances on the laurel forest was related to moderate increase in bird abundance and diversity near edges, but at the cost of losing presence of forest-demanding species playing important ecological roles.

Nepôvodná burina Xanthium spinosum na Slovensku I: rozšírenie a biotopy

Xanthium spinosum is a naturalized neophyte of agricultural land, its distribution and habitats have not yet been studied in detail in Slovakia. The aim of the work was to collect all floristic data of this weed species, to present its current and historical distribution, and to characterize its typical habitats in Slovakia. As shown in analysis, Xanthium spinosum occurs mainly in the Pannonian region; in the Carpathians it was more frequent only in the 19th century and in connection with the transport of diaspores by sheep wool. The number of localities increased gradually until the 1970s, but then fell sharply due to the intensification of agriculture. Consequently, it is currently not considered to be a significant weed in Slovakia. X. spinosum mostly occupies open and sunny ruderal habitats (road edges, manure pits, field roads, abandoned fields and places) and especially pastures, rarely river banks. Both in the past and today, the species rarely occurs in fields.

On Comparing the Similarity and Dissimilarity Between Two Distinct Vehicular Trajectories

In this paper, we study the problem of comparing the similarity and dissimilarity between two distinct vehicular trajectories by proposing an adjacency-based metric. This approach has a broad application in building truthfulness by comparing the similarity between two vehicles and evaluating the dissimilarity between two distinct paths in hazardous materials transportation. Given two sequences $A$ and $B$ of Point of Interests (POIs) visited by two vehicles in a road/transportation network, the problem is to delete some nodes from $A$ and $B$ to obtain $A'$ and $B'$ such that the number of adjacencies in $A'$ and $B'$ is maximized. In the sequences $A'$ and $B'$ duplicated nodes are allowed, e.g., to represent road edges. We prove that this problem is NP-hard when noisy POIs are deleted and all the remaining POIs must be involved in some adjacency. On the other hand, when the adjacency involvement constraint is dropped, a variation of the problem is as hard as Exact Set Cover hence cannot be approximated within a constant factor unless P=NP. At last, we design a practical approach based on local search and show that the algorithm is very effective on simulation data.