scholarly journals FOREST ROADIDENTIFICATION AND EXTRACTIONOF THROUGH ADVANCED LOG MATCHING TECHNIQUES

2017 ◽  
Vol XLII-3/W3 ◽  
pp. 201-207
Author(s):  
W. Zhang ◽  
B. Hu ◽  
L. Quist
Keyword(s):  
Road Network ◽  
Test Area ◽  
Lidar Data ◽  
Tensor Voting ◽  
Multispectral Imagery ◽  
Visual Examination ◽  
Forest Road ◽  
The Road ◽  
Matching Techniques ◽  
Road Segments

A novel algorithm for forest road identification and extraction was developed. The algorithm utilized Laplacian of Gaussian (LoG) filter and slope calculation on high resolution multispectral imagery and LiDAR data respectively to extract both primary road and secondary road segments in the forest area. The proposed method used road shape feature to extract the road segments, which have been further processed as objects with orientation preserved. The road network was generated after post processing with tensor voting. The proposed method was tested on Hearst forest, located in central Ontario, Canada. Based on visual examination against manually digitized roads, the majority of roads from the test area have been identified and extracted from the process.

Optimales Layout einer Walderschliessung

2016 ◽  
Vol 167 (5) ◽  
pp. 294-301
Author(s):  
Leo Bont
Keyword(s):  
Road Network ◽  
Spatial Arrangement ◽  
Problem Situation ◽  
Optimal Layout ◽  
Forest Road ◽  
The Road ◽  
Network Cost ◽  
User Friendly ◽  
Short Time

Optimal layout of a forest road network The road network is the backbone of forest management. When creating or redesigning a forest road network, one important question is how to shape the layout, this means to fix the spatial arrangement and the dimensioning standard of the roads. We consider two kinds of layout problems. First, new forest road network in an area without any such development yet, and second, redesign of existing road network for actual requirements. For each problem situation, we will present a method that allows to detect automatically the optimal road and harvesting layout. The method aims to identify a road network that concurrently minimizes the harvesting cost, the road network cost (construction and maintenance) and the hauling cost over the entire life cycle. Ecological issues can be considered as well. The method will be presented and discussed with the help of two case studies. The main benefit of the application of optimization tools consists in an objective-based planning, which allows to check and compare different scenarios and objectives within a short time. The responses coming from the case study regions were highly positive: practitioners suggest to make those methods a standard practice and to further develop the prototype to a user-friendly expert software.

scholarly journals Towards a Rule-driven Approach for Updating Dynamic Road Segments

2012 ◽  
Vol 22 (6) ◽  
pp. 405-411
Author(s):  
Mohammad Reza Jelokhani-Niaraki ◽  
Ali Asghar Alesheikh ◽  
Abbas Alimohammadi ◽  
Abolghasem Sadeghi-Niaraki
Keyword(s):  
Data Model ◽  
Road Network ◽  
Road Maintenance ◽  
The Road ◽  
Dynamic Segmentation ◽  
Transportation Organization ◽  
Manual Tasks ◽  
The City ◽  
Transportation Applications ◽  
Road Segments

In recent years, the development of the GIS-T (Geographic Information System for Transportation) applications has gained much attention, providing the transportation planners and managers with in-depth knowledge to achieve better decisions. Needless to say, developing a successful GIS for transportation applications is highly dependent on the design of a well-structured data model. Dynamic segmentation (DS) data model is a popular one being used more and more for different GIS-T analyses, serving as a data model that splits linear features into new set of segments wherever its attributes change. In most cases, the sets of segments presenting a particular attribute change frequently. Transportation managers place great importance on having regular update and revision of segmented data to ensure correct and precise decisions are made. However, updating the segmented data manually is a difficult task and a time-consuming process to do, demanding an automatic approach. To alleviate this, the present study describes a rule-based method using topological concept to simply update road segments and replace the manual tasks that users are to carry out. The proposed approach was employed and implemented on real road network data of the City of Tehran provided by the Road Maintenance and Transportation Organization (RMTO) of Iran. The practical results demonstrated that the time, cost, human-type errors, and complexity involved in update tasks are all reduced. KEYWORDS: GIS-T, dynamic segmentation, segment, automatic update, change type, rule

Taxi Global Positioning System Data in Urban Road Network: A Methodology to Identify Key Road Clusters Based on Travel Speed–Traffic Volume Correlation

2021 ◽  
pp. 036119812110366
Author(s):  
Yi Li ◽  
Weifeng Li ◽  
Qing Yu ◽  
Han Yang
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Travel Speed ◽  
Detection Algorithm ◽  
Traffic Volume ◽  
Urban Traffic ◽  
Mitigation Strategies ◽  
Operating Characteristics ◽  
The Road ◽  
Road Segments

Urban traffic congestion is one of the urban diseases that needs to be solved urgently. Research has already found that a few road segments can significantly influence the overall operation of the road network. Traditional congestion mitigation strategies mainly focus on the topological structure and the transport performance of each single key road segment. However, the propagation characteristics of congestion indicate that the interaction between road segments and the correlation between travel speed and traffic volume should also be considered. The definition is proposed for “key road cluster” as a group of road segments with strong correlation and spatial compactness. A methodology is proposed to identify key road clusters in the network and understand the operating characteristics of key road clusters. Considering the correlation between travel speed and traffic volume, a unidirectional-weighted correlation network is constructed. The community detection algorithm is applied to partition road segments into key road clusters. Three indexes are used to evaluate and describe the characteristic of these road clusters, including sensitivity, importance, and IS. A case study is carried out using taxi GPS data of Shanghai, China, from May 1 to 17, 2019. A total of 44 key road clusters are identified in the road network. According to their spatial distribution patterns, these key road clusters can be classified into three types—along with network skeletons, around transportation hubs, and near bridges. The methodology unveils the mechanism of congestion formation and propagation, which can offer significant support for traffic management.

scholarly journals Forest road erosion

2012 ◽  
Vol 51 (No. 1) ◽  
pp. 37-46 ◽  
Author(s):  
J. Dobiáš
Keyword(s):  
Road Network ◽  
Mechanical Damage ◽  
Mountainous Areas ◽  
Water Stream ◽  
Forest Road ◽  
The Road ◽  
Water Flows ◽  
Tangential Stresses ◽  
Precipitation Water ◽  
Forest Lands

The forest road network influences surface runoff of uninfiltrated precipitation water on forest lands, mainly in hilly and mountainous areas. This water flows onto the road crown in unpaved forest roads that do not have any ditches. Dragging of extracted logs causes mechanical damage to the crown of unpaved forest road, and tracks after tractor wheels and furrows after dragged logs originate. Flowing water is accumulated in these depressions and the water stream causes erosion. The method for evaluation of conditions for the origination and degree of this erosion damage consists in the calculation of tangential stresses near the bottom at various depths of water and various gradients of road. Limit gradients of road for the origination of greater or smaller damage by erosion for the subsoil grain of various sizes are determined by a comparison of calculated tangential stresses with critical tangential stresses. Rates of discharge were calculated for the particular models of damage.

A Safe-Region Approach to a Moving k-RNN Queries in a Directed Road Network

2017 ◽  
Vol 26 (05) ◽  
pp. 1750071 ◽  
Author(s):  
Kamil Zeberga ◽  
Rize Jin ◽  
Hyung-Ju Cho ◽  
Tae-Sun Chung
Keyword(s):  
Road Network ◽  
Nearest Neighbor ◽  
Exact Formula ◽  
Specific Situation ◽  
The Road ◽  
Query Answer ◽  
Safe Region ◽  
On The Road ◽  
Conventional Solution ◽  
Road Segments

In road networks, [Formula: see text]-range nearest neighbor ([Formula: see text]-RNN) queries locate the [Formula: see text]-closest neighbors for every point on the road segments, within a given query region defined by the user, based on the network distance. This is an important task because the user's location information may be inaccurate; furthermore, users may be unwilling to reveal their exact location for privacy reasons. Therefore, under this type of specific situation, the server returns candidate objects for every point on the road segments and the client evaluates and chooses exact [Formula: see text] nearest objects from the candidate objects. Evaluating the query results at each timestamp to keep the freshness of the query answer, while the query object is moving, will create significant computation burden for the client. We therefore propose an efficient approach called a safe-region-based approach (SRA) for computing a safe segment region and the safe exit points of a moving nearest neighbor (NN) query in a road network. SRA avoids evaluation of candidate answers returned by the location-based server since it will have high computation cost in the query side. Additionally, we applied SRA for a directed road network, where each road network has a particular orientation and the network distances are not symmetric. Our experimental results demonstrate that SRA significantly outperforms a conventional solution in terms of both computational and communication costs.

Lowering Bicycle Stress One Link at a Time: Where Should We Invest in Infrastructure?

2018 ◽  
Vol 2672 (36) ◽  
pp. 33-41 ◽  
Author(s):  
Sarah K. Moran ◽  
William Tsay ◽  
Sean Lawrence ◽  
Gregory R. Krykewycz
Keyword(s):  
Road Network ◽  
Regional Scale ◽  
Shortest Paths ◽  
Connectivity Analysis ◽  
Street Segment ◽  
The Road ◽  
Computational Optimization ◽  
Ranked List ◽  
Road Segments

This paper presents a new, regional-scale application of low-stress bicycle connectivity analysis. While prior network-based analyses have focused on the overall improvement in connectivity that could be achieved by implementing a package of projects from a comprehensive bike plan, the purpose of this project was to wholly evaluate potential improvements in connectivity through individual improvements at the street segment level. Using scripts and database tools, levels of traffic stress were assigned to the road network. Incorporating numerous computational optimization measures, shortest paths were calculated between millions of origin and destination pairs to identify the road segments that could most benefit low-stress connectivity. The resulting ranked list of links providing the greatest connectivity benefit allows planners to more efficiently prioritize locations for further investigation and analysis.

scholarly journals Continuous Anonymity with Users in the Same Direction in Road Networks

2018 ◽  
Vol 220 ◽  
pp. 10001
Author(s):  
Yu Lili ◽  
Zhang Lei ◽  
Su Xiaoguang ◽  
Li Jing ◽  
Zhang Xu ◽  
...  
Keyword(s):  
Euclidean Space ◽  
Privacy Protection ◽  
Road Network ◽  
Location Privacy ◽  
Road Networks ◽  
The Road ◽  
Shortest Distance ◽  
Location Privacy Protection ◽  
Road Segments

Compared with the Euclidean space, road network is restricted by its direction in traveling, velocity and some other attribute profiles. So the algorithms that designed for the Euclidean space are usually invalid and difficult to provide privacy protection services. In order to cope with this problem, we have proposed an algorithm to provide the service of collecting anonymous users that their directions in traveling similar with the initiator in the road networks. In this algorithm, the shortest distance between multiple road segments is calculated, and then utilizes the distance to select the user who has the same direction in traveling with the initiator. Consequently, the problem of the discrepancy of the anonymous users in the routing that invalidates the location privacy protection is solved. At last, we had compared this algorithm with other similar algorithms, and through the results of the comparison and the cause of this phenomenon, we have concluded that this algorithm is better not only in the level of privacy protection, but in the performance of execution efficiency.

scholarly journals AUTOMATIC DETECTION OF FOREST-ROAD DISTANCES TO IMPROVE CLEARING OPERATIONS IN ROAD MANAGEMENT

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1083-1088 ◽  
Author(s):  
A. Novo ◽  
H. González-Jorge ◽  
J. Martínez-Sánchez ◽  
L. M. González-de Santos ◽  
H. Lorenzo
Keyword(s):  
Forest Management ◽  
Forest Fires ◽  
Sustainable Forest Management ◽  
Lidar Data ◽  
Escape Route ◽  
Forest Road ◽  
The Road ◽  
Complex Relation ◽  
Road Management ◽  
Management Optimization

<p><strong>Abstract.</strong> There is a complex relation between roads and fires. Several major wildfires were ignited near to roads (Morrison 2007) and how they progressed is an important role to understand the importance to forest management in this environment. Nowadays, a sustainable forest management is necessary both for environment and politics. One of the reasons of road management is that these infrastructures provide an effective firewall in case of forest fires and an escape route for the population. Forest management optimization in road surroundings would improve wildfires prevention and mitigate their effects. One of the main indicators of road safety is the distance between road and vegetation.</p><p>The aim of this work is to develop a methodology to determine what areas do not obey current laws about safety distances between forest and roads. The acquisition of LiDAR data is done by Lynx Mobile Mapper System from University of Vigo. The methodology is automated using LiDAR data processing. The developed algorithms are based in height and length segmentation of the road. The objective is classifying vegetation groups by height and calculate the distance to the edges of road. The vegetation is divided in groups of height of 5, 10, 15 and 30&amp;thinsp;m. The minimum distance calculation is 2&amp;thinsp;m, for the vegetation of 5&amp;thinsp;m height and a maximum of 60&amp;thinsp;m for vegetation 30&amp;thinsp;m height. The height of vegetation has a directly relation with the distance separation with the road.</p>

scholarly journals Effect of the standard levels of forest road segments on soil loss

2021 ◽  
Vol 67 (No. 2) ◽  
pp. 80-86
Author(s):  
Ghaffar Yolmeh ◽  
Aidin Parsakhoo ◽  
Vahedberdi Sheikh ◽  
Jahangir Mohamadi
Keyword(s):  
Soil Loss ◽  
High Standard ◽  
Forest Road ◽  
The Road ◽  
Sediment Volume ◽  
Standard Level ◽  
Longitudinal Slope ◽  
High Level ◽  
Cut Slopes ◽  
Road Segments

Roads with the low standard level are often more susceptible to soil loss and production of sediment during rainfall events. The main aims of this research were to investigate the relationships between the standard level of the road and soil loss and determine the most effective road attributes in soil loss. Therefore, 30 road segments were selected in Bahramnia forest district, Golestan Province. These segments were classified into low standard, medium standard and high standard levels based on longitudinal slope, coverage on cut slopes, distance from runoff origin to culvert, traffic volume, and surfacing quality. A rubber bar was installed at the end of each segment to divert runoff into a sediment trap. In each trap, a series of wooden pins marked the locations for repeated elevation measurements of trapped sediment. Sediment volume was measured after each rainfall event. Results of the study showed that the most effective road attributes in soil loss were distance from runoff origin to trap and depth of ditch. Soil loss from road segments increased with the decreasing standard level of segments but this relationship was moderately strong (correlation coefficient: –0.45). An average amount of soil loss from low level standard road segments was 6.56 t·ha<sup>–1</sup>·year<sup>–1</sup> while an amount of soil loss for high level standard roads was 2.66 t·ha<sup>–1</sup>·year<sup>–1</sup>. Indeed, by improving the road attributes and standard level, less sediment is produced from road segments.

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