Cost Path Algorithm Research Articles

A Dempster–Shafer Enhanced Framework for Urban Road Planning Using a Model-Based Digital Twin and MCDM Techniques

Rapid urbanization in developing countries presents a critical challenge in the need for extensive and appropriate road expansion, which in turn contributes to traffic congestion and air pollution. Urban areas are economic engines, but their efficiency and livability rely on well-designed road networks. This study proposes a novel approach to urban road planning that leverages the power of several innovative techniques. The cornerstone of this approach is a digital twin model of the urban environment. This digital twin model facilitates the evaluation and comparison of road development proposals. To support informed decision-making, a multi-criteria decision-making (MCDM) framework is used, enabling planners to consider various factors such as traffic flow, environmental impact, and economic considerations. Spatial data and 3D visualizations are also provided to enrich the analysis. Finally, the Dempster–Shafer theory (DST) provides a robust mathematical framework to address uncertainties inherent in the weighting process. The proposed approach was applied to planning for both new road constructions and existing road expansions. By combining these elements, the model offers a sustainable and knowledge-based approach to optimize urban road planning. Results from integrating weights obtained through two weighting methods, the Analytic Hierarchy Process (AHP) and the Bayesian best–worst Method (B-BWM), showed a very high weight for the “worn-out urban texture” criterion and a meager weight for “noise pollution”. Finally, the cost path algorithm was used to evaluate the results from all three methods (AHP, B-BWM, and DST). The high degree of similarity in the results from these methods suggests a stable outcome for the proposed approach. Analysis of the study area revealed the following significant challenge for road planning: 35% of the area was deemed unsuitable, with only a tiny portion (4%) being suitable for road development based on the selected criteria. This highlights the need to explore alternative approaches or significantly adjust the current planning process.

An automated procedure to determine construction year of roads in forested landscapes using a least‐cost path and a Before‐After Control‐Impact approach

AbstractProximity to roads is one of the main determinants of deforestation in the Amazon basin. Determining the construction year of roads (CYR) is critical to improve the understanding of the drivers of road construction and to enable predictions of the expansion of the road network and its consequent impact on ecosystems. While recent artificial intelligence approaches have been successfully used for road extraction, they have typically relied on high spatial‐resolution imagery, precluding their adoption for the determination of CYR for older roads. In this article, we developed a new approach to automate the process of determining CYR that relies on the approximate position of the current road network and a time‐series of the proportion of exposed soil based on the multidecadal remote sensing imagery from the Landsat program. Starting with these inputs, our methodology relies on the Least Cost Path algorithm to co‐register the road network and on a Before‐After Control‐Impact design to circumvent the inherent image‐to‐image variability in the estimated amount of exposed soil. We demonstrate this approach for a 357 000 km2 area around the Transamazon highway (BR‐230) in the Brazilian Amazon, encompassing 36 240 road segments. The reliability of this approach is assessed by comparing the estimated CYR using our approach to the observed CYR based on a time‐series of Landsat images. This exercise reveals a close correspondence between the estimated and observed CYR (). Finally, we show how these data can be used to assess the effectiveness of protected areas (PAs) in reducing the yearly rate of road construction and thus their vulnerability to future degradation. In particular, we find that integral protection PAs in this region were generally more effective in reducing the expansion of the road network when compared to sustainable use PAs.

Identification of historical trackways in forests using contextual geospatial analyses

AbstractThis article demonstrates the application of the methods unravelling microtopographic features, specifically, sunken linear landforms indicating remains of historical trackways in forests. These are related to the ‘Magna Via’ route in the vicinity of the Deserted Castle and the Peťuša Castle in Central Slovakia. The microtopography validation dataset indicating sunken linear landforms was used to evaluate the data overlap of tracks identified by the global positioning and navigation system (GNSS) and a model of tracks created with the least cost path (LCP) algorithm. Microtopographic features derived from a digital relief model generated by high‐resolution Light Detection and Ranging (LiDAR) scans (density of 5 points/pixel) allowed us to determine the exact position (submeter total vertical and horizontal accuracy) of certain segments of the GNSS tracks and LCP overlapping the sunken linear landforms. Moreover, the LCP model shows the most efficient trackways considering the travel costs depending on the slope parameter.

Highway Route Planning via Least Cost Path Algorithm and Multi Criteria Decision Analysis Integration, a Comparison of AHP, TOPSIS and VIKOR

Highways are one of the main structures of cities in the field of economic, social, and environmental facilities that connect cities, regions, and people each other. Determining the suitable highway routes includes difficult and complex processes due to the construction costs. Additionally, priorities, expectations, and constraints for economic, social, and environmental parameters must be considered together to provide efficient solutions to requirements. Multi Criteria Decision Analysis (MCDA) techniques such as Analytical Hierarchy Process (AHP), Ideal Solution Similarity Selection Ranking Technique (TOPSIS), and Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Least Cost Path Algorithm (LCPA) with Geographical Information Systems (GIS) combination are the most suitable way to overcome these complexities. In this study, slope, aspect, geology, elevation, distances to roads, settlements, water bodies, fault lines, buildings, natural disasters, protected sites, population, and land use were selected to determine most suitable highway construction areas and route. The AHP, TOPSIS, and VIKOR methods were applied to calculate cost surfaces for least cost paths generation with LCPA, and the generated three routes were compared. As a result of the comparisons VIKOR route was the most suitable route considering the topographical statistics and all the three methods consistent with each other and current road.

An improved minimal path selection approach with new strategies for pavement crack segmentation

Intelligent pavement detection technology provides a new research idea for identifying pavement cracks. To solve the problem that traditional minimal cost path selection (MPS) is computationally intensive and inefficient in crack segmentation, this study proposes an improved minimal cost path algorithm (IMPS). The contribution of IMPS is reflected in its more efficient path planning than MPS and better choice of source and destination of each path by using new strategies. First, a grayscale pavement image is divided into nonoverlapping cells with a certain size. Next, the darkest points in each cell are selected as candidate points and adjacent candidate points are connected based on IMPS. Then pseudocracks are removed based on postprocessing steps before cracks are well segmented. IMPS is compared with other crack segmentation algorithms to prove its reliability. The efficiency of IMPS is increased by approximately 56% than MPS. The accuracy of IMPS is higher than that of MPS and other methods, with Mean Intersection over Union reaching 73.99%.

An integrated micro-macro approach for high-speed railway energy-efficient timetabling problem

Energy efficiency of train operations is influenced largely by the speed control and the scheduled running time in the train timetable. In practice, the running time of a train is often determined in the train timetabling process at the macroscopic level while the energy-efficient speed control of a train on a segment is often determined at the microscopic level with the given timetable. They are usually optimized separately due to limited computational resources, which however may result in sub-optimal solutions. To address this issue, this paper proposes a novel integrated micro-macro approach for better incorporating train energy-efficient speed control into the railway timetabling process. Firstly, we formulated the integrated train timetabling and speed control optimization problem as a nonlinear mixed-integer programming model. Due to its complexity, we reformulate it on the basis of flow conservation theory in a space–time-speed (STS) network and solve the problem in two steps. In the first step, a set of pre-solved energy-efficient train trajectory templates is generated by a segment-level optimization approach with consideration of train travel time, entry speed and exit speed to save computation time. In the second step, a near-optimum train energy-efficient timetable solution is found by a fast algorithm, which consists of the shortest generalized cost path algorithm, conflict detection and resolution algorithm, and calculation of dynamic headways between two successive trains. The numerical experiments demonstrate that the developed approach provides better outcomes than the benchmark case in terms of both train journey time and energy consumption.

Planning conservation corridors in mountain areas based on integrated conservation planning models: A case study for a giant panda in the Qionglai Mountains

With the accelerated urbanization, human activities pose serious threats to species because of fragmentation. Planning conservation corridors between habitats could improve species mobility in order to address the human disturbance. However, there are a limited number of studies that focus on assessing the effect of human activities on species movement in mountain areas as well as how to integrate different conservation models relating to conservation corridors identification. In our study, we modified the resistance model and took land use data as input parameters to quantify the impacts of human activities in mountain areas. Meanwhile, different conservation planning models, including Circuit model and Least Cost Path (LCP) algorithm, were integrated. Moreover, our approach was applied to identify giant panda corridors in Miarro nature reserve, Caopo nature reserve, and Wolong nature reserve. The results suggested that the impacts of human activities were limited in valley regions due to topography by resistance model. Secondly, Circuit model demonstrated that the conservation corridors for giant panda could not be identified between the Miarro and the Caopo nature reserves. Additionally, more detailed corridors between habitats were planned by the LCP algorithm. Furthermore, we also identified bottlenecks for migration in each corridor, indicating that human activities’ interference was the primary cause. Our approach not only could connect habitats for conservation in mountain areas but also found out that the corridor could not be identified between habitats.

Automatic Pipeline Route Design with Multi-Criteria Evaluation Based on Least-Cost Path Analysis and Line-Based Cartographic Simplification: A Case Study of the Mus Project in Turkey

The design of a natural gas pipeline route is a very important stage in Natural Gas Transmission Pipeline projects. It is a very complicated process requiring many different criteria for various areas to be evaluated simultaneously. These criteria include geographical, social, economic, and environmental aspects with their obstacles. In the classical approach, the optimum route design is usually determined manually with gathering the spatial references for suitable places and obstructions from the ground. This traditional method is not effective because it does not consider all the factors that affect the route of the pipeline. Today, the powerful tools incorporated in Geographical Information Systems (GIS) can be used to automatically determine the optimum route. An automatic pipeline route finder algorithm can calculate the best convenient route avoiding geographic and topological obstructs and selecting suitable places depending on their weights. In this study, an automatic natural gas pipeline design study was carried out in the east western region of Turkey. At the end of the study, an automatic natural gas pipeline route was determined using GIS and a least cost path algorithm, and an alternative study was conducted using a traditional method. In addition, a cartographic line simplification process with a point removal algorithm was used to eliminate the high vertex points and a simplified route was determined. The results were compared with the results of a finished Muş natural gas project constructed by The Turkish Petroleum Pipeline Corporation (BOTAŞ) and the negative and positive effects were evaluated. It was concluded that the use of GIS capabilities and the lowest cost path distance algorithm resulted in a 20% reduction of the cost through the simplification.

Raster Least Cost Approach for Automated Corridor Alignment in Undulated Terrain

A raster based route alignment using multi criteria factors created as raster layers is useful for evolving total cost raster layer utilized at different stages for multi-criteria decision analysis (MCDA). The integration of least cost path algorithm into the 3-D view of the terrain or false color composite Remote sensing data can give value addition in planning process and formulation of action plans. The designing of optimum route alignment depends upon the number of factor considered in the process of corridor analysis model for finding the optimum route for alignment to ensure designing of the road from source to a destination within two specified end point locations. The raster data layer on land use and land cover type can be prepared for generating relative cost layer using the image classification algorithms and the slope raster layer can be obtained from the digital Elevation Model. The optimum route has the least cost and it can incorporate parameters on environmental, technical, social, and economic issues. The raster corridor analysis has been implemented to design optimum route alignment between two locations in the Himalayan region of India to consider the suitability of the technique for hill road construction. The details of the same are given in the paper.

The Use of Travel Time to Measure Geographic Accessibility to Breast Screening Services in New South Wales, Australia Short Paper

In 2018, the World Health Organization set a goal to increase the proportion of breast cancers identified at an early stage. Early detection allows for more effective treatment and a reduction in the risk of death from breast cancer. Poor access may restrict participation in screening, diagnostic and treatment services, with flow-on effects on stage at diagnosis and survival. This paper presents spatial analysis of travel time to breast screening services in New South Wales, Australia to measure the geographic accessibility of services to the population they serve. The travel time surface was created using a friction surface that estimates the time required to traverse each pixel within a global grid, and a least cost path algorithm to find the optimised route from each output pixel to the breast screen services. The friction surface was derived using a set of input layers, with the roads layer being the most critical for defining travel times. The generated surface of travel time to breast screen services in New South Wales has shown that over 90% of the population are within 20 min' drive time of either a fixed or mobile breast screen service and that 100% of the population are within 100 min' drive time of a breast screen service. The ability to identify and measure spatial variations in geographic accessibility via travel time is vital to plan breast screening services and reduce inequalities in health outcomes.

A combined algorithm for automated drainage network extraction from digital elevation models

AbstractDrainage networks are the basis for segmentation of watersheds, an essential component in hydrological modelling, biogeochemical applications, and resource management plans. With the rapidly increasing availability of topographic information as digital elevation models (DEMs), there have been many studies on DEM‐based drainage network extraction algorithms. Most of traditional drainage network extraction methods require preprocessing of the DEM in order to remove “spurious” sink, which can cause unrealistic results due to removal of real sinks as well. The least cost path (LCP) algorithm can deal with flow routing over sinks without altering data. However, the existing LCP implementations can only simulate either single flow direction or multiple flow direction over terrain surfaces. Nevertheless, terrain surfaces in the real world are usually very complicated including both convergent and divergent flow patterns. The triangular form‐based multiple flow (TFM) algorithm, one of the traditional drainage network extraction methods, can estimate both single flow and multiple flow patterns. Thus, in this paper, it is proposed to combine the advantages of the LCP algorithm and the TFM algorithm in order to improve the accuracy of drainage network extraction from the DEM. The proposed algorithm is evaluated by implementing a data‐independent assessment method based on four mathematical surfaces and validated against “true” stream networks from aerial photograph, respectively. The results show that when compared with other commonly used algorithms, the new algorithm provides better flow estimation and is able to estimate both convergent and divergent flow patterns well regarding the mathematical surfaces and the real‐world DEM.

Assessing transhumance corridors on high mountain environments by least cost path analysis: the case of yak herds in Gilgit-Baltistan, Pakistan.

Mountain environments in the world host highly specialized flora and fauna which are vulnerable because of land use and climate change. Transhumance and other land use traditional practices are present in most of the mountains of the world, and management tools able to cope with new socioeconomic settings and environmental changes are urgently needed. During past centuries, yak (Bos grunniens) herding in Northern Pakistan involved the migration of herds to high mountain international rangelands, but the recent establishment of international borders breaks the traditional transhumance paths, promoting several ecological problems. In this paper, we propose the use of least cost path (LCP) algorithm to identify the most efficient corridors of transhumance for yak herds on northern high altitudes of Pakistan. Specifically, LCP was implemented to identify the critical grazing areas and the connecting zones to be accounted in a new management plan for the yaks in the region. The LCP analysis showed that some grazing areas are connected with several paths, whereas other areas are connected to a lesser extent. The analyses identified a set of best minimum cost paths able to guarantee local connectivity. We also delineated several medium and low efficient paths that could play a crucial role for maintaining regional connectivity which is essential for reducing the isolation of herds and the consequent inbreeding problems. The analytical framework implemented in this study allowed to (1) provide valuable information concerning the movement of yak herds in Gilgit-Baltistan, (2) identify potential corridors that are able to promote herd movement between villages and high mountain rangelands, and (3) identify critical areas for the connectivity of yaks by ranking of the potential corridors according to their length and permeability. The analysis would be extended to other transhumant herds and high mountain areas that are facing sociopolitical transformations and environmental changes.

Dispersal corridors for plant species in the Poyang Lake Basin of southeast China identified by integration of phylogeographic and geospatial data.

Measuring the dispersal of wildlife through landscapes is notoriously difficult. Recently, the categorical least cost path algorithm that integrates population genetic data with species distribution models has been applied to reveal population connectivity. In this study, we use this method to identify the possible dispersal corridors of five plant species (Castanopsis tibetana, Schima superba, Cyclocarya paliurus, Sargentodoxa cuneata, Eomecon chionantha) in the Poyang Lake Basin (PLB, largely coinciding with Jiangxi Province), China, in the late Quaternary. The results showed that the strongest population connectivity for the five species occurred in the Wuyi Mountains and the Yu Mountains of the eastern PLB (East Corridor) during the late Quaternary. In the western PLB, populations of the five species were connected by the Luoxiao Mountains and the Jiuling Mountains (West Corridor) but with a lower degree of connectivity. There were some minor connections between the eastern and the western populations across the Gannan Hills. When the corridors of five species were overlaid, the East Corridor and the West Corridor were mostly shared by multiple species. These results indicate that plant species in the PLB could have responded to the Quaternary climate changes by moving along the East Corridor and the West Corridor. Given that dispersal corridors have seldom been considered in the governmental strategies of biodiversity conservation in the PLB, preserving and restoring natural vegetation along these corridors should be prioritized to mitigate the effects of anthropogenic climate change by facilitating migration of plant species and other biota.

LandScape Corridors (lscorridors): a new software package for modelling ecological corridors based on landscape patterns and species requirements

Summary Maintaining connectivity is one of the main challenges for biodiversity conservation world‐wide. Ecological corridors are important to maintain landscape connectivity, but their efficiency depends on landscape patterns and species responses at different spatial extents and landscape contexts. We developed a new ecologically oriented free software package, LandScape Corridors (lscorridors), to improve ecological corridor design by considering biodiversity responses to landscape attributes at a variety of spatial extents. LandScape Corridors considers stochastic variation, species perception and landscape influence on organisms in the design of ecological corridors. In addition to the least cost path algorithm, we propose four different methods for the simulation of multiple‐path functional ecological corridors. One method uses the information for each pixel separately, whereas the three other methods permit corridor simulation considering the landscape context at different spatial extents. LandScape Corridors permits to simulate corridors for species with different requirements and considers that different species perceive and respond to the surrounding landscape in different ways, as many species may choose to move through areas that may not be the most permeable ones in the landscape. Two parameters in lscorridors modulate the stochasticity in corridors simulations. The first parameter is the level of variability added to the input resistance map in each simulation, resulting in more variable and spatially spread‐out corridors. The other parameter is the spatial extent that may influence each pixel; larger extents result in larger spatial zones affecting each pixel during corridors simulations. In addition, when considering spatial influence, the simulations may be performed for species highly, medially or less sensitive to habitat quality. Some currently available software are not free or depend on a paid GIS software to work. In addition, some software do not support large matrices in their simulations, limiting their use. LandScape Corridors is designed to deal with large rasters, is based on strictly freeware software, and is freely available online. This allows the users to implement new methods for modelling multi‐scale and ecologically based corridors. LandScape Corridors is a potential tool for the identification of protected areas, as corridor simulation considers species movement and landscape connectivity, essential characteristics to aid in large‐scale biodiversity conservation, especially in anthropogenic landscapes. LandScape Corridors provides what we may call a zone for conservation, showing a set of connected areas in the landscape which may be ordered according to their potential for ecological corridors or which may be used as an aid for conservation strategies or ecological restoration projects.

Road Network Planning for Sustainable Urban Development in Kirtipur Municipality, Nepal

Road network deals with the development of a comprehensive plan for construction and operation of transportation facilities. In order to develop efficient and better transport facility, it is necessary to have a proper road network. In sustainable road network planning, planners put into consideration factors like gradients or slope, land-use and geology with community and governmental interest. These different considerations make the planning process complex and generate confusion in the decision making process. The use of geographic information system (GIS) and multi-criteria analysis (MCA) has helped planners to reduce complexity and to achieve desired and more accurate results. MCA prevents the imposition of criteria limit and gives opportunity to decision makers to enter their own judgments. This provides a better communication among the community for creating a more open choice for analysis and possible changes if necessary. In this study, road network has been analyzed with optimal least cost path algorithm of spatial analysis in GIS using different ancillary data layers and each layer weight-scoring has been computed with MCA in spatial decision support system (SDSS). The optimal least cost path would provide the best option with certainty and considers a gradient, connected neighbors, thematic cost and surface distance in three dimensional spaces. The path gradient can be adjusted as per the requirements, depending upon the terrain conditions and possible to design a more realistic route automatically with appropriate parameters.Nepalese Journal on Geoinformatics -13, 2014, Page: 34-40

Optimisation of pipeline route in the presence of obstacles based on a least cost path algorithm and laplacian smoothing

Subsea pipeline route design is a crucial task for the offshore oil and gas industry, and the route selected can significantly affect the success or failure of an offshore project. Thus, it is essential to design pipeline routes to be eco-friendly, economical and safe. Obstacle avoidance is one of the main problems that affect pipeline route selection. In this study, we propose a technique for designing an automatic obstacle avoidance. The Laplacian smoothing algorithm was used to make automatically generated pipeline routes fairer. The algorithms were fast and the method was shown to be effective and easy to use in a simple set of case studies.

Modeling and optimizing transmission lines with GIS and Multi-Criteria Decision Analysis

Abstract In planning transmission lines with the use of Geographic Information Systems, the use of the Least Cost Path (LCP) algorithm has been established while relevant criteria are modeled using Multi-Criteria Decision Analysis (MCDA). Despite their established use, this combination (MCDA/LCP) often leads to results that do not correspond to realistic conditions. Therefore, the MCDA/LCP computation must usually be optimized on an algorithmic level as well as on the decision model and the underlying data relevant for the MCDA. The current paper presents the state-of-the-art of an ongoing research project that aims to solve these issues. First results are promising since a stable algorithm has been developed that computes a cost surface, a Least Cost Corridor (LCC), a LCP, and the transmission towers' positions by simple additive weighting based on user's weights. Optimizations on the MCDA models have already been implemented and tested. The findings are integrated into a 3D Decision Support System which aims at facilitating the work of TL planners by realistic modeling and by reducing the approval process for new TL.

LEAST COST PATH ALGORITHM DESIGN FOR HIGHWAY ROUTE SELECTION

Highway route design is a difficult process due to the complex structure of the environment. The topography and the natural geographical objects constitute an obstacle for highway constructions. On the other hand, the cost parameter and protecting the environment are main two issues which planners have to consider. Thus, the priorities of the highway routes should be decided according to the requirements and expectations. At this point, Least Cost Path Algorithm (LCPA) makes it possible to investigate least cost path for highway routes. This cost can be assigned as the cost of the constructions such as avoiding slope and swampy areas or an environmental object such as keeping the forests and not damaging to agricultural lands. When the cost parameter is decided, then LCPA can calculate the least cost path from origin point to destination. In this study, new highway routes are investigated for Konya city with economic, environmentally and hybrid approaches. The cost parameter and related surfaces are generated according to the highway construction requirements and then with LCPA, three different routes are calculated. The result maps are generated and the three approaches are compared for environmental and cost parameters.

Identification of Optimum Route Alignment in Landslide Areas: A Case Study from Sri Lanka

In Sri Lanka road network, especially in hilly terrain is affected by landslide in every rainy season. Therefore, the maintenance cost of the Road Development Authority is increasing and roads have to be closed for traffic due to landslides. Hence developing a methodology to identify an optimum route alignment in landslide areas is essential in the planning of roads. To identify the optimum route alignment for Beragala-Koslanda landslide area, geo-informatics approach was used considering engineering factors simultaneously in the present study. 1:10,000 scale topographic map, 30 m resolution downloaded USGS DEM, 1: 100,000 geology map and 1: 50,000 landslide hazard zone map were used as basic input data for the analysis. Using the basic input data, seven layers (Landslide hazard zone, Land use and management, Slope, Drainage density, Populated area, Sensitivity area and Lithology) were extracted and further they were weighted and ranked using Spatial Multi Criteria Analysis (SMCA) according to the values given by experts in the field of geology and highway engineering. The least cost path for the area was identified by using the least cost path algorithm in Arc GIS 10.2. Field verification was conducted with the participation of civil engineers and GPS (Global Positioning System) were used to go through the identified path. Finally, 15.414 km length alternative route was identified from Beragala to Koslanda landslide area. The final result obtained in this study supports other researches in the application of GIS and SMCA in complex planning. Possibilities of applying GIS and SMCA in identifying the route alignment avoiding landslide risk areas, was proved in this study.

The influence of declining sea ice on shipping activity in the Canadian Arctic

AbstractSignificant attention has focused on the potential for increased shipping activity driven by recently observed declines in Arctic sea ice cover. In this study, we describe the first coupled spatial analysis between shipping activity and sea ice using observations in the Canadian Arctic over the 1990–2015 period. Shipping activity is measured by using known ship locations enhanced with a least cost path algorithm to generate ship tracks and quantified by computing total distance traveled in kilometers. Statistically significant increases in shipping activity are observed in the Hudson Strait (150–500 km traveled yr−1), the Beaufort Sea (40–450 km traveled yr−1), Baffin Bay (50–350 km traveled yr−1), and regions in the southern route of the Northwest Passage (50–250 km traveled yr−1). Increases in shipping activity are significantly correlated with reductions in sea ice concentration (Kendall's tau up to −0.6) in regions of the Beaufort Sea, Western Parry Channel, Western Baffin Bay, and Foxe Basin. Changes in multiyear ice‐dominant regions in the Canadian Arctic were found to be more influential on changes to shipping activity compared to seasonal sea ice regions.