Search Results (38)

The use of unmanned aerial vehicles (UAVs) is increasing in transportation applications due to their high versatility and maneuverability in complex environments. Search and rescue is one of the most challenging applications of UAVs due to the non-homogeneous nature of the environmental and communication landscapes. In particular, mountainous areas pose difficulties due to the loss of connectivity caused by large valleys and the volumes of hazardous weather. In this paper, the connectivity issue in mountainous areas is addressed using a path planning algorithm for UAV relay. The approach is based on two main phases: (1) the detection of areas of interest where the connectivity signal is poor, and (2) an energy-aware and resilient path planning algorithm that maximizes the coverage links. The approach uses a viewshed analysis to identify areas of visibility between the areas of interest and the cell-towers. This allows the construction of a blockage map that prevents the UAV from passing through areas with no coverage, whilst maximizing the coverage area under energy constraints and hazardous weather. The proposed approach is validated under open-access datasets of mountainous zones, and the obtained results confirm the benefits of the proposed approach for communication networks in remote and challenging environments. Full article

The effectiveness of fire towers in combating forest fires relies on their appropriate observation angles, enabling a swift and efficient response to fire incidents. The purpose of this study is to examine the effectiveness of 49 fire towers located within the Antalya Forestry Regional Directorate, situated in the Mediterranean basin—a region prone to frequent forest fires. The assessment encompasses the visibility of the entire study area, including forested regions, as well as the visibility of 2504 forest fires recorded by the towers between 2008 and 2021. Furthermore, the evaluation considers the objectives based on Forest Management Directorates and conducts a location suitability analysis for the six towers with the lowest visibility. We utilized the Viewshed Tool in the ArcGIS application and employed the Best–Worst approach. Two scenarios were devised, considering smoke height at 0 m or 100 m, to determine the visibility of fire lookout towers. In Scenario I, assuming a smoke height of 100 m, only three towers exhibited visibility above 70%. However, in Scenario II, assuming a smoke height of 0 m, no towers achieved visibility above 70%. Scenario I indicated that only two towers possessed a view of more than 70% of the forested region, while Scenario II suggested that no towers met this criterion. For the visibility of forest fires, Scenario I identified seven towers capable of observing more than 70%, whereas Scenario II indicated that no towers possessed such capability. In the tower suitability analysis, the visibility rates varied from 41.18% to 1016.67%. Based on the evaluation results, the current visibility capacities of the 49 fire towers proved insufficient for effective preventive measures. Full article

In this study, we developed a 3D-model-based technology that can evaluate solar access by analyzing solar radiation and shade to find the optimal location for a solar system. We developed an algorithm that can quickly calculate viewshed by applying ray-casting technology, which is useful in the field of computer graphics. To apply the developed technology, an unmanned aerial vehicle (DJI MAVIC 3) was used to create a 3D model by taking 320 photos of the Kangwon National University Samcheok campus. To verify the developed technology, a comparison with image-based analysis using a 360-degree camera was performed for 30 points. As a result of applying the developed technology to the study area, it was possible to calculate the solar access for each point. In general, image-based analysis exaggerates the effects of objects such as trees, whereas the developed technique can produce realistic results if the 3D objects were well built. If the technology is further developed in the future, it can be used to increase the efficiency of solar power generation. Full article

This study evaluated the positioning accuracy of moving forest harvesters using global navigation satellite system (GNSS) signals under a forest canopy, and developed approaches for forecasting accuracy under a mature spruce canopy cover. Real-time kinematic positioning with a Trimble R12 receiver on top of a harvester achieved high positioning accuracy, with 86% of observations meeting a maximum precision of 8 mm. However, the presence of a canopy cover hampered the GNSS’s performance as there were fewer satellites available, leading to an increased number of inaccurate positions and larger values of the dilution of precision in geometry (GDOP), position (PDOP), vertical (VDOP) and horizontal directions (HDOP). The canopy cover estimated from the viewshed analysis of the digital surface model (DSM) was found to be a significant predictor of the dilution of precision and maximum deviation from the true position. These findings suggest that viewshed analysis provides more precise results than a mere canopy cover percentage for evaluating the impact of canopy cover on the GNSS’s positioning of a harvester, despite its computational demands. Developing intelligent algorithms for precise positioning under the canopy can facilitate autonomous harvesting and forwarding, allowing for the implementation of digitalization in forest operations. Full article

Visibility analyses in geographical information systems (GIS) are used to quantify the visible and non-visible parts of the landscape. This study aims to evaluate the changes in viewshed outputs after the unmanned aerial vehicle (UAV) data refinement for the near surroundings of the observer. This research accounts for the influence of data age, mainly due to vegetation growth, and the impact of the input data quality on the final study output. The raw data that were used for UAV refinement were publicly available data (one dataset at the global level, two datasets at the national level of the Czech Republic) and airborne laser scanning (ALS) data. Three localities were selected in order to compare the viewshed evaluation that was processed over ten raster elevation models. The comparison was performed using the kappa coefficient, which considers not only the matching visible pixels, but also false visibility and invisibility. Over the span of five years (2013–2018), the visible area at two sites has decreased by more than 7%. Although with some variations (kappa coefficient varied from 0.02 to 0.92), all the study sites showed a decreasing trend of the visible area with the data aging, which was caused by the vegetation growth or landscape changes. The results showed the effect of data aging in forested areas on the resulting visibility within a couple of years. At all the sites, major changes in visibility were observed after three years (2021 vs. 2018) due to vegetation growth, forest management, and natural phenomena, such as windfalls. This study concludes that UAV data will increase the accuracy of visibility analysis, even when using freely available low-resolution data, and may also help us to update obsolete input data. The results of this research can be used to refine visibility analysis when current digital surface model (DSM) data is not available. Full article

Viewshed analysis is a terrain visibility computation method based on the digital elevation model (DEM). With the rapid growth of remote sensing and data collection technologies, the volume of large-scale raster DEM data has reached a great size (ZB). However, the data storage and GIS analysis based on such large-scale digital data volume become extra difficult. The usually distributed approaches based on Apache Hadoop and Spark can efficiently handle the viewshed analysis computation of large-scale DEM data, but there are still bottleneck and precision problems. In this article, we present a multi-level distributed XDraw (ML-XDraw) algorithm with Apache Spark to handle the viewshed analysis of large DEM data. The ML-XDraw algorithm mainly consists of 3 parts: (1) designing the XDraw algorithm into a multi-level distributed computing process, (2) introducing a multi-level data decomposition strategy to solve the calculating bottleneck problem of the cluster’s executor, and (3) proposing a boundary approximate calculation strategy to solve the precision loss problem in calculation near the boundary. Experiments show that the ML-XDraw algorithm adequately addresses the above problems and achieves better speed-up and accuracy as the volume of raster DEM data increases drastically. Full article

The visual impact of crop shelters in the rural landscape is of paramount importance for the sustainability of landscape planning. It is of utmost importance to protect a beautiful landscape characterized by archaeological sites and natural ecosystems but it is also fundamental to preserve a key economy based on agriculture. To preserve the landscape there is the need to understand its landscape units and to assess the feasibility of the application of landscape character assessment (LCA) at a local scale and adaptation to higher scales in the land-use planning process. In this study, a methodology based on viewshed analysis was integrated into LCA in order to define landscape character areas and types. An application of the method was done on greenhouse systems. Landscape evaluation was carried out by using both ECOVAST guidelines for landscape identification and indicators, which were defined and computed in order to describe the visual impact of greenhouses. The method was applied to a study area located in South Italy, in the Province of Ragusa, in the eastern part of Sicily, where the greenhouse system highly characterizes agricultural activities and made it possible to define landscape guidelines. Finally, a visibility map was drawn up to highlight the areas subject to the greatest visibility. In addition to objectifying the visual impact of greenhouses, the research verified that the proposed LCA-based methodology combined with viewshed analysis can be feasible for supporting the analysis phases of landscape and urban planning under the new territorial governance laws issued for the Region of Sicily in recent years. These analyses were useful to provide information that objectively takes into account the importance of the visual component in the context of landscape planning. Due to the limited surface of the sample area considered in this study, this research work should be considered a pilot or preliminary study. The extension of this methodology to the adjacent municipalities could represent the practical application performed by local authorities to define common regulations suitable to preserve landscape components. Full article

In this paper, an integrated methodology is developed to determine optimum areas for Photovoltaic (PV) installations that minimize the relevant visual disturbance and satisfy spatial constraints associated with land use, as well as environmental and techno-economic siting factors. The visual disturbance due to PV installations is quantified by introducing and calculating the “Social Disturbance” (SDIS) indicator, whereas optimum locations are determined for predefined values of two siting preferences (maximum allowable PV locations—grid station distance and minimum allowable total coverage area of PV installations). Thematic maps of appropriate selected exclusion criteria are produced, followed by a cumulative weighted viewshed analysis, where the SDIS indicator is calculated. Optimum solutions are then determined by developing and employing a Genetic Algorithms (GAs) optimization process. The methodology is applied for the municipality of La Palma Del Condado in Spain for 100 different combinations of the two siting preferences. The optimization results are also employed to create a flexible and easy-to-use web-GIS application, facilitating policy-makers to choose the set of solutions that better fulfils their preferences. The GAs algorithm offers the ability to determine distinguishable, but compact, regions of optimum locations in the region, whereas the results indicate the strong dependence of the optimum areas upon the two siting preferences. Full article

Wildland firefighters must be able to maintain situational awareness to ensure their safety. Crew members, including lookouts and crew building handlines, rely on visibility to assess risk and communicate changing conditions. Geographic information systems and remote sensing offer potential solutions for characterizing visibility using models incorporating terrain and vegetation height. Visibility can be assessed using viewshed algorithms, and while previous research has demonstrated the utility of these algorithms across multiple fields, their use in wildland firefighter safety has yet to be explored. The goals of this study were to develop an approach for assessing visibility at the handline level, quantify the effects of spatial resolution on a lidar-driven visibility analysis, and demonstrate a set of spatial metrics that can be used to inform handline safety. Comparisons were made between elevation models derived from airborne lidar at varying spatial resolutions and those derived from LANDFIRE, a US-wide 30 m product. Coarser resolution inputs overestimated visibility by as much as 223%, while the finest-scale resolution input was not practical due to extreme processing times. Canopy cover and slope had strong linear relationships with visibility, with R² values of 0.806 and 0.718, respectively. Visibility analyses, when conducted at an appropriate spatial resolution, can provide useful information to inform situational awareness in a wildland fire context. Evaluating situational awareness at the handline level prior to engaging a fire may help firefighters evaluate potential safety risks and more effectively plan handlines. Full article

Terrain viewshed analysis based on the digital elevation model (DEM) is of significant application value. A lot of viewshed analysis algorithms have been proposed, including R3 as the accurate one and others as efficient ones. The R3 algorithm is accurate because of its comprehensive but time-consuming computation, while the others are efficient due to proper approximation. However, no algorithm is capable of taking advantage of both until one algorithm is proposed, which is based on a ‘proximity-direction-elevation’ (PDE) coordinate system and named the PDE spatial reference line (PDERL) algorithm. The original research proves the PDERL algorithm is perfectly accurate by theory and experimental results, in comparison with R3 as standard, and even more efficient than R3. However, the original research does not mention the cases where the observer is placed on grid points, and the original implementation does not produce very accurate results in practice. It is important to find out and correct the errors. In this paper, a checking algorithm for PDERL is proposed to allow further investigation of errors. With the fundamental ideas of PDERL unchallenged, an improved implementation of the PDERL algorithm is proposed, named HiPDERL. By experimental results, this paper proves HiPDERL utilizes the potential of PDERL on accuracy at the cost of a little efficiency when the observer is placed on grid points. Full article

The landscape visual aesthetic quality (LVAQ) of urban residential districts is an important index for measuring urban livability and is a tripartite concern among urban managers, real estate developers and residents. The LVAQ of residential districts is determined by their visual openness and the aesthetic degree of the surrounding landscape, a value combining subjective evaluation and objective analysis. Although existing studies have carried out empirical analyses on the LVAQ of residential districts and have summarized some influencing factors, they have largely overlooked the specific impact and interactions of various factors, failing to establish 3D city models meeting LVAQ analysis requirements and falling short in developing appropriate evaluation approaches suitable for whole city scale. In this study, we propose a spatial simulation analysis for the LVAQ of residential districts based on 3D city modeling, aesthetic evaluation and viewshed analysis. In order to improve the accuracy of the study, we collected massive RS data and established a 3D city model covering a large amount of architecture and landscape information. We analyzed three representative cases and calculated the LVAQ of 1258 residential districts in Changsha City, Hunan, China, evaluating the results with various construction and planning indicators. Our results show that the LVAQ of residential districts is affected by their own construction conditions and the surrounding districts and landscape areas. Various architectural and planning indicators have restrictive and direct effects on LVAQ. Optimizing the layout of landscape areas and the construction mode of residential districts through urban planning and urban renewal may help improve their LVAQ. This study helps better understand the general principles that affect the LVAQ of residential districts and supports the development of urban scale LVAQ analysis methods for residential districts. The findings are expected to provide methodological support for the landscape analysis and evaluation of urban residential districts in China and other developing countries and provide optimization ideas for urban human settlement environment sustainability. Full article

A visual analysis is useful to assess potential impacts to our surroundings. There has been tremendous progress toward the optimization, accuracy, and techniques of these analyses. Viewshed analyses are a common type of visual analysis. The purpose of this study was to identify the optimal trade-off between the number of viewpoints needed to generate an accurate viewshed for a given route. In this study, we focused on identifying how a viewshed differs based on the sampling distance (interval) of viewpoints, topography, and distance of analysis. We employed the Geospatial Route Analysis and Visual Impact Assessment (GRAVIA) tool, a type of advanced viewshed that uses visual-magnitude measures. GRAVIA was applied across three different topographical environments (flat, hilly, and mountainous). We generated a one-mile-long segment for each environment and systematically discretized the route by varying the sampling-distance intervals from 1 m to 100 m. We also compared how the calculated results differed by distance from the route. The results showed a linear decrease in the correlation, though this was sensitive to the distance. When all distances were combined, a 30 m and 50 m sampling distance correlated to 0.9 and 0.7, respectively. However, when the results compared calculations beyond 300 m away from the route, the correlation values exceeded 97% for all the viewpoint-sampling distances. This suggests that for route-based analyses using visual magnitude, reducing the sampling rate can produce equivalent results with far less processing time while maintaining model precision. Full article

The visibility of a landscape is an important aspect of landscape protection planning because different rules or norms can be defined to regulate land-use and human activities depending on the degree of landscape visibility. Viewshed analyses are common GIS-based approaches to evaluate which parts of the landscape can be seen from certain points or by people located or moving in the landscape. In this work, the visibility of the entire landscape of the Slovak Republic is assessed from the network of major national roads. The results of the landscape visibility analysis are then used to propose appropriate planning norms and regulations to protect the identified visibility values and avoid potential visual obstructions from new buildings or infrastructure development. Particularly, the proposed norms indicate allowable changes to the landscape and the maximum height of new or existing buildings and other urban infrastructure. Maps of the spatial distribution of the proposed norms identify possible situations of consistency or conflict with potential urban development trends, to support landscape protection planning processes at the national level. On average, the most visible land-use/land-cover categories are glacial mountains relief, plane depressions, and wide alluvial plains, while the planning indications/prescriptions to protect landscape visibility have been proposed for irrigated land and forests. Thanks to the limited use of geographic datasets, the method ensures high transferability to other different geographic contexts, and allows to derive planning indications for large national contexts. Full article

Urban planning, noise propagation modelling, viewshed analysis, etc., require determination of routes or supply lines for propagation. A point-to-point routing algorithm is required to determine the best routes for the propagation of noise levels from source to destination. Various optimization algorithms are present in the literature to determine the shortest route, e.g., Dijkstra, Ant-Colony algorithms, etc. However, these algorithms primarily work over 2D maps and multiple routes. The shortest route determination in 3D from unlabeled data (e.g., precise LiDAR terrain point cloud) is very challenging. The prediction of noise data for a place necessitates extraction of all possible principal routes between every source of noise and its destination, e.g., direct route, the route over the top of the building (or obstruction), routes around the sides of the building, and the reflected routes. It is thus required to develop an algorithm that will determine all the possible routes for propagation, using LiDAR data. The algorithm uses the novel cutting plane technique customized to work with LiDAR data to extract all the principal routes between every pair of noise source and destination. Terrain parameters are determined from routes for modeling. The terrain parameters, and noise data when integrated with a sophisticated noise model give an accurate prediction of noise for a place. The novel point-to-point routing algorithm is developed using LiDAR data of the RGIPT campus. All the shortest routes were tested for their spatial accuracy and efficacy to predict the noise levels accurately. Various routes are found to be accurate within ±9 cm, while predicted noise levels are found to be accurate within ±6 dBA at an instantaneous scale. The novel accurate 3D routing algorithm can improve the other urban applications too. Full article

The cultural landscape of Chiang Mai city, which is characterized by the interlinkage between mountain and historical settlement, has faced the adverse impacts of visual intrusion in its buffer zone from urbanization. However, there are challenges to creating a quantitative visual evaluation for decision making in response to rapid urban change. This study evaluated the impact of building height on the city skyline and utilized existing cultural heritage locations on the mountain to define a protected visual zone while conducting a 3D-GIS-based visibility analysis to identify obstruction in three scenarios: the actual condition scenario (ACS) considering current conditions, the land use scenario (LUS) considering the land use ordinance, and the proposed scenario (PPS) considering mountain skyline protection, using computer-generated 3D city modeling. The comparative results from the analysis of viewshed, line of sight, and development area calculations revealed that the number of obstructed locations in the LUS decreased by 48.46%, and in the PPS, they decreased by 77.99%, while the development area increased by similar amounts, demonstrating that the city can grow and develop despite stricter height controls. In addition, based on a visual assessment, this study established a buffer distance and intensity to protect the integrity of the heritage while allowing the city to develop. Full article