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The objective of this study is the production and visualization of an emotional map to reveal the unique emotions inherent to the areas surrounding the Yeongsan River, which is often referred to as ‘the cradle of civilization’ in Korea. The sites selected for this study are the 11 cities and districts (5667.6 km2) that cut across the vast granary in the southeastern region of Korea, near the Yeongsan River. The emotional map was produced by extracting features of historical and cultural heritage distributed throughout this region and by using a geographic information systems program and its functions for spatial analysis. A database was constructed through interviews with locals and Global Positioning System to index 4318 pieces of cultural heritage to achieve the visualization of emotions. Among the 558 historical relics considered for representing the regional culture, 100 with the largest emotional impact were selected. It was determined that loyalty (), justice (), courtesy (), resentment (), and anger () should be the major emotional elements. Methodologically, a set of regional, periodic, historical, and emotional classification codes were first systematized. After subjecting this data to inverse distance weight interpolation and vertical exaggeration coefficients, the three-dimensional emotional map could be visualized.  相似文献   

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ABSTRACT

The aim of site planning based on multiple viewshed analysis is to select the minimum number of viewpoints that maximize visual coverage over a given terrain. However, increasingly high-resolution terrain data means that the number of terrain points will increase rapidly, which will lead to rapid increases in computational requirements for multiple viewshed site planning. In this article, we propose a fast Candidate Viewpoints Filtering (CVF) algorithm for multiple viewshed site planning to lay a foundation for viewpoint optimization selection. Firstly, terrain feature points are selected as candidate viewpoints. Then, these candidate viewpoints are clustered and those belonging to each cluster are sorted according to the index of viewshed contribution (IVC). Finally, the candidate viewpoints with relatively low viewshed contribution rate are removed gradually using the CVF algorithm, through which, the viewpoints with high viewshed contribution are preserved and the number of viewpoints to be preserved can be controlled by the number of clusters. To evaluate the effectiveness of our CVF algorithm, we compare it with the Region Partitioning for Filtering (RPF) and Simulated Annealing (SA) algorithms. Experimental results show that our CVF algorithm is a substantial improvement in both computational efficiency and total viewshed coverage rate.  相似文献   

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As increasingly large‐scale and higher‐resolution terrain data have become available, for example air‐form and space‐borne sensors, the volume of these datasets reveals scalability problems with existing GIS algorithms. To address this problem, a kind of serial algorithm was developed to generate viewshed on large grid‐based digital elevation models (DEMs). We first divided the whole DEM into rectangular blocks in row and column directions (called block partitioning), then processed these blocks with four axes followed by four sectors sequentially. When processing the particular block, we adopted the ‘reference plane’ algorithm to calculate the visibility of the target point on the block, and adjusted the calculation sequence according to the different spatial relationships between the block and the viewpoint since the viewpoint is not always inside the DEM. By adopting the ‘Reference Plane’ algorithm and using a block partitioning method to segment and load the DEM dynamically, it is possible to generate viewshed efficiently in PC‐based environments. Experiments showed that the divided block should be dynamically loaded whole into computer main memory when partitioning, and the suggested approach retains the accuracy of the reference plane algorithm and has near linear compute complexity.  相似文献   

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The calculation of visibility patterns associated with past monuments and sites is an important element in modern landscape archaeology. These types of investigations have been limited by the inability of current viewshed routines to incorporate vegetation information. The following paper presents a new viewshed algorithm aimed at calculating the probability of locations being visible in the presence of vegetation. To this day, little work has been done to address this limitation, a notable exception is Dean's Permeability Index Model (1997 Dean, D. J. 1997. Improving the accuracy of forest viewsheds using triangulated networks and the visual permeability method.. Canadian Journal of Forest Research, 27: 969977. [Crossref] [Google Scholar]). A review of Dean's model is provided here in the light of the new proposed algorithm. The new algorithm is based on mathematical principles found in Beer–Lambert's Attenuation Law, a physics law governing the attenuation of light through a medium. In addition to common viewshed parameters, the routine requires a 3D model of a tree/plant and a layer indicating the spatial distribution and density of vegetation on the landscape. The possibility of varying both, the spatial and density distribution of tree/plants, and the three‐dimensional model representing vegetation makes the model well suited to investigate the impact that vegetation may have on visibility patterns.  相似文献   

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Viewshed analysis remains one of the most popular GIS tools for assessing visibility, despite the recognition of several limitations when quantifying visibility from a human perspective. The visual significance of terrain is heavily influenced by the vertical dimension (i.e. slope, aspect and elevation) and distance from the observer, neither of which are adjusted for in standard viewshed analyses. Based on these limitations, this study aimed to develop a methodology which extends the standard viewshed to represent visible landscape as more realistically perceived by a human, called the ‘Vertical Visibility Index’ (VVI). This method was intended to overcome the primary limitations of the standard viewshed by calculating the vertical degrees of visibility between the eye-level of a human and the top and bottom point of each visible cell in a viewshed. Next, the validity of the VVI was assessed using two comparison methods: 1) the known proportion of vegetation visible as assessed through imagery for 10 locations; and 2) standard viewshed analysis for 50 viewpoints in an urban setting. While positive, significant correlations were observed between the VVI values and both comparators, the correlation was strongest between the VVI values and the image verified, known values (r = 0.863, p = 0.001). The validation results indicate that the VVI is a valid method which can be used as an improvement on standard viewshed analyses for the accurate representation of landscape visibility from a human perspective.  相似文献   

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A rapid and flexible parallel approach for viewshed computation on large digital elevation models is presented. Our work is focused on the implementation of a derivate of the R2 viewshed algorithm. Emphasis has been placed on input/output (IO) efficiency that can be achieved by memory segmentation and coalesced memory access. An implementation of the parallel viewshed algorithm on the Compute Unified Device Architecture (CUDA), which exploits the high parallelism of the graphics processing unit, is presented. This version is referred to as r.cuda.visibility. The accuracy of our algorithm is compared to the r.los R3 algorithm (integrated into the open-source Geographic Resources Analysis Support System geographic information system environment) and other IO-efficient algorithms. Our results demonstrate that the proposed implementation of the R2 algorithm is faster and more IO efficient than previously presented IO-efficient algorithms, and that it achieves moderate calculation precision compared to the R3 algorithm. Thus, to the best of our knowledge, the algorithm presented here is the most efficient viewshed approach, in terms of computational speed, for large data sets.  相似文献   

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Selecting the set of candidate viewpoints (CVs) is one of the most important procedures in multiple viewshed analysis. However, the quantity of CVs remains excessive even when only terrain feature points are selected. Here we propose the Region Partitioning for Filtering (RPF) algorithm, which uses a region partitioning method to filter CVs of a multiple viewshed. The region partitioning method is used to decompose an entire area into several regions. The quality of CVs can be evaluated by summarizing the viewshed area of each CV in each region. First, the RPF algorithm apportions each CV to a region wherein the CV has a larger viewshed than that in other regions. Then, CVs with relatively small viewshed areas are removed from their original regions or reassigned to another region in each iterative step. In this way, a set of high-quality CVs can be preserved, and the size of the preserved CVs can be controlled by the RPF algorithm. To evaluate the computational efficiency of the RPF algorithm, its performance was compared with simple random (SR), simulated annealing (SA), and ant colony optimization (ACO) algorithms. Experimental results indicate that the RPF algorithm provides more than a 20% improvement over the SR algorithm, and that, on average, the computation time of the RPF algorithm is 63% that of the ACO algorithm.  相似文献   

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Abstract

In this paper we address the problem of computing visibility information on digital terrain models in parallel. We propose a parallel algorithm for computing the visible region of an observation point located on the terrain. The algorithm is based on a sequential triangle-sorting visibility approach proposed by De Floriani et al. (1989). Static and dynamic parallelization strategies, both in terms of partitioning criteria and scheduling policies, are discussed. The different parallelization strategies are implemented on an MIMD multicomputer and evaluated through experimental results.  相似文献   

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