On IO-efficient viewshed algorithms and their accuracy

Given a terrain T and a point v, the viewshed or visibility map of v is the set of points in T that are visible from v. To decide whether a point p is visible one needs to interpolate the elevation of the terrain along the line-of-sight (LOS) vp. Existing viewshed algorithms differ widely in which and how many points they chose to interpolate, how many lines-of-sight they consider, and how they interpolate the terrain. These choices crucially affect the running time and accuracy of the algorithms. In this paper our goal was to obtain an IO-efficient algorithm that computes the viewshed on a grid terrain with as much accuracy as possible given the resolution of the data. We describe two algorithms which are based on computing and merging horizons, and we prove that the complexity of horizons on a grid of n points is O(n), improving on the general O(na(n)) bound on triangulated terrains. Our finding is that, in practice, horizons on grids are significantly smaller than their theoretical worst case bound, which makes horizon-based approaches very fast. To measure the differences between viewsheds computed with various algorithms we implement an error metric that averages differences over a large number of viewsheds computed from a set of viewpoints with topological significance, like valleys and ridges. Using this metric we compare our current approach, Van Kreveld's model used in our previous work [7], the algorithm of Ferreira et al. [6], and the viewshed module r.los in the open source GIS GRASS

Towards Optimal Line of Sight Coverage

Maintaining the line of sight to a moving object or person over long distances is critical in many applications, e.g., mobile communications, security, surveillance. Determining the best places to position (or build) technologies is difficult because even small changes in the location can greatly affect the so-called viewshed, which is the collection of land areas within line of sight of a given observer. The need for multiple sensors or towers further complicates this problem, as they often need to work cooperatively to achieve the best possible coverage. This study proposes a novel approach that consists of three separate inventions: 1) An algorithm for calculating viewsheds from many sensors in parallel, 2) Introduction of a meaningful measure of quality for coverage to compare competing configurations; and 3) Optimization of that well-defined objective function to find the best suitable sensor parameters for practical applications. Preliminary results suggest unprecedented performance on a wide range of real terrains

Mapping invisibility: GIS approaches to the analysis of hiding and seclusion

Analyses of visibility have become a commonplace within landscape-based archaeological research, whether through rich description, simple mapping or formal modelling and statistical analysis, the latter increasingly carried out using the viewshed functionality of GIS. The research presented here challenges current obsessions with what is visible to focus instead upon the interpretative benefits of considering the invisible and the complex interplay of visibility and concealment that frequently accompany landscape movement and experience. Having highlighted the difficulties in analysing relational properties such as invisibility and hiding using traditional archaeological techniques, a series of new GIS methodologies are presented and evaluated in the context of an original study of a series of remarkably small, visually non-intrusive prehistoric megalithic monuments. The results serve to challenge dominant interpretations of these enigmatic sites as well as demonstrating the utility, value and potential of the GIS-based approaches developed

Space-time analytics of human physiology for urban planning.

Recent advancements in mobile sensing and wearable technologies create new opportunities to improve our understanding of how people experience their environment. This understanding can inform urban design decisions. Currently, an important urban design issue is the adaptation of infrastructure to increasing cycle and e-bike use. Using data collected from 12 cyclists on a cycle highway between two municipalities in The Netherlands, we coupled location and wearable emotion data at a high spatiotemporal resolution to model and examine relationships between cyclists' emotional arousal (operationalized as skin conductance responses) and visual stimuli from the environment (operationalized as extent of visible land cover type). We specifically took a within-participants multilevel modeling approach to determine relationships between different types of viewable land cover area and emotional arousal, while controlling for speed, direction, distance to roads, and directional change. Surprisingly, our model suggests ride segments with views of larger natural, recreational, agricultural, and forested areas were more emotionally arousing for participants. Conversely, segments with views of larger developed areas were less arousing. The presented methodological framework, spatial-emotional analyses, and findings from multilevel modeling provide new opportunities for spatial, data-driven approaches to portable sensing and urban planning research. Furthermore, our findings have implications for design of infrastructure to optimize cycling experiences

Total 3D-viewshed map: quantifying the visible volume in digital elevation models

The 3D perception of the human eye is more impressive in irregular land surfaces than in flat land surfaces. The quantification of this perception would be very useful in many applications. This article presents the first approach to determining the visible volume, which we call the 3D-viewshed, in each and all the points of a DEM (Digital Elevation Model). Most previous visibility algorithms in GIS (Geographic Information Systems) are based on the concept of a 2D-viewshed, which determines the number of points that can be seen from an observer in a DEM. Extending such a 2D-viewshed to 3D space, then to all the DEM-points, is too expensive computationally since the viewshed computation per se is costly. In this work, we propose the first approach to compute a new visibility metric that quantifies the visible volume from every point of a DEM. In particular, we developed an efficient algorithm with a high data and calculation re-utilization. This article presents the first total-3D-viewshed maps together with validation results and comparative analysis. Using our highly scalable parallel algorithm to compute the total-3D-viewshed of a DEM with 4 million points on a Xeon Processor E5-2698 takes only 1.3 minutes

I/O-Efficient Algorithms for Contour Line Extraction and Planar Graph Blocking

For a polyhedral terrain C, the contour at z-coordinate h, denoted Ch, is defined to be the intersection of the plane z = h with C. In this paper, we study the contour-line extraction problem, where we want to preprocess C into a data structure so that given a query z-coordinate h, we can report Ch quickly. This is a central problem that arises in geographic information systems (GIS), where terrains are often stored as Triangular Irregular Networks (TINS). We present an I/O-optimal algorithm for this problem which stores a terrain C with N vertices using O(N/B) blocks, where B is the size of a disk block, so that for any query h, the contour ch can be computed using o(log, N + I&l/B) I/O operations, where l&l denotes the size of Ch. We also present en improved algorithm for a more general problem of blocking bounded-degree planar graphs such as TINS (i.e., storing them on disk so that any graph traversal algorithm can traverse the graph in an I/O-efficient manner), and apply it to two problms that arise in GIS

Control of self-reconfigurable robot teams for sensor placement

Self Reconfigurable Robots (SRRs) are a system of many simple modules that can rearrange themselves to work together and better perform complicated tasks. They are in theory more extensible then traditional robotics. We investigate the particular problem of using SRRs to both explore and survey an unknown environment. The environment is explored by using the Robots internal sensors, and surveyed by placing a limited number of static sensors at ideal locations. The advantage of SRRs is that they can adapt to terrain difficulty by adjusting the number of individual robots on the field by reorganizing its modules. We test a distributed task driven implementation based on the ALLIANCE architecture in a simulated environment. The results show that SRRs are both able to cooperatively explore the environment as well as place sensors in useful locations, getting good results