Using reverse geocoding to identify prominent wildfire evacuation trigger points

Wildfire evacuation trigger points are prominent geographic features (e.g., ridge lines, rivers, and roads) utilized in timing evacuation warnings. When a fire crosses a feature, an evacuation warning is issued to the communities or firefighters in the path of the fire. Current methods for generating trigger buffers have limited utility because the resulting buffers are not explicitly tied to prominent geographic features, making it difficult to visually determine when a fire has breached a trigger point. This work aims to address this limitation by using reverse geocoding to identify prominent geographic trigger points that have more value to emergency managers. The method consists of three steps: 1) generate a trigger buffer using fire-spread modeling; 2) utilize online reverse-geocoding to retrieve geographic features proximal to the buffer boundary; and 3) identify the most prominent geographic features using viewshed analysis and compute the warning time each would offer given predicted fire spread rates to proximal communities. A case study of Julian, California is presented to identify prominent geographic trigger points that may have value to emergency managers in improving the timing of wildfire evacuation warnings in this region.     

Personalising the viewshed: Visibility analysis from the human perspective

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.     

Modeling visibility through vegetation

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: 969–977. [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.     

A partition‐based serial algorithm for generating viewshed on massive DEMs

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.     

Incorporating the visibility of coastal energy infrastructure into multi-criteria siting decisions

Concern about the visibility of large infrastructure development often drives public opposition to these projects. However, insufficient analytical tools to assess visibility across a large number of alternate sites prior to siting typically results in the omission of visibility in multi-criteria siting processes, leading to inferior site selection and often costly litigation. This paper presents an approach for deriving visibility maps based on the location and duration of viewing by residents and visitors and demonstrates its use in illuminating tradeoffs by comparing these maps to wind energy value maps in the context of offshore wind energy development in the Northeastern United States.     

An Investigation into the Causes of Errors and Inconsistencies in Predicted Viewsheds

Previous evaluations of viewshed analyses have raised concerns about the accuracy and repeatability of the process. Digital elevation model (DEM) errors, the limited spatial resolution of DEMs, and differing algorithms employed by different GIS packages have all been suggested as possible sources for inaccuracy and non‐repeatability. This study compared a field surveyed viewshed to predicted viewsheds generated using a variety of software packages and DEM databases, some of which contained known amounts of error. We found that each of the factors suggested by previous authors contributes to errors in predicted viewsheds. DEM errors contribute most to the discrepancies between surveyed and predicted viewsheds, and the majority of their negative impact occurred at very low levels of DEM error. Differing algorithms used by different GIS packages also contribute significantly to surveyed/predicted viewshed discrepancies, but more importantly, result in predicted viewsheds that disagree with one other, thereby confounding comparisons of results generated with differing software systems. Finally, the spatial resolution of DEMs also has a significant effect on the degree of agreement between surveyed and predicted viewsheds, but the magnitude of this effect is not as great as are the effects produced by DEM errors.