Using reverse geocoding to identify prominent wildfire evacuation trigger points. (October 2017)

• Record Type: Journal Article
• Authors: Li, Dapeng; Cova, Thomas J.; Dennison, Philip E.
• Is Part Of: Applied geography. Volume 87(2017)
• Page Start: 14
• Page End: 27
• Publication Date: 2017-10
• Subjects: Wildfire evacuation -- Evacuation timing -- Trigger modeling -- Reverse geocoding -- Fire spread modeling -- Viewshed analysis; Geography -- Periodicals; Human geography -- Periodicals; Human ecology -- Periodicals; 910
• DOI: 10.1016/j.apgeog.2017.05.008
• Languages: English
• ISSNs: 0143-6228

Abstract

Abstract: 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. Highlights: A novel reverse geocoding application is introduced to support wildfire evacuation decision making. The proposed method takes into account both evacuation timing and feature prominence. Reverse geocoding and viewshed analysis are used to identify prominent trigger points. Wildfire spread simulation is used to compute lead times. A case study is presented to highlight the utility of the proposed method.