Another small project I did ages ago. This is one I’d like to return to as there is so much more potential and remote sensing for forests is a particular interest of mine. However for now here is a quick look at a case study of the wildfire-urban interface.
The GiIl and Stephens article is an excellent article about the challenges posed by wildfires on the management of the wildland-urban interface (WUI). Building on this, this post will use GIS and remote sensing to look at asset protection zones in Wilson, Wyoming.
The expansion of cities has put more people in the WUI zone. Wildfires in the WUI have serious social, economic and ecological consequences. Several management problems arise from this and need to be taken into account such as safety of the population, organising defensible space and protecting the biodiversity of the wildland. The proximity of houses and fuel increases the risk to people and homes.
In 2001 there was a wildfire that threatened the town of Wilson, Wyoming. The fire covered 4,470 acres, and 100 families were evacuated. Set in the WUI, this is an area with concerns for fire management. There is free LiDAR data for this region, which was downloaded from OpenTopgraphy.org and past wildfire extents from the Teton National Park Website (I can’t find this source again but here’s a link to a site that provides similar data). LiDAR data was then processed in ENVI. From visual observations of the raw LiDAR data seen above, trees and buildings can already be observed to be in proximity to each other. Following this, the processed shapefiles were then exported into QGIS where the NNJoin tool was used to calculate the distance from each tree to the closest building. The results can be seen below.
As recommended by the US Government there should be a defensible space of 30 feet around the home, this is signified by the red coloured trees in the above image. In this area, vegetation should be limited and well spaced. There are on average 5 trees within the defensible space of each house, which is a significant number for a 9 m radius. However, the analysis in the above figure does not take into account the size of the tree or the spacing between each tree. Also, the government recommends a further 90 feet (orange trees in the figure above) in additional protective space. In this zone, grass should be short and trees 10ft apart. Further analysis needs to be done on the spacing of trees to each other for practical analysis. Though this shows the potential of LiDAR in this application and highlights areas of defensible space around these houses.
In conclusion, analysis of wildfire risk at the urban interface is enhanced by the use of information from GIS. Data can now be easily collected at individual tree level which can help in identifying potential fuel and create accurate decisions about where trees can be removed. Furthermore, maps are useful in determining possible problem areas and communicating these to a community. As well as the successful use of detailed maps in communicating wildfire risk options to communities and decision-makers.