Lab 4- Independent Spatial Analysis

Introduction:

The goal for this lab was to determine which areas within Shawano County had the highest risk for fire damage.  My objective was to find areas with the most fire occurrences in the past, are under intensive fire protection by the Wisconsin DNR (burning permit needed year-round), and at least 1 kilometer away from a water body.  The areas with most fire occurrences and with intensive protection by the DNR indicate a history of high fire risk, and the distance from water bodies indicates the dryness of the environment and access to abundant water.  My intended audience is government officials and developers working in resource management and in development.  Knowing where the fire risk is greatest can determine how buildings are built and what precautions are taken to prevent fire damage.  This information would be used by developers, politicians, or community members advocating for or against a building project. 

Data Sources: 

For this project, layers showing fire occurrences in the state of Wisconsin, the census block groups, fire protection areas of the DNR, rivers, and lakes were needed.  This data was obtained from the ESRI 2013 and Wisconsin DNR 2014 database.  One of the concerns is the age of the data.  For one, the databases are a year off from each other.  In addition, the data is now three or four years old.  Things could have changed since the data was created, such as increased fire occurrences in another area.  Another concern was the fire protection areas.  These are designations that the DNR makes based on climatic conditions such as rainfall.  This can vary greatly from year to year, and so the areas that are in need of intensive fire protection most likely have changed since the data was created.  

Methods:

First, the area of interest needed to be identified. To do this, Shawano County was queried from a shape file of Wisconsin. Next, a layer of all the block groups of the United States was clipped to only show the block groups of Shawano County.  Then, a spatial summarized join was performed on the clipped block groups and the fire occurrences to get the number of fire occurrences per block group in Shawano County.  On the fire protection data layer, a query was performed to only select areas under intensive protection by the Wisconsin DNR.  This selection was intersected with the block groups containing fire occurrence information.  On the river and lake layers, a buffer of 1 kilometer was made. Using these two buffers an area of 1 kilometer around water bodies was erased from the block groups.  Finally, a query was performed to find the block groups with over 100 fire occurrences.  The end result was a polygon layer showing the areas of Shawano County most at risk for fire damage.  These steps are summarized in Figure 1 below.  

Figure 1. Data flow model for finding areas with a high risk of fire damage.

 Results:

The result of the project was one large section and one smaller area with high fire damage risk.  These areas are found in the western and northern parts of the county.  This corresponds to the intensive fire protection area that covers the northern half of the state that changes to extensive or no fire protection in the southern half of the state. Extensive fire protection indicates that a burning permit is required during the months of January to May while the no fire protection area means that the DNR does not regulate burning permits.  Shawano County contains a lake and several rivers that travel throughout the entire county.  This would indicate that the county as a whole should be sufficiently watered to prevent fires. But one must also consider the type of soil and vegetation that covers much of the area.  Forests are common that often are fire suppressed and thus have abundant fuel to start a fire.  There are also many sand prairie and former prairie habitat that are historically affected by fire.  One should also consider the urbanization of the rural areas like Shawano County and the increased risk this poses for fires in buildings and other structures.  Figure 2 below shows a map of the area mapped within Shawano County and also a location map showing Shawano County within the context of the state of Wisconsin.  

Figure 2. Map of the highest fire risk areas of Shawano County, WI.

 Evaluation:

This project was a great way to apply concepts from lecture and practiced in class to a real-world example.  It required careful planning of the steps needed to come to the final result.  For example, during the planning process it was important to map out a rough sketch of the data flow model the project would take on as well as summarizing the needed results in a list format in order to work from a concise framework.  This made doing the actual steps easier and quicker to complete.  The creative freedom given to each student was fun and challenging.  It meant that each person had to find a spatial question that could be answered and find the data needed to complete it, one of the biggest complications in GIS work.  If the project was to be repeated, there are several things that could be improved.  The first and most important would be to find current data.  The world today is constantly changing in many respects, and employers want the most up-to-date information possible.  If a developer was to use this data for zoning and building, they would want it to reflect the area as it is today to prevent complications in the development process.  Another aspect to change would be the river and stream data.  This was made by the Wisconsin DNR, but was intended for the entire state.  This means that many smaller streams and rivers did not get factored into the river and streams layer.  To a developer or politician looking at Shawano County specifically, they would want more detailed data used.  During this project, I encountered difficulties with different projections on different datasets.  This was especially prevalent when I learned that some of my data was corrupted and I needed to find new data to use.  I also had to carefully choose the data and the processes I would use to make a clear, accurate, and concise map.