As a final project for a university GIS course, I was tasked with determining the ideal locations for survey locations to spot the flammulated owl within Yosemite National Park, California.
Research shows that these owls primarily breed in low-to-mid-elevation montane forests with moderate levels of canopy closure. Forests dominated by Ponderosa Pines are preferred breeding locations, though flammulated owls have also been found to breed in Douglas fir forests and, to a lesser degree, Lodgepole pines and other conifers. There is also evidence of these owls preferring stands on moderately sloping terrain, as well as ridgetops, particularly sites with east or south facing slopes.
These attributes defining breeding location of the flammulated owls were grouped together into a site suitability model, with numeric ranks being applied to different variables, namely elevation, TPI(topographical position index), aspect, vegetation type, cover percentage, and distance to roads or trails.
Utilizing multiple datasets of Yosemite National Park, such as maps of vegetation type and elevation, numerical values for site suitability were found for found. I identified regions of the park suitable for flammulated owl breeding sites as those with site suitability in the 90th percentile of all park areas. These selected survey areas are shown in the map below.
As part of a university GIS course, I was tasked with finding the ideal habitat for the Riparian Woodrat within a region of California forest, in order to earmark ideal regions for protection. In order to do this, I conducted a site suitability analysis for the riparian woodrat, using known factors about its desired habitat location, similar to the above flammulated owl site suitability analysis. To better allow for easy modification, visualization, and reproduction of the final model, the model was built in ModelBuilder. The final produced map, as well as the ModelBuilder workflow used for said map, are included below.
As part of a GIS spatial analysis course, I was tasked with determining which police station in San Francisco would be the most logistically ideal to close down. A network analysis of the road network of the city was used to determine the 'response time' of any given police station, defined as the time it would take for a police cruiser to travel from the station to the location in question. This response time map, seen below, was combined with data on crime types and locations within the city over the past year to analyize the number of crimes each police station was in the ideal location to respond to. This analysis led to the selection of a police station ideal for closure(pictured below), as the number of crimes it was ideally located to respond to was very low, due to adjacent police stations having overlapping response zones.
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