MEDIUM: Data Visualization, Map, Digital Illustration, Digital Photography
DESCRIPTION:
We applied a spectral unmixing algorithm to Landsat imagery to estimate sub-pixel land-cover fractions. For each pixel, the proportion of impervious surfaces (e.g., buildings, roads, paved areas) was mapped in red, woody vegetation (trees and shrubs) in green, and non-woody vegetation (grasses and herbs) in blue.
ARTIST’S STATEMENT:
I am currently a PhD student at the University of Wisconsin–Madison, where I study the growth of the Wildland–Urban Interface (WUI), areas where human development and wildlands overlap, increasing wildfire risk across global Mediterranean ecosystems. My research examines the drivers of WUI expansion and its impacts on wildfire activity and vegetation communities. Using satellite imagery and remote sensing methods, I analyze the expansion of housing development into wildland areas and its effects on fire activity. I am also interested in art–science collaborations that communicate research in creative ways and allow broader audiences to engage with environmental science.
