Abstract
In the past, gathering data to support research in the biological sciences has traditionally required that people be on site, despite any ecological vulnerability of such sites. Within the last 50 years, the advent of extremely sensitive instrumentation, such as satellite imagery and synthetic aperture radar, has permitted the collection of data from many miles away. This is referred to as “remote sensing.” The primary hypothesis of this paper is that remote sensing may eliminate much of the potential harm caused by traditional field methods for determining ecologically sensitive areas, specifically fawning sites. This study utilized mule deer, Odocoileus hemionus, in Fort Carson, Colorado, as a surrogate species for endangered ungulates. We used Landsat5 Thematic Mapper (TM) imagery, vegetation indices, and digital elevation models to explore the advantages and challenges of using remote sensing to assess habitat and landscape use by mule deer. We conducted a maximum likelihood supervised classification in order to characterize fawning sites (determined by GPS-collar outputs) through the use of Landsat5TM imagery. The null-hypothesis testing method showed that multiphenomenological data is highly significant (z-scores > 5) for identifying fawning sites on a regional scale.