| Certain songbird species have declined throughout the United States over the past several decades. In most cases, this decline is directly correlated with loss of critical habitat. To prevent further loss of songbird species, an understanding of habitat needs is critical to species preservation. The development of geospatial methodologies and models that can effectively delineate areas of critical habitat on a variety of spatial scales is needed to help reduce the further loss of avian species and diversity. In this research effort, I used 30m Landsat Thematic Mapper (TM) satellite imagery and digital elevation models (DEMs) to create a predictive model of songbird distribution on an isolated mountain range in southeastern Utah. The question addressed in this study was: can songbird presence be predicted effectively using remotely sensed imagery and DEMs in a geographic information system (GIS)? The model showed a strong correlation between avian species, which were more specialized in their habitat selection and both elevation and remotely sensed spectral data. |
