Potential of LIDAR data to improve species modeling and habitat characterization

Three-dimensional habitat structure is an important variable influencing animal-habitat associations; however, modeling and mapping habitat structural information over large areas can be challenging.  Current methods for characterizing habitats and mapping species distribution are based on field data that are often limited in spatial extent, and/or on remotely sensed data (i.e. land cover and vegetation maps) that are unable to detect the vertical structure of vegetation. Lidar remote sensing can provide unprecedented fine-grained information about the 3-D physical structure of terrestrial and aquatic environments and over broad areas, and therefore is a promising tool for species-habitat modeling and vegetation characterization. In this presentation we will (1) present an overview of the relevant lidar technology, including recent applications for habitat modeling and vegetation mapping, (2) introduce current USGS Gap Analysis efforts using lidar, and (3) discuss how lidar can be integrated into the USGS Gap Analysis framework.