The National Forest's plan and project decisions often rely on accurate and precise descriptions of landscape features. The technologies used to collect these data are rapidly evolving from field collection methods to remote sensing. Currently most remote sensing data are airbore and collect data at too coarse a resolution to be useful for all decisions. This is especially true when data are necessary for habitats that are rare at the landscape scale. An example of such a features are stream and riparian systems. Much of the data collected at stream sites are currently collected by field crews measuring attributes at a sample of locations within a stream reach. The primary advantage of such an approach is they can measure attributes below the water's surface. New remote sensing technologies are now emerging such as ground-based LiDaR that permit fine-scale census of stream habitats. These data will certainly differ in some ways from data that is currently collected by the field crews. The purpose of this project will be to compare these two approaches to evaluating stream reaches. Results will provide an understanding of the stream attributes field methods and LIDAR can summarize similarly as well as where each of the techniques are stronger. These data are important to the Forest Service because they can provide guidance on which approach should be used in which situations.
US Forest Service Challenge Cost Share Agreement