|SANKEY, TEMUULEN - Idaho State University|
|GLENN, NANCY - Idaho State University|
|SHRESTHA, RUPESH - Idaho State University|
Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 9/1/2010
Publication Date: 12/6/2010
Citation: Sankey, T.T., Glenn, N.F., Shrestha, R., Hardegree, S.P. 2010. Fine-scale characterization of juniper expansion via LiDAR data and fusion with Landsat 5 TM image. In: EOS Transactions, American Geophysical Union Annual Meeting, Vol 91, December 2010. San Francisco, CA (CD-ROM Abstract).
Technical Abstract: Juniper encroachment into rangelands is one of the most prominent land cover changes occurring in the western North America. Development of image-based methods to assess juniper encroachment over large areas is needed to identify priority areas for juniper intensive management. We fused lidar data with multi-temporal Landsat 5 TM image and detected 85% juniper expansion since 1965, which was corroborated with tree-ring data. Lidar applications for characterizing juniper encroachment phases at finer scales were also explored. Lidar point cloud data were used to separate overlapping juniper tree canopies and to estimate juniper tree height, age, density, and canopy percent cover. Fusion approaches for both pixel-level and sub-pixel juniper cover classifications were compared. Among them, a multiple regression-based approach performed best. Lidar data fused with Landsat 5 TM data produced superior results in both juniper presence/absence and sub-pixel juniper cover classifications than either one of the image sources alone. However, the improvement via the fusion was marginal (up to 6% increase) over the lidar data alone. Lidar-derived estimates can be sufficiently used alone for pixel-level and sub-pixel juniper cover classifications, but spectral data are necessary for locating juvenile junipers dispersed amongst shrubs.