Forest Inventory and Analysis USDA Forest Service PNW Research Station Remote sensing; The world beyond aerial photos
Forest Inventory and Analysis USDA Forest Service PNW Research Station In the beginning: Invention New applications from large to small proliferate Small: LiDAR for Harvest unit profiles 1990’s Large: National mapping and estimation tools for carbon
Forest Inventory and Analysis USDA Forest Service PNW Research Station North American Forest Dynamics (NAFD) mapping forest disturbance and cause mapping forest disturbance and cause Monitoring, Reporting, and Verification (MRV) accounting system current and historic baseline carbon stocks and trends current and historic baseline carbon stocks and trends Landscape Change Monitoring System (LCMS) land use and land cover change mapping land use and land cover change mapping National Land Cover Dataset (NLCD) – Tree Canopy Cover this 30 meter nationwide (CONUS) map depicts tree canopy cover in this 30 meter nationwide (CONUS) map depicts tree canopy cover in Image-based Change Estimation (ICE) land use and land cover change information land use and land cover change information National Assessments Monitoring Change, Carbon Assessments, land use, land cover
Forest Inventory and Analysis USDA Forest Service PNW Research Station Small Scale applications LiDAR individual tree species classification Brown: Hardwood Green: Conifer
Forest Inventory and Analysis USDA Forest Service PNW Research Station Validation Consolidation Applications Integration What is next?
Forest Inventory and Analysis USDA Forest Service PNW Research Station Validation USFS (Cohen – PI, Andersen, Healey, Moisen, Schroeder, Woodall, Domke), OSU (Yang), SUNY (Stehman), BU (Kennedy, Woodcock, Zhu), USGS (Vogelmann, Steinwand), UMD (Huang) Uncertainty Analyses: Compare biomass estimates and precision from different frameworks and input datasets Design-based with (1) inventory plots alone (current US NGHGI), (2) plots and LiDAR, and (3) plots, LiDAR, and Landsat Model-based with (4) plots and Landsat, and (5) plots, LiDAR, and Landsat (6) Current v. (7) high-precision georeferenced plot locations
Forest Inventory and Analysis USDA Forest Service PNW Research Station FROM: Purpose Consolidation Process Data Product 2 Process Data Data Product 1 Product 2 Purpose Purpose TO: Process Data Product 1
Forest Inventory and Analysis USDA Forest Service PNW Research Station Accurate plot locations are critical for matching high-res remote sensing & field data In 2-phase sampling designs, error in plot locations directly influences the precision of parameter estimates In 2-phase sampling designs, error in plot locations directly influences the precision of parameter estimates Dual-frequency GPS+GLONASS receivers can acquire coordinates with < 1 m error in all boreal forest conditions Courtesy: Ray Koleser Courtesy: Ray Koleser Acquiring accurate FIA plot locations using survey-grade GPS receiver on Kenai Peninsula (August, 2008) Application 2014 Tanana Pilot: High-accuracy GPS
Forest Inventory and Analysis USDA Forest Service PNW Research Station Integration
Forest Inventory and Analysis USDA Forest Service PNW Research Station