USDA Forest Service Remote Sensing Applications Center Forest Inventory and Analysis New Technology How is FIA integrating new technological developments.

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USDA Forest Service Remote Sensing Applications Center Forest Inventory and Analysis New Technology How is FIA integrating new technological developments such as remote sensing? Ken Brewer Washington Office

FIA Strategic Plan: January 2007 New Technology: “Integrating new technology is critical to the efficient delivery of the FIA program.”

New Technology: 1.Team with USGS to improve accuracy of National Land Cover Data (NLCD) forest cover mapping…..Technology partnership with Multi-Resolution Land Characterization Consortium (MRLC) for NLCD 2.Technology partnerships with National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), and Natural Resources Conservation Service (NRCS)

NLCD Tree Canopy Cover = Response developed by classifying Tree crown cover on high resolution Imagery for 3-4, 1-4 km 2 sampling chips per Landsat scene. Model developed using regression tree (random forest) algorithm Fig. from Homer et al General modeling approach

FIA Data Use Rationale FIA is a fundamental component of Forest Service research. FIA is a data rich program Consistency between map based and plot based estimates FIA survey design is easily intensified

NLCD Tree Canopy Cover = Response developed by photo Interpreting Tree crown cover on NAIP Imagery for ~ m 2 sampling chips per Landsat scene. Random forest algorithm K nearest neighbor imputation Support vector machines Example modelling techniques Fig. from Homer et al General modeling approach

NLCD Pilot Study Areas 4x Intensity Photo-based Sample Locations 105 photo points to estimate % tree canopy cover for model development

North American Forest Dynamics Project NASA funded project designed to characterize disturbance patterns and recovery rates of forests across the continent. Goal: Determine the role of forest dynamics in North American carbon balance Uses FIA data for validation and training

Monitoring Trends in Burn Severity Project MTBS characterizes burn severity on all large fires in CONUS, AK, HI, PR –All ownerships –Historical (since 1984) –Landsat-based, 30m resolution Jointly implemented by USFS (RSAC) and USGS (EROS) Interagency sponsorship by WFLC FIA data used for estimates LandsatNBR Pre-fire Post-fire dNBR Burn Severity Fire Perimeter Difference

Dimensions of Change TemporalSpatial

MTLCC Workshop Recommendation Hierarchical approach using multiple datasets: –MODIS data –Landsat data –NAIP & DOQ data –FIA field data

NASA-RSAC-FIA Inventory UAS Mission

Automated Image Acquisition Yellow points = Plots Red points = Images

High Resolution Imagery 16 Band Multi-spectral

Takeoff Unsuccessful

Questions? USDA Forest Service Remote Sensing Applications Center Forest Inventory and Analysis