1. Bootstrap Operation for Generating Hi- Resolution Inventory Estimates Using Incompatible Multi-Source Data rcl7820@owl.forestry.uga.edu Lowe, 04 Roger Lowe, Chris Cieszewski, Kim Iles 2004 Western Forest Mensurationists Conference Kah-Nee-Ta Resort, Warm Springs, OR June 20-22, 2004 2004 Western Forest Mensurationists Conference Kah-Nee-Ta Resort, Warm Springs, OR June 20-22, 2004

2. rcl7820@owl.forestry.uga.edu Lowe, 04 I have inserted running commentary throughout the slides in these blue text boxes. Maybe they’ll help you understand (somewhat) what we’re trying to do.

3. rcl7820@owl.forestry.uga.edu Lowe, 04 How can we create a spatially explicit inventory if the data of interest are not sufficiently spatially explicit? What’s the Problem?

4. rcl7820@owl.forestry.uga.edu Lowe, 04 How can we create a spatially explicit inventory if the data of interest are not sufficiently spatially explicit? What’s the Problem?

5. rcl7820@owl.forestry.uga.edu Lowe, 04 For Example… Total Conifer Volume per County (mil. cuft.)

6. rcl7820@owl.forestry.uga.edu Lowe, 04 How can we create a spatially explicit inventory if the data of interest are not sufficiently spatially explicit? What’s the Problem? How can simulations that incorporate adjacency constraints be run using ground information summarized at the county-level?

7. rcl7820@owl.forestry.uga.edu Lowe, 04 Instead of running simulations at the county resolution,

8. rcl7820@owl.forestry.uga.edu Lowe, 04 …can we run them at a finer spatial resolution?

9. rcl7820@owl.forestry.uga.edu Lowe, 04Data Landsat 5 Thematic Mapper satellite data USFS FIA plot-level tabular data (no locations) Forest industry inventory data (tabular, spatial) Other GIS data (rivers, roads, DEMs, etc.)

10. rcl7820@owl.forestry.uga.edu Lowe, 04Approach Create forested “stands” from the LTM imagery to populate with inventory information

11. rcl7820@owl.forestry.uga.edu Lowe, 04Approach Somehow rank those polygons according to amount of timber out there Create forested “stands” from the LTM imagery to populate with inventory information

12. rcl7820@owl.forestry.uga.edu Lowe, 04Approach Create forested “stands” from the LTM imagery to populate with inventory information Somehow rank those polygons according to amount of timber out there Rank the FIA data similarly

13. rcl7820@owl.forestry.uga.edu Lowe, 04Approach Distribute FIA information to LTM-generated polygons

14. rcl7820@owl.forestry.uga.edu Lowe, 04Approach Distribute FIA information to LTM-generated polygons Scale distributed information back to the unbiased FIA totals

15. rcl7820@owl.forestry.uga.edu Lowe, 04 Create Forested “Stands” Group similar pixels to create the forest polygons Used Euclidean spectral distance to group similar pixels Initial minimum group size of 5 pixels (~1 acre) Done separately for the 8 scenes (and fractions of scenes) required for complete LTM imagery coverage of Georgia

16. rcl7820@owl.forestry.uga.edu Lowe, 04 Create Forested “Stands”

17. rcl7820@owl.forestry.uga.edu Lowe, 04 Rank Data Basal area – Euclidean spectral distance model P19R38 ED VS Pine BA -20 0 20 40 60 80 100 120 140 160 0.00010.00020.00030.00040.00050.00060.000 EDistance PineBA Observed Predicted Poly. (Observed) R 2 = 0.63 RMSE = 23.2 Nonlinear regression models relating Euclidean spectral distance and basal area Populated LTM-generated polygons with est. basal area from these models Ranked LTM-generated polygons using these estimated values Ranked FIA data using their ba measures

18. rcl7820@owl.forestry.uga.edu Lowe, 04 Rank Data Basal area – Euclidean spectral distance model Have 2 sorted lists polygon list sorted by LTM-estimated basal area FIA condition-level list sorted by ground-measured basal area

19. rcl7820@owl.forestry.uga.edu Lowe, 04 Distribute FIA Information LTM polygon area scaled to the area represented by the FIA plots (for data distribution) Polygon area equals the area represented by the FIA plots This aides the distribution process

20. rcl7820@owl.forestry.uga.edu Lowe, 04 Distribute FIA Information LTM polygon area scaled to the area represented by the FIA plots (for data distribution) Info from highly ranked FIA plots distributed to highly ranked LTM-polygons - Poly ac / FIA ac => volume - Poly ac / FIA ac => volume - All others - All others Trying to put information from similar FIA plots into LTM- generated polygons with similar characteristic(s) Volume was scaled by the ratio of polygon acreage to FIA acreage Other information was transferred as well (tpa, age, si, etc.)

21. rcl7820@owl.forestry.uga.edu Lowe, 04 Distribute FIA Information LTM polygon area scaled to the area represented by the FIA plots (for data distribution) Info from highly ranked FIA plots distributed to highly ranked LTM-polygons LTM polygon areas recalculated, total volume calculated Volume per acre recalculated using correct polygon acreage

22. rcl7820@owl.forestry.uga.edu Lowe, 04 Scale Distributed Info Back to FIA Totals Polygons currently contain LTM-estimated basal area, and FIA plot information

23. rcl7820@owl.forestry.uga.edu Lowe, 04 Scale Distributed Info Back to FIA Totals Polygons currently contain LTM-estimated basal area, and FIA plot information LTM area-weighted vol/ac scaled up/down to match FIA area-weighted vol/ac Yields an unbiased volume per acre estimate for each scene processed

24. rcl7820@owl.forestry.uga.edu Lowe, 04 Scale Distributed Info Back to FIA Totals Polygons currently contain LTM-estimated basal area, and FIA plot information LTM area-weighted vol/ac scaled up/down to match FIA area-weighted vol/ac Differences in sum totals due to differences in land area

25. rcl7820@owl.forestry.uga.edu Lowe, 04 Now, What Have We Got? ~ 1.5 million polygons populated with FIA data

26. rcl7820@owl.forestry.uga.edu Lowe, 04 Now, What Have We Got? ~ 1.5 million polygons populated with FIA data Riparian zone and urban buffer information included

27. rcl7820@owl.forestry.uga.edu Lowe, 04 Now, What Have We Got? ~ 1.5 million polygons populated with FIA data Riparian zone and urban buffer information included Enough information to run spatially explicit fiber supply simulations

28. rcl7820@owl.forestry.uga.edu Lowe, 04 Thanks