Dan Couch Olympia, WA DNR January, 2016. Outline Rogue Valley LiDAR Background Stand Metrics Comparison Results:  LiDAR vs Timber Cruise BLM Forest Inventory.

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Presentation transcript:

Dan Couch Olympia, WA DNR January, 2016

Outline Rogue Valley LiDAR Background Stand Metrics Comparison Results:  LiDAR vs Timber Cruise BLM Forest Inventory Implications

Rogue Valley LiDAR Ref: OLC Rogue River – LiDAR Remote Sensing Data Final Report Flown in 2012

LiDAR BLM Sample Plot Development Ref: Rogue Valley BLM Stratified LIDAR Sample Plot Methodology

Steps to Derive Stand Metrics LiDAR Bins  75 foot pixels Correlation Plot Tree Data Harvest Unit Polygons  Basis of comparison

Principle Components Analysis 80 th Percentile Height  80% of LiDAR height returns below this point above 10’  Six fixed height classes (~30 ft)  Highly accurate height predictions Total Cover %  Three equal width density classes  Low, Moderate, High LiDAR

18 Bins (Strata) 6 Height Classes 3 Density Classes Low Med High

Correlation Plot Tree Data ~13 Plots per Bin (strata)  ~42 foot radius 240 Plots, measured 2013 Trees counted & measured Trees less than 6.5” DBH not sampled Ref: Rogue Valley LIDAR Inventory Plot Establishment – Inventory Report

LiDAR Derived Stand Metrics Raster 75 foot pixel (8 th ac) data coverage by metric  Height (BA-weighted)  Basal area (BA)  Density (TPA)  Avg diameter at breast height (QMD)  Volume (ft 3 per acre)  Canopy cover (%) Ref: Rogue Valley LIDAR-assisted Inventory Final Report to BLM

Regression Model Predictions Description Forest variable (live trees >=6.5” DBH) LiDAR Raster Labels live hardwood & softwood (hs) trees >= 6.5” DBH (6in) R2R2 BA-weighted heightLLOR (ft) LLOR_hs_6in 0.91 Basal areaLBA (sqft/ac) LBA_hs_6in 0.70 DensityLDEN (TPA) LDEN_hs_6in 0.63 Quadratic mean diameterLQMD (in) LQMD_hs_6in 0.72 VolumeLVOL (cuft/ac) LVOL_hs_6in 0.79 Canopy CoverPC_1 st (% > 6.6’) PC_1st N/A Height related predictors best fit Stem density (TPA) worst fit

LiDAR Stand Metrics Compared to Timber Cruise

Comparing LiDAR & Timber Cruise White Castle 9 Units – Timber Cruised 2012  High degree of accuracy – BA, TPA, QMD, Vol  Count included retention trees  Good comparison of stand metrics  Spatial unit GPS’d to high accuracy  Canopy cover NOT compared

Comparing LiDAR & Timber Cruise In GIS, LiDAR pixelated metrics interesected and averaged for each White Castle unit  BA, TPA, QMD, Vol summarized by unit.  LiDAR Ft 3 volume converted to MBF by factor of 6.

LiDAR vs Timber Cruise Results Quadratic Mean Diameter (DBH) Unit #AcresCruise/Retain QMDLidar QMDQMD Difference% Diff % % 3 & % % % 7** % % % Avg %

LiDAR vs Timber Cruise Results Basal Area Unit #AcresCruise/Retain BA/AcLidar BA/AcBA Difference% Diff % % 3 & % % % 7** % % % Avg 2613%

LiDAR vs Timber Cruise Results Volume (MBF/Ac) Unit #Acres Cruise/Retain Short Log Vol/Ac (MBF) Lidar Converted* Vol/Ac (MBF) MBF Vol/Ac Difference % Diff % % 3 & % % % 7** % % % Avg %

LiDAR vs Timber Cruise Results Trees Per Acre Unit #AcresCruise/Retain TPA/AcLidar TPA/AcTPA Difference% Diff % % 3 & % % % 7** % % % Avg 82%

BLM Forest Inventory Implications

BLM Micro*Storms Application Western Oregon BLM’s corporate forest data repository and application for: Forest Vegetation (FOI-VEG) Forest Surveys Forest Treatments BURN REVEG - PLANT HARVEST

FOI-VEG vs Treatments/Surveys FOI-VEG Describes BLM Forest Vegetation Entire Western Oregon Coverage Polygon Overlap Not Allowed Treatments/Surveys Overlap

FOI-VEG – Forest Vegetation Data Structure

FOI-VEG Published Version ID, Geographic Ref, Acres (Unit # - Twnshp, Rg, Section) Forest Stand Description (Spp, size class, density, birth yr)  Need stand exams for spp mix Forest Stand Metrics (Stand level regardless of spp)  Independent from stand description  Can use LiDAR for stand by stand metrics Attributes For Each Forest Stand

FOI-VEG Published Version ID ReferenceLayers AttributesStand Attributes OI_KEYCLASSIFIERGIS ACRESSTAND_DESC AGECLS BYR AGECLS 10 LYR_SRCLYR_SRC_DTCANOPYCOVTPA7QMD7BA7MBF_ACSTAND_SRCSTAND_SRC_DT Person Importing LiDAR Stand Metrics 32.6FCO D3H3-= Stand Exam-EcoSurvey8/25/ LiDAR12/31/ FCO D4-1780/D3H3= Stand Exam-EcoSurvey8/24/ LiDAR12/31/ FCO D4-1890/D3H2= Stand Exam-EcoSurvey9/1/ LiDAR12/31/ FCO D4-1780/D3D2-= Stand Exam-EcoSurvey9/2/ LiDAR12/31/ FCO D4-1780/D3D2-= Stand Exam-EcoSurvey8/25/ LiDAR12/31/ FCO D4-1780/D3D2-= Stand Exam-EcoSurvey8/25/ LiDAR12/31/ FCO D4-1780/D3D2-= Stand Exam-EcoSurvey8/18/ LiDAR12/31/ FCO D4H3-=1910/H2=1973/H Stand Exam-EcoSurvey8/9/ LiDAR12/31/2013 Resulting changes from importing LiDAR stand metrics.

QUESTIONS?