Forest Inventory in New Brunswick: A Year with LiDAR. Adam Dick New Brunswick Department of Natural Resources NEMO/SOMENS November 2014
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1 Forest Inventory in New Brunswick: A Year with LiDAR Adam Dick New Brunswick Department of Natural Resources NEMO/SOMENS November 2014
2 New Brunswick 750,000 people 7.3 million hectares 83% forested 9.5 million m 3 of wood harvested in 2012 Forest industry - 30% of total manufacturing output 5.1% of provincial GDP (2012) Most forestry dependent province in Canada 2
3 Area (Ha.) x Forest inventory Regenerating Young Immature Mature Overmature Forest Development Stage 3
4 4 35-year old softwood plantation
5 5 35-year old plantation
6 6
7 7
8 LiDAR inventory - Pilot The Forestry Chronicle 2011, 87 (04):
9 LiDAR metrics Metric Description MEAN Mean height (m) STD_DEV Standard Deviation ABS_DEV Absolute Standard Deviation SKEW Skewness KURTOSIS Kurtosis MIN Minimum height (m) P01 First percentile LiDAR Height (m) P05 Fifth percentile LiDAR Height (m) P25 Twenty-fifth percentile LiDAR Height (m) P75 Seventy-fifth percentile LiDAR Height (m) P95 Ninety-fifth percentile LiDAR Height (m) P99 Ninety-ninth percentile LiDAR Height (m) P10 First Decile LiDAR Height (m) P20 Second Decile LiDAR Height (m) P80 Eighth Decile LiDAR Height (m) P90 Ninth Decile LiDAR Height (m) MAX Maximum height (m) D1 Cumulative percentage of the number of returns found in Bin 1 of 10 D2 Cumulative percentage of the number of returns found in Bin 2 of 10 D8 Cumulative percentage of the number of returns found in Bin 8 of 10 D9 Cumulative percentage of the number of returns found in Bin 9 of 10 DA First returns/ All Returns DV First Vegetation Returns/All Returns DB First and only return / All Returns VDR Vertical Distribution Ratio = [Max Median]/Max Canopy_relief_ratio (Mean - Min) / (Max Min) Using All Returns Covar Std Dev (all Returns)/ mean ((All Returns) CanCovar Std Dev (First Returns Only)/ mean ((First Returns Only) [represents the canopy layer] FIRST Number of First Returns ALLRETURNS Number of all Returns FIRSTVEG Number of First Vegetation Returns only ALLGROUND Number of Ground Returns cc2 Crown closure 2 m Cc4 Crown closure 4 m cc24 Crown closure 24 m cc26 Crown closure 26 m STRAT1 Percentage of Total Return Count Below 0m STRAT2 Percentage of Total Return Count Between 0m and 2m STRAT14 Percentage of Total Return Count Between 24m and 26m STRAT15 Percentage of Total Return Count Above 26m 9
10 Forest inventory attributes Basal area Softwood basal area 10
11 Metrics Maximum Tolerance Level Inventory Metric 95% confidence) Average merchantable tree height (m) 1 meter Average tree height (merchantable and non-merchantable) (m) 1 meter Base of Live Crown 1 meter Total basal area (m 2 /ha) 5m 2 /ha Merchantable basal area (m 2 /ha) 5 m 2 /ha Merchantable quadratic mean diameter (QMD) (cm) 4 cm Total quadratic mean diameter (QMD) (cm) 4 cm Merchantable tree density (stems/ha) 100 stems/ha Total gross total volume (m 3 /ha) 15 m 3 /ha 11
12 Company Profile 12
13 Ground sampling 2km grid established LiDAR extracted at each point, metrics derived PCA used to identify subset of points that will cover range of conditions Considers conditions already sampled in other areas Results in efficient sampling 13
14 Plot design Plot centre located using survey grade GPS units 400m 2 fixed area circular plot Trees 3.1cm sampled Regen (<3cm) sampled in 3m radius sub-plot 3m BAF angle gauge used to select trees for height measurements 14
15 Model development/calibration Height Run 1 Run 2 Run 3 Run 4 Run 5 Run 6 Run 7 Run 8 Run 9 Run 10 P95 P95 cc12 P95 P95 cc12 cc12 cc12 P95 P95 cc12 cc12 P95 cc12 cc18 P95 P99 P95 cc12 STRAT8 STRAT7 P80 cc18 P99 cc12 P99 cc18 STRAT7 P99 cc12 P80 STRAT7 P99 cc18 P99 P80 P95 P99 P80 cc18 P99 P99 STRAT7 P80 STRAT8 STDDEV P90 P80 cc18 P99 STRAT8 cc18 STRAT4 STRAT7 STRAT7 STRAT7 P80 STRAT8 STRAT4 STRAT7 STRAT4 STRAT4 STRAT6 STRAT4 P80 cc18 STRAT8 STRAT4 STRAT6 P80 DA STRAT8 STDDEV DA STRAT4 STRAT8 STRAT4 cc18 AAD STRAT4 P90 STDDEV P90 STRAT8 STDDEV DA DA P90 P90 STDDEV cc16 DA STRAT5 STRAT6 STRAT5 STRAT4 STRAT7 STRAT6 DA P90 STDDEV P90 STRAT8 P90 DA STRAT6 STRAT5 DA STDDEV STRAT5 cc18 STRAT5 P80 STRAT5 P90 P90 STDDEV STRAT5 cc16 STRAT6 cc14 AAD cc16 STDDEV AAD cc14 DB STDDEV cc14 cc14 STRAT5 STRAT6 cc14 cc14 cc14 AAD P75 cc6 cc4 DB DB DB DA DB STRAT6 cc16 cc16 DB DB AAD STRAT6 cc16 AAD cc16 P75 STRAT5 cc14 AAD P70 DA cc4 cc14 P75 cc4 cc10 DB STRAT6 cc16 cc6 cc16 AAD P75 DB AAD cc16 cc6 AAD cc14 STRAT5 P75 P75 cc6 cc6 P75 cc6 cc4 cc10 P75 CANCOVA R CANCOV AR P70 cc10 cc10 P70 cc2 cc10 cc6 cc4 cc8 cc6 15
16 Model development/calibration Volume Run 1 Run 2 Run 3 Run 4 Run 5 Run 6 Run 7 Run 8 Run 9 Run 10 STRAT3 STRAT3 SKEW STRAT3 SKEW STRAT3 CANCOVAR STRAT7 SKEW STRAT7 SKEW SKEW STRAT5 SKEW STRAT3 SKEW SKEW SKEW cc4 STRAT3 STRAT5 CANCOVAR STRAT7 STRAT5 STRAT7 cc4 STRAT3 CANCOVAR STRAT3 SKEW CANCOVA R STRAT7 STRAT7 STRAT3 STRAT2 CANCOVAR CANCOVAR cc4 STRAT3 STRAT7 CANCOVAR STRAT5 P50 cc4 STRAT5 STRAT7 P50 cc4 CANCOVAR P30 cc4 P50 VDR cc2 P50 STRAT5 STRAT7 STRAT2 P50 STRAT5 P50 P50 CANCOVAR STRAT7 STRAT2 P80 STRAT5 STRAT5 STRAT5 cc4 VDR P25 STRAT2 P50 cc4 P50 P05 Can_rel_rat P60 P10 Can_rel_rat cc8 cc2 VDR VDR P25 DA P50 Can_rel_rat P50 STRAT2 COVAR P60 P60 COVAR VDR VDR VDR VDR P05 P10 P99 cc4 CANCOVAR cc2 P60 Can_rel_rat P99 cc14 P60 cc14 cc4 P25 P25 Can_rel_rat STRAT2 STRAT2 P10 P10 cc14 cc6 cc2 cc8 P80 P10 cc8 P70 P30 P25 STRAT2 P60 cc20 Can_rel_rat cc8 cc6 STRAT4 P75 P25 P80 cc8 P05 cc6 P90 P30 cc8 COVAR cc6 cc20 cc6 cc6 COVAR P10 P30 P10 DB P30 cc2 DB cc8 DA P25 Can_rel_rat P75 cc6 P99 cc6 P80 STRAT12 DB DB cc8 cc14 P70 COVAR P70 cc14 P20 P60 DA P99 P30 P05 cc6 cc20 KURT Can_rel_rat P60 cc8 STRAT12 cc20 P70 P30 COVAR STDDEV P95 STRAT12 STRAT12 P20 P70 cc2 16
17 17 bs plantation 35 years old
18 18 bs plantation 35 years old
19 bs plantation 35 years old Metric Points Mean Std. Dev CV Error % Error BA 1, % BAmerch 1, % BLC 1, % GTV 1, % HtAve 1, % Htmerch 1, % QMD 1, % QMDmerch 1, % TPHmerch 1,218 1, % Metric Points Mean Std. Dev CV Error % Error BA % BAmerch % BLC % GTV % HtAve % Htmerch % QMD % QMDmerch % TPHmerch %
20 20 Stand splitting
21 Stand splitting Metric Points Mean Std. Dev CV Error % Error BA 1, % BAmerch 1, % BLC 1, % GTV 1, % HtAve 1, % Htmerch 1, % QMD 1, % QMDmerch 1, % TPHmerch 1,218 1, % Metric Points Mean Std. Dev CV Error % Error BA % BAmerch % BLC % GTV % HtAve % Htmerch % QMD % QMDmerch % TPHmerch 336 1, % Metric Points Mean Std. Dev CV Error % Error BA % BAmerch % BLC % GTV % HtAve % Htmerch % QMD % QMDmerch % TPHmerch 882 1, %
22 22 Operational queries
23 23 Operational queries
24 Additional metrics Maximum Tolerance Level Inventory Metric 95% confidence) Average merchantable tree height (m) 1 meter Average tree height (merchantable and non-merchantable) (m) 1 meter Base of Live Crown 1 meter Total basal area (m 2 /ha) 5m 2 /ha Merchantable basal area (m 2 /ha) 5 m 2 /ha Merchantable quadratic mean diameter (QMD) (cm) 4 cm Total quadratic mean diameter (QMD) (cm) 4 cm Merchantable tree density (stems/ha) 100 stems/ha Total gross total volume (m 3 /ha) 15 m 3 /ha NMV = f(tov, BA merch, BA total, QMD, Height) 24
25 Additional metrics
26 26 Net merchantable volume
27 Sawlog volume RMSE=13.7m3/ha 27
28 Sawlog volume incl. Stand type RMSE=11.6m3/ha 28
29 Density by DBH class Density 0-9cm RMSE=76.2 Density 10-16cm RMSE=
30 Density by DBH class Density 20-30cm RMSE= 36.0 Density 30-40cm RMSE=
31 The plan New Brunswick inventory follows a 10-year cycle Currently acquiring block 2/10 LiDAR has fundamentally changed forest inventory in NB Applications are still being discovered Investment will pay off, possibility to accelerate acquisition 31
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