Use of airborne laser scanning (LIDAR) as a tool for ...USDA Forest Service PNW Research Station RMA Vegetation Monitoring and Remote Sensing Team Not all LIDAR data are the same Things

RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station

Use of airborne laser scanning (LIDAR) as a tool Use of airborne laser scanning (LIDAR) as a tool for forest measurement and monitoring: for forest measurement and monitoring:

use and potentialuse and potential

Steve ReutebuchSteve Reutebuch HansHans--Erik Andersen Erik Andersen BobBob McGaugheyMcGaughey

Resource Monitoring & Assessment ProgramResource Monitoring & Assessment ProgramVegetation Monitoring & Remote Sensing TeamVegetation Monitoring & Remote Sensing Team

USDA Forest ServiceUSDA Forest ServicePNW Research StationPNW Research Station


LIDARLIDAR——what is it?what is it?

Light detection and ranging (LIDAR)Light detection and ranging (LIDAR)Uses laser light to measure distanceUses laser light to measure distance

Different detection approachesDifferent detection approachesTime of flightTime of flightPhase differencePhase difference

Hundreds of applicationsHundreds of applications

In natural resources, 3 LIDAR types are In natural resources, 3 LIDAR types are widely availablewidely available


WidelyWidely available LIDARavailable LIDAR

Terrestrial laser scanning Terrestrial laser scanning (TLS)(TLS)

Primarily used in engineeringPrimarily used in engineering

Some use in forestry research Some use in forestry research scanning plots or individual scanning plots or individual trees and logs trees and logs


WidelyWidely available LIDARavailable LIDAR

NASANASA IceSATIceSAT satellite LIDARsatellite LIDARGlobalGlobal-- and continentaland continental--scalescaleforest canopy height and forest canopy height and biomass estimatesbiomass estimates

70 m diameter footprint70 m diameter footprint175 meters spacing175 meters spacing

Difficult to remove topographic Difficult to remove topographic effects on canopy heightseffects on canopy heightsOperational 2003Operational 2003--20092009IceSATIceSAT--2 launch 2016 ???2 launch 2016 ???


Widely available LIDARWidely available LIDAR

Airborne laser scanning Airborne laser scanning (ALS)(ALS)

Routinely flown commercially Routinely flown commercially over large areasover large areasLarge vendor poolLarge vendor poolMature mission specs & Mature mission specs & deliverablesdeliverablesMature software to process dataMature software to process dataMany state and federal partnersMany state and federal partners


Example LIDAR Point CloudExample LIDAR Point Cloud

2009 Savannah River DOE Site LIDAR Project


ALS LIDAR data usesALS LIDAR data uses

Topographic mapping of bare earth Topographic mapping of bare earth surfacesurface——primary useprimary use

EngineeringEngineeringFlood risk mappingFlood risk mappingHydrologic modelingHydrologic modelingGeologic mappingGeologic mappingLandslide mappingLandslide mapping

Infrastructure mappingInfrastructure mapping——still developingstill developingVegetation measurement and mappingVegetation measurement and mapping——still developing, with operational usesstill developing, with operational uses


2010 State LIDAR efforts2010 State LIDAR efforts

8 states have statewide LIDAR programs8 states have statewide LIDAR programsNorth Carolina, Louisiana, New Jersey, Maryland, North Carolina, Louisiana, New Jersey, Maryland, Delaware, Pennsylvania, Ohio, IowaDelaware, Pennsylvania, Ohio, Iowa

8 states have program initiatives8 states have program initiativesFlorida, Texas, New York, Oregon, Washington, Florida, Texas, New York, Oregon, Washington, Minnesota, South Carolina, MississippiMinnesota, South Carolina, Mississippi

Many more projects areas have been flownMany more projects areas have been flown~25% of the conterminous US already has LIDAR ~25% of the conterminous US already has LIDAR collectedcollectedUnknown amount of private forest coverageUnknown amount of private forest coverage


2010 Oregon LIDAR Consortium 2010 Oregon LIDAR Consortium


2010 Puget Sound LIDAR 2010 Puget Sound LIDAR ConsortiumConsortium


Not all LIDAR data are the sameNot all LIDAR data are the same

Things that affect LIDAR data for forest Things that affect LIDAR data for forest measurements:measurements:

Mission specs (pulse rate, scan pattern, flying Mission specs (pulse rate, scan pattern, flying height, airspeed, pulse diameter, etc.)height, airspeed, pulse diameter, etc.)

Time of year (leafTime of year (leaf--off, leafoff, leaf--on, snow free, etc.)on, snow free, etc.)

LIDAR sensor and data processingLIDAR sensor and data processing

Experience of LIDAR vendorExperience of LIDAR vendor


LIDAR used in forest LIDAR used in forest measurementmeasurement


Remote sensing

Field plots

Wall-to-wall low-resolution coverage w/ LANDSAT TM, SPOT, etc.

Subsampling with high res. LIDAR, aerial photos

Measurements of trees, shrubs, moss, soils, down wood.

Example: MultiExample: Multi--level sampling to support forest level sampling to support forest inventory in remote northern regionsinventory in remote northern regions

Subsampling with high res. satellite imagery


PNWPNW--RMA (Anchorage) is carrying out a project to test a RMA (Anchorage) is carrying out a project to test a multimulti--level approach for biomass estimation in the level approach for biomass estimation in the TokTok

(1,911 sq km) (1,911 sq km)

MultiMulti--level approach level approach will use:will use:

Satellite imagery Satellite imagery ((LandsatLandsat, SPOT, , SPOT, PALSAR,PALSAR, QuickbirdQuickbird))27 High27 High--density LIDAR density LIDAR strip samplesstrip samplesField plot data (80 plots)Field plot data (80 plots)



WhenWhen ““wallwall--toto--wallwall”” LIDAR coverageLIDAR coverage isisavailable 2 types of measurements can be available 2 types of measurements can be made:made:

1.1. Forest layers computed solely from the LIDARForest layers computed solely from the LIDAR

2.2. Inventory layers predicted from regression models Inventory layers predicted from regression models or imputation methods using LIDAR or imputation methods using LIDAR andand wellwellmeasured ground plotsmeasured ground plots


11–– Layers computed solely from the Layers computed solely from the LIDAR point cloudLIDAR point cloud——obvious onesobvious ones

Canopy surface modelCanopy surface modelBare earth modelBare earth model


33--ft bare earth modelft bare earth model33--ft canopy surface modelft canopy surface model1:12,000 aerial photo1:12,000 aerial photo


Layers computed solely from the Layers computed solely from the LIDAR point cloudLIDAR point cloud——obvious onesobvious ones

Bare earth modelBare earth model

Canopy surface modelCanopy surface model

Canopy height modelCanopy height model(Canopy surface minus ground surface)(Canopy surface minus ground surface)


33--ft resolution canopy height modelft resolution canopy height model

BuildingsBuildings





Canopy height modelCanopy height model

Canopy cover modelCanopy cover model


% Canopy Cover (0.1 acre pixels) % Canopy Cover (0.1 acre pixels)





Canopy height modelCanopy height model

Canopy cover modelCanopy cover model

Intensity image from 1Intensity image from 1stst returnsreturns


1.51.5--ft resolution intensity imageft resolution intensity image


Layers computed solely from the Layers computed solely from the LIDAR point cloudLIDAR point cloud——not so obviousnot so obvious

Variance, standard deviation, Variance, standard deviation, skewnessskewness,,kurtosis, etc. of the canopykurtosis, etc. of the canopy

Mean, min, max, percentile heights of the Mean, min, max, percentile heights of the canopycanopy

Density of the canopyDensity of the canopy

Forest / nonForest / non--forest maskforest mask


Standard Deviation of Canopy HeightStandard Deviation of Canopy Height



WhenWhen ““wallwall--toto--wallwall”” coverage is available 2 coverage is available 2 types of measurements can be made:types of measurements can be made:

1.1. Forest layers computed solely from the LIDARForest layers computed solely from the LIDAR

2.2. Inventory layers predicted from regression models Inventory layers predicted from regression models or imputation methods using LIDAR or imputation methods using LIDAR andand wellwellmeasured ground plotsmeasured ground plots


WARNINGS !!!WARNINGS !!!

CanCan’’t get species information from the t get species information from the LIDAR dataLIDAR data

In some cases, can get:In some cases, can get:DeciduousDeciduous vsvs nonnon--deciduousdeciduousLive crowns Live crowns vsvs dead crownsdead crowns

CanCan’’t get understory, down wood, etc.t get understory, down wood, etc.

Not all LIDAR is the same:Not all LIDAR is the same:Changes in LIDAR sensors, sensor settings, Changes in LIDAR sensors, sensor settings, and flight parameters can change resultsand flight parameters can change results


MORE WARNINGS !!!!!MORE WARNINGS !!!!!

Most difficult part of a LIDAR project is:Most difficult part of a LIDAR project is:Getting good ground plot data:Getting good ground plot data:

1.1. Matched with regards to geographic position Matched with regards to geographic position to an accuracy ~ equal to the LIDAR to an accuracy ~ equal to the LIDAR horizontal accuracy (~+/horizontal accuracy (~+/-- 1m)1m)

2.2. Matched with regard to the primary element Matched with regard to the primary element being measuredbeing measured——large enough to minimize large enough to minimize plot edge effect, but small enough to plot edge effect, but small enough to characterize tree size differences within plots characterize tree size differences within plots (~0.1(~0.1 –– 0.2 ac circular plot)0.2 ac circular plot)


MORE WARNINGS !!!!! (cont.)MORE WARNINGS !!!!! (cont.)

Most difficult part of a LIDAR project is:Most difficult part of a LIDAR project is:Getting good ground plot data:Getting good ground plot data:

3.3. Matched in time of measurementMatched in time of measurement----generallygenerallywithin 1within 1--2 yrs of LIDAR acquisition2 yrs of LIDAR acquisition

4.4. Matched in whatMatched in what’’s measured by the LIDAR s measured by the LIDAR and on the plotand on the plot——all stems that make up a all stems that make up a significant portion of the above ground significant portion of the above ground canopycanopy——generally down to a 7generally down to a 7--10 cm DBH 10 cm DBH lower limit, including all specieslower limit, including all species


Examples of layers predicted Examples of layers predicted from regression modelsfrom regression models

Sherman Pass Scenic Byway Sherman Pass Scenic Byway Colville National ForestColville National Forest100,000 acres flown in 2008100,000 acres flown in 2008

74 1/10th acre plots used to develop 74 1/10th acre plots used to develop LIDAR inventory regressions measured in LIDAR inventory regressions measured in 20082008


Sherman Pass LIDAR ProjectSherman Pass LIDAR Project

Forest cover minimum: 10ft ht & Forest cover minimum: 10ft ht & 2% cover in 66ft pixel2% cover in 66ft pixel

Ground PlotsGround Plots


Regression modelsRegression modelsLoreyLorey’’ss BABA--weighted Height ftweighted Height ft

[LHT_ft] = 21.4980 + [ElevP90] * 0.7242


Regression modelsRegression modelsLoreyLorey’’ss BABA--weighted Height ftweighted Height ft


Regression modelsRegression modelsLive Basal Area Live Basal Area sqftsqft/ac/ac

[LBA_sqftac] = sqr ( -5.0579 + [ElevSD] * -0.4280 + [ElevP95] * 0.2307 + [PC1stRtsCC] * 0.1039) + 2.809


Regression modelsRegression modelsLive Basal Area Live Basal Area sqftsqft/ac/ac


Red areas have LIDAR predictor values Red areas have LIDAR predictor values >+/>+/--10% beyond the range of the ground plots10% beyond the range of the ground plots

Greater than +/- 10% beyond ground plot LIDAR Metrics


ExampleExample ArcGISArcGIS CalculationsCalculations

Any of the LIDAR layers can be used in GIS to Any of the LIDAR layers can be used in GIS to calculate combinations of forest structure calculate combinations of forest structure variablesvariables


Live Basal Area > 200 Live Basal Area > 200 sqftsqft/ac/ac


Canopy Cover 80%+ and Height 100ft+Canopy Cover 80%+ and Height 100ft+


Current limitations on using Current limitations on using existing LIDAR dataexisting LIDAR data

No coordination within natural resource No coordination within natural resource organizations at any level for:organizations at any level for:

1.1. LIDAR specifications necessary for forest LIDAR specifications necessary for forest measurementsmeasurements

2.2. Ground plot measurements when large, Ground plot measurements when large, multimulti--agency LIDAR acquisitions occuragency LIDAR acquisitions occurMissed opportunity to leverage existing LIDARMissed opportunity to leverage existing LIDAR


Possible problems with use of Possible problems with use of FIA plots for LIDAR projectsFIA plots for LIDAR projects

Plots not Plots not georeferencedgeoreferenced well enoughwell enough

Not enough plots measured in area within Not enough plots measured in area within 11--2 years of LIDAR acquisition2 years of LIDAR acquisition

Plot layout not well designed for use with Plot layout not well designed for use with highhigh--resolution remote sensing dataresolution remote sensing data


Future for LIDAR in forest Future for LIDAR in forest measurement?measurement?

Faster, cheaper, better LIDAR data, but Faster, cheaper, better LIDAR data, but doesndoesn’’t solve ground plot problemst solve ground plot problems

MultiMulti--temporal LIDAR datasets for change temporal LIDAR datasets for change analysisanalysis

Multispectral LIDAR for species classificationMultispectral LIDAR for species classification

New satelliteNew satellite--based systems for samplingbased systems for sampling

Beyond LIDARBeyond LIDAR——other 3D sensors (other 3D sensors (IFSAR,etcIFSAR,etc.).)


LIDAR software DEMO ThursLIDAR software DEMO Thurs

2009 Savannah River DOE Site LIDAR Project

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Use of airborne laser scanning (LIDAR) as a tool for ...USDA Forest Service PNW Research Station RMA Vegetation Monitoring and Remote Sensing Team Not all LIDAR data are the same Things