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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW 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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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 ???
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
Example LIDAR Point CloudExample LIDAR Point Cloud
2009 Savannah River DOE Site LIDAR Project
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
2010 Oregon LIDAR Consortium 2010 Oregon LIDAR Consortium
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
2010 Puget Sound LIDAR 2010 Puget Sound LIDAR ConsortiumConsortium
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
LIDAR used in forest LIDAR used in forest measurementmeasurement
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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)
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
LIDAR used in forest LIDAR used in forest measurementmeasurement
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
33--ft bare earth modelft bare earth model33--ft canopy surface modelft canopy surface model1:12,000 aerial photo1:12,000 aerial photo
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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)
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
33--ft resolution canopy height modelft resolution canopy height model
BuildingsBuildings
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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 cover modelCanopy cover model
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
% Canopy Cover (0.1 acre pixels) % Canopy Cover (0.1 acre pixels)
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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 cover modelCanopy cover model
Intensity image from 1Intensity image from 1stst returnsreturns
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
1.51.5--ft resolution intensity imageft resolution intensity image
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
Standard Deviation of Canopy HeightStandard Deviation of Canopy Height
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
LIDAR used in forest LIDAR used in forest measurementmeasurement
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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)
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
Regression modelsRegression modelsLoreyLorey’’ss BABA--weighted Height ftweighted Height ft
[LHT_ft] = 21.4980 + [ElevP90] * 0.7242
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
Regression modelsRegression modelsLoreyLorey’’ss BABA--weighted Height ftweighted Height ft
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
Regression modelsRegression modelsLive Basal Area Live Basal Area sqftsqft/ac/ac
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
Live Basal Area > 200 Live Basal Area > 200 sqftsqft/ac/ac
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
Canopy Cover 80%+ and Height 100ft+Canopy Cover 80%+ and Height 100ft+
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
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.).)
RMA Vegetation Monitoring and Remote Sensing TeamRMA Vegetation Monitoring and Remote Sensing TeamUSDA Forest Service PNW Research Station USDA Forest Service PNW Research Station
LIDAR software DEMO ThursLIDAR software DEMO Thurs
2009 Savannah River DOE Site LIDAR Project