EXPLOITING FULLWAVEFORM LIDAR SIGNALS TO ESTIMATE TIMBER VOLUME AND ABOVE-GROUND BIOMASS OF...

Exploiting fullwaveform lidar signals to estimatetimber volume and above-ground biomass of

individual trees

Tristan Allouis1, Sylvie Durrieu1 Cédric Véga2Pierre Couteron3

1Cemagref/AgroParisTech, UMR TETIS, Montpellier, France

2French Institute of Pondicherry, Pondicherry, India

3Institut de Recherche pour le Développement, UMR AMAP, Montpellier, France

2011 IEEE IGARSS, Vancouver, Canada

1/18 Tristan Allouis, S. Durrieu, C. Véga, P. Couteron Estimation of individual tree biomass using lidar signals

Introduction: Context

Why assessing forest biomass?

Estimating forest productivity and carbon sequestration rateDefining strategies for sustainable forest management andclimate change mitigation

How?

Through allometric equations using field-measured truncdiameter at breast height (DBH) → Cost and assess issuesThrough remote sensing techniques → Do not give access tothe DBH


Introduction: Background

Lidar technique overview

Light detection and ranging

1 Emission/reception of laser pulses2 Signal processing3 Signal and echoes geo-positioning

Advantages:High resolution products(several pt/m2)Ground echoes under the canopy


Introduction: Background

State of the art3D information derived from lidar data:

Height, basal area, volume (director indirect methods)Topography under cover

Scope:Timber inventory and managementHabitat monitoringEcosystem modelling


Introduction: Aim of the study

Questions

Can other tree metrics replaceDBH in allometric equations?Can full-waveform signals improvevolume/biomass estimates?What is the accuracy of suchestimates at tree level?


Material: Study site

Study area

Located in the French Alps(mountainous)Planted with Black Pine

Field data

6 circular plots of 15 mradius (61 trees)Tree DBH, total height,crown base height


Material: Study site

Reference VolumeEquation by the French Institute for Agricultural Research forBlack Pine within France (C=trunc circonference; H=total height):

Volume = 34111.14+ 0.020833846 · H · C2 − 1486.2307 · C +2.2695012·C ·H+15.664201·C2−56.250923·H−0.0061317691·H2

Reference BiomassEquation by Gil et al. (2011) for Black Pine within Spain:

Biomass = 0.6073 · DBH2 − 5.0998 · DBH − 23.729

Gil, Blanco, Carballo, Calvo, 2011. Carbon stock estimates for forests in theCastilla y León region, Spain. A GIS based method for evaluating spatial distributionof residual biomass for bio-energy, Biomass and Bioenergy, vol. 35, pp. 243-252


Material: Lidar data

Characteristics

Small-footprint size (' 25 cm)Density = 5 shots/m2

⇒ Sample rate of 98% per surface unit

2 types of lidar data

Canopy Height Model (CHM):classical lidar data derived fromdiscrete returnsFull-Waveform lidar signals


Method: Deriving metrics from the CHM

CHM metricsSegmentation of individual trees(Véga and Durrieu, 2011) andextraction of:

Total tree height (HtCHM)Crown projected area (AcrownCHM)Tree bounding volume(BVCHM = AcrownCHM · HtCHM)

Véga, Durrieu, 2011. Multi-level filtering segmentation to measure individual treeparameters based on Lidar data: application to a mountainous forest withheterogeneous stands, International Journal of Applied Earth Observations andGeoinformation 13, 646–656.


Method: Deriving metrics from full-waveform lidar signals

Method

Aggregation of signals falling insidemodeled tree crowns ⇒ Oneaggregrated signal corresponds toone individual treeVegetation profile calculation(correction of signal attenuation,more details in Allouis et al. 2010)

Allouis, Durrieu, Cuesta, Chazette, Flamant, Couteron, 2010. Assessment of treeand crown heights of a maritime pine forest at plot level using a fullwaveformultraviolet lidar prototype, International Geoscience and Remote Sensing Symposium(IGARSS), pp. 1382-1385



FW metrics

Curve integral (ISIG , IPROF ,I2SIG , I2PROF )Ratio beween I and groundcomponent integral(RSIG , RPROF )Maximum signal amplitudeexcept ground (MaxSIG)Crown base height(HcrownPROF )Height of maximum profileamplitude except ground(HmaxPROF )

Range Range

Power Density

Aggregated waveform Vegetation profile



FW metrics

Curve integral (ISIG , IPROF ,I2SIG , I2PROF )Ratio beween I and groundcomponent integral(RSIG , RPROF )Maximum signal amplitudeexcept ground (MaxSIG)Crown base height(HcrownPROF )Height of maximum profileamplitude except ground(HmaxPROF )

Range Range

Power Density

Aggregated waveform Vegetation profile

HcrownPROF

HmaxPROFMaxSIG


Method: Building estimation models

ProcessBuilding volume and biomass estimation models:

1 Selection of significant metrics (stepwise algorithm)2 Construction of final models (10 subsamples for

calibration/validation)3 Comparision of model performance (for CHM-only, CHM+FW

and benchmark models)


Results: Replacing DBH in allometric equations

→ Strong relationshipbetween DBH and crownprojected area.

Perspectives⇒ Using crown area intraditional DBH models⇒ Building new modelswith other metrics

West, Enquist, Brown, 2009. A general quantitative theory of forest structure anddynamics, Proceedings of the National Academy of Sciences of the United States ofAmerica, vol. 106, pp. 7040-7045


Results: Estimation models

Metrics selected in linear models

BenchmarkVolume and biomass: BVtrunkREF , DBHREF , HtREF

CHM-onlyVolume: BVcrownCHM , HtCHM , AcrownCHMBiomass: BVcrownCHM , HtCHM

CHM+FWVolume: BVcrownCHM , AcrownCHM , I2SIG , HtCHMBiomass: I2SIG , BVcrownCHM , AcrownCHM , HtCHM , RPROF

Volume BiomassAdjR2 Error AdjR2 Error

Benchmark 1 1 % 1 8 %CHM-only 0.93 15 % 0.87 30 %CHM+FW 0.95 17 % 0.91 25 %


Results: Estimation models

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Conclusion

Crown area is a good predictor of DBHTree bounding volume (height x crown area) is one of themost efficient lidar metric for volume and biomass estimationSlight improvement using FW lidar metrics in biomassestimation models but no improvement in volume estimationsApproach limited to monospecific and single-storey forestsFuture work: evaluating FW metrics worth at plot level


Thank you for your attention


Exploiting fullwaveform lidar signals to estimatetimber volume and above-ground biomass of

individual trees

Tristan Allouis1, Sylvie Durrieu1 Cédric Véga2Pierre Couteron3

1Cemagref/AgroParisTech, UMR TETIS, Montpellier, France

2French Institute of Pondicherry, Pondicherry, India

3Institut de Recherche pour le Développement, UMR AMAP, Montpellier, France

2011 IEEE IGARSS, Vancouver, Canada


EXPLOITING FULLWAVEFORM LIDAR SIGNALS TO ESTIMATE TIMBER VOLUME AND ABOVE-GROUND BIOMASS OF...

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