remote sensing assessment of tree size inequalitycgat.webs.upv.es/forestructure/documents/... ·...

Remote sensing assessment of

tree size inequalityRubén Valbuena

Marie S. Curie Research Fellow

Department of Plant Sciences. Forest Ecology and Conservation

In the long term

(2010-2014): “Pan-European Indicators of Forest Structural Complexity from Airborne Laser

Scanning” at European Forest Institute (EFI).

Grant awarded by Foundation for European Forest Research (FEFR).

(2014-2016): Doctoral thesis + PostDoc at University of Eastern Finland (Joensuu).

Most relevant related publications:

Forest Ecology Management 276 (2012): 185–195

Canadian Journal of Forest Research 43 (2013-11): 1063–74

Ecological Indicators 60 (2016) 574–585

Remote Sensing of Environment (2016) in press

(2016-2018): “LorenzLiDAR: Classification of Forest Structural Types with LiDAR Remote

Sensing Applied to Study Tree Size-Density Scaling Theories” at University of Cambridge (UK).

Marie Skłodowska-Curie Actions (MSCA) Individual Fellowship (IF).

Outline

• What is tree size inequality?

• Tree size inequality as an important element of forest structure

• Potential applications

• How tree size inequality is measured and evaluated in the forest?

• Tree diameter distributions

• Indicators of tree size inequality

• How tree size inequality can be assessed using remote sensing?

• Inductive: statistical relationships for production of estimation maps

• Deductive: supporting theories in relation to tree size inequality


Forest Structure & Tree Size Inequality

• Structure

• Abundance (a.k.a. stand parameters: density, basal area, mean

quadratic diameter, dominant height, above-ground biomass)

• Spatially explicit indicators (neighbourhood) – horizontal structure

• Non-spatial indicators – size differentiation

Indicators of structural diversity / tree size inequality

• Composition (species richness and abundances)

• Function (nutrient cycling, species interactions; e.g. competition)

Elements of Forest Complexity (McElhinny et al. 2005):

?Structural

Diversity

Tree size

inequality

Forest Structural Diversity or Tree Size Inequality

Applications of RS Indicators of Tree Size Inequality

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• Monitoring forest conservation status

• Provision of ecosystem services

• Habitat suitability for fauna / flora

• Incorporation conservation objectives in

forest management

• Supporting increasingly complex

management systems

• Fire spread

?


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Forest Structure Indicators from LIDAR

The forest is surveyed with a device called LIDAR: a laser scanner mounted onboard a plane.

Developing the use of Lorenz curve to describe tree dominance and diameter distributions.

Indicators: The Gini coefficent of tree size inequality + asymmetry.

Developing methods for assessing these indicators and classifying forest areas into structural types.


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Gini Coefficient: Conservation vs. Commercial Forests

Valbuena R., Eerikäinen K., Packalen P. & Maltamo M. (2016) Gini Coefficient

Predictions from Airborne Lidar Remote Sensing Display the Effect of

Management Intensity on Forest Structure. Ecological Indicators 60: 574-585


31/10/2016 31/10/2016

Forest

disturbance

Self-thinning

Seed

regenerationSenescence

of mature

trees

Even-sized

Reverse JBimodal

Even-sized Even-sized

Reverse J

Ingrowth

Forest

development

Valbuena R., Packalen P., García-Abril A., Mehtätalo L. & Maltamo M. (2013) Characterizing

Forest Structural Types and Shelterwood Dynamics from Lorenz-based Indicators Predicted

by Airborne Laser Scanning. Canadian Journal of Forest Research 43: 1063-1074.


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From Indicators to Forest Structural Types

Outline











Forest Indicators of Tree Size Inequality

Forest simulation.


Theoretical distribution functions.

Weibul distribution


Concise Indicators

Forest Structure & Tree Size Inequality

• Richness: number of different size classes

• Equitability: relative abundances (evenness)

• Diversity (entropy): Shannon, etc. Size class diversityDiameter class diversity / evenness

Foliage height diversity (McArthur & McArthur, 1961)

• Homogeneity (size variation): Tree size inequality• Dispersion (spread): Diameter standard deviation

• Concentration: Diameter coefficient of variation / Gini coefficient

• Dominance or rarity: Asymmetry / Skewness?

Forest structural diversity / Tree size inequality

Forest Structural Diversity

Proof: Testing Intrinsic Diversity Ordering

Some attention on the definition of Diversity.

What means to be more/less diverse? An initial

situation in the structure of a forest plot (F1) can

develop into an intrinsically more diverse state

(F2) by a finite sequence of either of these events

(Patil & Taillie 1982):

(a) introducing new size classes

(b) transferring abundances between two

classes to make them more identical

(c) permuting the components of its

abundance vector (should remain equal)

Intrinsic Diversity Ordering

Intrinsic Diversity Ordering Curve

Ranked Abundance Vector:

Arranging the components of p in descending order

k is the rank of each size class (1st most dominant size

class, 2nd, … )

Curve of Cumulated Dominance

Majorization method (Solomon 1979):

Solomon (1979) A comparative approach to species

diversity. In: Grassle, Patil, Smith, & Taillie (Eds.), Ecological

Diversity in Theory and Practice. International Cooperative

Publishing House, Fairland, Maryland, USA, pp. 29–35.

Intrinsic Diversity Ordering

Diversity = Richness + Equitability (relative abundance)

Intrinsic Equitability Ordering Curve

Ranked Abundance Vector:

Curve of Cumulated Dominance

Majorization method (Solomon 1979):

Cumulative Richness Proportions

Intrinsic Equitability

(Lorenz Ordering)

Evenness among Size Classes...

...or Inequality among Individual Tree Sizes?

Valbuena R., Packalén P., Martín-Fernández S.

& Maltamo M. (2012) Diversity and Equitability

Ordering Profiles Applied to the Study of Forest

Structure. Forest Ecology and Management

276: 185-195

.

?Structural

Diversity

Tree size

inequality

Forest Structural Diversity or Tree Size Inequality

The Lorenz curve of Tree Size Inequality


31/10/2016 31/10/2016

Forest

disturbance

Self-thinning

Seed


of mature

trees

Even-sized

Reverse JBimodal


Reverse J

Ingrowth

Forest

development





31/10/2016

31/10/2016

Forest

disturbance

Self-thinning

Seed


of mature

trees

Even-sized

Reverse JBimodal


Reverse J

Ingrowth

Forest

development





03/11/2016

03/11/2016

Forest

disturbance

Self-thinning

Seed


of mature

trees

Even-sized

Reverse JBimodal


Reverse J

Ingrowth

Forest

development




Forest structure & Tree Size Inequality

31/10/2016

Tree Size Inequality(Gini Coefficient)

+Tree Size Dominance (Lorenz Asymmetry,

Basal Area larger than mean)




Outline










Remote Sensing Assessment of Tree Size Inequality

RS Assessment of Tree Size Inequality

• Individual Tree Detection Methods

Valbuena R., Vauhkonen J., Packalen P., Pitkänen J. & Maltamo M. (2014) Comparison

of Airborne Laser Scanning Methods for Estimating Forest Structure Indicators Based

on Lorenz Curves. ISPRS Journal of Photogrammetry & Remote Sensing 95: 23-33

.

• Semi – ITD (Beidenbach et al. (2010)

Remote Sensing of

Environment 114: 911-924)


Area-based approach

XPredictors

(ALS metrics)


Area-based

approach

• Regression Trees


• Random Forest

GC < 0.28

• Nearest neighbour methods

• Many types of distance metrics (Hudak et al. 2008

Remote Sensing of Environment 112: 2232):

• Euclidean (k-NN)

• Mahalanobis

• Canonical Correlation Projectors

(Most Similar Neighbour)

• Gradient nearest neighbour

• Random Forest proximity matrix

• Can be used for multivariate responses too.

• Tree list estimation (Packalen & Maltamo 2008

Canadian Journal of Forest Research 38: 1750)



• Modelling Quantitative variables • Classification of

Qualitative variables


Valbuena R., Maltamo M. & Packalen P. (2016) Classification

of multi-layered forest development stages from low-density

national airborne datasets. Forestry 89: 392-401.

Valbuena R., Packalen P., García-Abril A., Mehtätalo L. & Maltamo

M. (2013) Characterizing Forest Structural Types and Shelterwood

Dynamics from Lorenz-based Indicators Predicted by Airborne Laser

Scanning. Canadian Journal of Forest Research 43: 1063-1074.


Valbuena R., Maltamo M. & Packalen P. (2016) Classification of multi-layered forest

development stages from low-density national airborne datasets. Forestry 89: 392-401.

+ A comparison of machine learning methods. Revista de Teledetección 45: 15-25.


• Deductive Approaches:

• Conceptual models

• Asner, G.P., & Mascaro J. (2014). Mapping tropical forest carbon: Calibrating plot

estimates to a simple LiDAR metric. Remote Sensing of Environment 140, 614-624

• Bouvier, M., Durrieu, S., Fournier, R.A., & Renaud, J.P. (2015). Generalizing

predictive models of forest inventory attributes using an area-based approach with

airborne LiDAR data. Remote Sensing of Environment, 156, 322-334


• Deductive Approaches:

• Conceptual models

• Asner, G.P., & Mascaro J. (2014).

• Bouvier, et al. (2015).


Valbuena R., Maltamo M. Mehtätalo L., & Packalen P. (2016) Key Structural

Features of Boreal Forests may be Detected Directly using L-moments from

Airborne Lidar Data. Remote Sensing of Environment (in press)


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Using ALS predictors onlyForest Indicators





31/10/2016

Lidar datasets from National Land Survey Agencies are being surveyed and made largely available (under INSPIRE directive): Finland (NLS)

United Kingdom (ARSF)

Spain (PNOA)

Denmark (Kortforsyningen)

… and also others like Germany, France, Italy, Norway, Austria, etc.

Challenges to obtaining a trans-national monitoring tool: Research on the relevance of technical and survey configurations of Lidar

systems, and how changes affect the indicators.

Differences between surveys: point density, season of acquisition, and instruments used.

Effects of site characteristics. Water / light limitations to growth.

The Opportunity: National Laser Survey Programmes

Netherlands (AHN2)

Poland (ISOK)

Switzerland (DOM)

Sweden (Lantmateriet)

Thank you

Rubén Valbuena

Marie S. Curie Research Fellow

Department of Plant Sciences. Forest Ecology and Conservation

remote sensing assessment of tree size inequalitycgat.webs.upv.es/forestructure/documents/... ·...

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