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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
• How tree size inequality can be assessed using remote sensing?
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
• How tree size inequality can be assessed using remote sensing?
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
31/10/2016
• 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
?
Applications of RS Indicators of Tree Size Inequality
31/10/2016
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.
Applications of RS Indicators of Tree Size Inequality
31/10/2016
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
Applications of RS Indicators of Tree Size Inequality
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.
Applications of RS Indicators of Tree Size Inequality
31/10/2016
From Indicators to Forest Structural Types
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
• How tree size inequality can be assessed using remote sensing?
Forest Indicators of Tree Size Inequality
Forest simulation.
Forest Indicators of Tree Size Inequality
Theoretical distribution functions.
Weibul distribution
Forest Indicators of Tree Size Inequality
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
The Lorenz curve of Tree Size Inequality
The Lorenz curve of Tree Size Inequality
Applications of RS Indicators of Tree Size Inequality
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.
Applications of RS Indicators of Tree Size Inequality
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.
Applications of RS Indicators of Tree Size Inequality
03/11/2016
03/11/2016
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.
Forest structure & Tree Size Inequality
31/10/2016
Tree Size Inequality(Gini Coefficient)
+Tree Size Dominance (Lorenz Asymmetry,
Basal Area larger than mean)
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.
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
Remote Sensing Assessment of Tree Size Inequality
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)
Remote Sensing Assessment of Tree Size Inequality
Area-based approach
XPredictors
(ALS metrics)
Remote Sensing Assessment of Tree Size Inequality
Area-based
approach
Remote Sensing Assessment of Tree Size Inequality
Remote Sensing Assessment of Tree Size Inequality
Remote Sensing Assessment of Tree Size Inequality
• Regression Trees
Remote Sensing Assessment of Tree Size Inequality
• 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)
Remote Sensing Assessment of Tree Size Inequality
Remote Sensing Assessment of Tree Size Inequality
Remote Sensing Assessment of Tree Size Inequality
• Modelling Quantitative variables • Classification of
Qualitative variables
Remote Sensing Assessment of Tree Size Inequality
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.
Remote Sensing Assessment of Tree Size Inequality
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.
Remote Sensing Assessment of Tree Size Inequality
• 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
Remote Sensing Assessment of Tree Size Inequality
• Deductive Approaches:
• Conceptual models
• Asner, G.P., & Mascaro J. (2014).
• Bouvier, et al. (2015).
Remote Sensing Assessment of Tree Size Inequality
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)
Remote Sensing Assessment of Tree Size Inequality
31/10/2016
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)
Remote Sensing Assessment of Tree Size Inequality
31/10/2016
Using ALS predictors onlyForest Indicators
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)
Applications of RS Indicators of Tree Size Inequality
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