Characterization of Brazilian forest types utilizing canopy height profiles derived from airborne laser scanning

2016 ◽  
Vol 19 (3) ◽  
pp. 518-527 ◽  
Author(s):  
Eric B. Görgens ◽  
Carlos P.B. Soares ◽  
Matheus H. Nunes ◽  
Luiz C. E. Rodriguez
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Canopy Height ◽  
Forest Types ◽  
Airborne Laser

scholarly journals Deriving Stand Structural Complexity from Airborne Laser Scanning Data—What Does It Tell Us about a Forest?

2020 ◽  
Vol 12 (11) ◽  
pp. 1854
Author(s):  
Dominik Seidel ◽  
Peter Annighöfer ◽  
Martin Ehbrecht ◽  
Paul Magdon ◽  
Stephan Wöllauer ◽  
...  
Keyword(s):  
Forest Structure ◽  
Laser Scanning ◽  
Structural Complexity ◽  
Basal Area ◽  
Airborne Laser Scanning ◽  
Stand Age ◽  
Box Dimension ◽  
Forest Types ◽  
3D Point Clouds ◽  
Airborne Laser

The three-dimensional forest structure is an important driver of several ecosystem functions and services. Recent advancements in laser scanning technologies have set the path to measuring structural complexity directly from 3D point clouds. Here, we show that the box-dimension (Db) from fractal analysis, a measure of structural complexity, can be obtained from airborne laser scanning data. Based on 66 plots across different forest types in Germany, each 1 ha in size, we tested the performance of the Db by evaluating it against conventional ground-based measures of forest structure and commonly used stand characteristics. We found that the Db was related (0.34 < R < 0.51) to stand age, management intensity, microclimatic stability, and several measures characterizing the overall stand structural complexity. For the basal area, we could not find a significant relationship, indicating that structural complexity is not tied to the basal area of a forest. We also showed that Db derived from airborne data holds the potential to distinguish forest types, management types, and the developmental phases of forests. We conclude that the box-dimension is a promising measure to describe the structural complexity of forests in an ecologically meaningful way.

Characterization of land degradation along the receding Dead Sea coastal zone using airborne laser scanning

Geomorphology ◽  
2014 ◽  
Vol 206 ◽  
pp. 403-420 ◽  
Author(s):  
Sagi Filin ◽  
Yoav Avni ◽  
Amit Baruch ◽  
Smadar Morik ◽  
Reuma Arav ◽  
...  
Keyword(s):  
Coastal Zone ◽  
Land Degradation ◽  
Laser Scanning ◽  
Dead Sea ◽  
Airborne Laser Scanning ◽  
Airborne Laser

scholarly journals Airborne laser scanning of natural forests in New Zealand reveals the influences of wind on forest carbon

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
David A. Coomes ◽  
Daniel Šafka ◽  
James Shepherd ◽  
Michele Dalponte ◽  
Robert Holdaway
Keyword(s):  
New Zealand ◽  
Power Law ◽  
Laser Scanning ◽  
Forest Carbon ◽  
Airborne Laser Scanning ◽  
Canopy Height ◽  
Carbon Density ◽  
Airborne Laser ◽  
Aboveground Carbon Density ◽  
Estimation Models

Abstract Background Forests are a key component of the global carbon cycle, and research is needed into the effects of human-driven and natural processes on their carbon pools. Airborne laser scanning (ALS) produces detailed 3D maps of forest canopy structure from which aboveground carbon density can be estimated. Working with a ALS dataset collected over the 8049-km2 Wellington Region of New Zealand we create maps of indigenous forest carbon and evaluate the influence of wind by examining how carbon storage varies with aspect. Storms flowing from the west are a common cause of disturbance in this region, and we hypothesised that west-facing forests exposed to these winds would be shorter than those in sheltered east-facing sites. Methods The aboveground carbon density of 31 forest inventory plots located within the ALS survey region were used to develop estimation models relating carbon density to ALS information. Power-law models using rasters of top-of-the-canopy height were compared with models using tree-level information extracted from the ALS dataset. A forest carbon map with spatial resolution of 25 m was generated from ALS maps of forest height and the estimation models. The map was used to evaluate the influences of wind on forests. Results Power-law models were slightly less accurate than tree-centric models (RMSE 35% vs 32%) but were selected for map generation for computational efficiency. The carbon map comprised 4.5 million natural forest pixels within which canopy height had been measured by ALS, providing an unprecedented dataset with which to examine drivers of carbon density. Forests facing in the direction of westerly storms stored less carbon, as hypothesised. They had much greater above-ground carbon density for a given height than any of 14 tropical forests previously analysed by the same approach, and had exceptionally high basal areas for their height. We speculate that strong winds have kept forests short without impeding basal area growth. Conclusion Simple estimation models based on top-of-the canopy height are almost as accurate as state-of-the-art tree-centric approaches, which require more computing power. High-resolution carbon maps produced by ALS provide powerful datasets for evaluating the environmental drivers of forest structure, such as wind.

scholarly journals Assessing biomass based on canopy height profiles using airborne laser scanning data in eucalypt plantations

2015 ◽  
Vol 72 (6) ◽  
pp. 504-512 ◽  
Author(s):  
André Gracioso Peres Silva ◽  
Eric Bastos Görgens ◽  
Otávio Camargo Campoe ◽  
Clayton Alcarde Alvares ◽  
José Luiz Stape ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Canopy Height ◽  
Airborne Laser ◽  
Eucalypt Plantations

scholarly journals Towards Automated Characterization of Canopy Layering in Mixed Temperate Forests Using Airborne Laser Scanning

Forests ◽  
2015 ◽  
Vol 6 (12) ◽  
pp. 4146-4167 ◽  
Author(s):  
Reik Leiterer ◽  
Hossein Torabzadeh ◽  
Reinhard Furrer ◽  
Michael Schaepman ◽  
Felix Morsdorf
Keyword(s):  
Laser Scanning ◽  
Temperate Forests ◽  
Airborne Laser Scanning ◽  
Airborne Laser

scholarly journals Using discrete-return airborne laser scanning to quantify number of canopy strata across diverse forest types

2015 ◽  
Vol 7 (6) ◽  
pp. 700-712 ◽  
Author(s):  
Phil Wilkes ◽  
Simon D. Jones ◽  
Lola Suarez ◽  
Andrew Haywood ◽  
Andrew Mellor ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Forest Types ◽  
Airborne Laser

Evaluating the impact of leaf-on and leaf-off airborne laser scanning data on the estimation of forest inventory attributes with the area-based approach

2015 ◽  
Vol 45 (11) ◽  
pp. 1498-1513 ◽  
Author(s):  
Joanne C. White ◽  
John T.T.R. Arnett ◽  
Michael A. Wulder ◽  
Piotr Tompalski ◽  
Nicholas C. Coops
Keyword(s):  
Laser Scanning ◽  
Forest Type ◽  
Airborne Laser Scanning ◽  
Forest Types ◽  
Quadratic Mean ◽  
Generic Models ◽  
Airborne Laser ◽  
Mean Diameter ◽  
Forest Attributes ◽  
Quadratic Mean Diameter

In this study, we explored the consequences of using leaf-on and leaf-off airborne laser scanning (ALS) data on area-based model outcomes in a lodgepole pine (Pinus contorta var. latifolia Engelm.) dominated forest in the foothills of the Rocky Mountains in Alberta, Canada. We considered eight forest attributes: top height, mean height, Lorey’s mean height, basal area, quadratic mean diameter, merchantable volume, total volume, and total aboveground biomass. We used 787 ground plots for model development, stratified by ALS acquisition conditions (leaf-on or leaf-off) and dominant forest type (coniferous or deciduous). We also generated pooled models that combined leaf-on and leaf-off ALS data and generic models that combined plot data for all forest types. We evaluated differences in ALS metrics and leaf-on and leaf-off model outcomes, as well as the impacts of pooling leaf-on and leaf-off ALS data, creating generic models, and of applying leaf-on models to leaf-off data (and vice versa). In general, leaf-off and leaf-on ALS metrics were not significantly different (p < 0.05), except for the 5th percentile of height (coniferous) and canopy density metrics (deciduous). Overall, coniferous leaf-on and leaf-off models were comparable, with differences in relative root mean square error (RMSE) and bias of <2% for all attributes except volume, which differed by <4%. RMSE and bias for deciduous leaf-on and leaf-off models for height attributes and quadratic mean diameter differed by <2%, whereas models for volume and biomass differed by <7%. These results affirm that leaf-off data can be used in an area-based approach to estimate forest attributes for both coniferous and deciduous forest types. Relative RMSE and bias for pooled models (combining leaf-on and leaf-off ALS data) differed by <2% relative to leaf-on and leaf-off models, suggesting that in the forests studied herein, combining leaf-on and leaf-off data in an area-based approach does not adversely impact model outcomes. Generic models that did not account for forest type had large errors for volume and biomass (e.g., the relative RMSE for merchantable volume was twice as large as forest type specific models). Likewise, the mixing of leaf-on models with leaf-off data and vice versa resulted in large RMSE and bias for both forest types, and therefore mixing of models and data types should be avoided.

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