scholarly journals Airborne laser scanning proxies of canopy light transmission in forests

2021 ◽  
Author(s):  
Adam Erickson ◽  
Nicholas Coops
Keyword(s):  
Laser Scanning ◽  
Light Transmission ◽  
Canopy Cover ◽  
Field Measurements ◽  
Airborne Laser Scanning ◽  
Validation Data ◽  
Cloud Models ◽  
Airborne Laser ◽  
Gap Fraction ◽  
And Function

Reliable estimates of canopy light transmission are critical to understanding the structure and function of vegetation communities but are difficult and costly to attain by traditional field inventory methods. Airborne laser scanning (ALS) data uniquely provide multi-angular vertically resolved representation of canopy geometry across large geographic areas. While previous studies have proposed ALS indices of canopy light transmission, new algorithms based on theoretical advancements may improve existing models. Herein, we propose two new models of canopy light transmission (i.e., gap fraction, or Po, the inverse of angular canopy closure). We demonstrate the models against a suite of existing models and ancillary metrics, validated against convex spherical densiometer measurements for 950 field plots in the foothills of Alberta, Canada. We also tested the effects of synthetic hemispherical lens models on the performance of the proposed hemispherical Voronoi gap fraction (Phv) index. While vertical canopy cover metrics showed the best overall fit to field measurements, one new metric, point-density-normalized gap fraction (Ppdn), outperformed all other gap fraction metrics by two-fold. We provide suggestions for further algorithm enhancements based on validation data improvements. We argue that traditional field measurements are no longer appropriate for ‘ground-truthing’ modern LiDAR or SfM point cloud models, as the latter provide orders of magnitude greater sampling and coverage. We discuss the implications of this finding for LiDAR applications in forestry.

scholarly journals Regional Modeling of Forest Fuels and Structural Attributes Using Airborne Laser Scanning Data in Oregon

2021 ◽  
Vol 13 (2) ◽  
pp. 261
Author(s):  
Francisco Mauro ◽  
Andrew T. Hudak ◽  
Patrick A. Fekety ◽  
Bryce Frank ◽  
Hailemariam Temesgen ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Field Measurements ◽  
Point Clouds ◽  
Semiparametric Models ◽  
Airborne Laser Scanning ◽  
Parametric Models ◽  
Fuel Load ◽  
Forest Fuels ◽  
Airborne Laser

Airborne laser scanning (ALS) acquisitions provide piecemeal coverage across the western US, as collections are organized by local managers of individual project areas. In this study, we analyze different factors that can contribute to developing a regional strategy to use information from completed ALS data acquisitions and develop maps of multiple forest attributes in new ALS project areas in a rapid manner. This study is located in Oregon, USA, and analyzes six forest structural attributes for differences between: (1) synthetic (i.e., not-calibrated), and calibrated predictions, (2) parametric linear and semiparametric models, and (3) models developed with predictors computed for point clouds enclosed in the areas where field measurements were taken, i.e., “point-cloud predictors”, and models developed using predictors extracted from pre-rasterized layers, i.e., “rasterized predictors”. Forest structural attributes under consideration are aboveground biomass, downed woody biomass, canopy bulk density, canopy height, canopy base height, and canopy fuel load. Results from our study indicate that semiparametric models perform better than parametric models if no calibration is performed. However, the effect of the calibration is substantial in reducing the bias of parametric models but minimal for the semiparametric models and, once calibrations are performed, differences between parametric and semiparametric models become negligible for all responses. In addition, minimal differences between models using point-cloud predictors and models using rasterized predictors were found. We conclude that the approach that applies semiparametric models and rasterized predictors, which represents the easiest workflow and leads to the most rapid results, is justified with little loss in accuracy or precision even if no calibration is performed.

Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction

2006 ◽  
Vol 104 (1) ◽  
pp. 50-61 ◽  
Author(s):  
Felix Morsdorf ◽  
Benjamin Kötz ◽  
Erich Meier ◽  
K.I. Itten ◽  
Britta Allgöwer
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Fractional Cover ◽  
Airborne Laser ◽  
Gap Fraction ◽  
Small Footprint

scholarly journals ALGORITHM FOR THE AUTOMATIC ESTIMATION OF AGRICULTURAL TREE GEOMETRIC PARAMETERS USING AIRBORNE LASER SCANNING DATA

2016 ◽  
Vol XLI-B8 ◽  
pp. 629-632 ◽  
Author(s):  
E. Hadaś ◽  
A. Borkowski ◽  
J. Estornell
Keyword(s):  
Laser Scanning ◽  
Tree Height ◽  
Field Measurements ◽  
Point Clouds ◽  
Average Density ◽  
Geometric Parameters ◽  
Airborne Laser Scanning ◽  
Maximum Height ◽  
Airborne Laser ◽  
Crown Base Height

The estimation of dendrometric parameters has become an important issue for the agricultural planning and management. Since the classical field measurements are time consuming and inefficient, Airborne Laser Scanning (ALS) data can be used for this purpose. Point clouds acquired for orchard areas allow to determine orchard structures and geometric parameters of individual trees. In this research we propose an automatic method that allows to determine geometric parameters of individual olive trees using ALS data. The method is based on the α-shape algorithm applied for normalized point clouds. The algorithm returns polygons representing crown shapes. For points located inside each polygon, we select the maximum height and the minimum height and then we estimate the tree height and the crown base height. We use the first two components of the Principal Component Analysis (PCA) as the estimators for crown diameters. The α-shape algorithm requires to define the radius parameter <i>R</i>. In this study we investigated how sensitive are the results to the radius size, by comparing the results obtained with various settings of the R with reference values of estimated parameters from field measurements. Our study area was the olive orchard located in the Castellon Province, Spain. We used a set of ALS data with an average density of 4 points&thinsp;m<sip>&minus;2</sup>. We noticed, that there was a narrow range of the <i>R</i> parameter, from 0.48&thinsp;m to 0.80&thinsp;m, for which all trees were detected and for which we obtained a high correlation coefficient (>&thinsp;0.9) between estimated and measured values. We compared our estimates with field measurements. The RMSE of differences was 0.8&thinsp;m for the tree height, 0.5&thinsp;m for the crown base height, 0.6&thinsp;m and 0.4&thinsp;m for the longest and shorter crown diameter, respectively. The accuracy obtained with the method is thus sufficient for agricultural applications.

scholarly journals Estimating aboveground carbon density and its uncertainty in Borneo’s structurally complex tropical forests using airborne laser scanning

2018 ◽  
Author(s):  
Tommaso Jucker ◽  
Gregory P. Asner ◽  
Michele Dalponte ◽  
Philip Brodrick ◽  
Christopher D. Philipson ◽  
...  
Keyword(s):  
Tropical Forests ◽  
Laser Scanning ◽  
Canopy Cover ◽  
Carbon Stocks ◽  
Forest Carbon ◽  
Airborne Laser Scanning ◽  
Tropical Asia ◽  
Airborne Laser ◽  
Dipterocarp Forests ◽  
The Tropics

Abstract. Borneo contains some of the world’s most biodiverse and carbon dense tropical forest, but this 750 000-km2 island has lost 62 % of its old-growth forests within the last 40 years. Efforts to protect and restore the remaining forests of Borneo hinge on recognising the ecosystem services they provide, including their ability to store and sequester carbon. Airborne Laser Scanning (ALS) is a remote sensing technology that allows forest structural properties to be captured in great detail across vast geographic areas. In recent years ALS has been integrated into state-wide assessment of forest carbon in Neotropical and African regions, but not yet in Asia. For this to happen, new regional models, need to be developed for estimating carbon stocks from ALS in tropical Asia, as the forests of this region are structurally and compositionally distinct from those found elsewhere in the tropics. By combining ALS imagery with data from 173 permanent forest plots spanning the lowland rain forests of Sabah, on the island of Borneo, we develop a simple-yet-general model for estimating forest carbon stocks using ALS-derived canopy height and canopy cover as input metrics. An advanced feature of this new model is the propagation of uncertainty in both ALS- and ground-based data, allowing uncertainty in hectare-scale estimates of carbon stocks to be quantified robustly. We show that the model effectively captures variation in aboveground carbons stocks across extreme disturbance gradients spanning tall dipterocarp forests and heavily logged regions, and clearly outperforms existing ALS-based models calibrated for the tropics, as well as currently available satellite-derived products. Our model provides a simple, generalised and effective approach for mapping forest carbon stocks in Borneo, and underpins ongoing efforts to safeguard and facilitate the restoration of its unique tropical forests.

scholarly journals Single strata canopy cover estimation using airborne laser scanning data

2013 ◽  
Author(s):  
Antonio Ferraz ◽  
Clement Mallet ◽  
Gil Goncalves ◽  
Margarida Tome ◽  
Paula Soares ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Canopy Cover ◽  
Airborne Laser Scanning ◽  
Airborne Laser

scholarly journals Puittaimestiku kaardistamine aerolidari andmete põhjal metsana lisanduvatel aladel/ Estimation of fractional forest cover from airborne laser scanning data in abandoned agricultural land

2013 ◽  
Vol 59 (1) ◽  
pp. 45-58
Author(s):  
Marta Mõistus ◽  
Mait Lang ◽  
Allan Sims
Keyword(s):  
Laser Scanning ◽  
Agricultural Land ◽  
Canopy Cover ◽  
Airborne Laser Scanning ◽  
Tree Canopy ◽  
Maximum Height ◽  
Plant Canopy ◽  
Actual Problem ◽  
Airborne Laser ◽  
The Impact

Abstract The abandonment of agricultural land is an actual problem in Estonia due to significant impact on landscape ecology and structure. Abandoned agricultural fields are usually converting into forest. Mapping of agricultural land use is a strategic interest of each country. Airborne laser scanning (ALS) is used in many countries for topographical mapping and the laser pulse return positions are promising datasets for mapping the abandonment of agricultural land. We used ALS data based woody plant canopy cover estimates made at certain reference height unachievable for field crops to map abandoned agricultural land in nine test sites in Tartumaa, Estonia. The maximum height of trees in test sites ranged from 6.5 m to 13.4 m. The lidar pulse returns based canopy cover estimate was assessed 1) by using ortophoto based digitized maps of tree canopy, 2) repeated measurements made with plant canopy analyzer LAI-2000 and 3) by using allometric crown radius models and repeated tree measurements from sample plots. The interpretation of canopy boundaries and separation of small spaces between tree crowns from ortophotos is a challenging task for an operator. The relationship between ALS based canopy cover and ortophoto based canopy cover was linear in all test sites except when ALS data from beginning of June were used. It the beginning of June foliage is not fully developed on trees. An increase in the woody canopy cover was detected from repeated LAI-2000 measurements and also from repeated tree measurements-based simulated crowns. The impact of reference height change from 2.0 m to 1.3 m on canopy cover estimations was not significant and much smaller compared to the tree growth induced increase in canopy cover, indicating that similar errors originating from e.g. digital elevation model are not problematic for the proposed method in practical applications.

Refining and evaluating a Horvitz– Thompson-like stand density estimator in individual tree detection based on airborne laser scanning

2021 ◽  
Author(s):  
Kasper Kansanen ◽  
Petteri Packalen ◽  
Timo Lähivaara ◽  
Aku Seppänen ◽  
Jari Vauhkonen ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Stand Density ◽  
Airborne Laser Scanning ◽  
Tuning Parameter ◽  
Density Estimator ◽  
Validation Data ◽  
Data Set ◽  
Individual Tree ◽  
Tree Detection ◽  
Airborne Laser

Horvitz--Thompson-like stand density estimation is a method for estimating the stand density from tree crown objects extracted from airborne laser scanning data through individual tree detection. The estimator is based on stochastic geometry and mathematical morphology of the (planar) set formed by the detected tree crowns. This set is used to approximate the detection probabilities of trees. These probabilities are then used to calculate the estimate. The method includes a tuning parameter, which needs to be known to apply the method. We present a refinement of the method to allow more general detection conditions than the previous papers and present and discuss the methods for estimating the tuning parameter of the estimator using a functional $k$-nearest neighbors method. We test the model fitting and prediction in two spatially separate data sets and examine the plot-level accuracy of estimation. The estimator produced a $13$\% lower RMSE than the benchmark method in an external validation data set. We also analyze the effects of similarity and dissimilarity of training and validation data to the results.

scholarly journals Quantification of Lichen Cover and Biomass Using Field Data, Airborne Laser Scanning and High Spatial Resolution Optical Data—A Case Study from a Canadian Boreal Pine Forest

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 682
Author(s):  
Ashley C. Hillman ◽  
Scott E. Nielsen
Keyword(s):  
High Resolution ◽  
Spectral Data ◽  
Laser Scanning ◽  
Canopy Cover ◽  
Jack Pine ◽  
Pine Forest ◽  
Airborne Laser Scanning ◽  
Woodland Caribou ◽  
Airborne Laser ◽  
Pine Stands

Ground-dwelling macrolichens dominate the forest floor of mature upland pine stands in the boreal forest. Understanding patterns of lichen abundance, as well as environmental characteristics associated with lichen growth, is key to managing lichens as a forage resource for threatened woodland caribou (Rangifer tarandus caribou). The spectral signature of light-coloured lichen distinguishes it from green vegetation, potentially allowing for mapping of lichen abundance using multi-spectral imagery, while canopy structure measured from airborne laser scanning (ALS) of forest openings can indirectly map lichen habitat. Here, we test the use of high-resolution KOMPSAT (Korea Multi-Purpose Satellite-3) imagery (280 cm resolution) and forest structural characteristics derived from ALS to predict lichen biomass in an upland jack pine forest in Northeastern Alberta, Canada. We quantified in the field lichen abundance (cover and biomass) in mature jack pine stands across low, moderate, and high canopy cover. We then used generalized linear models to relate lichen abundance to spectral data from KOMPSAT and structural metrics from ALS. Model selection suggested that lichen abundance was best predicted by canopy cover (ALS points > 1.37 m) and to a lesser extent blue spectral data from KOMPSAT. Lichen biomass was low at plots with high canopy cover (98.96 g/m2), while almost doubling for plots with low canopy cover (186.30 g/m2). Overall the model fit predicting lichen biomass was good (R2 c = 0.35), with maps predicting lichen biomass from spectral and structural data illustrating strong spatial variations. High-resolution mapping of ground lichen can provide information on lichen abundance that can be of value for management of forage resources for woodland caribou. We suggest that this approach could be used to map lichen biomass for other regions.

Predicting and calibrating tree attributes by means of airborne laser scanning and field measurements

2012 ◽  
Vol 42 (11) ◽  
pp. 1896-1907 ◽  
Author(s):  
Matti Maltamo ◽  
Lauri Mehtätalo ◽  
Jari Vauhkonen ◽  
Petteri Packalén
Keyword(s):  
Laser Scanning ◽  
Practical Importance ◽  
Field Measurements ◽  
Airborne Laser Scanning ◽  
Tree Level ◽  
Best Linear Unbiased Predictor ◽  
Individual Tree ◽  
Airborne Laser ◽  
Dead Branch ◽  
Best Linear Unbiased

This paper examines the calibration of airborne laser scanning based tree attribute models to separate data by applying a best linear unbiased predictor. Firstly, single Scots pine ( Pinus sylvestris L.) trees were identified from dense airborne laser scanning data. Secondly, seemingly unrelated mixed-effects models for diameter at breast height, tree height, volume, dead branch height, and crown base height were constructed using airborne laser scanning based height metrics as predictors at both the area and individual tree level. Finally, these models were calibrated to validation stands using field measurements of some of the five abovementioned tree attributes. The models were calibrated by applying the best linear unbiased predictor to predict the random stand effects for the validation stand. In a system of several models, the correlation of random effects enabled the prediction of stand effects for all models, providing the response of at least one of the models was known for one or more sample trees of the validation stand. The results showed that the accuracy of tree attribute prediction improved in most cases as the number of sample trees increased. The level of improvement was highest for volume and dead branch height. The practical importance of the results of this study lies in applications where forest stands are visited in the field, for example, before making cutting decisions.

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