Estimating the Height and Basal Area at Individual Tree and Plot Levels in Canadian Subarctic Lichen Woodlands Using Stereo WorldView-3 Images

Lichen woodlands (LW) are sparse forests that cover extensive areas in remote subarctic regions where warming due to climate change is fastest. They are difficult to study in situ or with airborne remote sensing due to their remoteness. We have tested a method for measuring individual tree heights and predicting basal area at tree and plot levels using WorldView-3 stereo images. Manual stereo measurements of tree heights were performed on short trees (2–12 m) of a LW region of Canada with a residual standard error of ≈0.9 m compared to accurate field or UAV height data. The number of detected trees significantly underestimated field counts, especially in peatlands in which the visual contrast between trees and ground cover was low. The heights measured from the WorldView-3 images were used to predict the basal area at individual tree level and summed up at plot level. In the best conditions (high contrast between trees and ground cover), the relationship to field basal area had a R2 of 0.79. Accurate estimates of above ground biomass should therefore also be possible. This method could be used to calibrate an extensive remote sensing approach without in-situ measurements, e.g., by linking precise structural data to ICESAT-2 footprints.

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High-Resolution Multisensor Remote Sensing to Support Date Palm Farm Management

Agriculture ◽

10.3390/agriculture9020026 ◽

2019 ◽

Vol 9 (2) ◽

pp. 26

Author(s):

Maggie Mulley ◽

Lammert Kooistra ◽

Laurens Bierens

Keyword(s):

Remote Sensing ◽

Precision Agriculture ◽

Vegetation Index ◽

Date Palm ◽

Sub Saharan Africa ◽

Added Value ◽

Tree Level ◽

Individual Tree ◽

Red Edge ◽

Height Data

Date palms are a valuable crop in areas with limited water availability such as the Middle East and sub-Saharan Africa, due to their hardiness in tough conditions. Increasing soil salinity and the spread of pests including the red palm weevil (RPW) are two examples of growing threats to date palm plantations. Separate studies have shown that thermal, multispectral, and hyperspectral remote sensing imagery can provide insight into the health of date palm plantations, but the added value of combining these datasets has not been investigated. The current study used available thermal, hyperspectral, Light Detection and Ranging (LiDAR) and visual Red-Green-Blue (RGB) images to investigate the possibilities of assessing date palm health at two “levels”; block level and individual tree level. Test blocks were defined into assumed healthy and unhealthy classes, and thermal and height data were extracted and compared. Due to distortions in the hyperspectral imagery, this data was only used for individual tree analysis; methods for identifying individual tree points using Normalized Difference Vegetation Index (NDVI) maps proved accurate. A total of 100 random test trees in one block were selected, and comparisons between hyperspectral, thermal and height data were made. For the vegetation index red-edge position (REP), the R-squared value in correlation with temperature was 0.313 and with height was 0.253. The vegetation index—the Vogelmann Red Edge Index (VOGI)—also has a relatively strong correlation value with both temperature (R2 = 0.227) and height (R2 = 0.213). Despite limited field data, the results of this study suggest that remote sensing data has added value in analyzing date palm plantations and could provide insight for precision agriculture techniques.

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Using tree rings to assess the potential of thinning to alleviate drought stress in a dry forest of western Canada

10.5194/egusphere-egu21-13182 ◽

2021 ◽

Author(s):

David Montwé ◽

Audrey Standish ◽

Miriam Isaac-Renton ◽

Jodi Axelson

Keyword(s):

Tree Ring ◽

Tree Rings ◽

Basal Area ◽

Dry Forest ◽

Tree Level ◽

Severe Drought ◽

Western Canada ◽

Drought Event ◽

Individual Tree ◽

Potential Benefits

Increasing frequency of severe drought events under climate change is a major cause for concern for millions of hectares of forested land. One practical solution to improving forest resilience may be thinning. There may be several potential benefits, chief of which is that drought tolerance could be improved in the remaining trees due to lower competition for resources and increased precipitation throughfall. By improving resilience to drought, this may increase productivity of the remaining trees while lowering risks of mortality. Such potential benefits can effectively be quantified with data from statistically-sound, long-term field experiments, and tree rings provide a suitable avenue to compare treatments. We work with an experiment that applied different levels of tree retention to mature interior Douglas fir (Pseudotsuga menziesii var. glauca) in a dry ecosystem of western Canada. The treatments were applied in the winter of 2002/2003, coinciding with the aftermath of a severe natural drought event in 2002. We used tree-rings to quantify the extent to which thinning improves recovery and resilience of treated trees as compared to non-thinned controls. Tree-ring samples as well as height and diameter data were obtained from 83 trees from 8 treatment units of the randomized experimental design. Indicators for resilience to drought were calculated based on basal area increments. Thinning substantially increased basal area increments at the individual tree level, but more importantly, led to significantly higher recovery and resilience relative to the control. The results of this tree-ring analysis suggest that thinning may be a viable silvicultural intervention to counteract effects of severe drought events and to maintain tree cover.

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The Rosetta mission orbiter science overview: the comet phase

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2016.0262 ◽

2017 ◽

Vol 375 (2097) ◽

pp. 20160262 ◽

Cited By ~ 35

Author(s):

M. G. G. T. Taylor ◽

N. Altobelli ◽

B. J. Buratti ◽

M. Choukroun

Keyword(s):

Remote Sensing ◽

Solar System ◽

Cometary Nucleus ◽

Rosetta Mission ◽

Interstellar Material ◽

The Relationship ◽

Mission Operations ◽

Comet 67P ◽

Cometary Activity

The international Rosetta mission was launched in 2004 and consists of the orbiter spacecraft Rosetta and the lander Philae. The aim of the mission is to map the comet 67P/Churyumov–Gerasimenko by remote sensing, and to examine its environment in situ and its evolution in the inner Solar System. Rosetta was the first spacecraft to rendezvous with and orbit a comet, accompanying it as it passes through the inner Solar System, and to deploy a lander, Philae, and perform in situ science on the comet's surface. The primary goals of the mission were to: characterize the comet's nucleus; examine the chemical, mineralogical and isotopic composition of volatiles and refractories; examine the physical properties and interrelation of volatiles and refractories in a cometary nucleus; study the development of cometary activity and the processes in the surface layer of the nucleus and in the coma; detail the origin of comets, the relationship between cometary and interstellar material and the implications for the origin of the Solar System; and characterize asteroids 2867 Steins and 21 Lutetia. This paper presents a summary of mission operations and science, focusing on the Rosetta orbiter component of the mission during its comet phase, from early 2014 up to September 2016. This article is part of the themed issue ‘Cometary science after Rosetta’.

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An individual-tree basal area growth model for black spruce in second-growth peatland stands

Canadian Journal of Forest Research ◽

10.1139/x99-032 ◽

1999 ◽

Vol 29 (5) ◽

pp. 621-629 ◽

Cited By ~ 22

Author(s):

Hannu Hökkä ◽

Arthur Groot

Keyword(s):

Growth Model ◽

Black Spruce ◽

Basal Area ◽

Random Parameter ◽

Considerable Change ◽

Tree Level ◽

Individual Tree ◽

Basal Area Growth ◽

Second Growth ◽

Area Growth

A basal area growth model was developed to predict the growth of individual trees in second-growth black spruce (Picea mariana (Mill.) BSP) stands on northeastern Ontario peatlands. The data were derived from stem analysis trees collected in 1985 and 1986 from stands harvested 47-68 years earlier. For a period starting from the date of data collection and going back to 10 years from the harvesting, tree basal area growth, diameters, and stand characteristics were retrospectively calculated at 5-year intervals. To estimate previous mortality, self-thinning relationships for black spruce were applied. In the model, 5-year basal area growth of a tree was expressed as a function of tree diameter, stand-level competition, tree-level competition, and peat thickness. There was considerable change in the growth-size relationship over time. A random parameter approach was applied in model construction to account for the spatial and temporal correlations of the observations. The proposed model explicitly incorporates factors normally included in a "random error" term and, therefore, should provide more sensitive tests of the contributions of the various factors to growth prediction. The estimated model showed only slight bias against the modeling data and the predicted stand basal area development was comparable with that given in other studies.

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Species Mixing Effects on Forest Productivity: A Case Study at Stand-, Species- and Tree-Level in the Netherlands

Forests ◽

10.3390/f9110713 ◽

2018 ◽

Vol 9 (11) ◽

pp. 713 ◽

Cited By ~ 3

Author(s):

Huicui Lu ◽

Godefridus Mohren ◽

Miren del Río ◽

Mart-Jan Schelhaas ◽

Meike Bouwman ◽

...

Keyword(s):

Forest Management ◽

Soil Fertility ◽

Basal Area ◽

Tree Level ◽

Stand Age ◽

Forest Plot ◽

Mixed Species ◽

Mixed Stands ◽

Individual Tree ◽

Species Mixtures

Many monoculture forests have been converted to mixed-species forests in Europe over the last decades. The main reasons for this conversion were probably to increase productivity, including timber production, and enhance other ecosystem services, such as conservation of biodiversity and other nature values. This study was done by synthesizing results from studies carried out in Dutch mixed forests compared with monoculture stands and evaluating them in the perspective of the current theory. Then we explored possible mechanisms of higher productivity in mixed stands, in relation to the combination of species, stand age and soil fertility, and discussed possible consequences of forest management. The study covered five two-species mixtures and their corresponding monoculture stands from using long-term permanent forest plots over multiple decades as well as two inventories (around 2003 and 2013) across the entire Netherlands. These forest plot data were used together with empirical models at total stand level, species level and tree level. Overyielding in Douglas-fir–beech and pine–oak mixtures was maintained over time, probably owing to the intensive thinning and was achieved on the poorer soils. However, this overyielding was not always driven by fast-growing light-demanding species. On individual tree level, intra-specific competition was not necessarily stronger than inter-specific competition and this competitive reduction was less seen at lower soil fertility and dependent on species mixtures. Moreover, size-asymmetric competition for light was more associated with tree basal area growth than size-symmetric competition for soil resources. Overall, this study suggests a substantial potential of species mixing for increasing productivity and implies developing forest management strategies to convert monospecific forests to mixed-species forests that consider the complementarity in resource acquisition of tree species.

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Spatial-Temporal Patterns of Spruce Budworm Defoliation within Plots in Québec

Forests ◽

10.3390/f10030232 ◽

2019 ◽

Vol 10 (3) ◽

pp. 232 ◽

Cited By ~ 1

Author(s):

Mingke Li ◽

David MacLean ◽

Chris Hennigar ◽

Jae Ogilvie

Keyword(s):

Spatial Autocorrelation ◽

Hot Spot ◽

Basal Area ◽

Temporal Patterns ◽

Spruce Budworm ◽

Balsam Fir ◽

Tree Level ◽

Cold Spot ◽

Individual Tree ◽

Tree Defoliation

We investigated the spatial-temporal patterns of spruce budworm (Choristoneura fumiferana (Clem.); SBW) defoliation within 57 plots over 5 years during the current SBW outbreak in Québec. Although spatial-temporal variability of SBW defoliation has been studied at several scales, the spatial dependence between individual defoliated trees within a plot has not been quantified, and effects of defoliation level of neighboring trees have not been addressed. We used spatial autocorrelation analyses to determine patterns of defoliation of trees (clustered, dispersed, or random) for plots and for individual trees. From 28% to 47% of plots had significantly clustered defoliation during the 5 years. Plots with clustered defoliation generally had higher mean defoliation per plot and higher deviation of defoliation. At the individual-tree-level, we determined ‘hot spot trees’ (highly defoliated trees surrounded by other highly defoliated trees) and ‘cold spot trees’ (lightly defoliated trees surrounded by other lightly defoliated trees) within each plot using local Getis-Ord Gi* analysis. Results revealed that 11 to 27 plots had hot spot trees and 27% to 64% of them had mean defoliation <25%, while plots with 75% to 100% defoliation had either cold spot trees or non-significant spots, which suggested that whether defoliation was high or low enough to be a hot or cold spot depended on the defoliation level of the entire plot. We fitted individual-tree balsam fir defoliation regression models as a function of plot and surrounding tree characteristics (using search radii of 3–5 m). The best model contained plot average balsam fir defoliation and subject tree basal area, and these two variables explained 80% of the variance, which was 2% to 5% higher than the variability explained by the neighboring tree defoliation, over the 3–5 m search radii tested. We concluded that plot-level defoliation and basal area were adequate for modeling individual tree defoliation, and although clustering of defoliation was evident, larger plots were needed to determine the optimum neighborhood radius for predicting defoliation on an individual. Spatial autocorrelation analysis can serve as an objective way to quantify such ecological patterns.

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How Much Can We See from a UAV-Mounted Regular Camera? Remote Sensing-Based Estimation of Forest Attributes in South American Native Forests

Remote Sensing ◽

10.3390/rs13112151 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2151

Author(s):

Alejandro Miranda ◽

Germán Catalán ◽

Adison Altamirano ◽

Carlos Zamorano-Elgueta ◽

Manuel Cavieres ◽

...

Keyword(s):

Remote Sensing ◽

Mixed Models ◽

Forest Canopy ◽

Complex Structure ◽

Boosted Regression Trees ◽

Tree Level ◽

Old Growth ◽

Individual Tree ◽

Native Forests ◽

Old Growth Forests

Data collection from large areas of native forests poses a challenge. The present study aims at assessing the use of UAV for forest inventory on native forests in Southern Chile, and seeks to retrieve both stand and tree level attributes from forest canopy data. Data were collected from 14 plots (45 × 45 m) established at four locations representing unmanaged Chilean temperate forests: seven plots on secondary forests and seven plots on old-growth forests, including a total of 17 different native species. The imagery was captured using a fixed-wing airframe equipped with a regular RGB camera. We used the structure from motion and digital aerial photogrammetry techniques for data processing and combined machine learning methods based on boosted regression trees and mixed models. In total, 2136 trees were measured on the ground, from which 858 trees were visualized from the UAV imagery of the canopy, ranging from 26% to 88% of the measured trees in the field (mean = 45.7%, SD = 17.3), which represented between 70.6% and 96% of the total basal area of the plots (mean = 80.28%, SD = 7.7). Individual-tree diameter models based on remote sensing data were constructed with R2 = 0.85 and R2 = 0.66 based on BRT and mixed models, respectively. We found a strong relationship between canopy and ground data; however, we suggest that the best alternative was combining the use of both field-based and remotely sensed methods to achieve high accuracy estimations, particularly in complex structure forests (e.g., old-growth forests). Field inventories and UAV surveys provide accurate information at local scales and allow validation of large-scale applications of satellite imagery. Finally, in the future, increasing the accuracy of aerial surveys and monitoring is necessary to advance the development of local and regional allometric crown and DBH equations at the species level.

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LiDAR Applications to Estimate Forest Biomass at Individual Tree Scale: Opportunities, Challenges and Future Perspectives

Forests ◽

10.3390/f12050550 ◽

2021 ◽

Vol 12 (5) ◽

pp. 550

Author(s):

Dandan Xu ◽

Haobin Wang ◽

Weixin Xu ◽

Zhaoqing Luan ◽

Xia Xu

Keyword(s):

Remote Sensing ◽

Laser Scanning ◽

Forest Biomass ◽

Remotely Sensed ◽

Tree Level ◽

Biomass Estimation ◽

Future Perspectives ◽

Individual Tree ◽

The Individual ◽

Individual Trees

Accurate forest biomass estimation at the individual tree scale is the foundation of timber industry and forest management. It plays an important role in explaining ecological issues and small-scale processes. Remotely sensed images, across a range of spatial and temporal resolutions, with their advantages of non-destructive monitoring, are widely applied in forest biomass monitoring at global, ecoregion or community scales. However, the development of remote sensing applications for forest biomass at the individual tree scale has been relatively slow due to the constraints of spatial resolution and evaluation accuracy of remotely sensed data. With the improvements in platforms and spatial resolutions, as well as the development of remote sensing techniques, the potential for forest biomass estimation at the single tree level has been demonstrated. However, a comprehensive review of remote sensing of forest biomass scaled at individual trees has not been done. This review highlights the theoretical bases, challenges and future perspectives for Light Detection and Ranging (LiDAR) applications of individual trees scaled to whole forests. We summarize research on estimating individual tree volume and aboveground biomass (AGB) using Terrestrial Laser Scanning (TLS), Airborne Laser Scanning (ALS), Unmanned Aerial Vehicle Laser Scanning (UAV-LS) and Mobile Laser Scanning (MLS, including Vehicle-borne Laser Scanning (VLS) and Backpack Laser Scanning (BLS)) data.

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Predicting Forest Inventory Attributes Using Airborne Laser Scanning, Aerial Imagery, and Harvester Data

Remote Sensing ◽

10.3390/rs11070797 ◽

2019 ◽

Vol 11 (7) ◽

pp. 797 ◽

Cited By ~ 3

Author(s):

Atte Saukkola ◽

Timo Melkas ◽

Kirsi Riekki ◽

Sanna Sirparanta ◽

Jussi Peuhkurinen ◽

...

Keyword(s):

Remote Sensing ◽

Forest Inventory ◽

Prediction Models ◽

Basal Area ◽

Sample Plot ◽

Weighted Mean ◽

Individual Tree ◽

Plot Size ◽

Head Positions ◽

Mean Square Errors

The aim of the study was to develop a new method to use tree stem information recorded by harvesters along operative logging in remote sensing-based prediction of forest inventory attributes in mature stands. The reference sample plots were formed from harvester data, using two different tree positions: harvester positions (XYH) in global satellite navigation system and computationally improved harvester head positions (XYHH). Study materials consisted of 158 mature Norway-spruce-dominated stands located in Southern Finland that were clear-cut during 2015–16. Tree attributes were derived from the stem dimensions recorded by the harvester. The forest inventory attributes were compiled for both stands and sample plots generated for stands for four different sample plot sizes (254, 509, 761, and 1018 m2). Prediction models between the harvester-based forest inventory attributes and remote sensing features of sample plots were developed. The stand-level predictions were obtained, and basal-area weighted mean diameter (Dg) and basal-area weighted mean height (Hg) were nearly constant for all model alternatives with relative root-mean-square errors (RMSE) roughly 10–11% and 6–8%, respectively, and minor biases. For basal area (G) and volume (V), using either of the position methods, resulted in roughly similar predictions at best, with approximately 25% relative RMSE and 15% bias. With XYHH positions, the predictions of G and V were nearly independent of the sample plot size within 254–761 m2. Therefore, the harvester-based data can be used as ground truth for remote sensing forest inventory methods. In predicting the forest inventory attributes, it is advisable to utilize harvester head positions (XYHH) and a smallest plot size of 254 m2. Instead, if only harvester positions (XYH) are available, expanding the sample plot size to 761 m2 reaches a similar accuracy to that obtained using XYHH positions, as the larger sample plot moderates the uncertainties when determining the individual tree position.

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A simulation-based approach to a near-optimal thinning strategy: allowing harvesting times to be determined for individual trees

Canadian Journal of Forest Research ◽

10.1139/cjfr-2019-0053 ◽

2019 ◽

pp. 320-331

Author(s):

Peter Fransson ◽

Oskar Franklin ◽

Ola Lindroos ◽

Urban Nilsson ◽

Åke Brännström

Keyword(s):

Optimal Strategy ◽

Management Strategy ◽

Basal Area ◽

Forest Growth ◽

Tree Level ◽

Individual Tree ◽

Area Reduction ◽

Forest Growth Model ◽

The Individual ◽

Individual Trees

As various methods for precision inventories, including light detection and ranging (LiDAR), are becoming increasingly common in forestry, planning at the individual-tree level is becoming more viable. In this study, we present a method for finding the optimal thinning times for individual trees from an economic perspective. The method utilizes a forest growth model based on individual trees that has been fitted to Norway spruce (Picea abies (L.) Karst.) stands in northern Sweden. We find that the optimal management strategy is to thin from above (i.e., harvesting trees that are larger than average). We compare our optimal strategy with a conventional management strategy and find that the optimal strategy results in approximately 20% higher land expectation value. Furthermore, we find that for the optimal strategy, increasing the discount rate will reduce the final harvest age and increase the basal area reduction. Decreasing the cost to initiate a thinning (e.g., machinery-related transportation costs) increases the number of thinnings and delays the first thinning.

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