Incorporating predictions into an annual forest inventory

1996 ◽  
Vol 26 (9) ◽  
pp. 1709-1713 ◽  
Author(s):  
Paul C. Van Deusen
Keyword(s):  
Forest Inventory ◽  
Variance Components ◽  
Growth Modeling ◽  
Estimation Procedure ◽  
Regression Estimator ◽  
Forest Types ◽  
Model Estimate ◽  
Individual Tree ◽  
Time Period ◽  
The Individual

Growth modeling of forests at the individual tree and stand levels is a highly refined procedure for many forest types. A method to incorporate predictions from such models into a forest inventory system is developed. Variance components from the actual measurements and from the predicted measurements are used to estimate the variance of the combined predicted value. The only assumption required to justify this method is that the model estimate has a bias that does not change from one time period to the next. The estimation procedure proposed here can also incorporate remotely sensed information via a regression estimator.

scholarly journals Country and regional carbon stock in forest cover – estimates based on the first cycle of the Czech National Forest Inventory data (2001–2004)

2017 ◽  
Vol 63 (2-3) ◽  
pp. 113-125 ◽  
Author(s):  
Ján Merganič ◽  
Katarína Merganičová ◽  
Bohdan Konôpka ◽  
Miloš Kučera
Keyword(s):  
Forest Inventory ◽  
Carbon Stock ◽  
Forest Cover ◽  
Regional Distribution ◽  
National Forest Inventory ◽  
National Forest ◽  
Individual Tree ◽  
The Individual ◽  
Species Specific ◽  
Total Tree

AbstractSince forests can play an efficient role in the mitigation of greenhouse gas emissions, objective information about the actual carbon stock is very important. Therefore, the presented paper analysed the carbon stock in the living merchantable trees (with diameter at breast height above 7 cm) of the Czech forests with regard to groups of tree species and tree compartments (wood under bark with diameter above 7 cm, wood under bark with diameter below 7 cm, bark, green twigs, foliage, stump and roots). We examined its regional distribution and relationship to the number of inhabitants and the gross domestic product. The data used for the analysis originated from 13,929 forest plots of the first Czech National Forest Inventory performed between 2001 and 2004. The total tree carbon stock was obtained as a sum of the carbon stock in the individual tree compartments estimated from the biomass amount in the compartments multiplied by the relative carbon content. Wood biomass amount was calculated by multiplying a particular part of tree volume with species-specific green wood density. The total amount of carbon stored in forest trees in the Czech Republic was over 327 mill. t, which is about 113 t of carbon per ha of forests. The highest carbon amount (160 mill. t, i.e. 49.0% of the total amount) was fixed in spruce. The minimum carbon amount fixed in the forest cover (14.35 mill. t) was calculated for Ústecký kraj (region), while the maximum carbon amount (51.51 mill. t) was found in Jihočeský kraj.

Données LiDAR aériennes: pertinence de l'interprétation visuelle pour la foresterie

2017 ◽  
Vol 168 (3) ◽  
pp. 127-133
Author(s):  
Matthew Parkan
Keyword(s):  
Cross Sections ◽  
Forest Edge ◽  
Airborne Lidar ◽  
Visual Interpretation ◽  
Individual Tree ◽  
Small Areas ◽  
Interactive 3D ◽  
The Individual ◽  
Airborne Lidar Data ◽  
Stem Position

Airborne LiDAR data: relevance of visual interpretation for forestry Airborne LiDAR surveys are particularly well adapted to map, study and manage large forest extents. Products derived from this technology are increasingly used by managers to establish a general diagnosis of the condition of forests. Less common is the use of these products to conduct detailed analyses on small areas; for example creating detailed reference maps like inventories or timber marking to support field operations. In this context, the use of direct visual interpretation is interesting, because it is much easier to implement than automatic algorithms and allows a quick and reliable identification of zonal (e.g. forest edge, deciduous/persistent ratio), structural (stratification) and point (e.g. tree/stem position and height) features. This article examines three important points which determine the relevance of visual interpretation: acquisition parameters, interactive representation and identification of forest characteristics. It is shown that the use of thematic color maps within interactive 3D point cloud and/or cross-sections makes it possible to establish (for all strata) detailed and accurate maps of a parcel at the individual tree scale.

scholarly journals Development and Performance Evaluation of a Very Low-Cost UAV-Lidar System for Forestry Applications

2020 ◽  
Vol 13 (1) ◽  
pp. 77
Author(s):  
Tianyu Hu ◽  
Xiliang Sun ◽  
Yanjun Su ◽  
Hongcan Guan ◽  
Qianhui Sun ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Low Cost ◽  
Canopy Cover ◽  
Tree Height ◽  
Flying Height ◽  
Tree Level ◽  
Forest Site ◽  
Lidar System ◽  
Individual Tree ◽  
Gap Fraction

Accurate and repeated forest inventory data are critical to understand forest ecosystem processes and manage forest resources. In recent years, unmanned aerial vehicle (UAV)-borne light detection and ranging (lidar) systems have demonstrated effectiveness at deriving forest inventory attributes. However, their high cost has largely prevented them from being used in large-scale forest applications. Here, we developed a very low-cost UAV lidar system that integrates a recently emerged DJI Livox MID40 laser scanner (~$600 USD) and evaluated its capability in estimating both individual tree-level (i.e., tree height) and plot-level forest inventory attributes (i.e., canopy cover, gap fraction, and leaf area index (LAI)). Moreover, a comprehensive comparison was conducted between the developed DJI Livox system and four other UAV lidar systems equipped with high-end laser scanners (i.e., RIEGL VUX-1 UAV, RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE). Using these instruments, we surveyed a coniferous forest site and a broadleaved forest site, with tree densities ranging from 500 trees/ha to 3000 trees/ha, with 52 UAV flights at different flying height and speed combinations. The developed DJI Livox MID40 system effectively captured the upper canopy structure and terrain surface information at both forest sites. The estimated individual tree height was highly correlated with field measurements (coniferous site: R2 = 0.96, root mean squared error/RMSE = 0.59 m; broadleaved site: R2 = 0.70, RMSE = 1.63 m). The plot-level estimates of canopy cover, gap fraction, and LAI corresponded well with those derived from the high-end RIEGL VUX-1 UAV system but tended to have systematic biases in areas with medium to high canopy densities. Overall, the DJI Livox MID40 system performed comparably to the RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE systems in the coniferous site and to the Velodyne Puck LITE system in the broadleaved forest. Despite its apparent weaknesses of limited sensitivity to low-intensity returns and narrow field of view, we believe that the very low-cost system developed by this study can largely broaden the potential use of UAV lidar in forest inventory applications. This study also provides guidance for the selection of the appropriate UAV lidar system and flight specifications for forest research and management.

scholarly journals Crown Structure Explains the Discrepancy in Leaf Phenology Metrics Derived from Ground- and UAV-Based Observations in a Japanese Cool Temperate Deciduous Forest

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 425
Author(s):  
Noviana Budianti ◽  
Hiromi Mizunaga ◽  
Atsuhiro Iio
Keyword(s):  
Deciduous Forest ◽  
Leaf Expansion ◽  
Image Resolution ◽  
Leaf Phenology ◽  
Visual Interpretation ◽  
Temperate Deciduous Forest ◽  
Individual Tree ◽  
Crown Structure ◽  
Uav Images ◽  
The Individual

Unmanned aerial vehicles (UAV) provide a new platform for monitoring crown-level leaf phenology due to the ability to cover a vast area while offering branch-level image resolution. However, below-crown vegetation, e.g., understory vegetation, subcanopy trees, and the branches of neighboring trees, along with the multi-layered structure of the target crown may significantly reduce the accuracy of UAV-based estimates of crown leaf phenology. To test this hypothesis, we compared UAV-derived crown leaf phenology results against those based on ground observations at the individual tree scale for 19 deciduous broad-leaved species (55 individuals in total) characterized by different crown structures. The mean crown-level green chromatic coordinate derived from UAV images poorly explained inter- and intra-species variations in spring leaf phenology, most probably due to the consistently early leaf emergence in the below-crown vegetation. The start dates for leaf expansion and end dates for leaf falling could be estimated with an accuracy of <1-week when the influence of below-crown vegetation was removed from the UAV images through visual interpretation. However, a large discrepancy between the phenological metrics derived from UAV images and ground observations was still found for the end date of leaf expansion (EOE) and start date of leaf falling (SOF). Bayesian modeling revealed that the discrepancy for EOE increased as crown length and volume increased. The crown structure was not found to contribute to the discrepancy in SOF value. Our study provides evidence that crown structure is a pivotal factor to consider when using UAV photography to reliably estimate crown leaf phenology at the individual tree-scale.

scholarly journals Using Airborne Light Detection and Ranging (LIDAR) to Characterize Forest Stand Condition on the Kenai Peninsula of Alaska

2009 ◽  
Vol 24 (2) ◽  
pp. 95-102 ◽  
Author(s):  
Hans-Erik Andersen
Keyword(s):  
Forest Inventory ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Grid Cell ◽  
Forest Stand ◽  
Light Detection And Ranging ◽  
Inventory Analysis ◽  
Light Detection ◽  
Individual Tree ◽  
Kenai Peninsula

Abstract Airborne laser scanning (also known as light detection and ranging or LIDAR) data were used to estimate three fundamental forest stand condition classes (forest stand size, land cover type, and canopy closure) at 32 Forest Inventory Analysis (FIA) plots distributed over the Kenai Peninsula of Alaska. Individual tree crown segment attributes (height, area, and species type) were derived from the three-dimensional LIDAR point cloud, LIDAR-based canopy height models, and LIDAR return intensity information. The LIDAR-based crown segment and canopy cover information was then used to estimate condition classes at each 10-m grid cell on a 300 × 300-m area surrounding each FIA plot. A quantitative comparison of the LIDAR- and field-based condition classifications at the subplot centers indicates that LIDAR has potential as a useful sampling tool in an operational forest inventory program.

scholarly journals Estimation of Genetic and Phenotypic Parameters for Growth Traits in a Clonal Seed Orchard of Pinus kesiya in Malawi

ISRN Forestry ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Edward Missanjo ◽  
Gift Kamanga-Thole ◽  
Vidah Manda
Keyword(s):  
Growth Traits ◽  
Seed Orchard ◽  
Direct Selection ◽  
Tree Model ◽  
Individual Tree ◽  
Individual Level ◽  
Clonal Seed Orchard ◽  
Pinus Kesiya ◽  
Individual Tree Model ◽  
The Individual

Genetic and phenotypic parameters for height, diameter at breast height (dbh), and volume were estimated for Pinus kesiya Royle ex Gordon clonal seed orchard in Malawi using an ASReml program, fitting an individual tree model. The data were from 88 clones assessed at 18, 23, 30, 35, and 40 years of age. Heritability estimates for height, dbh, and volume were moderate to high ranging from 0.19 to 0.54, from 0.14 to 0.53, and from 0.20 to 0.59, respectively, suggesting a strong genetic control of the traits at the individual level, among families, and within families. The genetic and phenotypic correlations between the growth traits were significantly high and ranged from 0.69 to 0.97 and from 0.60 to 0.95, respectively. This suggests the possibility of indirect selection in trait with direct selection in another trait. The predicted genetic gains showed that the optimal rotational age of the Pinus kesiya clonal seed orchard is 30 years; therefore, it is recommended to establish a new Pinus kesiya clonal seed orchard. However, selective harvest of clones with high breeding values in the old seed orchard should be considered so that the best parents in the old orchard can continue to contribute until the new orchard is well established.

Stratified forest inventory estimation with mapped plots

2005 ◽  
Vol 35 (10) ◽  
pp. 2382-2386 ◽  
Author(s):  
Paul C Van Deusen
Keyword(s):  
Forest Inventory ◽  
Forest Service ◽  
Forest Types ◽  
Inventory Data ◽  
Expansion Factor ◽  
Usda Forest Service ◽  
Weighted Estimation ◽  
Forest Conditions

Weighted estimation formulas are developed for producing stratified estimates of means and variances where data come from plots that can contain multiple forest conditions. Each plot is mapped to allow the analyst to focus on specific forest types or conditions. The weights required to accommodate mapped plots are somewhat more complicated than the weights for unmapped plots. In particular, these weights depend on the mapped condition of interest. The implication is that a single plot weight or expansion factor will not suffice for all analyses as it does for unmapped plots. The methods are demonstrated using USDA Forest Service inventory data.

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