scholarly journals Remote-sensing support for the Estonian National Forest Inventory, facilitating the construction of maps for forest height, standing-wood volume, and tree species composition

2020 ◽  
Vol 73 (1) ◽  
pp. 77-97
Author(s):  
Mait Lang ◽  
Allan Sims ◽  
Kalev Pärna ◽  
Raul Kangro ◽  
Märt Möls ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Species Composition ◽  
Tree Species ◽  
Forest Inventory ◽  
Point Clouds ◽  
National Forest Inventory ◽  
National Forest ◽  
Tree Species Composition ◽  
Wood Volume ◽  
Forest Height

Abstract Since 1999, Estonia has conducted the National Forest Inventory (NFI) on the basis of sample plots. This paper presents a new module, incorporating remote-sensing feature variables from airborne laser scanning (ALS) and from multispectral satellite images, for the construction of maps of forest height, standing-wood volume, and tree species composition for the entire country. The models for sparse ALS point clouds yield coefficients of determination of 89.5–94.8% for stand height and 84.2–91.7% for wood volume. For the tree species prediction, the models yield Cohen's kappa values (taking 95% confidence intervals) of 0.69–0.72 upon comparing model results against a previous map, and values of 0.51–0.54 upon comparing model results against NFI sample plots. This paper additionally examines the influence of foliage phenology on the predictions and discusses options for further enhancement of the system.

Monitoring Canada's forests: The National Forest Inventory

2005 ◽  
Vol 81 (2) ◽  
pp. 214-221 ◽  
Author(s):  
M D Gillis ◽  
A Y Omule ◽  
T. Brierley
Keyword(s):  
Remote Sensing ◽  
Sustainable Development ◽  
Forest Inventory ◽  
Forest Cover ◽  
Sustainable Forest Management ◽  
Remote Sensing Data ◽  
National Forest Inventory ◽  
National Forest ◽  
Inventory Data ◽  
International Reporting

A new national forest inventory is being installed in Canada. For the last 20 years, Canada's forest inventory has been a compilation of inventory data from across the country. Although this method has a number of advantages, it lacks information about the nature and rate of changes to the resource, and does not permit projections or forecasts. To address these limitations a new National Forest Inventory (NFI) was developed to monitor Canada's progress in meeting a commitment towards sustainable forest management, and to satisfy requirements for national and international reporting. The purpose of the new inventory is to "assess and monitor the extent, state and sustainable development of Canada's forests in a timely and accurate manner." The NFI consists of a plot-based system of permanent observational units located on a national grid. A combination of ground plot, photo plot and remote sensing data are used to capture a set of basic attributes that are used to derive indicators of sustainability. To meet the monitoring needs a re-measurement strategy and framework to guide the development of change estimation procedures has been worked out. A plan for implementation has been drafted. The proposed plan is presented and discussed in this paper. Key words: Canada, forest cover, inventory, monitoring, National Forest Inventory, re-measurement, panel

Structural changes in protected forests in Sweden: implications for conservation functionality

2015 ◽  
Vol 45 (9) ◽  
pp. 1215-1224 ◽  
Author(s):  
Per-Ola Hedwall ◽  
Grzegorz Mikusiński
Keyword(s):  
Species Composition ◽  
Tree Species ◽  
Structural Changes ◽  
Fire Suppression ◽  
National Forest Inventory ◽  
Active Management ◽  
Tree Species Composition ◽  
Small Areas ◽  
Large Trees

Protected forest areas (PFAs) are key features of biodiversity conservation, and knowledge about long-term development is crucial in evaluating their efficiency and management needs. Longitudinal data on forest structure in PFAs is uncommon and often from small areas. Here we use data from the Swedish National Forest Inventory to study changes in more than 750 000 ha of PFAs over 60 years. Structures important for biodiversity, e.g., number of large trees and the volume of hard deadwood, including both standing and down wood, have more than doubled. The initial volume of deadwood, however, was very low. The overall tree species composition was stable over time, and only among the largest trees were there indications of a shift towards the late successional Norway spruce (Picea abies (L.) Karst.). Deadwood increased independent of species, size of wood, and site characteristics. This increase was positively related to the volume of living trees and forest age. We conclude that Swedish PFAs, in the absence of active management and under fire suppression at the landscape scale, develop structural components that are crucial for conservation of biodiversity. However, although tree species composition appears stable, present disturbance regimes in the PFAs are considerably different from those in naturally dynamic forests, which may have implications for long-term biodiversity maintenance.

scholarly journals Prediction and model-assisted estimation of diameter distributions using Norwegian national forest inventory and airborne laser scanning data

2021 ◽  
Author(s):  
Janne Räty ◽  
Rasmus Astrup ◽  
Johannes Breidenbach
Keyword(s):  
Tree Species ◽  
Forest Inventory ◽  
Laser Scanning ◽  
National Forest Inventory ◽  
Airborne Laser Scanning ◽  
Systematic Sampling ◽  
National Forest ◽  
Prediction Errors ◽  
K Nearest Neighbor ◽  
Airborne Laser

Diameter at breast height (DBH) distributions offer valuable information for operational and strategic forest management decisions. We predicted DBH distributions using Norwegian national forest inventory and airborne laser scanning data and compared the predictive performances of linear mixed- effects (PPM), generalized linear-mixed (GLM) and k nearest neighbor (NN) models. While GLM resulted in smaller prediction errors than PPM, both were clearly outperformed by NN. We therefore studied the ability of the NN model to improve the precision of stem frequency estimates by DBH classes in the 8.7 Mha study area using a model-assisted (MA) estimator suitable for systematic sampling. MA estimates yielded greater than or approximately equal efficiencies as direct estimates using field data only. The relative efficiencies (REs) associated with the MA estimates ranged between 0.95–1.47 and 0.96–1.67 for 2 and 6 cm DBH class widths, respectively, when dominant tree species were assumed to be known. The use of a predicted tree species map, instead of the observed information, decreased the REs by up to 10%.

scholarly journals Das Potenzial der Totholzakkumulation im deutschen Wald | Potential of deadwood accumulation in German forests

2010 ◽  
Vol 161 (5) ◽  
pp. 171-180 ◽  
Author(s):  
Franz Kroiher ◽  
Katja Oehmichen
Keyword(s):  
Tree Species ◽  
Forest Inventory ◽  
Decay Constant ◽  
Dead Wood ◽  
Large Diameter ◽  
Timber Harvesting ◽  
National Forest Inventory ◽  
Time Span ◽  
National Forest

Deadwood is an important part of the forest ecosystem. The quantity available depends on the rates of accumulation and of decomposition. A comprehensive pool of data regarding the deadwood stock for Germany is collected by the German national forest inventory. Moreover, the Projection Modelling of Forest Development and Timber Harvesting Potential (WEHAM) adds other important parameters such as growth rates and potential roundwood availability. Using this data, scenarios for the accumulation of deadwood were developed. For the calculation of deadwood decomposition, independent of tree species, a decay constant k = 0.054 was derived for the whole of Germany. The study shows that a long-term stop in timber harvesting in Germany, assuming the proportions of different tree species remained constant, would lead to a saturation of deadwood with a total of 184 m3/ha. If the German forest presented a natural composition of tree species, a deadwood stock of 150 m3/ha at most could be accumulated. Based on these scenarios, rates of accumulation of total dead-wood and of deadwood of large diameter can be calculated taking into account the deadwood stock levels desired and the time span involved. It has been shown that 7.3% of the WEHAM potential roundwood availability must remain in the forest per year if the quantity of deadwood is to be maintained at 11.5 m3/ha. If an increase in the accumulation of deadwood is to be aimed for, the annual input rate together with the desired deadwood stocks are increasingly influenced by the time span involved. Thus shorter time spans with greater stocks of deadwood to be achieved make it possible to approach the WEHAM potential roundwood availability. The results presented in this paper should assist in decision-making concerning stocks of deadwood to be aimed for in the forest and, in the future, serve as a basis for the selection, evaluation and discussion of quantities of dead-wood to be achieved.

scholarly journals Production of Douglas-Fir in the Czech Republic based on national forest inventory data

2013 ◽  
Vol 59 (No. 10) ◽  
pp. 398-404 ◽  
Author(s):  
V. Podrázský ◽  
R. Čermák ◽  
D. Zahradník ◽  
J. Kouba
Keyword(s):  
Czech Republic ◽  
Tree Species ◽  
Forest Inventory ◽  
National Forest Inventory ◽  
Douglas Fir ◽  
National Forest ◽  
Northern Red Oak ◽  
Forest Land ◽  
Land Area ◽  
The Czech Republic

This article summarizes basic estimates of productivity and trend analysis of one of the principal introduced forest tree species in the Czech Republic, i.e. Douglas-fir (Pseudotsuga menziesii [Mirbel] Franco). As a comparison, we also examine grand fir (Abies grandis [D. Don] Lindl), northern red oak (Quercus rubra L. syn. Quercus borealis Michx.) and black locust (Robinia pseudoacacia L). This paper presents estimates of forest land area, standing volume, annual and total increments, distribution of age classes, average ages and site indexes for the period 1979–2010. All data were obtained from the national forest inventory of the Czech Republic. Korf’s growth function was used for the assessment of current and mean annual increments (CAI, MAI) of Douglas-fir compared to other tree species. Our results suggest a decline in the annual area afforested by Douglas-fir, as influenced by the State administration management choices, a low rate of an increase in the forest land area, increasing average age of the forests. On the other hand, we observed a dramatic increase in the standing volume as well as high annual increments in volume. Douglas-fir is the most productive major tree species in the Czech Republic and there is a great potential to expand its use throughout the country.

The Norwegian Forest Resource Map SR16: Mapping Forest Attributes Using Heterogeneous Sets of Airborne Laser Scanning and National Forest Inventory Data

2021 ◽  
Author(s):  
Marius Hauglin ◽  
Johannes Rahlf ◽  
Johannes Schumacher ◽  
Rasmus Astrup ◽  
Johannes Breidenbach
Keyword(s):  
Tree Species ◽  
Forest Inventory ◽  
Laser Scanning ◽  
National Forest Inventory ◽  
Mixed Effects ◽  
National Forest ◽  
Forest Resource ◽  
Airborne Laser ◽  
Maturity Class ◽  
Species Specific

Abstract Background The Norwegian forest resource map SR16 combines national forest inventory (NFI) and airborne laser scanning (ALS) data. While the ALS data were acquired over a time interval of 10 years using various sensors and settings, the NFI data are continuously collected. Aims of this study were to analyze the effects of stratification on models linking remotely sensed and field data, and assess the accuracy overall and at the ALS project level. Material and methods The model dataset consisted of 9203 NFI field plots and data from 367 ALS projects, covering 17 Mha and ⅔ of the productive forest in Norway. Mixed-effects regression models were used to account for differences among ALS projects. Two types of stratification were used to fit models: 1) strata by the three main tree species groups spruce, pine and deciduous resulted in species-specific models that can utilize a satellite-based species map for improving predictions, and 2) a stratification by species and maturity class resulted in stratum-specific models that can be used in forest management inventories where each stand regularly is stratified accordingly. Stratified models were compared to general models that were fit without stratifying the data. Results The species-specific models had relative root-mean-squared errors (RMSEs) of 35, 34, 31, and 12% for volume, aboveground biomass, basal area, and Lorey’s height, respectively. These RMSEs were 2-7 percentage points (pp) smaller than those of general models. When validating using predicted species, RMSEs were 0-4 pp smaller than those of general models. Models stratified by main species and maturity class further improved RMSEs compared to species-specific models by up to 1.8 pp. Using mixed-effects models over ordinary least squares models resulted in a decrease of RMSE for timber volume of 1.0 – 3.9 pp, depending on the main tree species. RSMEs for timber volume ranged between 19 – 59% among individual ALS projects.Conclusions The stratification by tree species considerably improved models of forest structural variables. A further stratification by maturity class improved these models only moderately. The accuracy of the models utilized in SR16 were within the range reported from other ALS-based forest inventories, but local variations are apparent.

Combining national forest inventory field plots and remote sensing data for forest databases

2008 ◽  
Vol 112 (5) ◽  
pp. 1982-1999 ◽  
Author(s):  
Erkki Tomppo ◽  
Håkan Olsson ◽  
Göran Ståhl ◽  
Mats Nilsson ◽  
Olle Hagner ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Inventory ◽  
Remote Sensing Data ◽  
National Forest Inventory ◽  
National Forest ◽  
Sensing Data ◽  
Field Plots

scholarly journals Large scale mapping of forest attributes using heterogeneous sets of airborne laser scanning and National Forest Inventory data

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Marius Hauglin ◽  
Johannes Rahlf ◽  
Johannes Schumacher ◽  
Rasmus Astrup ◽  
Johannes Breidenbach
Keyword(s):  
Tree Species ◽  
Forest Inventory ◽  
Laser Scanning ◽  
National Forest Inventory ◽  
Mixed Effects ◽  
Airborne Laser Scanning ◽  
National Forest ◽  
Airborne Laser ◽  
Maturity Class ◽  
Species Specific

Abstract Background The Norwegian forest resource map (SR16) maps forest attributes by combining national forest inventory (NFI), airborne laser scanning (ALS) and other remotely sensed data. While the ALS data were acquired over a time interval of 10 years using various sensors and settings, the NFI data are continuously collected. Aims of this study were to analyze the effects of stratification on models linking remotely sensed and field data, and assess the accuracy overall and at the ALS project level. Materials and methods The model dataset consisted of 9203 NFI field plots and data from 367 ALS projects, covering 17 Mha and 2/3 of the productive forest in Norway. Mixed-effects regression models were used to account for differences among ALS projects. Two types of stratification were used to fit models: 1) stratification by the three main tree species groups spruce, pine and deciduous resulted in species-specific models that can utilize a satellite-based species map for improving predictions, and 2) stratification by species and maturity class resulted in stratum-specific models that can be used in forest management inventories where each stand regularly is visually stratified accordingly. Stratified models were compared to general models that were fit without stratifying the data. Results The species-specific models had relative root-mean-squared errors (RMSEs) of 35%, 34%, 31%, and 12% for volume, aboveground biomass, basal area, and Lorey’s height, respectively. These RMSEs were 2–7 percentage points (pp) smaller than those of general models. When validating using predicted species, RMSEs were 0–4 pp. smaller than those of general models. Models stratified by main species and maturity class further improved RMSEs compared to species-specific models by up to 1.8 pp. Using mixed-effects models over ordinary least squares models resulted in a decrease of RMSE for timber volume of 1.0–3.9 pp., depending on the main tree species. RMSEs for timber volume ranged between 19%–59% among individual ALS projects. Conclusions The stratification by tree species considerably improved models of forest structural variables. A further stratification by maturity class improved these models only moderately. The accuracy of the models utilized in SR16 were within the range reported from other ALS-based forest inventories, but local variations are apparent.

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