Canadian national taper models

2013 ◽  
Vol 89 (02) ◽  
pp. 211-224 ◽  
Author(s):  
Chhun-Huor Ung ◽  
Xiao Jing Guo ◽  
Mathieu Fortin

Work was done to gather stem taper data for most forest tree species across Canada. They were used for producing taper models to be applied for the purposes of the national forest inventory and for regional purposes when regional taper models are not available. The models are based on squared DBH and on measured or predicted tree height. A taper equation based on the dimensional analysis approach was adopted to fit Canadian national taper models using the collected data. The model parameters were estimated using a mixed model for taking into account variance heterogeneity and withintree autocorrelation. In spite of the different protocols for data collection, the accuracy of the proposed stem taper models is similar to that found in previous studies. Consequently, the models seem suitable for pre-harvest estimation of sawlog volume nationally or regionally.

2016 ◽  
Vol 167 (3) ◽  
pp. 118-127 ◽  
Author(s):  
Berthold Traub ◽  
Fabrizio Cioldi ◽  
Christoph Düggelin

Repeat surveys as a quality assurance tool in the Swiss National Forest Inventory The Swiss National Forest Inventory (NFI) repeats surveys to guarantee the quality of fieldwork. To this end, approximately 10% of sample plots are completely surveyed a second time over a field season. Based on the results of the repeat survey, the current investigation focuses on the assessment precision, i.e. the reproducibility of various tree and stand attributes in NFI4. It also investigates whether the change from periodic (NFI1–NFI3) to continuous (NFI4) fieldwork has had a positive effect on the reproducibility of the attributes. The current results of the repeat surveys for NFI4 (2009/2017) are compared with those for NFI3 (2004/2006) to this end. We used statistical measures as well as measurement quality objectives (MQO) set by the NFI instructor team as a reference for evaluating reproducibility. The results vary for tree attributes which are vital for estimating stock. The result for the diameter at breast height (dbh) corresponds to the expected values, while that for upper stem diameter at seven meters height and tree height were approximately 5% below the expected values. With regard to the seven stand attributes also analyzed, four of them exceeded the quality goals (stand age, stand stability, the degree of cover of secured regeneration, and stage of development). The results for the mixture proportion, the stand structure and crown closure were between 5 and 18% below MQO. The result for presence of woody species shows that the recording of larger plants (above 130 cm) is clearly more reproducible than for smaller plants (40–130 cm). In NFI4, the reproducibility for almost all studied attributes was improved. The results suggest that the modified structure of fieldwork (with only three field teams and continuous fieldwork in NFI4) has a positive influence on the reproducibility of the included attributes.


2008 ◽  
Vol 54 (No. 10) ◽  
pp. 476-483 ◽  
Author(s):  
Š. Šmelko ◽  
J. Merganič

The work presents the conceptual information about the National Forest Inventory and Monitoring in Slovakia. It introduces some methodological approaches to the field data collection (determination of tree heights by two-phase method, regression formulas for tree volumes and assortments of forest tree species, quantification of deadwood volume in sample plots) and biometrical models prepared for data processing and generalisation of the results. The design and conception of Slovak National Forest Inventory and Monitoring were set with the aim to enable providing complex and integrated information about the state and changes of production and ecological characteristics of the forest ecosystems.


2009 ◽  
Vol 160 (11) ◽  
pp. 334-340 ◽  
Author(s):  
Pierre Mollet ◽  
Niklaus Zbinden ◽  
Hans Schmid

Results from the monitoring programs of the Swiss Ornithological Institute show that the breeding populations of several forest species for which deadwood is an important habitat element (black woodpecker, great spotted woodpecker, middle spotted woodpecker, lesser spotted woodpecker, green woodpecker, three-toed woodpecker as well as crested tit, willow tit and Eurasian tree creeper) have increased in the period 1990 to 2008, although not to the same extent in all species. At the same time the white-backed woodpecker extended its range in eastern Switzerland. The Swiss National Forest Inventory shows an increase in the amount of deadwood in forests for the same period. For all the mentioned species, with the exception of green and middle spotted woodpecker, the growing availability of deadwood is likely to be the most important factor explaining this population increase.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Matieu Henry ◽  
Zaheer Iqbal ◽  
Kristofer Johnson ◽  
Mariam Akhter ◽  
Liam Costello ◽  
...  

Abstract Background National forest inventory and forest monitoring systems are more important than ever considering continued global degradation of trees and forests. These systems are especially important in a country like Bangladesh, which is characterised by a large population density, climate change vulnerability and dependence on natural resources. With the aim of supporting the Government’s actions towards sustainable forest management through reliable information, the Bangladesh Forest Inventory (BFI) was designed and implemented through three components: biophysical inventory, socio-economic survey and remote sensing-based land cover mapping. This article documents the approach undertaken by the Forest Department under the Ministry of Environment, Forests and Climate Change to establish the BFI as a multipurpose, efficient, accurate and replicable national forest assessment. The design, operationalization and some key results of the process are presented. Methods The BFI takes advantage of the latest and most well-accepted technological and methodological approaches. Importantly, it was designed through a collaborative process which drew from the experience and knowledge of multiple national and international entities. Overall, 1781 field plots were visited, 6400 households were surveyed, and a national land cover map for the year 2015 was produced. Innovative technological enhancements include a semi-automated segmentation approach for developing the wall-to-wall land cover map, an object-based national land characterisation system, consistent estimates between sample-based and mapped land cover areas, use of mobile apps for tree species identification and data collection, and use of differential global positioning system for referencing plot centres. Results Seven criteria, and multiple associated indicators, were developed for monitoring progress towards sustainable forest management goals, informing management decisions, and national and international reporting needs. A wide range of biophysical and socioeconomic data were collected, and in some cases integrated, for estimating the indicators. Conclusions The BFI is a new information source tool for helping guide Bangladesh towards a sustainable future. Reliable information on the status of tree and forest resources, as well as land use, empowers evidence-based decision making across multiple stakeholders and at different levels for protecting natural resources. The integrated socio-economic data collected provides information about the interactions between people and their tree and forest resources, and the valuation of ecosystem services. The BFI is designed to be a permanent assessment of these resources, and future data collection will enable monitoring of trends against the current baseline. However, additional institutional support as well as continuation of collaboration among national partners is crucial for sustaining the BFI process in future.


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Johannes Schumacher ◽  
Marius Hauglin ◽  
Rasmus Astrup ◽  
Johannes Breidenbach

Abstract Background The age of forest stands is critical information for forest management and conservation, for example for growth modelling, timing of management activities and harvesting, or decisions about protection areas. However, area-wide information about forest stand age often does not exist. In this study, we developed regression models for large-scale area-wide prediction of age in Norwegian forests. For model development we used more than 4800 plots of the Norwegian National Forest Inventory (NFI) distributed over Norway between latitudes 58° and 65° N in an 18.2 Mha study area. Predictor variables were based on airborne laser scanning (ALS), Sentinel-2, and existing public map data. We performed model validation on an independent data set consisting of 63 spruce stands with known age. Results The best modelling strategy was to fit independent linear regression models to each observed site index (SI) level and using a SI prediction map in the application of the models. The most important predictor variable was an upper percentile of the ALS heights, and root mean squared errors (RMSEs) ranged between 3 and 31 years (6% to 26%) for SI-specific models, and 21 years (25%) on average. Mean deviance (MD) ranged between − 1 and 3 years. The models improved with increasing SI and the RMSEs were largest for low SI stands older than 100 years. Using a mapped SI, which is required for practical applications, RMSE and MD on plot level ranged from 19 to 56 years (29% to 53%), and 5 to 37 years (5% to 31%), respectively. For the validation stands, the RMSE and MD were 12 (22%) and 2 years (3%), respectively. Conclusions Tree height estimated from airborne laser scanning and predicted site index were the most important variables in the models describing age. Overall, we obtained good results, especially for stands with high SI. The models could be considered for practical applications, although we see considerable potential for improvements if better SI maps were available.


2021 ◽  
Vol 13 (10) ◽  
pp. 1863
Author(s):  
Caileigh Shoot ◽  
Hans-Erik Andersen ◽  
L. Monika Moskal ◽  
Chad Babcock ◽  
Bruce D. Cook ◽  
...  

Forest structure and composition regulate a range of ecosystem services, including biodiversity, water and nutrient cycling, and wood volume for resource extraction. Forest type is an important metric measured in the US Forest Service Forest Inventory and Analysis (FIA) program, the national forest inventory of the USA. Forest type information can be used to quantify carbon and other forest resources within specific domains to support ecological analysis and forest management decisions, such as managing for disease and pests. In this study, we developed a methodology that uses a combination of airborne hyperspectral and lidar data to map FIA-defined forest type between sparsely sampled FIA plot data collected in interior Alaska. To determine the best classification algorithm and remote sensing data for this task, five classification algorithms were tested with six different combinations of raw hyperspectral data, hyperspectral vegetation indices, and lidar-derived canopy and topography metrics. Models were trained using forest type information from 632 FIA subplots collected in interior Alaska. Of the thirty model and input combinations tested, the random forest classification algorithm with hyperspectral vegetation indices and lidar-derived topography and canopy height metrics had the highest accuracy (78% overall accuracy). This study supports random forest as a powerful classifier for natural resource data. It also demonstrates the benefits from combining both structural (lidar) and spectral (imagery) data for forest type classification.


2022 ◽  
Author(s):  
Tom Brandeis ◽  
Jeffery Turner ◽  
Andrés Baeza Motes ◽  
Mark Brown ◽  
Samuel Lambert

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