Forest inventory
Forest inventory is the systematic collection of data and forest information for assessment or analysis. An estimate of the value and possible uses of timber is an important part of the broader information required to sustain ecosystems.[1] When taking forest inventory the following are important things to measure and note: species, diameter at breast height (DBH), height, site quality, age, and defects. From the data collected one can calculate the number of trees per acre, the basal area, the volume of trees in an area, and the value of the timber. Inventories can be done for other reasons than just calculating the value. A forest can be cruised to visually assess timber and determine potential fire hazards and the risk of fire. The results of this type of inventory can be used in preventative actions and also awareness. Wildlife surveys can be undertaken in conjunction with timber inventory to determine the number and type of wildlife within a forest. The aim of the statistical forest inventory is to provide comprehensive information about the state and dynamics of forests for strategic and management planning.
History
Surveying and taking inventory of trees originated in Europe in the late 18th century out of a fear that wood (the main source of fuel) would run out. The first information was organized into maps used to plan out usage. In the early 19th century forest harvesters estimated the volume and dispersal of trees within smaller forests with their eyes. More diverse and larger forests were divided into smaller sections of similar type trees that were individually estimated by visual inspection. These estimates were related together to figure out the entire forest’s available resources. As the 19th century progressed so did the measurement techniques. New relationships between diameter, height, and volume were discovered and exploited. These newfound relationships allowed for a more accurate assessment of wood types and yields of much larger forests. By 1891, these surveys were conducted through sample-based methods involving statistical averages and more sophisticated measuring devices were implemented. In the 20th century, the statistical method of sampling had become well established and commonly used. Further developments, such as unequal probability sampling, arose. As the 20th century progressed, an understanding of co efficients of error became clearer and the new technology of computers combined with the availability of aerial as well as satellite photography, further refined the process. Laser Scanning both terrestrially and aerially are now used alongside more manual methods. As a result sampling accuracy and assessment values became more accurate and allowed for modern practices to arise.
A forest inventory does not only record the trees height, DBH and number for tree yield calculations. But it also records the conditions of the forest. So this would include, geology, site conditions, tree health and other forest factors.
Merely looking at the forest for assessment is called taxation.
Timber cruise
A timber cruise is a sample measurement of a stand used to estimate the amount of standing timber that the forest contains. These measurements are collected at sample locations called plots, quadrants, or strips. Each of these individual sample areas is one observation in a series of observations called a sample. These sample areas are generally laid out in some random fashion usually in the form of a line plot survey. Depending on the size of the plot and the number of plots measured, the data gathered from these plots can then be manipulated to achieve varying levels of certainty for an estimate that can be applied to the entire timber stand. This estimate of stand conditions, species composition, volume and other measured attributes of a forest system can then be used for various purposes. For example in British Columbia the sale of Crown timber is a business proposition and both the buyer and the Ministry of Forests and Range (seller) must know the quantity and the quality of timber being sold. The cruise provides the essential data for determining stumpage rates, for establishing conditions of sale and for planning of the logging operations by the licensee. Generally a timber cruise includes measurements or estimates of timber volume by forest product sort (and sometimes grade), log defect, and log lengths, whether the estimates are made in the field or using computer software.
Stand examination
Today, the most common type of inventory is one that uses a random sampling technique which groups similar forests into one category based on age, stand structure, species, and location. The next step would be to begin from a random place and measure circular plots that are equidistant from one another. Inventory undertaken in conjunction with wildlife surveys has a regularized distance between plots. When taking inventory, a decision has to be made about which types of plots to measure. There are several different types of plots. The two most common types are fixed radius and variable radius, also known as prism radius. In a fixed radius plot, the forester finds the center of a plot and every tree within a certain fixed distance away from that point is measured. Variable radius plots are used more for inventory of volume. During this method, an angle is created and projected from the plot center and all trees that are larger than the projected angle are measured.
Types of sample plots
Fixed area plot
Fixed area plot sample measurements are taken so that they are a fraction of the entire timber stand. This means that the numbers are all proportional to the actual stand values and that by multiplying by the correct corresponding value you can obtain the actual tract values. These plots are taken randomly so that each sample point has an equal probability of being included in the random sample. Commonly a 100m² plot is taken.
Variable size plots
A variable size plot is more dependent of the size of the trees. The tract is measured on a series of points and the trees are tallied for being in or out depending on their size and location relevant to the plot center. Usually an angle gauge or a wedge prism are used to gather data for this type of plot. This allows for a very quick estimate of the volume and species of a given tract. A common way of doing this is to select BAF 4.
Transects
Transects are arbitrarily determined lines (to prevent sampling bias) through a stand employed as a linear form of sample plot. They are sometimes referred to as "strip lines."
Plot selection
Plots are samples of the forest being inventoried and so are selected according to what is looked for.
Simple random sampling
A computer or calculator random number generator is used to assign plots to be sampled. Here random means an equal chance of any plot being selected out of all of the plots available. It does not mean haphazard. Often it is modified to avoid sampling roads, ensure coverage of unsampled areas and for logistics of actually getting to the plots.
Systematic sampling
Commonly this is done by a random point and then laying a grid over a map of the area to be sampled. This grid will have preassigned plot areas to be sampled. It means more efficient logistics and removes some of the human bias that may be there with simple random sampling.
Systematic stratified sampling
There is some broad grouping, for example by age classes or soil characteristics or slope elevation. And then plots are chosen from each grouping by another sampling technique. It requires some knowledge of the land first and also trust that the groupings have been done properly. In forestry it may be done to separate plantation areas from mixed forest for example and reduce the amount of sampling time needed.
Systematic clustered sampling
When it is not possible to make strata for stratified sampling, there may be some knowledge about the forest where it can be said that small groupings are possible. These small groupings of plots if they are near to each other form a cluster. These clusters are then randomly sampled with the belief that they are representing the actual mix of the forest. As they are close to each other there is less waking needed and so it is more efficient.
Timber metrics
The amount of standing timber that a forest contains is determined from:
- Basal area – defines the area of a given section of land that is occupied by the cross-section of tree trunks and stems at their base
- Diameter at breast height (DBH) – measurement of a tree's girth standardized at 1.3 meters (about 4.5 feet) above the ground
- Form factor – the shape of the tree, based on recorded trees and commonly then given for calculating tree volumes for a given species. It is usually related to DBH or age class. It is distinct from taper.[2] So it can be Cone or paraboloid for example.
- Girard form class – an expression of tree taper calculated as the ratio of diameter inside the bark at 16 feet above ground to the to that outside bark at DBH, primary expression of tree form used in the United States
- Quadratic mean diameter – diameter of the tree that coordinates to the stand's basal area
- Site index – a species specific measure of site productivity and management options, reported as the height of dominant and co-dominant trees (site trees)in a stand at a base age such as 25, 50 and 100 years
- Tree taper – the degree to which a tree's stem or bole decreases in diameter as a function of height above ground. So it can be sharp or gradual.
Volume estimation
- Stocking – a quantitative measure of the area occupied by trees relative to an optimum or desired level of density
- Stand Density Index – a measure of the stocking of a stand of trees based on the number of trees per unit area and DBH of the tree of average basal area
- Volume table – a chart based on volume equations that uses correlations between certain aspects of a tree to estimate the standing volume
- Stand density management diagram – model that uses current stand density to project future stand composition
Volume can be calculated from the metrics recorded in a plot sample. For example if a tree was measured to be 20m tall and with a DBH of 19 cm using previous measured tree data a volume could be approximated according to species. Such a table has been constructed by Josef Pollanschütz[3] in Austria.
Volume of tree = BA X h x f pollanschutz
So f pollanschütz would be derived from the table and is properly called the Form Factor.
To scale this up to a hectare level the result would have to be multiplied by the number of trees of that size. This is called the blow up factor.
Tools used in inventory
- Biltmore stick – utilizes ocular trigonometry to quickly measure diameter and height
- Diameter tape – cloth or metal tape that is wrapped around the bole, scaled to diameter
- Caliper – two prongs connected to a measuring tape are placed around the most average part of the bole to determine diameter
- Relascope – multiple-use tool that is able to find tree height, basal area, and tree diameter anywhere along the bole
- Clinometer – common tool used to measure changes in elevation and tree height
- Cruising rod – similar to a caliper, calculates the number of pieces of lumber yielded by a given piece of timber by measuring its diameter
- LASER Scanner used with computer software to calculate the metrics from the collected data by use of Lidar.[4]
- Wedge prism – a small glass wedge that refracts light to create visible offsets in order to be able to choose which trees at a sampling point should be included in the sample.
- Data collector – an electronic device used to quickly enter sample data, geo-locate the data, and, in more modern times, to also access reference, web and historic materials while timber cruising.[5]
- Increment borer – a device used to retrieve a cylindrical sample of wood material orthogonally from the stem while doing as little damage as possible to the remaining tissues.[6]
In 2014, the Food and Agriculture Organization of the United Nations and partners, with the support of the Government of Finland, launched Open Foris – a set of open-source software tools that assist countries in gathering, producing and disseminating reliable information on the state of forest resources. The tools support the entire inventory lifecycle, from needs assessment, design, planning, field data collection and management, estimation analysis, and dissemination. Remote sensing image processing tools are included, as well as tools for international reporting for REDD+ MRV and FAO's Global Forest Resource Assessments.
See also
- Eastern Native Tree Society
- Forest informatics
- Forest management
- Reducing Emissions from Deforestation and Forest Degradation (REDD)
- National forest inventory (NFI)
- Tree measurement
External links
References
Notes
- ↑ L. J. Moores, B. Pittman, G. Kitchen (1996), "Forest ecological classification and mapping: their application for ecosystem management in Newfoundland", Environmental Monitoring and Assessment 39 (1–3): 571–577, doi:10.1007/bf00396169
- ↑ http://www.bodley.ox.ac.uk/users/millsr/isbes/ODLF/IP32.pdf
- ↑ http://www.fs.fed.us/pnw/pubs/pnw_rp345.pdf
- ↑ "Treemetrics.com | Treemetrics | Cutting Edge Forest Optimization". Treemetrics. 2013-01-22. Retrieved 2013-10-04.
- ↑ "Forest Metrix – Forest Inventory and Timber Cruise Software". Forestmetrix.com. 2013-06-16. Retrieved 2013-10-04.
- ↑ "Keepers of Prometheus: The World’s Oldest Tree". UANews. Retrieved 2013-10-04.
Bibliography
- Brack, Cris L. “A Brief History of Forest Inventory.” History of Inventory. 27 Mar. 2008
- Leblanc, John W. "What Do We Own: Understanding Forest Inventory." Working in the Woods. University of California Cooperative Extension. 28 Mar. 2008
- R. Hédl, M. Svátek, M. Dancak, Rodzay A.W., M. Salleh A.B., Kamariah A.S. A new technique for inventory of permanent plots in tropical forests: a case study from lowland dipterocarp forest in Kuala Belalong, Brunei Darussalam, In Blumea 54, 2009, p 124–130. Publié 30. 10. 2009.
- http://www.fs.fed.us/fmsc/measure/cruising/index.shtml
- http://www.for.gov.bc.ca/ftp/hva/external/!publish/Web/Manuals/Cruising/2010/Cruising2010MayMaster_Red.pdf
- Avery and Burkhart, Forest Measurements. 5th ed. McGraw Hill, New York, 2002
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