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Selected Results of the Third National Forest Inventory

Surveying the forest

Ninety billion trees are growing in Germany’s forests. Approximately 7.6 billion of these trees are over 7 centimetres in diameter – too many to measure every single one. Scientists therefore use sampling techniques. They survey a small, but representative section of the forests and derive information from this about the German forests.

In the years 2011/2012, the National Forest Inventory was conducted for the third time. Earlier inventories were conducted in 1986-1988 and 2001/2002. The National Forest Inventory is an official mandate pursuant to Article 41a of the Federal Forest Act. It must be repeated every ten years.

For the Third National Forest Inventory, 60 inventory teams all over Germany measured approximately 420,000 trees at roughly 60,000 sample points and recorded many more terrain, stand and tree characteristics. But before inventory teams survey data in the forest, scientists have to answer many methodological questions. How should the samples be distributed over the forest? What and how many tree characteristics should be surveyed on site? What methods are efficient and economical? How can the quality of the data be ensured? What estimation methods provide statistically substantiated results?

Scientists at the Thünen Institute of Forest Ecosystems and experts of the Länder are constantly further developing the inventory procedure. Specially trained staff conduct the data survey in the forest.

Systematic sampling method

The National Forest Inventory is a terrestrial sample with permanent sampling points. Inventory teams always record data in the forest at the same sampling points. This is done in all of the Länder and in forests of all types of ownership according to a uniform method every ten years.

In order to produce a representative portrayal of the German forests, back in the 1980s the founders of the National Forest Inventory laid a four-by-four-kilometre sampling grid over the entire country that is used for every inventory. The samples are located at the grid’s junctions. Some of the Länder additionally densified the sampling grid.

Each sample, called a tract, is a square with 150 metre-long sides. The inventory teams survey the data at each of the corners, or plots, which are the sample points.

Preparing for field surveys

For each sample point, the Länder compile information in advance that is not recognizable on site. Using forest distribution maps, aerial photographs, cadastral plans, information from the local forestry offices and other forestry information, they ascertain characteristics such as the type of ownership, the size of the communal and private forests, restrictions to timber use, for example due to nature protection zones, or incidences of hoofed game animals.

Roaming the forests with laptops and tree height measurement devices

The sample point is invisibly marked with a metal rod. Satellite navigation, a map, a compass, distance measurements and a metal detector help to relocate the sample points after ten years.

Equipped with field laptops and measuring devices, the inventory teams record over 150 characteristics at each sample point according to a uniform method. These characteristics include the tree species, tree height and diameter of selected sample trees as well as the type and amount of deadwood.

Ensuring the quality of the data

The validity of an inventory stands and falls with the quality of the data. The quality controls therefore already begin while the data is being recorded in the forest.

It is based on a three-phase control system:

a) Controls during data entry: The inventory teams record the data with mobile field computers. Plausibility checks in the survey software are already run in the forest and indicate possible data errors. This means the inventory staff can correct the recorded data while still on site by re-measuring a value or survey and add overlooked values.

b) Controls of data collection: The Land inventory supervisors control on-site data collection at a minimum of 5% of the sample points, by recording trees and characteristics on site independently of the team.

c) Plausibility checks: The data in the survey database are sent to the central database. Using check runs and error logs, the Federal and Land inventory supervisors control the quality of the data compiled. The Land inventory supervisors either correct errors themselves, if possible, or demand that the respective inventory teams make the corrections.

Evaluating the data

Scientists at the Thünen Institute of Forest Ecosystems evaluate the individual data with the support of Länder experts.

Prior to analysis, they restructure the data for extrapolation and carry out a number of preparatory calculations. An example: The diameter of each sample tree is measured. Later, its volume is evaluated in order to calculate the timber stock.

Once the data basis has been created and checked, extrapolations are carried out for variables such as the forest area and for changes that the development of the forest exhibits since 2002. The complete evaluation of the data requires extensive analyses, interpretations, reconciliation and more checks.

Comparability of the results

Ten years passed between the Second and Third National Forest Inventory. The comparability of their results is one of the most important criteria for the inventory design. Still, the inventory procedure has to be adjusted again and again. Technical advancements, new scientific findings and new issues have to be taken into account. Differences to earlier published results can arise when new statistical estimation methods were applied. Therefore, the scientists re-evaluate the data from the 2002 inventory using the current methods so that the results can be compared with the 2012 National Forest Inventory and changes can be correctly estimated.

The sample size of the National Forest Inventory is representative and supplies reliable assertions for the entire German forest and most Länder.

If the region is too small or the question too detailed, the sample representativeness suffers so that assertions for small-area question cannot be reliably answered.

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