Data and information
Forest inventories usually generate a specific set of data mainly descriptive statistics including precision statements on qualitative (e.g. species) and quantitative (e.g. tree diameter) attributes. Also maps can be generated if remote sensing is being integrated as data source. Only very rough maps can be generated from field sampling alone. Of interest is the estimation of the current status of the forest resource - but even more so the estimation of the changes that are taking place in the forests. It is mainly the interpretation of those changes that are an integral element of efficient monitoring systems for forest management and forest policy.
The data generated from a forest inventory need to follow quality “standards” with respect to statistical precision, accuracy and spatial resolution (size of reporting units). It is important to stress the aspect of data quality in all steps of a forest inventory; in particular the field crews, who are usually not further involved in the analysis and reporting process, need to know about the relevance of high quality measurements.
The information is usually of interest for many stakeholders including forestry and wood industry, agriculture, conservation, tourism etc. where each one of these groups has its specific interests and its specific ideas, expectations and also interpretations of forest inventory results.
Here, it is important to emphasize the difference between data and information: a forest inventory produces data. Data have a certain quality (in terms of measurement errors and standard error of estimation, for example) – but they are “objective”. When interpreting and assessing this data, information is generated. And the information derived from one and the same data can be different. It is mainly the information that is of interest for the forest manager and forest politician.
Many different variables (forest and tree attributes) are being observed in forest inventories. Usually, there is a core set of attributes that includes dbh, tree height, forest type etc., and the remaining attributes depend on the specific purpose of the inventory. We may group the attributes into those which refer to plot location (e.g. geographical data, ownership data, etc.), to production aspects (e.g. timber production, utilization options, accessibility, etc.), to forest state and structure (e.g. forest structure, regeneration, etc.) and other data including data on the inventory teams etc.
In forest management inventories usually about 20-35 variables are observed. In large area forest inventories, however, the number of variables may be more than 200! Sources of information include maps (using remote sensing methods), existing documents (e.g. publications or accounts), expert estimations and guesses, model estimation and projection of prior results, statistical and non-statistical inventory, etc.
