Improving the precision of sample-based forest damage inventories through two-phase sampling and post-stratification using remotely sensed auxiliary information.

Many countries have a national forest inventory (NFI) designed to produce statistically sound estimates of forest parameters. However, this type of inventory may not provide reliable results for forest damage which usually affects only small parts of the forest in a country. For this reason, specially designed forest damage inventories are performed in many countries, sometimes in coordination with the NFIs. In this study, we evaluated a new approach for damage inventory where existing NFI data form the basis for two-phase sampling for stratification and remotely sensed auxiliary data are applied for further improvement of precision through post-stratification. We applied Monte Carlo sampling simulation to evaluate different sampling strategies linked to different damage scenarios. The use of existing NFI data in a two-phase sampling for stratification design resulted in a relative efficiency of 50 % or lower, i.e., the variance was at least halved compared to a simple random sample of the same size. With post-stratification based on simulated remotely sensed auxiliary data, there was additional improvement, which depended on the accuracy of the auxiliary data and the properties of the forest damage. In many cases, the relative efficiency was further reduced by as much as one-half. In conclusion, the results show that substantial gains in precision can be obtained by utilizing auxiliary information in forest damage surveys, through two-phase sampling, through post-stratification, and through the combination of these two approaches, i.e., post-stratified two-phase sampling for stratification.

Adapting forest health assessments to changing perspectives on threats--a case example from Sweden.

A revised Swedish forest health assessment system is presented. The assessment system is composed of several interacting components which target information needs for strategic and operational decision making and accommodate a continuously expanding knowledge base. The main motivation for separating information for strategic and operational decision making is that major damage outbreaks are often scattered throughout the landscape. Generally, large-scale inventories (such as national forest inventories) cannot provide adequate information for mitigation measures. In addition to broad monitoring programs that provide time-series information on known damaging agents and their effects, there is also a need for local and regional inventories adapted to specific damage events. While information for decision making is the major focus of the health assessment system, the system also contributes to expanding the knowledge base of forest conditions. For example, the integrated monitoring programs provide a better understanding of ecological processes linked to forest health. The new health assessment system should be able to respond to the need for quick and reliable information and thus will be an important part of the future monitoring of Swedish forests.

The accuracy of forest damage assessments--experiences from Sweden.

In this article the consistency of forest damage assessments on conifer trees is analysed, by using different methods in estimating the accuracy in assessments of defoliation and discolouration. The data originate from control surveys in the Swedish national forest damage survey, as well as from national and international training courses. Standard deviation of differences in the assessment of defoliation on single trees is found to be about 10% units for Norway spruce and 8.5% for Scots pine. Problems in correctly assessing damaged Scots pine trees and discoloured Norway spruce trees are revealed by measures of agreement (Kappa statistic). Results from several years of national training courses indicate that, on an average, the observer teams do not significantly differ from a national standard, but significant differences between observer teams are found. The presented estimates indicate a substantial within observer error compared to the between observer error. The results indicate that the long-term development of forest damage, rather than short-term fluctuations, is the most important information from these kinds of inventories.