Climate change is creating an increasingly dynamic forest structure and there is a need to collect data more frequently in order to maintain up-to-date information for forest management.
The Institute of Forest Management at the Technische Universität München has explored the use of RapidEye satellite data to provide more frequent updates to the information database. Forest structural information such as quadratic mean diameter, basal area, stem number and volume were estimated using multi-seasonal analysis of three RapidEye datasets.
A correlation analysis was conducted between terrestrial inventory data and that derived from RapidEye data. A cross-validated stepwise forward regression analysis was performed and showed that stratification improved the regression models and results were of an acceptable level of accuracy.
The analysis confirmed the potential of RapidEye data to support forest management.
Click here for source (Forestry: An international journal of forest research)
