Scholarly record
REMOTE SENSING BASED FOREST MANAGEMENT IN CONJUNCTION WITH A SUCCESSION SIMULATION
Abstract
In this paper we will describe a novel approach for forest management that includes remote sensing based monitoring, simulation and planning. When we think about sustainable forest management, it is important to know the vital facts about the forest, especially the annual increment of the timber volume for each forestry unit. A terrestrial census could deliver the required information, but it is too expensive to be carried out frequently. The alternative is a census based on remote sensing data. In this area we observe a growing offer of available data sources, as well as an increased quality of the available data. The presented approach describes the forest on the level of forestry units as well as on the level of individual trees. It scales up to the level of states and can consider heterogeneous data that was recorded with different sensors and with different flight parameters. The resulting dataset lays the foundation for several analyses. We will show an automatic and an assisted forest inventory. But the generated forest information is more than just another inventory. It is included in a 4d geo information, visualization and simulation system and therefore can be used to display the forest in a multitude of applications. We will show, how a calculation model for the succession of species in grasslands and woodlands (GraS, WoodS), can benefit from the calculated description to initialize its grid-based model and its temporal simulation based on this structure. The result of GraS/WoodS is precise information about the number of individuals, their species, as well as their size and growth. It can predict the development of those areas when there is no intervention by the human. The results of the GraS/WoodS model are fed back in the forest information system, in order to support further calculation steps.
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