Abstract
A key factor for operational forest management and forest monitoring is the availability of up-to-date spatial information on the state of forest resources. Earth observation can provide valuable contributions to these information needs. The German federal state of Rhineland-Palatinate transferred its inherited forest information system to a new architecture that is better able to serve the needs of centralized inventory and planning services, down to the level of forest districts. During this process, a spatially adaptive classification approach was developed to derive high-resolution forest information layers (e.g., forest type, tree species distribution, development stages) based on multi-temporal satellite data. This study covers the application of the developed approach to a regional scale (federal state level) and the further adaptation of the design to meet the information needs of the state forest service. The results confirm that the operational requirements for mapping accuracy can, in principle, be fulfilled. However, the state-wide mapping experiment also revealed that the ability to meet the required level of accuracy is largely dependent on the availability of satellite observations within the optimum phenological time-windows.
Highlights
IntroductionForests and forest ecosystems are under accelerating pressure from regional impacts of global warming and changing socio-economic conditions [3]
Accurate and up-to-date information on the spatial distribution of forest type, forest cover, and tree species composition is a key factor for sustainable forest management and a central component of forest monitoring programs [10]
Production of satellite-based forest information layers for the complete federal state of RLP, comprising maps of forest/non-forest distribution, forest types, tree species at stand level, and tree species enhanced by three corresponding developmental stages
Summary
Forests and forest ecosystems are under accelerating pressure from regional impacts of global warming and changing socio-economic conditions [3]. Within this framework, multiple national and international commitments dealing with forest resources, sustainable forest management, and biodiversity—such as the Montréal Process [4], the Kyoto Protocol [5], the Convention on Sustainable. Accurate and up-to-date information on the spatial distribution of forest type, forest cover, and tree species composition is a key factor for sustainable forest management and a central component of forest monitoring programs [10]
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