Journal
FORESTS
Volume 6, Issue 6, Pages 1982-2013Publisher
MDPI
DOI: 10.3390/f6061982
Keywords
remote sensing; forest information layers; tree species mapping; spatially adaptive classification; Central Europe; operational forest management
Categories
Funding
- EU
- project: Extraktion und Klassifikation inventurrelevanter Forstparameter aus multi-temporalen Sentinel-2-Daten [FKZ 50EE1202]
- INTERREG IVB program in Northwest Europe
- German Federal Ministry for Economic Affairs and Energy
- RESA project [628]
- Zentralstelle der Forstverwaltung-Research Institute for Forest Ecology and Forestry Rhineland-Palatinate (FAWF)
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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.
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