Forest Cover Mapping Based on a Combination of Aerial Images and Sentinel-2 Satellite Data Compared to National Forest Inventory Data
Open Access
- 11 December 2020
- Vol. 11 (12), 1322
- https://doi.org/10.3390/f11121322
Abstract
Research Highlights: This study developed the first remote sensing-based forest cover map of Baden-Württemberg, Germany, in a very high level of detail. Background and Objectives: As available global or pan-European forest maps have a low level of detail and the forest definition is not considered, administrative data are often oversimplified or out of date. Consequently, there is an important need for spatio-temporally explicit forest maps. The main objective of the present study was to generate a forest cover map of Baden-Württemberg, taking the German forest definition into account. Furthermore, we compared the results to NFI data; incongruences were categorized and quantified. Materials and Methods: We used a multisensory approach involving both aerial images and Sentinel-2 data. The applied methods are almost completely automated and therefore suitable for area-wide forest mapping. Results: According to our results, approximately 37.12% of the state is covered by forest, which agrees very well with the results of the NFI report (37.26% ± 0.44%). We showed that the forest cover map could be derived by aerial images and Sentinel-2 data including various data acquisition conditions and settings. Comparisons between the forest cover map and 34,429 NFI plots resulted in a spatial agreement of 95.21% overall. We identified four reasons for incongruences: (a) edge effects at forest borders (2.08%), (b) different forest definitions since NFI does not specify minimum tree height (2.04%), (c) land cover does not match land use (0.66%) and (d) errors in the forest cover layer (0.01%). Conclusions: The introduced approach is a valuable technique for mapping forest cover in a high level of detail. The developed forest cover map is frequently updated and thus can be used for monitoring purposes and for assisting a wide range of forest science, biodiversity or climate change-related studies.Keywords
This publication has 43 references indexed in Scilit:
- Economic impact of enhanced forest inventory information and merchandizing yards in the forest product industry supply chainSocio-Economic Planning Sciences, 2014
- New global forest/non-forest maps from ALOS PALSAR data (2007–2010)Remote Sensing of Environment, 2014
- High-Resolution Global Maps of 21st-Century Forest Cover ChangeScience, 2013
- Linking landscape patterns with ecological functions: A case study examining the interaction between landscape heterogeneity and carbon stock of urban forests in Xiamen, ChinaForest Ecology and Management, 2013
- Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational ServicesRemote Sensing of Environment, 2012
- Quantification of global gross forest cover lossProceedings of the National Academy of Sciences, 2010
- Different methods, different wilds: Evaluating alternative mappings of wildness using fuzzy MCE and Dempster-Shafer MCEComputers, Environment and Urban Systems, 2009
- Pan-European forest/non-forest mapping with Landsat ETM+ and CORINE Land Cover 2000 dataISPRS Journal of Photogrammetry and Remote Sensing, 2009
- High‐resolution digital surface models (DSMs) for modelling fractional shrub/tree cover in a mire environmentInternational Journal of Remote Sensing, 2008
- Forest Cover of Insular Southeast Asia Mapped from Recent Satellite Images of Coarse Spatial ResolutionAMBIO, 2003