Skip to content
Login has been disabled on EnviDat Legacy. Please log in via https://envidat.ch first, then refresh this page.

Changes

View changes from to


On March 10, 2025 at 8:12:58 PM UTC, Gravatar Lars Waser:
  • Updated description of resource Forest Type NFI 2016 in Forest Type NFI from

    This dataset presents a countrywide map with the two classes broadleaf and coniferous in Switzerland based on digital aerial imagery. The spatial resolution of the data set is 3 m. The pixel values correspond to the probabilities (0-100 %) of the class broadleaf. The classification approach incorporates a RF classifier, predictors from multispectral aerial imagery (ADS80) and the SwissAlti3D terrain model. The model was tested, trained and validated using 90,000 digitized polygons and achieved an overall accuracy of 0.99 and a kappa of 0.98. Independent validation and plausibility check included the comparison of the predicted results with aerial image interpretations of the NFI. Significant deviations were observed, primarily due to an underestimation of broadleaved trees (median underestimation of 3.17%), especially in mixed forest stands. For more details, see Waser et al. (2017). Data 'Forest Type NFI 2016' is freely available on request (lars.waser@wsl.ch).
    to
    This dataset presents a countrywide map with the two classes broadleaf and coniferous in Switzerland based on digital aerial imagery. The spatial resolution of the data set is 3m. The pixel values correspond to the probabilities (0-100 %) of the class broadleaf. The classification approach incorporates a RF classifier, predictors from multispectral aerial imagery (ADS80) and the SwissAlti3D terrain model. The model was tested, trained and validated using 90,000 digitized polygons and achieved an overall accuracy of 0.99 and a kappa of 0.98. Independent validation and plausibility check included the comparison of the predictions with aerial image interpretations of the NFI. Significant deviations were observed, primarily due to an underestimation of broadleaved trees (median underestimation of 3.17%), especially in mixed forest stands. For more details, see Waser et al. (2017). Data 'Forest Type NFI 2016' is freely available on request (lars.waser@wsl.ch).