Integration of statistical forest reflectance model and Sentinel-2 MSI images into a continuous forest inventory system

  • Andres Kuusk University of Tartu, Tartu Observatory
  • Dr. Mait Lang Estonian University of Life Sciences. University of Tartu, Tartu Observatory.

Abstract

Spectral signatures of forest stands in Sentinel-2 MSI spectral bands are simulated with the statistical forest reflectance (SFRM) model and compared to the spectral signatures measured in spectral images at ten study sites in Estonia. As an overall measure of the agreement between simulated and measured spectral signatures we used the total error calculated as the sum of relative errors over spectral bands B2 to B11 of Sentinel-2. The distribution of the total error has strongly positive skewness at all study sites and all types of forests (broadleaf, pine and spruce forests). The right tail of the distribution is low. The stands of high value of the total error far right in the tail of the distribution may have some errors in their inventory data, or the inventory data are outdated. Pertinent stands should have priority in their in situ checking process. The SFRM model is a simple and reliable tool for the validity checking of forest inventory data, using routinely collected forest inventory data and operational satellite information of moderate spatial resolution. The model is simple and computationally efficient. Preparing input data for the model is a simple query in the forest inventory database. The suggested procedure can be incorporated into the automated systems of continuous forest inventory.   Keywords: Forest inventory, Sentinel-2 MSI images, Statistical forest reflectance model
Published
2020-07-31
Section
Remote Sensing Technology