Utilization of hyperspectral image optical indices to assess the Norway spruce forest health status

Abstract

The work is concerned with assessing the health status of trees of the Norway spruce species using airborne hyperspectral (HS) data (HyMap). The study was conducted in the Sokolov basin in the western part of the Czech Republic. First, statistics were employed to assess and validate diverse empirical models based on spectral information using the ground truth data (biochemically determined chlorophyll content). The model attaining the greatest accuracy (D718/D704∶RMSE = 0.2055 mg/g, R² = 0.9370) was selected to produce a map of foliar chlorophyll concentrations (Cab). The Cab values retrieved from the HS data were tested together with other nonquantitative vegetation indicators derived from the HyMap image reflectance to create a statistical method allowing assessment of the condition of Norway spruce. As a result, we integrated the following HyMap derived parameters (Cab, REP, and SIPI) to assess the subtle changes in physiological status of the macroscopically undamaged foliage of Norway spruce within the four studied test sites. Our classification results and the previously published studies dealing with assessing the condition of Norway spruce using chlorophyll contents are in a good agreement and indicate that this method is potentially useful for general applicability after further testing and validation.