Evaluation of red-edge spectral information for biotope mapping using RapidEye

Abstract

Mapping of Landscape Protection Areas with regard to user requirements for detailed land cover and biotope classes has been limited by the spatial and temporal resolution of Earth observation data. With the new spatial high resolution RapidEye data providing an additional channel in the red-edge region potentially new possibilities for vegetation mapping should be investigated. The presented work is part of the ENVILAND-2 project, which focuses on the complementary use of RapidEye and TerraSAR-X data to derive land cover and biotope classes as needed by the environmental agencies. The goal is to semi-automatically update the corresponding maps by utilising more Earth observation data and less field work derived information. The red-edge spectral region located between the red and near infrared (NIR) wavelengths, has proven to held valuable information on vegetation type, age and condition. In this study the goal is to evaluate the red-edge spectral information compared to the shorter and longer wavelength of the RapidEye sensor. This is done with regard to the classification capability of different land cover classes. Four RapidEye images were used covering two study sites: 1. Rostocker Heide, Mecklenburg-Vorpommern and 2. Elsteraue, Saxony. The spectral bands were analysed for redundant information by using regression and hypothesis testing. For the rededge band and for every class combination present in the study area different separability measurements like divergence or Bhattacharyya distance were computed. As result there are for every class a separability values. The separability values are provided for all spectral bands. A comparison of the values showed the applicability of the red-edge for the classification. Results have shown that additional red-edge information leads to similar class separability for vegetation classes as using red and NIR spectral information. Some specific classes can be classified with a higher accuracy by additional using the red-edge information.