Object‐oriented and textural image classification of the Siberia GBFM radar mosaic combined with MERIS imagery for continental scale land cover mapping

Boreal forests and wetlands play an important role in the climate system, in particular through biosphereatmosphere flux exchanges. They are an important pool of carbon and their role as sink or source of greenhouse gases is not fully understood. Accurate mapping of the vegetation of Siberia can therefore contribute to a better understanding of these processes at regional scale and of their effects on the climate\nthrough regional biosphere modeling. The potential of the combination of radar data with medium-resolution optical data to obtain regional scale land cover mapping is investigated using multi-spectral imagery from the MERIS sensor at 300 m resolution and a high resolution radar mosaic (pixel spacing of 100 m) covering Western and Eastern Siberia compiled in the framework of the Global Boreal Forest Mapping project, an initiative of the Japan Agency for Space Exploration (JAXA). For this purpose, capabilities of oriented-object image analysis associated to wavelet multi-resolution techniques are investigated. Results show that wavelet multi-resolution textures bring relevant additional information for land cover classification. Suggestions are made for the implementation of an object-based wavelet multi-resolution texture estimator.