Forest woody biomass classification with satellite-based radar coherence over 900 000 km2 in Central Siberia.

In the current context of global deforestation and global warming, a wide range of organisations, with local to international remits, need estimates of forest biomass to assess the state of the World’s forests and their rate of change. The task would be impossible without space-based Earth observation, which allows the rapid generation of extensive data sets describing land surface properties. It is the task of remote sensing scientists to interpret these data into a meaningful source of forest information. Here, a fast and easily automated method for classifying boreal forests in terms of growing stock volume is presented. The work was conducted as part of the SIBERIA project, which has resulted in the recent publication of a map of forest growing stock volume covering 900 000 km² in Central Siberia. The paper describes the use of satellite-based radar coherence to differentiate categories of forest growing stock volume, the application of this method to classify and map Central Siberian forests, and the characterisation of the forest classes to help in the interpretation. A list of acronyms and abbreviations used in the text is provided in . [Copyright &y& Elsevier]