ALOS Palsar Winter Coherence and Summer Intensities for Large Scale Forest Monitoring in Siberia
Christian Thiel(1), Carolin Thiel(1), Johannes Reiche(1), Reik Leiterer(1), Maurizio Santoro(2) and Christian Schmullius(1)
(1) Friedrich-Schiller University, Loebdergraben 32, 07743 Jena, Germany
(2) Gamma Remote Sensing, Worbstrasse 225, CH-3073 Gümligen, Switzerland
SAR data has proved to offer great potential for forest cover mapping, forest disturbance mapping (e.g. logging, forest fire, and wind damage) and forest biomass assessment. Lower radar frequencies proved to be of particular adequacy. E.g. L-band SAR backscatter data acquired by the JERS-1 SAR was found to be suitable for mapping forest cover in the boreal zone. Radar backscatter and interferometric coherence have been successfully implemented. The launch of ALOS PALSAR offers new dimensions regarding spaceborne SAR data driven investigations. Compared to its antecessor JERS-1, PALSAR features a much increased performance in terms of image radiometry, geometry, and orbit steadiness. The controlled interferometric baseline combined with the well-defined observation strategy over the boreal zone very much enlarges the potential of interferometry based SAR data examinations in this region. Moreover, the capability of PALSAR to acquire multiple polarisations is of massive interest for forestry applications.
In this paper summer intensity and winter coherence images are used for large scale forest monitoring. The intensities (FBD HH/HV) have been acquired during summer 2007 and feature the K&C intensity stripes. The processing consisted of the conversion of the amplitude data to SAR intensities, including radiometric calibration and orthorectification. The coherence has been estimated from interferometric pairs with 46-days repeat-pass intervals. The pairs have been acquired during the winters 2006/2007 and 2007/2008. During both winters suited weather conditions (temperatures permanently below 0°C) have been reported. Interferometric processing consisted of SLC co-registration at sub-pixel level, common-band filtering in range and azimuth and generation of a differential interferogram. This was used in the coherence estimation procedure based on adaptive estimation. All images were geocoded using SRTM height data. The pixel size of the final SAR products is 50 m x 50 m.
It could already be demonstrated, that by using PALSAR intensities and PALSAR winter coherence forest and non-forest can be clearly separated. By combining both data types hardly any overlap of the class signatures was detected. Even though the analysis was conducted on pixel level and no speckle filter has been applied. Thus, the delineation of a forest cover mask could be executed operationally. The major difficulty is the definition of a biomass threshold for regrowing forest to be distinguished as forest.