An evaluation of AIRSAR and SIR-C/X-SAR images for mapping northern forest attributes in Maine, USA

Abstract

In previous work by the authors, multifrequency, polarimetric airborne synthetic aperture radar (AIRSAR) data were used to characterize forest categories and biomass density of a forest area in Maine, USA. This study area was included as a test site for ecological studies during the Spaceborne Imaging Radar C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) missions in 1994. The SIR-C/X-SAR missions provided the first opportunity for Earth scientists to receive multifrequency and multipolarization SAR data from space from a single platform. During the Space Radar Laboratory missions in April and October 1994, images from AIRSAR and SIR-C/X-SAR were acquired for the same areas within a few days of each other. In this paper, the capabilities of AIRSAR and SIR-C/X-SAR images for characterizing a northern hardwood-boreal transitional forest were evaluated and compared. The use of multiple frequency, polarimetric information to produce forest-cover classification, biomass estimates, and forest spatial pattern analysis were investigated. The results from SIR-C/X-SAR compared with those from AIRSAR were generally similar despite different available frequencies (C-band, L-band, X-band vs. C-band, L-band, P-band) and resolution (25.0 m vs. 8.3 m). AIRSAR data better enabled the mapping of stands of hardwood and mixed forests than did SIR-C/X-SAR data. However, SIR-C/X-SAR produced better classification results for conifer forest stands. There was no great benefit from using higher resolution for classification except for forest stands in which there were mixtures of species (i.e., hardwood and softwood). A comparison of the image data also showed that both instruments could provide reasonable estimates of biomass density up to about 15 kg/m 2. At higher biomass levels, both AIRSAR and SIR-C showed the well-known biomass saturation effect. The average biomass densities determined from the AIRSAR and SIR-C images were reasonably close at 9.7 kg/m 2 and 9.0 kg/m 2, respectively. Finally, spatial character of the image data was examined by using perimeter and area relations and lacunarity analysis. The results were consistent between the two instruments and showed that the forest opening patterns were self-similar for openings greater than about 3 ha.