Use of satellite SAR for monitoring rain forest

Christopher John Oliver; Kevin O. Grover; Sidnei Sant'Anna; Corina da Costa Freitas

doi:10.1117/12.373160

10 December 1999 Use of satellite SAR for monitoring rain forest

Christopher John Oliver, Kevin O. Grover, Sidnei Sant'Anna, Corina da Costa Freitas

Proceedings Volume 3869, SAR Image Analysis, Modeling, and Techniques II; (1999) https://doi.org/10.1117/12.373160
Event: Remote Sensing, 1999, Florence, Italy

Abstract

In this paper we compare the capability of Landsat TM optical imagery, JERS L-band and Radarsat C-band SAR for classifying rain forest into forest and not forest categories. In each case, simulated annealing provides the global optimum segmentation of the underlying variable. For the optical image the information is carried by the brightness, for JERS1 by the mean intensity and for Radarsat by the scene texture, where texture can be optimally measured in terms of the normalized log. We demonstrate that JERS1 and Radarsat provide similar classification into forest and not forest categories, when Landsat TM Band 5 imagery is adopted as the reference. Most of the discrepancies arise in regions of regeneration, where the physical difference between the imaging mechanisms of the three sensors has greatest impact.

Citation Download Citation

Christopher John Oliver, Kevin O. Grover, Sidnei Sant'Anna, and Corina da Costa Freitas "Use of satellite SAR for monitoring rain forest", Proc. SPIE 3869, SAR Image Analysis, Modeling, and Techniques II, (10 December 1999); https://doi.org/10.1117/12.373160

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