I. Introduction
The normalization of synthetic aperture radar (SAR) imagery for systematic terrain variations is required for meaningful multi-sensor or even single-sensor multi-track intercomparisons. Accurate backscatter estimates enable more robust use of the retrieved values in applications such as the monitoring of deforestation, land-cover classification, and delineation of wet snow covered area. Accurate estimates of backscatter in the presence of severe terrain furthermore relax constraints on same-orbit exact-repeat observations for change detection: this enables shorter temporal intervals between observations, especially given wide swath imagery, and also opens the door to multi-sensor backscatter overlays. Where the local terrain is ignored due to either lack of DHM-availability or runtime-constraints leading to a need for a simpler Earth model, then the quality of the retrievable backscatter estimate is compromised. This paper extends prevailing traditional concepts of backscatter normalization, introducing a new standard known as terrain-corrected gamma naught.