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Abstract:New forest inventory methods must be developed in order to create good conditions for decision‐making regarding ecological and economical issues in forestry. There are good field measurement methods to use, but they are often very expensive. Coherent all radio band sensing (CARABAS) is a newly developed synthetic aperture radar (SAR) sensor. It differs significantly from the earlier SARs by using longer wavelengths. The CARABAS sensor is more adapted to the scatterers of interest in the forest, due to its longer wavelengths. In this study, CARABAS imagery is compared with forest tree volume. Regression analysis was used to relate radar backscattering to forest tree volume. Due to the large range of incidence angle (45°‐68°), the CARABAS image had to be radiometrically relative‐calibrated. Radar backscattering from five forest stands with similar volume contents were plotted against the distance from the sensor. The plot revealed a linear relationship between these variables. By linear regression on that material the other pixels were relative‐calibrated in the image. Finally, radar backscattering was related to forest stand volumes by using linear regression. The results showed that the backscattering component of the CARABAS imagery is highly correlated to forest tree volume (R2 = 74.9%). In this material, there seemed to be no saturation level of the backscattering component up to 300 m3 ha?1.
Keywords:forest inventory  forest tree volume  remote sensing  synthetic aperture radar
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