The report describes an evaluation of algorithms and models for change detection using SAR images in the VHFand UHF-band. Four algorithms with different test statistics have been evaluated using CARABAS (20-85 MHz) and LORA (225-470 MHz) data, respectively: 1) Amplitude ratio, 2) GLRT (Generalized Likelihood Ratio Test) using amplitude data, 3) GLRT using the logarithm of amplitude data, and 4) GLRT using complex data. The results show that different algorithms are optimal for CARABAS and LORA data, i.e. gives the lowest false-alarm-probability for a given detection probability. The reason is that the SAR data have different statistical distributions. GLRT using complex or amplitude data gives the best and almost identical results for CARABAS data with incidence angles 58° and 68°. Best results for 75° are given by GLRT using amplitude or the logarithm of amplitude data. GLRT using the logarithm of amplitude data gives the best results for LORA with incidence angles 50° and 64°. Best results for 75° are given by the amplitude ratio or GLRT using the logarithm of amplitude data. Several statistical models have also been tested for CARABAS (incidence angel 58° only) and LORA (incidence angle 50° only): 1) Gaussian, 2) complex Gaussian, 3) lognormal, 4) K-distribution, and 5) complex Gaussian + lognormal scene. The latter model gave the best fit to both CARABAS and LORA data.