A Comparison of Two Methods for Detecting Tropical Forest Change Cover

Objective  In this paper, two methods from two "variant data" to detect tropical forest change were compared. Method  After Tasseled Cap transformation, the combine of Brightness index, Greenness index, Wetness index (MKT) and Disturbance index (DI) were obtained by masking the dark object and extracting local histogram threshold. Change information was discovered by the differences of MKT and DI, According to the connection between vegetation cover and Brightness index, Greenness index, Wetness index, the change information was extracted by decision tree classification, and the results were assessed and compared. Result  The results showed that they were all able to detect the subtle change of tropical forest, but, MKT-D take an obvious advantage to detect the small change spots, and the total kappa coefficient from MKT-D (0.763 0) was higher than that from MDI-D (0.655 9). For tropical forest change detection in this research, the result from MKT-D was better than that from MDI-D. Conclusion  MKT could enhance the effect of near-infrared and short wave infrared band to forest change information. Moreover, MKT-D is accessible to extraction and interpretation of target change information.