Remote sensing of forest diversities: the effect of image resolution and spectral plot extent

Detecting field diversities via remote sensing is becoming important to monitor vegetation dynamics at large scale. The characteristics of the remotely sensed image, depending on study organism and habitat, affect efficiency measuring ?-and ?-diversities. Therefore, we examined impact image resolutions spectral plot extents accuracy estimating forest ?-diversities compositional variances active volcano Mount Usu, northern Japan. Low- (3.2 m) high-resolution (0.8 IKONOS multispectral images were used create indicators from pixels covering plots (narrow extent) including neighbouring area (wide extent). Six diversity indices obtained for canopy canopy-herb layer (total diversity): species richness (S), Shannon (H’), evenness (J’), Gini-Simpson (D), true order 1 (N1 = expH’) 2 (N2 1/D). Changes in composition assessed by dissimilarity matrices. calculated combination extents, then compared with diversities. low-resolution–narrow extent based showed highest correlations total best derived scores first axis principal component analysis near infrared band, reaching high both indices. Of six diversities, J’ single indicators, N1, pairs indicators. between dissimilarities lower than unaffected resolution extent. In conclusion, combination, estimated temperate forests equally.