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

Automated summary

Detecting field diversities using remote sensing is important for monitoring vegetation dynamics at large scale. The impact of image resolutions and spectral plot extents on estimating forest alpha-diversities and compositional variances was examined on Mount Usu in Japan. Low-resolution spectral indicators from narrow plot extents showed the highest correlations with canopy and total diversities, with the best indicators derived from principal component analysis and near infrared band.