Predicting and mapping mangrove biomass from canopy grain analysis using Fourier-based textural ordination of IKONOS images

Predicting structural organization and biomass of tropical forest from remote sensing observation constitutes a great challenge. We assessed the potential of Fourier-based textural ordination (FOTO) to estimate mangrove forest biomass from very high resolution (VHR) IKONOS images. The FOTO method computes texture indices of canopy grain by performing a standardized principal component analysis (PCA) on the Fourier spectra obtained for image windows of adequate size. For two distinct study sites in French Guiana, FOTO indices derived from a 1 m panchromatic channel were able to consistently capture the whole gradient of canopy grain observed from the youngest to decaying stages of mangrove development, without requiring any intersite image correction. In addition, a multiple linear regression based on the three main textural indices yielded accurate predictions of mangrove total aboveground biomass. Since FOTO indices did not saturate for high biomass values, predictions were furthermore unbiased, even for levels above 450 t of dry matter per hectare. Maps of canopy texture (with RGB coding) and biomass were then produced over 8000 ha of unexplored, low accessibility mangrove. Applying the FOTO method to the 4 m near-infrared channel yielded acceptable results with some limitations for characterization of juvenile mangrove types. We finally discuss the influence of technical aspects pertaining to VHR images and to FOTO implementation (especially the size of the window used to compute Fourier spectra) and we evoke the interesting prospect of broad regional validity offered by the method to characterize high biomass tropical forest from standardized measures of canopy grain.