Abstract: [Objective] The periodical information of forest areas in the high spatial resolution remote sensing image contains the structural and spatial distribution of forest canopy grains.We used the Fourier-based textural ordination (FOTO) indices for estimating forest aboveground biomass (AGB). This research explored FOTO textural indices as a potential technique to estimate forest AGB of temperate forest.[Method] The study area is located in the Liangshui Natural Reserve (47°11'N, 128°53'E), northeast of China. Based on the high spatial resolution airborne CCD data (0.5 m spatial resolution) acquired in September 2009, we derived the FOTO indices from CCD data and established the AGB regression model with multiple stepwise regression. The airborne LiDAR-derived AGB map was used as reference value. We compared the model performances of FOTO indices derived from three spectral reflection bands of CCD data with those from the average spectral reflection band of the CCD data. The window sizes for FOTO method were set as 60 m×60 m, 80 m×80 m, 100 m×100 m, 120 m×120 m and 150 m×150 m. Then the FOTO indices derived from different size windows were used as independent variables to build regression model with LiDAR-derived biomass. Ten-fold validation was performed to verify the generalization capability of the estimation model.[Result] The results showed that texture indices derived from FOTO method had a high correlation with forest AGB. The determination coefficient R² between the FOTO indices (9 FOTO indices from three spectral reflection bands) and LiDAR derived AGB were all above 0.67 for five windows sizes. The estimation accuracies were 67.3%, 73.4%, 74.4%, 78.3% and 80.9% for window size 60 m×60 m, 80 m×80 m, 100 m×100 m, 120 m×120 m and 150 m×150 m, respectively. The determination coefficient R² between the FOTO indices (3 FOTO indices from the average band) and LiDAR derived AGB were all above 0.57 for five windows sizes. The estimation accuracies were 58.2%, 62.1%, 64.3%, 67.4% and 70.9% for five windows sizes, respectively. We produced a wall-to-wall forest AGB map with the accuracy of 74.41% and the RMSE of 50.55 t·hm^-2.[Conclusion] This study results indicated that texture indices derived from FOTO method have great potential in estimating forest AGB without significant saturation phenomenon in temperate forests. FOTO indices have great potential for estimating AGB of temperate forests. The forest biomass derived from FOTO indices with the multiple stepwise regression showed a good relationship with the LiDAR-derived AGB, with R²=0.81, RMSE=46.78 t·hm^-2.

Key words: temperate forest, high spatial resolution data, forest AGB, FOTO, texture indices