Biomass estimation of mixed forest landscape using a Fourier transform texture-based approach on very-high-resolution optical satellite imagery
The estimation and monitoring of forest biomass from satellite data is of vital importance for efforts to preserve forests using their carbon value, but remains a technical challenge. We have a paper out (led by former MPhil student Jojo Singh) in the International Journal of Remote Sensing that explores if the texture of a high resolution satellite image can yield information about biomass, by capturing the dimensions of the crowns of the dominant trees. We apply this to the SAFE field site in Sabah, Malaysia, in a heterogeneous landscape of old growth forests, logged forests of varying intensity, and oil palm plantations. The paper shows that such Fourier transform approaches do a decent job at estimating and mapping biomass.
Assessment of forest structure parameters via remote-sensing data offers the opportu- nity to examine stand parameters and to detect degradation and forest dynamics, such as above-ground biomass (AGB), at the landscape scale. While much attention has focused on spectrum-based and radar backscatter approaches for assessing forest biomass, texture-based approaches show strong promise. This work makes use of the novel Fourier transform textural ordination (FOTO) method, which involves the combination of 2D fast Fourier transform (FFT) and ordination through principal component analysis (PCA) for characterizing the structural and textural properties of vegetation. This technique presents the potential of Fourier transform approaches in estimating the different forest types, their stand structure, and biomass dynamics in the context of an oil palm–tropical forest landscape in Sabah, Malaysian Borneo. The method was applied to the recordings of very-high-resolution (VHR) Satellite Pour l’Observation de la Terre (SPOT) imagery of the study area. The technique proved useful in distinguishing between the forest types and developing individual biomass estimate models for various forest types. Results show that the FOTO method is able correctly to resolve high AGB values of various forest types. These findings are in agreement with the results based on ground measurements.
Singh M., Malhi Y. Bhagwat S. (2014) Biomass estimation of mixed forest landscape using a Fourier transform texture-based approach on very-high-resolution optical satellite imagery, International Journal of Remote Sensing, 35, 9
Yadvinder Malhi is an ecosytem ecologist and Professor of Ecosystem Science at Oxford University