COMBINING TANDEM-X AND GEDI DATA FOR MAPPING FOREST STRUCTURE PARAMETER DYNAMICS

Kurzfassung

The synergy of TanDEM-X interferometric data with GEDI lidar full waveform measurements for large-scale forest mapping has been addressed in a number of studies in the last years [1-9]. In a number studies, the GEDI lidar full waveforms have been used to approximate the TanDEM-X X-band radar vertical reflectivity function (e.g. the vertical distribution of scatterersr) in order to enable the inversion of single-pol single-baseline TanDEM-X datasets. This allows the generation of continuous high-resolution forest height maps at large and global scales without the need / use of external information as of about the underlying topography. Fig. 1 shows the forest height map derived from the combination of TanDEM-X and GEDI data over the whole Brazilian Amazon (including more than 12,000 TanDEM-X scenes and 250 millions GEDI lidar measurements). More recently, the low penetration capability at X-band and the high spatial resolution of TanDEM-X have been explored to characterize horizontal forest structure. Accordingly, from the spatial variability of the interferometric phase center it is possible to determine the horizontal canopy heterogeneity and/or density on a 1 Hectare scale. The canopy heterogeneity map, for the Brazilian Amazon is shown on the left of Fig. 1. Figure 1: Brazilian Amazon. Top left: TanDEM-X InSAR Coherence; Top right: GEDI RH98 Height measurements; Bottom left: forest height map derived from the combination of TanDEM-X and GEDI data; Bottom right: Canopy heterogeneity map. (12,000 TanDEM-X scenes and 250 millions GEDI lidar measurements). Figure 2: Canopy heterogeneity change map at 1 Hectare for the time between 2011/2013 and 2018/2020. TanDEM-X performed complete forest coverage in 2011-2013 and 2018-2020. There is thus the ability to measure changes in height and structure 10-year period. Methods for predicting changes using TDX data combined with GEDI. In this paper we discuss the potential of estimating forest height and structure change using TanDEM-X data combined with GEDI meassurements. The canopy heterogeneity can be used directly to detect structural changes in the canopy and to differentiate between different change and disturbance processes. An example of such a structure change map is shown in Fig. x. It shows the change of standard deviation of the interferometric phase center estimated at 25 m spatial resolution within a 1 Hectare window in the time between 2011/2013 and 2018/2020. The area corresponds to area marked by the white rectangle in the map of Fig. x. An increase of standard deviation indicates an increase in canopy heterogeneity caused by processes as stand thinning or selective logging while an degrease of the standard deviation indicates an degrease in canopy heterogeneity that can be caused by regrowth. 5. REFERENCES [1] W. Qi and R. O. Dubayah, "Combining Tandem-X InSAR and simulated GEDI lidar observations for forest structure mapping," Remote Sens. Environ., vol.187, p.253–266, 2016. [2] W. Qi, S. K. Lee, S. Hancock, S. Luthcke, H. Tang, J. Armston, and R. Dubayah, "Improved forest height estimation by fusion of simulated GEDI Lidar data and TanDEM-X InSAR data," Remote Sens. Environ., vol.221, pp.621–634, 2019. [3] A. Olesk, J. Praks, O. Antropov, K. Zalite, T. Arumae, and K. Voormansik, “Interferometric SAR coherence models for characterization of hemiboreal forests using TanDEM-X data”, Remote Sens., 8, 1–23, 2016. [4] C. Gómez, J.M. Lopez-Sanchez, N. Romero-Puig, J. Zhu, H. Fu, W. He, Y. Xie, & Q. Xie, “Canopy height estimation in mediterranean forests of Spain with TanDEM-X data,” IEEE J. Sel. Top. Appl. Remote Sens. Earth Obs., vol. 14, pp. 2956–2970, 2021. [5] R. Guliaev, V. Cazcarra-Bes, M. Pardini, and K. Papathanassiou, “Forest Height Estimation by Means of TanDEM-X InSAR and Waveform Lidar Data,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., vol. 14, pp. 3084-3094, 2021. [6] R. Dubayah, J. B. Blair, S. Goetz, L. E. Fatoyinbo, M. Hansen, S. Healey, M. Hofton, G. Hurtt, J. Kellner, S. Luthcke, J. Armston, H. Tang, L. Duncanson, S. Hancock, P. Jantz, S. Marselis, P. L. Patterson, W. Qi, and C. Silva, “The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography,” Science of Remote Sens., vol.1, 2020. [7] R. Dubayah, M. Hofton, J.B. Blair, J. Armston, H. Tang, and S. Luthcke, “GEDI L2A elevation and height metrics data global footprint level V002” NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/GEDI/GEDI02_A.002, 2021. [8] H. Chen, S. R. Cloude, and J. C. White, “Using GEDI Waveforms for Improved TanDEM-X Forest Height Mapping: A Combined SINC + Legendre Approach,” Remote Sens., 2021. [9] M. Schlund, A. Wenzel, N. Camarretta, C. Stiegler, and S. Erasmi, “Vegetation canopy height estimation in dynamic tropical landscapes with TanDEM‐X supported by GEDI data,” Methods in Ecology and Evolution, 2022.