Forest canopy structure is very important to measure forest change and forest coverage. And TerraSAR-X data are well suited for inversion applications at tree height. Based on the Random Volume over Ground model, the three-stage algorithm and its PSO improvement are studied in this paper. Taking the TerraSAR-X data of Mengla County in Yunnan Province China as the data source, the forest height inversion algorithm were compared in the experiment part. Finally, the results are verified with the field measured data. The results show that the precision of forest height inversion based on the PSO intelligent algorithm is better than the traditional three-stage algorithm, and the correlation coefficient is improved by more than 20%.

Forest canopy structure is an important parameter for measuring forest changes and forest coverages. It is significant to explore the application of TerraSAR-X/TanDEM-X data in tree height inversion. In this research, the phase differencephase coherence magnitude algorithm and the digital elevation model (DEM) method were investigated based on the random-volume-over-ground (RVoG) model. With Mengla County in Xishuangbanna Dai Autonomous Prefecture in Yunnan Province as the research area, the forest height inversion was performed based on TerraSAR-X/TanDEM-X data. Finally, the results were verified by combining field-measured data. For natural forests and rubber plantations, the DEM height difference method magnitude tree height inversion algorithm improves the estimation of the earth phase and canopy phase favorably, while the traditional algorithm presents a high height inversion precision for rubber plantations.