Canopy penetration depth estimation with TanDEM-X and its compensation in temperate forests

Abstract

Abstract The potential of X-band interferometric synthetic aperture radar (InSAR) heights (e.g. from the TanDEM-X mission) for vegetation canopy height estimation has long been recognized. However, the penetration of the X-band into the canopy results in a height bias and substantially affects this estimation. The aim of the study was to apply a physical model to compensate the penetration depth (i.e. height bias) in canopy height estimation and evaluate its performance. We applied a penetration depth model on different TanDEM-X data in three German forests. This model is based on the volume coherence and imaging geometry of the InSAR acquisitions. We extracted the volume coherence from the TanDEM-X data and retrieved the height bias based on the penetration depth compared to actual surface heights. The modeled height bias was used to compensate the height bias in InSAR heights. The corrected TanDEM-X heights were evaluated with LiDAR data. In general, the penetration depth compensation in the InSAR heights improved the performance compared to the original InSAR heights resulting in elevations with a lower root mean squared error and the mean error decreased to less than 1\u202fm with the LiDAR heights used as reference. This suggested that the height bias was accurately modeled for temperate forests, which can be of high relevance when InSAR heights are used for canopy height estimation or used in multi-temporal analysis such as forest growth, degradation and deforestation monitoring.