Monitoring Forest Height Dynamics by Means of L-Band Multi-Baseline PolInSAR Data

Kurzfassung

Forest height is one of the most important parameters for forest characterization, since it is closely related to biomass. It provides information on stand condition and site index, and it allows characterizing the successional state of the forest. At the same time, the distribution of forest heights within a stand can be used to assess the disturbance regime and to detect logging activities. Beyond absolute height measurements, the knowledge of forest height changes is of extreme importance in the characterization of dynamic forest processes. Indeed, forest height changes can be directly used to characterize forest growth, mortality and deforestation, and to conclude about the associated carbon fluxes independently of the successional status of the forest. Forest dendrometric variables are usually measured by airborne laser scanning by using LIDAR instruments that are very precise in characterizing the tree heights and the main related parameters. However, LIDAR technology is expensive and in many cases not affordable, especially in a multitemporal monitoring scenario. Low frequency synthetic aperture radar (SAR) sensors in a polarimetric-interferometric configuration represent a very promising alternative tool to LIDAR for estimating forest height from space and its dynamics as they can provide large continuous coverage and high spatial and temporal resolution. Polarimetric SAR interferometry (PolInSAR) combines the inherent sensitivity of the interferometric coherence to the vertical structure of volume scatterers combined with the potential of SAR polarimetry to interpret and characterise the individual scattering processes. Exploiting this combination, forest height estimations evolved in the last years from a pre-operational to an operational PolInSAR product that have been validated in the frame of several campaigns over a wide range of forests, terrains and environmental conditions. The overall obtained estimation error is in the order of 10% or smaller. The objective of this thesis is to assess qualitatively and quantitatively the capability of monitoring forest dynamics by using PolInSAR height maps. The analysis is based on a multibaseline-multitemporal PolInSAR L-band airborne dataset acquired over the temperate forest site of Traunstein (South of Germany) covering more than ten years by the German Aerospace Center DLR’s E- and F-SAR radar platforms. For each acquisition date, a multibaseline PolInSAR inversion has been carried out using tracks characterized by short temporal baseline (of the order of one hour). Accordingly, a time series of accurately estimated forest heights has been obtained without disturbances due to long-term temporal decorrelation. For each campaign, each single baseline has been inverted by means of the Random Volume over Ground (RVoG) model. In order to obtain a single height map, different methodologies can be employed combining the single-baseline results. The related height estimation accuracies have been quantified and critically compared. Next, an experimental analysis has been carried out in order to characterize the effects of different sources on height estimation, like weather condition (i.e. rain event), seasonal cycles, disturbances and management activities. Extensive results of this analysis are presented, and the capability of distinguishing between different sources of PolInSAR height changes are discussed together with their potentials for identifying and monitoring ecosystem changes.