Aire Olesk will defend her doctoral thesis titled "Hemiboreal forest mapping with Interferometric Synthetic Aperture Radar" on 23. November 2016 at 10.00 at W. Ostwaldi 1, room B103.
dr Mart Noorma, Institute of Physics, University of Tartu
dr Jaan Praks, Aalto University, Finnland
dr Kaupo Voormansik, Institute of Physics, University of Tartu / Tartu Observatory
dr Svein Solberg, Norwegian Institute of Bioeconomy Research
dr Rivo Uiboupin, Tallinn University of Technology
This thesis presents research in the field of radar remote sensing and contributes to the forest monitoring application development using space-borne synthetic aperture radar (SAR). Satellite data is particularly useful for large-scale forestry applications making high revisit monitoring of the state of forests worldwide possible. The sensitivity of SAR to the dielectric and geometrical properties of the targets, penetration capacity and coherent imaging properties make it a unique tool for mapping and monitoring forest biomes. SAR satellites are also capable of retrieving additional information about the structure of the forest, tree height and biomass estimates as an essential input for monitoring the changes in the carbon stocks.
Interferometric SAR (InSAR) is an advanced SAR imaging technique that allows the retrieval of forest parameters while working in nearly all weather conditions, independently of daylight and cloud cover. This research concentrates on assessing the impact of different variables affecting hemiboreal forest height estimation from space-borne X-band interferometric SAR coherence data. In particular, the research analyses the changes in coherence dynamics related to seasonal conditions, tree species and imaging properties using a large collection of interferometric SAR images from different seasons over a four-year period.
The study is carried out over three test sites in Estonia using the extensive multi-temporal dataset of 23 TanDEM-X images, covering 2291 hectares of forests to describe the relation between the interferometric SAR coherence magnitude and forest parameters. The work demonstrates how the correlation of interferometric coherence and Airborne LiDAR Scanning (ALS)-derived forest height varies for pine and deciduous tree species, for summer (leaf-on) and winter (leaf-off) conditions and for flooded forest floor. A simple semi-empirical modelling approach is proposed as being suitable for wide area forest mapping with limited a priori information under a range of seasonal and environmental conditions. A Random Volume over Ground (RVoG) model and three semi-empirical models are compared and validated against a large dataset of coherence magnitude and ALS-measured data over hemiboreal forests in Estonia.
The results show that all proposed models perform well in describing the relationship between hemiboreal forest height and interferometric coherence, allowing future applications to derive forest stand height with an accuracy suitable for a wide range of applications.