M.Sc thesis: Deciduous forest parameter retrieval using polarimetric synthetic aperture radar (SAR) interferometry (PolInSAR) and LIDAR approaches

M.Sc thesis: Deciduous forest parameter retrieval using polarimetric synthetic aperture radar (SAR) interferometry (PolInSAR) and LIDAR approaches

September 12, 2017

Earth observation methods have been important tools for forest management applications for several decades. Nevertheless, it is necessary to improve existing processes on the local and regional scales, in particular for retrieving biophysical forest attributes. TanDEM-X data with high spatial resolution are predestinated information sources for precise estimation of forest parameters such as tree height and aboveground biomass. Once the tree-scale estimates are validated across relevant forest types (e.g. deciduous forests, coniferous or mixed), these can be extrapolated to larger plot, watershed, regional or even national scales.

The utilization of three-dimensional remote sensing data sources like TanDEM-X and LIDAR for forest attribute estimation is an ongoing field of research. The derivation of forest parameters as a part of forest monitoring approaches is currently an important issue. This M.Sc thesis follows this idea by testing Tandem-X data using PolInSAR approach to derive forest parameters (e.g. height and aboveground biomass) for a small deciduous forest site in northeast Germany. A second pillar of research will focus on single tree-based estraction of tree heights using LiDAR point clouds. The results will be compared to enable drawing general and site-specific conclusions. Within the six-month project, the student will evaluate existing algorithms and processes and accordingly compare PolInSAR-, LiDAR- and field-based results. The aim is to improve the estimation of fundamental forest parameters such as forest height and biomass, in particular in context of Small-Scale Forest Inventories. The planned project will improve the calibration and validation of existing methods for analyzing Tandem-X datasets. It is worth mentioning that the methodology also entails estimation of potential errors and uncertainties.

This research will be carried out in the nature reserve Eldena, called Elisenhain. Established in 1961 and located in the southeast of Greifswald in Mecklenburg-Vorpommern, Germany. The protected area encompasses 407 ha and consists of mixed deciduous forests with high portions of European Beech (Fagus sylvatica) and common oak (Quercus robur). A small fraction of the whole nature reserve was chosen as test site, for which also reference field data have been already collected on aboveground biomass.

Briefly, the objective of this work is:

  • To evaluate the capability of spaceborne TDX data to map essential forest inventory parameters by applying polarimetric and polarimetric SAR interferometry techniques.
  • Ability to detect forest height and biomass at high spatial resolution using three-dimensional data sources including RADAR and LiDAR.

Test Site Location: Eldena, Greifswald with Tandem-X data (left) and Flat Earth Estimation and Removal (right)

In this regard, development and testing the existing models and algorithms to retrieve forest parameters from PolInSAR data will be performed to generate spatial maps of tree height, and biomass. Later, errors will be retrieved via validation with ground data and LiDAR data in terms of tree height and biomass.

 

Contact:

Dr. Nima Ahmadian (ahmadian.n@gmail.com)

Dr. Hooman Latifi (hooman.latifi@uni-wuerzburg.de)

Dept. of Remote Sensing, University of Würzbrug

you may also like:

New staff member Luisa Pflumm

New staff member Luisa Pflumm

Luisa Pflumm joined the Earth Observation Research Cluster in May 2024 as part of the EcoGlob project and is working with the UAS team in the context of remote sensing for biodiversity and nature conservation. She received her Bachelor's degree in Geography from the...

New team member: Ása Dögg Adalsteinsdottir

New team member: Ása Dögg Adalsteinsdottir

Ása Dögg Adalsteinsdottir joined the Earth Observation Research Cluster in May 2024 as a member of the EO4CAM project team. After earning a bachelor's degree in geography from the University of Iceland, she moved to Germany to study in our EAGLE master's program. She...

NEW TEAM MEMBER: CHRISTIAN SCHÄFER

NEW TEAM MEMBER: CHRISTIAN SCHÄFER

Christian Schäfer joined the EO4CAM project in May 2024. He received his Master's degree in 2017 from Julius-Maximilians-Universität Würzburg (JMU), focusing on GIS-based synthesis of transboundary soil maps. During his work in the JMU BigData@Geo project, he enhanced...

GGW talk on geodata, mobility and social media

GGW talk on geodata, mobility and social media

On Monday the 13th of May our PhD students Ariane Droin and Johannes Mast were holding a talk at the Geographische Gesellschaft Würzburg organised by the Fachschaft Geographie about 'Geodaten, Mobilität und soziale Medien. Big data und die lokale Perspektive der...

NetCDA kick-off workshop

NetCDA kick-off workshop

Yesterday, on May 16th, the partners of the project "European Academic Network for Capacity Development in Climate Change Adaptations in Africa" (NetCDA) met to jointly and officially kick-off their project. The NetCDA team at the University of Würzburg invited all...