학술논문

Forest Height Estimation from TanDEM-X images with Semi-Empirical Coherence Models
Document Type
Conference
Source
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium Geoscience and Remote Sensing Symposium, IGARSS 2018 - 2018 IEEE International. :8805-8808 Jul, 2018
Subject
Aerospace
Computing and Processing
Fields, Waves and Electromagnetics
Geoscience
Photonics and Electrooptics
Signal Processing and Analysis
Vegetation
Forestry
Coherence
Data models
Synthetic aperture radar
Atmospheric modeling
Extraterrestrial measurements
Language
ISSN
2153-7003
Abstract
In this study we compare semi-empirical interferometric coherence models, proposed in [1], for tree height estimation from TanDEM-X coherence scenes. The models are derived from Random Volume over Ground model, by applying simplifications and introducing empirical parameters at different complexity levels so that the models can be adapted to available ancillary data. Several different TandDEM-X interferometric scenes from Estonia are used to test the model performance in various conditions. All the results are compared with highly accurate canopy height models measured using airborne laser scanning. We demonstrate that models which are very simple to invert, produce accurate tree height estimates when the conditions are most favorable. Best results can be seen for winter images for frozen and dry snow conditions. Simple parametric sinc model can produce accurate tree height maps over large areas with pixel-wise deviation only few meters.