TY - GEN
T1 - Estimating forest structure change by means of wavelet statistics using TanDEM-X datasets
AU - Albrecht, Lea
AU - Huth, Andreas
AU - Fischer, Rico
AU - Papathanassiou, Konstantinos
AU - Antropov, Oleg
AU - Lehnert, Lukas
N1 - Publisher Copyright:
© VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.
PY - 2024
Y1 - 2024
N2 - Understanding forest structure is crucial because it is shaped by forest dynamics and biophysical processes, and provides valuable insights into a forest's state and dynamics when monitored globally. The scale of observation is critical in understanding forest structure, as disturbances tend to homogenize patterns across different scales, while fine-scale processes introduce heterogeneity. Radar-based techniques like SAR interferometry and SAR tomography offer ways to characterize forest structure, primarily by analysing variations in radar reflectivity profiles. However, conventional methods, such as phase histograms, sacrifice spatial resolution. TanDEM-X, with its high spatial resolution allows the characterisation of structural heterogeneity by examining the centroid of the reflectivity profile. To fully capture structural variations, a multi-scale analysis using wavelet frames is applied. This research combines experimental SAR data from TanDEM-X and forest simulations to comprehensively assess and understand forest structure.
AB - Understanding forest structure is crucial because it is shaped by forest dynamics and biophysical processes, and provides valuable insights into a forest's state and dynamics when monitored globally. The scale of observation is critical in understanding forest structure, as disturbances tend to homogenize patterns across different scales, while fine-scale processes introduce heterogeneity. Radar-based techniques like SAR interferometry and SAR tomography offer ways to characterize forest structure, primarily by analysing variations in radar reflectivity profiles. However, conventional methods, such as phase histograms, sacrifice spatial resolution. TanDEM-X, with its high spatial resolution allows the characterisation of structural heterogeneity by examining the centroid of the reflectivity profile. To fully capture structural variations, a multi-scale analysis using wavelet frames is applied. This research combines experimental SAR data from TanDEM-X and forest simulations to comprehensively assess and understand forest structure.
UR - http://www.scopus.com/inward/record.url?scp=85193953081&partnerID=8YFLogxK
M3 - Conference article in proceedings
AN - SCOPUS:85193953081
T3 - Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR
SP - 658
EP - 662
BT - EUSAR 2024
PB - IEEE Institute of Electrical and Electronic Engineers
T2 - 15th European Conference on Synthetic Aperture Radar, EUSAR 2024
Y2 - 23 April 2024 through 26 April 2024
ER -