Name
Abstract | ||
|---|---|---|
InSAR time series analysis involves the processing of extremely large datasets to estimate the relative movements of points on Earth. The estimated movements may reveal geophysical processes, or strain in anthropogenic structures. In parametric estimation methods, it is important to chose the optimal mathematical functional model relating the satellite observations to the kinematic parameters of interest. A standard approach is to parameterize the kinematic behavior, in first order, as a linear function of time, but it is unlikely that all objects behave in this purely linear way. Ideally, the kinematic parameterization should be optimized for each individual measurement point in the area of interest. In this work, following [1] we introduce a method to select the optimal functional model, with a minimum but sufficient number of free parameters using a probabilistic method based on multiple hypotheses testing. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IGARSS.2016.7729876 | 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) |
Keywords | Field | DocType |
Deformation modeling, Multiple hypotheses testing, B-method of testing | Time series,Kinematics,Interferometric synthetic aperture radar,Parametrization,Computer science,Remote sensing,Model selection,Probabilistic method,Linear function,Free parameter | Conference |
ISSN | Citations | PageRank |
2153-6996 | 0 | 0.34 |
References | Authors | |
3 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ling Chang | 1 | 24 | 4.58 |
| Ramon F. Hanssen | 2 | 107 | 28.92 |