Advanced Methods for Time-series InSAR - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Chapitre D'ouvrage Année : 2022

Advanced Methods for Time-series InSAR

Ramon Hanssen
  • Fonction : Auteur
Marie-Pierre Doin
Erwan Pathier
  • Fonction : Auteur
  • PersonId : 1127817

Résumé

While many time‐series interferometric synthetic aperture radar (InSAR) methods have been developed in the last 20 years, most of them share similar characteristics so that they can be categorized into two types of techniques based on how they account for signal decorrelations. The first category of techniques is based on distributed scatterers (DSs) for deformation monitoring. A common way of reducing signal decorrelations is to select interferograms with short spatial and temporal baselines (small baseline (SB) techniques). The second approach is permanent/persistent scatterer (PS) InSAR techniques, which use individual scatterers that dominate the signal from within a resolution cell to track deformation through time. A recent advanced technique allows us to combine both PSs and DSs to overcome the sparsity of identified points for estimation (the persistent scatterer–distributed scatterer (PSDS) technique). This chapter describes the two main families of time‐series InSAR techniques (SB and PSDS).
Fichier non déposé

Dates et versions

hal-03798164 , version 1 (05-10-2022)

Identifiants

Citer

Dinh Ho Tong Minh, Ramon Hanssen, Marie-Pierre Doin, Erwan Pathier. Advanced Methods for Time-series InSAR. Surface Displacement Measurement from Remote Sensing Images, 1, Wiley, 2022, ⟨10.1002/9781119986843.ch5⟩. ⟨hal-03798164⟩
51 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More