In this final module of the class, you will be learning of a range of applications that can be supported by SAR data. Single image applications will be the focus of early lectures while later segments will focus more and more on time-series analysis methods. Due to the wealth of regularly observed data that is produced by recent and future SAR sensors (e.g., Sentinel-1 and NISAR), this latter piece is rapidly gaining importance. Please follow the lectures and labs and expand your knowledge by adding in further readings as suggested below.
Lecture 15: Applications and Processing Recipes for SAR Image Data
This lecture looks into the applications of SAR Amplitude data. Since the advent of ESA’s Sentinel-1 constellation, the use of SAR image data for monitoring the planet has skyrocketed. This increase is related both to the free-and-open data policy of Sentinel-1 and the operational character of this sensor, guaranteeing regularly observed image time series for all landmasses.
The first half of the lecture will deal with applications that can be supported with single SAR images while later parts of the lecture will look into information that can be extracted from time series of images.
In preparation for this lecture, please read (Meyer et al., 2015), which applies SAR amplitude images to the monitoring of volcanoes. In addition to that, please have a look at ASF’s Data Recipies page and read through the various recipes that are published on this page. Both resources will provide you with an impression of the range of applications that can be supported by SAR images.
Lecture 16: The Concepts of InSAR Time Series Analysis & The PS-InSAR Technique
With this lecture we will return to the topic of InSAR. After learning about the limitations of pairwise InSAR processing in Lecture 13, this session will introduce you to advanced processing techniques designed to overcome these limitations. Specifically, we will talk about InSAR Time-Series Analysis techniques, which analyze not only one but many interferograms with the goal to reduce estimation noise and mitigate nuisance parameters.
After an initial introduction of the general concepts of InSAR time-series analysis, we will discuss the so-called Persistent Scatterer InSAR (PSI) approach. You will learn about the general idea behind PSI and understand its processing workflow. We will exemplify the accuracy of PSI-derived surface deformation estimates and look at a range of examples that successfully applied PSI for the mapping of surface motion across large spatial scales.
In preparation for this lecture, please read (Ferretti et al, 2001), which introduced the PSI approach for the first time. Additional reading should also include Ferretti, A. (2014); Satellite InSAR Data: Reservoir Monitoring from Space. This book by Alessandro Ferretti is an excellent introduction to modern InSAR Time-Series Analysis techniques.
Lecture 17: The SBAS (Short BAseline Subset) Approach to InSAR Time Series Analysis
PS-InSAR is a great technique for monitoring surface deformation in areas with sufficient density of high amplitude point-like scatterers. These are mostly available in and around urbanized environments, providing the basis for long term deformation measurements at the mm/year accuracy level. Outside of urban centers, however, the lack of persistent scatterers renders PS-InSAR suboptimal and other InSAR time series analysis techniques are preferred.
In this lecture we will be discussing Short BAseline Subset (SBAS) InSAR, an alternative time series technique with better performance in natural environments. We will discuss the principles and processing strategies of SBAS and look at some of the relevant applications of this technique. Toward the end of the lecture, you will also hear about available public domain software for PS- and SBAS InSAR processing.
In preparation for this lecture, please read (Berardino et al., 2002), which introduced the SBAS InSAR approach for the first time. Additional reading should also include (Lanari et al., 2004) and Ferretti, A. (2014); Satellite InSAR Data: Reservoir Monitoring from Space. The latter is a book by Alessandro Ferretti that provides an excellent introduction to modern InSAR Time-Series Analysis techniques.
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