Time Series Analysis for Natural Hazard Monitoring

 Suggested by: Karima Hadj-Rabah

These images are displacement mean velocity maps of “Mitidja” Bassin (Algeria), using two different time series analysis techniques Permanent Scatterers (PS) on the left and Small Baseline Subset (SBAS) on the right. (c) LTIR/USTHB

Short description

Understanding long-term ground displacement is essential for assessing the impacts of environmental changes and human activities on land stability. Differential Interferometric Synthetic Aperture Radar (DInSAR) time series analysis provides a powerful method for detecting and quantifying such displacements over extended periods. This approach is particularly relevant for studying phenomena like subsidence caused by groundwater extraction and reduced precipitation, as seen in regions affected by similar dynamics to the Mitidja Basin in Algeria.

This master thesis focuses on using DInSAR time series analysis to monitor long-term displacement associated with natural hazards and environmental changes. By leveraging Sentinel-1 SAR data and open-source tools such as GMTSAR and LicSAR, the research aims to develop a workflow for detecting and analyzing ground displacement trends. The outcomes will provide valuable insights into the spatial and temporal dynamics of land deformation, contributing to sustainable land management and hazard mitigation strategies.

Start

As soon as possible

Prerequisites/qualification

• Remote Sensing & GIS
• Interest in the topic
• Basic Scripting/Programming (e.g., Python) 

Generating displacement maps for mapping geohazards using Sentinel-1 images

Suggested by: Karima Hadj-Rabah

The two images are displacement maps of “Thessaly” earthquake (Mar.2021), the left one is according to the radar line of sight while the right one is according to the radar platform movement direction. (c) LTIR/USTHB

Short description

Ground displacement caused by geohazards such as earthquakes, volcanic eruptions, and landslides is very challenging to monitor using traditional methods (GNSS, geotechnical instruments,...). Satellite radar images, such as those provided by Sentinel-1, offer a valuable way to detect and measure ground movements over large areas. Two main techniques can be used for that purpose: Differential Interferometric Synthetic Aperture Radar (DInSAR) and Multiple Aperture Interferometry (MAI) to map displacement with high accuracy.

 This master thesis objective is to create a workflow for generating ground displacement maps using Sentinel-1 images in order to support geohazard monitoring and management. The tasks to be accomplished are:

• Reviewing the state-of-the-art in geohazard displacement mapping using SAR data, with a focus on DInSAR and MAI techniques.
• Developing a workflow for processing Sentinel-1 images to generate displacement maps, using free tools such as ESA SNAP software.
• Applying the workflow to a specific case study such as an earthquake in California, volcanic activity of Etna, or landslide event in Salzburg.
• Evaluating the results and discussing how the displacement maps could help in disaster response or risk management.

The purpose of this master thesis is to conduct a case study-based analysis of displacement mapping techniques, with detailed documentation in English. The thesis is ideal for students with a background in remote sensing, and an interest in geohazard applications.

Suggested reading

Teodosio, B., Wasantha, P. L. P., Yaghoubi, E., Guerrieri, M., Fragomeni, S., & van Staden, R. C. (2022). Monitoring of geohazards using differential interferometric satellite aperture radar in Australia. International Journal of Remote Sensing, 43(10), 3769–3802.

Start

As soon as possible

Prerequisites/qualification

Remote Sensing & GIS
Interest in the topic