WP2 Remote sensing and in-situ data collection and processing for dynamic indicator analysis


Remote sensing can be a valuable tool for the large-scale mapping of indicators related to vulnerability, as well as for recovery and reconstruction processes and their evolution over time. Although generally less accurate than in-situ inspection and less rich in details about individual buildings, it can provide cheaper information in terms of acquisition costs and allows for the capture of large geographical extents that in-situ inspections cannot compete with. However, the integration of remotely sensed data is far from trivial. Hence, suitable strategies, tools and methods specifically for handling multi-temporal data will need to be developed, leading to a system capable of using such data in a dynamic way and automatized to the maximum extent possible for the purpose of extracting vulnerability and recovery/reconstruction related indicators.

This work package will deal with the (semi-)automated processing and integration of remote sensing data and products for dynamic indicator analysis. Among the objectives of this package, there is the efficient use of techniques for the processing of remotely sensed time-series data in order to extract relevant information for indicator analysis, with special attention being paid to changes and evolution over time. The methodologies and tools to be developed within this work package aim to be flexible enough to be able to cover the requirements of both multi-hazard vulnerability assessments and post-disaster recovery and reconstruction monitoring.

The key objectives of this WP are:

  • Review and implementation of remote sensing methods to extract vulnerability and recovery/reconstruction related indicators from satellite images, taking into account the indicators identified in WP4 and WP5.
  • Review and implementation of efficient in-situ data collection using ground-based imaging techniques.
  • Implementation and development of methodologies and tools for (semi-)automated remote sensing pre-processing (including data co-registration) as input for dynamic change-detection analysis.
  • Implementation and development of methodologies and tools for Iow-level (raw) change detection algorithms (dynamically detecting where changes occur, with uncertainties).
  • lmplementation and development of methodologies and tools for high-level, supervised and unsupervised analysis of changes.

The developed software modules will be made available as open-source software modules and integrated into a freely available and widely used GIS environment (e.g., QGIS). The output of this work package will provide the necessary input for a prototype vulnerability monitoring framework for seismic and landslide risk assessment (WP4) as well as for a prototype recovery and reconstruction monitoring framework (WP5).