Home

Dear User, thank you for your interest in the ADATools!

The availability of wide-area displacement maps based on Multi-Temporal Satellite Interferometry (MT-InSAR) has significantly increased in recent years. The launch of the Copernicus Sentinel-1 satellites in 2014 marked a turning point in both the exploitation and application of these techniques, thanks to a policy of global and regular acquisition and open and free data distribution. An example of this progress has been the development of regional, national, and continental services, providing displacement maps with highly detailed information on both natural and anthropogenic processes.

Since 2022, the European Ground Motion Service (EGMS) has been providing billions of displacement measurement points (MP) for free, updated annually, covering almost the entire European territory and characterized by their high reliability. Despite the potential utility of these maps for land management and risk assessment, their usage remains limited. The main cause of this is the sheer volume of information they contain and the lack of expertise in interpreting MT-InSAR results.

Unlocking the full potential of this extensive data requires advanced methodologies and tools designed to extract information efficiently and enhance their interpretation. By generating user-friendly secondary products, these advancements improve the operational exploitation of MT-InSAR, enabling users to utilize its benefits more effectively.

In this context, ADATools offer capabilities to swiftly detect and extract Active Deformation Areas (ADA-Finder tool), conduct an initial classification of potential ground displacement phenomena (ADA-Classifier tool), and evaluate their potential impact. This allows users to prioritize interventions and focus further analysis with precision and efficiency.

ADATools are a continually evolving set of tools that CTTC has been developing over the years within the framework of several EU projects (Safety, U-Geohaz, MOMIT, Riskcoast, RASTOOL). This ongoing development is the result of collaborations with project partners and the invaluable feedback and suggestions received from users.

The improvements aim to achieve the following goals:

User-Friendly Tools: Ensuring ease of use for all levels of users.
Operative Outputs: Providing actionable data for real-world applications.
Understandable Algorithms: Making the processes transparent and comprehensible.
Adaptability and Scalability: Ensuring the tools can be tailored to various needs and expanded as required.
Flexibility and Tuneability: Allowing customization to specific use cases.
Fast Operation: Ensuring the tools can handle large datasets efficiently.
Reliability Assessment: Guaranteeing the accuracy and dependability of the results.

Specifically, in recent years, within the RASTOOL project, the tools have been significantly improved to achieve these goals and to be ready for application on EGMS data formats. These enhancements ensure that ADATools remain at the forefront of EGMS and MT-InSAR data exploitation, providing vital support for disaster risk reduction, urban planning, and infrastructure management.

ADATools partners

The ADA tools (i.e., ADAtools) have a long history, starting with the first project, Safety (2015-2016), where the main ideas behind the tools were built. Initiated in the early years following the launch of the Copernicus Sentinel-1 satellites, Safety aimed to simplify and enhance the use of InSAR displacement maps by providing Civil Protection Authorities (CPA) with the capability to periodically evaluate and assess the potential impact of geohazards (volcanic activity, earthquakes, landslides, and subsidence) on urban areas. From Safety emerged the methodology to extract the so-called Active Deformation Areas (ADA), as published in Barra et al., 2017.

This foundation led to the development of several projects like U-Geohaz, MOMIT, Riskcoast, and finally RASTOOL. These projects have enabled the creation of user-friendly tools and the establishment of methodologies for other tools aimed at classifying the detected ADAs and assessing their potential impact on exposed elements such as population, buildings, roads, and critical infrastructures.

The tools are a result of continuous cooperation between several institutions that have been collaborating over the years and will continue to grow in the future. This collaborative effort ensures that the ADAtools are refined and updated, maintaining their relevance and effectiveness in the ever-evolving field of satellite interferometry for geohazard assessment and management.

The current version of ADAtools, developed under the RASTOOL project, marks a significant turning point in their evolution. The algorithms behind these tools are the outcome of a strong collaboration within the RASTOOL Consortium. The key contributors are listed below:

ADAtools

The ADA tools (i.e., ADAtools) include a set of primary tools and auxiliary ones to facilitate user data management and support the application to EGMS data. This version of ADAtools has been significantly enhanced within the RASTOOL project, with a focus on adapting them for application over wide areas using EGMS inputs.

Main tools

The main tools allow computing the following steps:

ADAfinder - Automatic Identification of Areas with Movements: This procedure is executed through the ADAfinder module, whose algorithms and workflow are detailed in Barra et al., 2017.
TSclassifier - Automatic Classification by Temporal Behavior: The TSclassifier module, implemented in Python, assesses the temporal evolution of each ADA by analyzing the mean Time Series (TS) of displacement. The current version of TSclassifier determines whether the movement is accelerating (indicating higher risk), decelerating (indicating lower risk), or remaining constant over time (suggesting the need for ongoing monitoring). This analysis is an optional steps that helps in understanding the dynamics of ground deformation and supports informed decision-making for risk management and mitigation efforts
ADAclassifier - Automatic Classification by Type of Movement: This module, known as ADAclassifier, employs parallel decision trees to categorize Active Deformation Areas (ADAs) into five types of phenomena: landslides, subsidence, uplift, construction/settlement consolidation, or sinkholes. The ADAclassifier tool incorporates auxiliary data to determine the most probable phenomena by evaluating factors such as the direction of movement, consistency of the movement's sign with the topography, intersection with existing inventories, and local lithological characteristics, among others. This comprehensive approach ensures a more accurate and reliable classification of ground deformation phenomena. The ADAclassifier is able to read the output of the TSclassifier, allowing to mantain this information in the output classified ADA map. This new version of the ADAClassifier is in its early stages, and the proposed default values will need to be fine-tuned based on the experience gained through its usage and application.

ADAimpact -Assessment of Potential Impact: The ADA-Impact tool focuses on evaluating the potential impact of geohazards monitored by InSAR, utilizing global and open data to characterize exposure. Exposure typically refers to the elements at risk, such as people, property, equipment, and systems located in hazardous zones and subject to potential losses (UNDDR, 2019). Developed as a QGIS plugin in Python, the ADA-Impact tool ranks the ADAs based on their potential impact. The methodology assesses the magnitude using output information from the ADAclassifier and incorporates exposure data provided by the user. The outputs are maps intended to support territorial and risk management. This tool is in its initial stage, and an experimental version of the plugin can be downloaded from the following GitHub repository.

EGMS ADA Auxiliary tools

These tools collectively support the seamless utilization of EGMS displacement maps, enhancing their applicability for wide-area assessments and management of geohazards.

Here's adescription of the EGMS ADA auxiliary tools:

Build_coverage: This tool simplifies the selection of CSV inputs by visualizing the coverage of each CSV file downloaded from the EGMS portal in GIS software. It helps users understand the spatial extent of the data before processing.
Launch_batch_ADAfinder: Developed in Python, this tool enables the automatic and parallel launch of the ADAfinder tool across multiple CSV inputs stored in the same folder. It streamlines the process of detecting Active Deformation Areas (ADAs) over wide areas covered by multiple EGMS CSV files.
Purge_overlaps: EGMS CSV inputs often contain overlapping zones, which can lead to the extraction of multiple ADAs representing the same movement in the same area. This tool removes overlapping ADAs while preserving the most significant information, ensuring clarity and accuracy in the results. It is recommended to execute this optional step after using ADAfinder and before TSclassifier or ADAclassifier.
Launch_batch_ADAclassifier: Also developed in Python, this tool facilitates the automatic and parallel launch of the ADAclassifier tool across multiple outputs generated by ADAfinder (and optionally TSclassifier). It enhances efficiency in classifying ADAs into different types of ground displacement phenomena over large datasets stored in the same folder location.

Download the Tools

The ADAtools are free to use and have been developed primarily to enhance territorial knowledge and management. Usage of the software is permitted only when obtained directly from the official website and download form.

The software is provided at no cost, but users must agree to the terms of the license agreement. Users are prohibited from sub-licensing, selling, renting, leasing, or otherwise transferring the ADAtools. Furthermore, any service descriptions, marketing materials, and documentation must clearly acknowledge the use of ADAtools.

WARNING: The ADAtools may be installed on Windows and Linux computers. For Windows, only Windows 10 and 11 are supported. For Linux, the ADAtools are available only for distributions based on the LATEST version of Ubuntu (such as Linux Mint). For the current available installers this means Ubuntu 24.10 (or Linux Mint 22 "Wilma").

Privacy Notice
CTTC is committed to protecting your personal data. The information you provide through this form will be processed for the following purposes:

To develop a list of users from each institution that downloads the ADAtools.
To assess the impact and real-world usage of the ADAtools.
To send communications strictly related to the ADAtools, such as updates, improvements, and new functionalities.

Your data will be kept confidential and will not be shared with third parties unless required by law. You may opt out of receiving communications at any time by contacting us at dpo@cttc.cat.

By submitting this form, you acknowledge and agree to the processing of your personal data as described.

ADAtools License Agreement

Please read the ADAtools License Agreement that you must agree to before downloading the tools.

Download form:

References

Algorithm behind the ADAfinder:

Barra, A., Solari, L., Béjar-Pizarro, M., Monserrat, O., Bianchini, S., Herrera, G., Crosetto, M., Sarro, R., González-Alonso, E., Mateos, R. M., Ligüerzana, S., López, C., & Moretti, S. (2017). A methodology to detect and update active deformation areas based on Sentinel-1 SAR images. Remote Sensing, 9(10), 1002. https://doi.org/10.3390/rs9101002

First versions of the ADAtools:

Navarro, J. A., Tomás, R., Barra, A., Pagán, J. I., Reyes-Carmona, C., Solari, L., Vinielles, J. L., Falco, S., & Crosetto, M. (2020). ADAtools: Automatic detection and classification of active deformation areas from PSI displacement maps. ISPRS International Journal of Geo-Information, 9(10). https://doi.org/10.3390/IJGI9100584
Tomás, R., Pagán, J. I., Navarro, J. A., Cano, M., Pastor, J. L., Riquelme, A., Cuevas-González, M., Crosetto, M., Barra, A., Monserrat, O., Lopez-Sanchez, J. M., Ramón, A., Ivorra, S., Del Soldato, M., Solari, L., Bianchini, S., Raspini, F., Novali, F., Ferretti, A., … Casagli, N. (2019). Semi-automatic identification and pre-screening of geological-geotechnical deformational processes using persistent scatterer interferometry datasets. Remote Sensing, 11(14). https://doi.org/10.3390/rs11141675

Contacts

E-mail: rastool@cttc.es