Project Description
The need for secure land border is, nowadays, a demanding task with critical necessities of time, cost and capabilities. The possibility to increase the detection capacity of certain events near the European external borders is a considerable benefit, mostly bearing in mind the vast extension of terrain to be covered. Depending on the type of event, and the vicinity to the land border, it is crucial to provide a service that can automatically detect and assess the type of change.
In CALLISTO, the aim of the Pilot Use Case (PUC) 4 is designed to test and prove that developed capabilities in CALLISTO platform are suitable to support the operational work of image analysts. The expectation is that CALLISTO platform will be able to process Sentinel data, perform accurate land change detection to infer relevant changes at borders and deliver alerts to the image analyst (IA). The alerts are the initial steps and can be obtained by analysing relevant open source information or using automatic change detection based on Sentinel 2 satellite images or, when applicable, (VHR) satellite images. If the alert is generated by open source information automatically extracted in the CALLISTO platform through the SMAS (Social Media Analytics Suite) module, the area of interest (AOI) is analysed using the change detection algorithm. That initial analysis can be followed by the acquisitions of Very High Resolution (VHR) satellite images (delivered in the frame of the Copernicus Contributing Missions’ agreement with CALLISTO) or even organizing an UAV (Unmanned Aerial Vehicle) mission to the affected EU external land border section. SMAS can be described as a crowdsourcing module collecting citizen-generated data from social media platforms in real-time, such as Twitter and Instagram, which are related to the CALLISTO use cases. All collected information is automatically geotagged and made available in the so-called SMAS user interface, displaying all the crowdsourced data and several analytics.
Figure 1 – SMAS (Social Media Analytics Suite) Module in CALLISTO platform
(some information was intentionally blurred)
In case of a potential event being detected during a routine verification of a certain AOI using the change detection algorithm, an automatic alert will pop up in CALLISTO platform. That system alert may trigger several processes such as the classification of the type of event based in an internal methodology, searching for collateral data in the SMAS module or even analysis of archive satellite or UAV images available in the platform.
Coming back to the story line (fictitious scenario) for the PUC 4, it is foreseen that the image analyst (IA) using CALLISTO platform get some indicators from the SMAS module on the potential construction works, situated in an unknown location close to the EU external border. IA decides to use the artificial intelligence model for land change detection integrated in CALLISTO platform and based on Sentinel 2 satellite images, getting an automated alert from the system indicating a high probability for a specific location to be a certain event. After that initial hint, the IA requests other distributed index geo-referenced data sources from the platform, resulting that such data is not available at that moment. Nevertheless, and due to the proximity of the detected change to the EU external border (less than 1km), the IA requests permission to launch an UAV mission to collect imagery and video over the location of interest, with the goal of verifying the information on the type of change detected. The data acquired from the UAV confirms the change as a new construction site. Based on the orography of the terrain and the type of detected change, IA uses the 3D visualization module on the acquired UAV dataset to enhance the observation on the type of construction detected, providing a more detailed overview. IA delivers a comprehensive imagery report in order to support decision-makers in how to better protect the affected EU external land border section.
Figure 2 – CALLISTO platform with selected Area of Interest in preparation for launching the automated change detection algorithm
The SMAS (Social Media Analytics Suite) Module is developed by CERTH and the CALLISTO Platform is developed by CS Group.
Project Details
- DateJune 30, 2023
- WriterEuropean Union Satellite Centre
- 2
