This project will develop novel methods for target detection and tracking in airborne and seaborne image sequences. The availability of low-cost visual sensors (visible and IR) and the recent developments on convolutional neural-networks and correlation filters are promising cost-effective and energy-efficient solutions for detection and tracking of targets capable of running onboard on air or sea vehicles. The results of the project can have a direct impact on strategic national activities such as ocean and forest monitoring. To demonstrate the applicability of the methods, three case scenarios will be considered: (i) detection of forest fires from airborne images, (ii) detection and tracking of sea vessels from airborne and seaborne images, and (iii) detection, tracking and pose estimation of aircrafts from seaborne images for teleguidance of unmanned aerial vehicles (UAV’s). These demonstrations will inform the responsible institutions for the protection of the environment and coastal operations of a novel technology to support their activities.