A system for neutralizing embers is disclosed. The system includes a laser turret with a sensor array and a laser emitter configured to dispense laser energy. The laser turret can also include a control system configured to move the laser emitter. The laser control system can receive information from the sensor array and sending signals to the control system to move the laser emitter. Using these features, the laser control system can select an incoming ember based on a thermal signature associated with the incoming ember, and the laser control system can issue commands to the control system to direct the laser emitter towards the incoming ember, and the laser emitter can direct laser energy at the incoming ember. The system can also include provisions to track an ember and determine if an ember has been depleted of fuel.

An apparatus configured to perform a prescribed burn of vegetative ground fuel comprises a movable platform configured to traverse ground that contains the vegetative ground fuel and a burn chamber disposed on the movable platform. A containment arrangement is situated relative to the burn chamber and configured to confine burning of the vegetative ground fuel to a prescribed burn region of the ground. The containment arrangement comprises an arrangement of interleaved plates having two or more different shapes and connected together via link members. A discharge apparatus is configured to expel residual effluent from the burn chamber.

An embodiment for predicting and mitigating forest fires based on low earth orbit (LEO) satellites is provided. The embodiment may include receiving historical LEO satellite images of a forested region. The embodiment may also include identifying a geographical area and a boundary of the geographical area. The embodiment may further include identifying a time range of a fire season in the geographical area. The embodiment may also include in response to determining at least one LEO satellite is not positioned within the boundary of the geographical area during the time range, adapting a location of the at least one LEO satellite to be within the boundary during the time range. The embodiment may further include capturing live LEO satellite images of inflammable material in the geographical area. The embodiment may also include identifying a range of changes in the inflammable material.

Machine-learning-based methods and systems for vegetation treatment project design. The approach autonomously creates, evaluates, and optimizes wildfire risk mitigation activities to intelligently reduce wildfire risk to communities in a resource-constrained environment. The methods and/or systems are accompanied by a cloud-enabled user interface that provides decision support to vegetation management specialists charged with implementing wildfire risk reduction measures.