Fivemind is a land management and bushfire mitigation tool. Using Satellite imagery, the tool automatically detect changes in vegetation and human built structures within specific terrestrial areas. These change observations are combined with terrain and climate data to produce a spatial risk assessment. Land Managers and Fire Authorities can then capture and evaluate higher resolution imagery of areas of concern by deploying UAVs or Drones over flight paths generated by the tool.
Less bushfire and greater crop yields can be achieved by monitoring vegetation more closely – computer vision and machine learning processes are generally more precise than the traditional masking methods. NVDI provides general trends across large areas, where as computer vision can identify specific places of change and group associated causes.
Fivemind consists of a satellite imagery pipeline and a web app interface. The pipeline called Spacelab processes imagery bands made available by Sentinel-2 multi-spectral instruments. It's main purposes is to create NVDI and EVI vegetation masks, NRG false colour images and gradient histograms. The role of the web interface is to easily identify risk level by colour code and create Drone missions across land areas of interest.
The project uses machine learning and computer vision technologies in a number of ways. A TSP variation of a Self Organising Feature Map is used to calculate near-optimal Drone flight paths from selected way points. The map algorithm is also used to group land areas with similar feature values. Histogram of Gradient descriptors and radial RANSAC detect vegetation and surface changes over time.
The generated flight path is downloadable and compatible with DJI flight quad copters and drones.