Mohammedi Ferhat
University of Biskra, Algeria
Title: Using drones to risk prevention and environmental monitoring in southern Algeria
Biography
Biography: Mohammedi Ferhat
Abstract
Introduction & Aim: The "drones" are unmanned mobile vehicles on board, remotely operated or programmed. They were originally developed for military applications reconnaissance (UAV mainly). This work is based in particular on aerospace remote sensing images. For data with very high spatial resolution methods to use visible low cost imaging sensors, near infrared and thermal infrared. These sensors, loaded onto drones used to finely study the soil and vegetation and to assist in research on various issues such as: The reduction in irrigation water consumption, and reduction of pesticides in the environment. The study of natural habitats, risks, etc. Consequences: Besides climatic problems, most air pollutants classic (SO2, NOx, CO, O3, lead, heavy metals and particles) have effects on human health, ecosystems and monuments. These acquisition systems are used in various geographical contexts, sometimes difficult to access (mountain, tropics). The drones used are multirotor type. The shots are programmed into the onboard navigation system. Examples: Environmental Metrology: 1) Measuring water stress of the plant, 2) Detection of adventitious, 3) Altitude measurement which is the calculation of digital terrain models by stereoscopy. Multiview allows fine estimate of the relief seen for the drone and to follow its evolution. Applications range from the evaluation of the erosion of bare soil monitoring of forest growth (example: relief of a forest canopy). Appearance embedded intelligence and autonomy: 3D Scan Software is built on a micro-UAV, the software uses information acquired by an on-board stereo bench to locate and reconstruct a 3D model of the environment, even in cluttered areas and without GPS location. It is therefore important to find the wind velocity and the diffusivity of pollutant which can be substituted in the model equations to get the exact concentration distribution.