Detection and mapping vegetation cover based on the Spectral Angle Mapper algorithm using NOAA AVHRR data

Satellite data, taken from the National Oceanic and Atmospheric Administration (NOAA) have been proposed and used for the detection and the cartography of vegetation cover in North Africa. The data used were acquired at the Analysis and Application of Radiation Laboratory (LAAR) from the Advanced Very High Resolution Radiometer (AVHRR) sensor of 1 km spatial resolution. The Spectral Angle Mapper Algorithm (SAM) is used for the classification of many studies using high resolution satellite data. In the present paper, we propose to apply the SAM algorithm to the moderate resolution of the NOAA AVHRR sensor data for classifying the vegetation cover. This study allows also exploiting other classification methods for the low resolution. First, the normalized difference vegetation index (NDVI) is extracted from two channels 1 and 2 of the AVHRR sensor. In order to obtain an initial density representation of vegetal formation distribution, a methodology, based on the combination between the threshold method and the decision tree, is used. This combination is carried out due to the lack of accurate data related to the thresholds that delimit each class. In a second time, and based on spectral behavior, a vegetation cover map is developed using SAM algorithm. Finally, with the use of low resolution satellite images (NOAA AVHRR) and with only two channels, it is possible to identify the most dominant species in North Africa such as: forests of the Liege oaks, other forests, cereal’s cultivation, steppes and bar soil.     

Energy based 3D trajectory tracking control of quadrotors with model-free based on-line disturbance compensation

In this work, a Revisited form of the so-called Model-Free Control (R-MFC) is derived. Herein, the MFC principle is employed to deal with the unknown part of a plant only (i.e., unmodeled dynamics, disturbances, etc.) and occurs beside an Interconnection and Damping Assignment-Passivity Based Control (IDA-PBC) strategy. Using the proposed formulation, it is shown that we can significantly improve the performance of the control through the reshaping properties of the IDA-PBC technique. Moreover, the control robustness level is increased via a compensation of the time-varying disturbances and the unmodeled system dynamics. This on-line compensation capability is provided by the MFC principle. The problem is studied in the case of Multi-Input Multi-Output (MIMO) mechanical systems with an explicit application to a small Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicle (UAV) where a stability analysis is also provided. Numerical simulations have shown satisfactory results, in comparison with some other control strategies, where an in-depth discussion with respect to the control performance is highlighted by considering several scenarios and using several metrics.