Geometric calibration of Colour and Stereo Surface Imaging System of ESA's Trace Gas Orbiter

There are many geometric calibration methods for "standard" cameras. These methods, however, cannot be used for the calibration of telescopes with large focal lengths and complex off-axis optics. Moreover, specialized calibration methods for the telescopes are scarce in literature. We describe the calibration method that we developed for the Colour and Stereo Surface Imaging System (CaSSIS) telescope, on board of the ExoMars Trace Gas Orbiter (TGO). Although our method is described in the context of CaSSIS, with camera-specific experiments, it is general and can be applied to other telescopes. We further encourage re-use of the proposed method by making our calibration code and data available on-line.Comment: Submitted to Advances in Space Researc

Low cost multimedia sensor networks for obtaining lighting maps

In many applications, video streams, images, audio streams and scalar data are commonly used. In these fields, one of the most important magnitudes to be collected and controlled is the light intensity in different spots. So, it is extremely important to be able to deploy a network of light sensors which are usually integrated in a more general Wireless Multimedia Sensor Network (WMSN). Light control systems have increasing applications in many places like streets, roads, buildings, theaters, etc. In these situations having a dense grid of sensing spots significantly enhances measuring precision and control performance. When a great number of measuring spots are required, the cost of the sensor becomes a very important concern. In this paper the use of very low cost light sensors is proposed and it is shown how to overcome its limited performance by directionally correcting its results. A correction factor is derived for several lighting conditions. The proposed method is firstly applied to measure light in a single spot. Additionally a prototype of a sensor network is employed to draw the lighting map of a surface. Finally the sensor grid is employed to estimate the position and power of a set of light sources in a certain region of interest (street, building,…). These three applications have shown that using low cost sensors instead of luxmeters is a feasible approach to estimate illuminance levels in a room and to derive light sources maps. The obtained error measuring spots illuminance or estimating lamp emittances are quite acceptable in many practical applications.Telefonica Chair "Intelligence in Networks" of the University of Seville (Spain

A Comparative Analysis of Phytovolume Estimation Methods Based on UAV-Photogrammetry and Multispectral Imagery in a Mediterranean Forest

Management and control operations are crucial for preventing forest fires, especially in Mediterranean forest areas with dry climatic periods. One of them is prescribed fires, in which the biomass fuel present in the controlled plot area must be accurately estimated. The most used methods for estimating biomass are time-consuming and demand too much manpower. Unmanned aerial vehicles (UAVs) carrying multispectral sensors can be used to carry out accurate indirect measurements of terrain and vegetation morphology and their radiometric characteristics. Based on the UAV-photogrammetric project products, four estimators of phytovolume were compared in a Mediterranean forest area, all obtained using the difference between a digital surface model (DSM) and a digital terrain model (DTM). The DSM was derived from a UAV-photogrammetric project based on the structure from a motion algorithm. Four different methods for obtaining a DTM were used based on an unclassified dense point cloud produced through a UAV-photogrammetric project (FFU), an unsupervised classified dense point cloud (FFC), a multispectral vegetation index (FMI), and a cloth simulation filter (FCS). Qualitative and quantitative comparisons determined the ability of the phytovolume estimators for vegetation detection and occupied volume. The results show that there are no significant differences in surface vegetation detection between all the pairwise possible comparisons of the four estimators at a 95% confidence level, but FMI presented the best kappa value (0.678) in an error matrix analysis with reference data obtained from photointerpretation and supervised classification. Concerning the accuracy of phytovolume estimation, only FFU and FFC presented differences higher than two standard deviations in a pairwise comparison, and FMI presented the best RMSE (12.3 m) when the estimators were compared to 768 observed data points grouped in four 500 m2 sample plots. The FMI was the best phytovolume estimator of the four compared for low vegetation height in a Mediterranean forest. The use of FMI based on UAV data provides accurate phytovolume estimations that can be applied on several environment management activities, including wildfire prevention. Multitemporal phytovolume estimations based on FMI could help to model the forest resources evolution in a very realistic way