A hybrid system for identifying the presence of clouds on the horizon line

Abstract

Common passive surveys for the presence of clouds in the sky are carried out using the digital processing of photographs taken using fish-eye type lenses. Another type of survey is carried out using active measuring systems, e.g. thermal imaging, active laser distance sensors, etc. A common feature of these sensors is the high cost of the measuring apparatus, which is hardly acceptable for small local short-term weather forecasting stations. The main task of these weather stations is to forecast local dynamic weather phenomena that have (or may have) an impact on the use or operation of technical facilities (e.g. photovoltaic farms, cranes, etc.) or agricultural plant protection measures. This paper proposes a hybrid method for detecting clouds and predicting changes in cloud cover on the horizon line. The proposed method is based on an analysis of colour photographs of the cross-section of the sky using chrominance distribution by the RGB method. In the next step, the CCT colour temperature and the ALS-based ambient light intensity resulting from spectral analysis are determined for the cross-section of the sky being identified. The survey results indicate the dependence of the variability of CCT and ALS parameters for classifying objects on the horizon line. The above analysis makes it possible to distinguish the sky on the horizon, a cloud, or agglomeration elements. The data obtained from the surveys show that the proposed structure of the hybrid system for analysing the presence and movement of clouds on the horizon line can provide the basis for further development of data processing algorithms for a passive sensor of the apparatus for detecting clouds and other objects on the horizon line.