## 2 Materials and Methods
### Cloud Observations  
Before describing the novelties of our proposed system, one has to be familiar with the standard procedures of estimating cloud properties by meteorological observers. Cloud base height is currently observed at airports worldwide in three steps:  
1. The human observer looks to the sky, and recognizes different cloud layers and cloud types, which indicate initial information of their typical height. 2. If there are some tall country features nearby, the observer utilizes them in a more precise estimation of the cloud base height. If such tall features are not available, this step is skipped. 3. In the workroom, the observer checks the ceilometer measurements of the cloud base height, and although they are only point measurements, these are utilized in a combination with Steps #1 and #2 to get as comprehensive information on the cloud base height as possible. The steps are not necessarily performed in the described order. The specific cases with no country features nearby (i.e., without Step #2) and/or with no ceilometer (i.e., without Step #3) will be discussed in Section 4 (Discussion). In our system, the remote human observer can perform Steps #1 and #2 remotely by cameras and Step #3 by a remote access to the ceilometer data, which are displayed in the same system as the camera imagery. In this way, it is ensured that the remote observer has the ability to perform the same steps as the local observer. Figure 3: The structure of the proposed system, as designed at LZTT. To test the functionality of the semi-automated subsystem targeted at the observation of cloud coverage and cloud heights, two cameras were installed at LZTT. The first one is aimed at taking photographs in the visible RGB spectrum (advantageous during the daytime), whereas the second, thermal camera is used to monitor the sky in the infrared spectrum (advantageous during the nighttime). At each observation time, both cameras take 61 photos of the sky, at a pre-defined angles and azimuths. In the first step of the processing, these images are stitched together, using the method of Lambert azimuthal equal-area projection from the hemisphere to the horizontal plane (Figure 4). The selection of an equal-area projection is important, as the ratio of the cloud surface to the whole sky surface in reality must be exactly the same as the ratio in the whole sky image [9]. The procedure of accurate image stitching needs special attention. Presets for every sub-image are always the same as the camera with the rotator were well fixed on the same place for the whole duration of the research. Countermeasures against possible differences from the pre-defined preset positions have been conducted. The camera with the rotator has a proclaimed operational wind load durability 216 km/h (135 mph), and during the research operation, no considerable wind gusts were observed. The 1-2 pixel movements could possibly be caused by the returning of the camera to the same preset position from a different side in the case of power supply outage, but such a difference is negligible for the final output and its usage. Overlapping parts of the sub-images are averaged if an image is darker than the neighboring one. Figure 4: A schematic of the Lambert azimuthal equal-area projection. Even though the procedure of image stitching is not trivial, we decided to use a rotating robotic camera instead of the commonly adopted fisheye lens approach [10; 11; 12; 13]. While the latter methodology produces easy-to-get images, their resolution may not be sufficient for the remote observers, for instance to distinguish sharp edges of the cloud layers. The HMI of the proposed system offers the remote observer several aiding tools to make the assessment of the cloud cover easier. These include displaying concentric circles and/or dividing the photo of the hemisphere into oktas (Figure 5).