The aesthetic beauty of a landscape is an integral value reflected in artistic inspiration. Science, in contrast, tries to quantify the landscape using various methods. Of these, geodiversity indices have been found to be a useful approach, and this geomorphological diversity is characterized through derivatives made from digital terrain models (DTM). While these methods are useful, they have a drawback that the value of some landscape features may be underestimated if they have regular forms. For example, the aesthetic and scientific attractiveness of our study area, the Chaîne des Puys (Auvergne, France), a UNESCO World Heritage site, is strongly related to the distinctive small volcanoes, but despite being an outstanding element of the landscape, the scoria cones do not stand out well in geodiversity indices. This is because they have almost symmetrical conical forms and regular slopes that score low in the available geodiversity methods. We explore this problem and investigate how to overcome the low geodiversity performance of these distinctive landscape elements. We propose a modified approach for scoria cones using the normal input layers but adapted to the cone geometry. The modified indices are easy to compute and consider the uniformity and symmetry of larger landscape elements that form scientifically integral and aesthetically vital components of the landscape. The method is applicable to the tens of thousands of small monogenetic volcanoes in the hundreds of volcanic fields around the world, and could be extended to other volcanic features, such as domes. It would be possible to use the method to study larger volcanoes, as they often share and replicate the small-scale monogenetic morphology considered here.

Nowadays, the public service practice applicability of drones and remote sensing sensors is being explored in almost all industrial and military areas. In the present research, in collaboration with different universities, we investigate the applicability of drones in airport procedures, assessing the various potential applications. By exploiting the data from remote sensing sensors, we aim to develop methodologies that can assist airport operations, including managing the risk of wildlife threats to runway safety, infrastructure maintenance, and foreign object debris (FOD) detection. Drones equipped with remote sensing sensors provide valuable insight into surface diagnostics, helping to assess aprons, taxiways, and runways. In addition, drones can enhance airport security with effective surveillance and threat detection capabilities, as well as provide data to support existing air traffic control models and systems. In this paper, we aim to present our experience with the potential airport applications of UAV high-resolution RGB, thermal, and LiDAR sensors. Through interdisciplinary collaboration and innovative methodologies, our research aims to revolutionize airport operations, safety, and security protocols, outlining a path toward a safer, more efficient airport ecosystem.

Morphometric studies of scoria cones have a long history in research. Their geometry and shape are believed to be related to evolution by erosion after their formation, and hence the morphometric parameters are supposed to be related with age. We analysed 501 scoria cones of four volcanic fields: San Francisco Volcanic Field (Arizona, USA), Chaîne des Puys (France), Sierra Chichinautzin (Mexico), and Kula Volcanic Field (Turkey). All morphometric parameters (cone height, cone width, crater width, slope angles, ellipticity) were derived using DTMs. As new parameters, we calculated Polar Coordinate Transformed maps, Spatial Elliptical Fourier Descriptors to study the asymmetries. The age groups of the four volcanic fields were created and their slope distributions were analysed. The age groups of individual volcanic fields show a statistically significant decreasing tendency of slope angles tested by Mann–Whitney tests. By mixing the age groups of the volcanic fields and sorting them by age interval, we can also observe a general, statistically significant decrease. The interquartile ranges of the distributions also tend to decrease with time. These observations support the hypothesis that whereas the geometry of individual scoria cones differs initially (just after formation), general trends may exist for their morphological evolution with time in the various volcanic fields.

Scoria cones are favorite targets of morphometric research. However, in-depth, DTM-based studies have appeared only recently, and new methods are being developed. This study provides a classic evaluation of the cones of Chaîne des Puys (Auvergne, France) as well as introduces a more detailed and statistics-based set of properties. Beside the classic parameters, a sectorial approach is applied to the slope distributions calculated from high resolution DTMs for 25 cones of different lithologies, in order to study the various (a)symmetries of the cones. DTM-based morphometric characteristics have been found to be different from classic descriptors, whereas the sectorial approach describes correctly the more and the less regular shapes. The distribution of interquartile ranges of the sectorial slope distributions is skewed. Sectorization discriminates various types of symmetries: there are almost circular cones, but the majority are elongated and have some asymmetry. The relationship between size parameters reflects the lithology, rather than the age of the cone. The attempt to relate morphometric parameters to age data is only partially successful: although there is a certain trend, within the same lithological group, subtle but possibly systematic trends can be detected for decreasing morphometric values (e.g., slope) with the age. The regression models indicate various outcomes. Further work is needed to understand all the diverse parameters, especially the lithology–shape relationship, and how symmetry is connected to different factors.

Driving is based on effective navigation. When using a navigation device, the user interface, the amount and quality of the underlying data and its representation all effect the quality of navigation. This study evaluates whether drivers in three different countries consider these devices to be useful and what functionality they would prefer. An online questionnaire was used to assess built-in navigation systems. The findings from 213 respondents show that current car GPSs are overloaded with features. Regardless of country, drivers simply require more basic functionality in the interface. It was also noted that the embedded functions in these devices are not fully utilized. In addition, many people use the navigation service to enter a new address while the car is moving. It may be worth examining how this option can be better implemented.

Today, integration into automated systems has become a priority in the development of remote sensing sensors carried on drones. For this purpose, the primary task is to achieve real-time data processing. Increasing sensor resolution, fast data capture and the simultaneous use of multiple sensors is one direction of development. However, this poses challenges on the data processing side due to the increasing amount of data. Our study intends to investigate how the running time and accuracy of commonly used image classification algorithms evolve using Altum Micasense multispectral and thermal acquisition data with GSD = 2 cm spatial resolution. The running times were examined for two PC configurations, with a 4 GB and 8 GB DRAM capacity, respectively, as these parameters are closer to the memory of NRT microcomputers and laptops, which can be applied “out of the lab”. During the accuracy assessment, we compared the accuracy %, the Kappa index value and the area ratio of correct pixels. According to our results, in the case of plant cover, the Spectral Angles Mapper (SAM) method achieved the best accuracy among the validated classification solutions. In contrast, the Minimum Distance (MD) method achieved the best accuracy on water surface. In terms of temporality, the best results were obtained with the individually constructed decision tree classification. Thus, it is worth developing these two directions into real-time data processing solutions.