Ice caves can be considered an indicator of the long-term changes in the landscape. Ice volume is dynamic in the caves throughout the year, but the inter-seasonal comparison of ice dynamics might indicate change in the hydrological–climatic regime of the landscape. However, evaluating cave ice volume changes is a challenging task that requires continuous monitoring based on detailed mapping. Today, laser scanning technology is used for cryomorphology mapping to record the status of the ice with ultra-high resolution. Point clouds from individual scanning campaigns need to be localised in a unified coordinate system as a time series to evaluate the dynamics of cave ice. Here we present a selective cloud-to-cloud approach that addresses the issue of registration of single-scan missions into the unified coordinate system. We present the results of monitoring ice dynamics in the Silická ľadnica cave situated in Slovak Karst, which started in summer of 2016. The results show that the change of ice volume during the year is continuous and we can observe repeated processes of degradation and ice formation in the cave. The presented analysis of the inter-seasonal dynamics of the ice volume demonstrates that there has been a significant decrement of ice in the monitored period. However, further long-term observations are necessary to clarify the mechanisms behind this change.

The use of solar radiation in the urban environment is becoming increasingly important for the sustainable development of cities and human societies. Several factors influence the distribution of solar radiation in urban areas, including urban morphology and the physical properties of urban materials. Most of these factors can be modeled with a relatively high accuracy using 2D and 3D solar radiation models. In this paper, the r.sun and v.sun solar radiation models are used to calculate solar radiation for the city of Košice in Eastern Slovakia to assess the accuracy of both approaches for vertical surfaces frequently found in urban areas. The results were validated by pyranometer measurements. The results showed relatively good estimates by the 3D v.sun model and poor estimates by the 2D r.sun model. This can be attributed to an improper representation of vertical surfaces by a digital surface model, which has a strong impact on solar resource assessments. We found that 3D city models prepared in level of detail 2 (LoD2) are not always adequate in case of complex buildings with morphological structures, such as terraces. These cast shadows on facades especially when solar altitude is high and, thus, assessments, even by a 3D model, are inaccurate.

Karst dolines, as geomorphologically diverse natural landforms, usually exhibit more or less steep microclimatic gradients that provide a mosaic of diverse microhabitat conditions, resulting in a high diversity of soil biota with numerous rare endemic and/or relict species occupying these habitats. In this study, we investigated the spatial patterns of Collembola abundance, species richness, community structure and distribution of functional groups at topographically and microclimatically different sites across three open (unforested) karst dolines in a north-south direction in the Slovak Karst, Slovakia. We also assessed the refugial capacity of dolines for collembolan communities. The Friedman ANOVA test confirmed the significant differences in soil mean temperatures between the sites of all the dolines selected. The diverse soil microclimatic conditions within the dolines supported higher Collembola diversity (species numbers, diversity indices) compared with sites on the karst plateau and showed a potential to facilitate the persistence of some species that are absent or very rare in the surrounding landscape. In dolines with circular morphology and comparable size, the topography and soil microclimate had a stronger effect on community composition and structure than soil organic carbon. Shallow solution dolines provided microhabitats for various functional groups of soil Collembola in relation to the microclimatic character of the individual sites. It was observed that such landforms can also function as microclimatic refugia for cold-adapted species through the accumulation of colder air and the buffering of the local microclimate against the ambient mesoclimate, thus underlying the necessity of adequate attention in terms of the conservation of the karst natural phenomena.

This study explores advanced methodologies for estimating subcanopy solar radiation using LiDAR (Light Detection and Ranging)-derived point clouds and GIS (Geographic Information System)-based models, with a focus on evaluating the impact of different LiDAR data types on model performance. The research compares the performance of two modeling approaches—r.sun and the Point Cloud Solar Radiation Tool (PCSRT)—in capturing solar radiation dynamics beneath tree canopies. The models were applied to two contrasting environments: a forested area and a built-up area. The r.sun model, based on raster data, and the PCSRT model, which uses voxelized point clouds, were evaluated for their accuracy and efficiency in simulating solar radiation. Data were collected using terrestrial laser scanning (TLS), unmanned laser scanning (ULS), and aerial laser scanning (ALS) to capture the structural complexity of canopies. Results indicate that the choice of LiDAR data significantly affects model outputs. PCSRT, with its voxel-based approach, provides higher precision in heterogeneous forest environments. Among the LiDAR types, ULS data provided the most accurate solar radiation estimates, closely matching in situ pyranometer measurements, due to its high-resolution coverage of canopy structures. TLS offered detailed local data but was limited in spatial extent, while ALS, despite its broader coverage, showed lower precision due to insufficient point density under dense canopies. These findings underscore the importance of selecting appropriate LiDAR data for modeling solar radiation, particularly in complex environments.

Keywords: urban greenery, 3D city model, LiDAR, urban microclimate Urban greenery has various positive micro-climate effects including mitigation of heat islands. The primary root of heat islands in cities is in absorption of solar radiation by the mass of building structures, roads and other solid materials. The absorbed heat is subsequently re-radiated into the surroundings and increases ambient temperatures. The vegetation can stop and absorb most of incoming solar radiation mostly via the photosynthesis and evapotranspiration process. However, vegetation in mild climate of Europe manifests considerable annual seasonality which can also contribute to the seasonal change in the cooling effect of the vegetation on the urban climate. Modern methods of high-resolution mapping and new generations of sensors have brought opportunity to record the dynamics of urban greenery in a high resolution in spatial, spectral, and temporal domains. In this paper, we use the case study of the city of Košice in Eastern Slovakia to demonstrate the methodology of 3D mapping and modelling the urban greenery during one vegetation season in 2016. The purpose of this monitoring is to capture 3D effects of urban greenery on spatial distribution of solar radiation in urban environment. Terrestrial laser scanning was conducted on four selected sites within Košice in ultra-high spatial resolution. The entire study area, which included these four smaller sites, comprised 4 km² of the central part of the city was flown within a single airborne lidar and photogrammetric mission to capture the upper parts of buildings and vegetation. The acquired airborne data were used to generate a 3D city model and the time series of terrestrial lidar data were integrated with the 3D city model. The results show that the terrestrial and airborne laser scanning techniques can be effectively used to monitor seasonal changes in foliage of trees in order to assess the transmissivity of the canopy for microclimate modelling.