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Various ice bodies are an important source of paleoenvironmental data, and their study improves the understanding of present and future environmental conditions. Their changes are an important indicator of climate change. This special issue of Acta geographica Slovenica draws attention to the changing and disappearing cryosphere across the globe, with an emphasis on the southeastern Alps, and the necessity to conduct research in this field before the ice disappears forever. This paper briefly summarizes the current body of knowledge on glaciers, permafrost, cave ice, lake and river ice, and snow in the southeastern Alps, and it presents the contribution of Acta geographica Slovenica to this research and the main highlights of all five papers included in this special issue.

Increasingly severe weather extremes are predicted as one of the consequences of climate change. According to climatic models, weather extremities induce higher risks for both flood and drought in the Carpathian Basin. Throughout the 19th and 20th centuries, flood control relied on cost-intensive engineering structures, but recently ecological solutions have come to the fore. Flood hazard on major rivers could be mitigated if multiple and cumulative water retention opportunities are exploited on the upper sections of tributary catchments. Appropriate land use and landscape pattern changes can shift the infiltration to run-off ratio to the benefit of the former. In the Transdanubian Hills of Southwest Hungary three study areas with different agricultural land use types had been selected and investigated for the impact of landscape micro-features on soil moisture retention capacity with the purpose of conserving water from wet periods for the times of drought. Marked differences in moisture dynamics have been detected between arable land, grasslands and orchards. This fact underlines the need for integrated soil and water conservation. Drought risk was found to be the highest on ploughland. Favourable soil water budgets have been observed in the fields as a function of land use: less intensive types, like grazing land and orchards (particularly tree rows), were identified as places of high water retention capacity. Although serious water stress conditions were also reached in the orchard, it markedly mitigated drought conditions compared to the ploughland.

This work discusses the historical development of landscape typologies of Slovenia, focusing on methodology, terminology, criteria for the division of territory, and landscape type hierarchy. It presents all five macrotypologies of Slovenia created between 1946 and 2013, Slovenia’s classification in nine selected macrotypologies of Europe produced between 1995 and 2016, and eight examples of microtypologies of smaller areas of Slovenia made between 1985 and 2020. It compares and evaluates similar typologies. If, in addition to the landscape typology, a geographical regionalization was also produced, common points are sought between the two. The macrotypologies and microtypologies of Slovenia are accompanied by an original and updated map.

Some landscape classifications officially determine financial obligations; thus, they must be objective and precise. We presume it is possible to quantitatively evaluate existing manually constructed classifications and correct them if necessary. One option for achieving this goal is a machine learning method. With (re)modeling of the landscape classification and an explanation of its structure, we can add quantitative proof to its original (qualitative) description. The main objectives of the paper are to evaluate the consistency of the existing manually constructed natural landscape classification with a machine learning-based approach and to test the newly developed general black-box explanation method in order to explain variable importance for the differentiation between natural landscape types. The approach consists of training a model of the existing classification and a general method for explaining variable importance. As an example, we evaluated the existing natural landscape classification of Slovenia from 1998, which is still officially used in the agricultural taxation process. Our results showed that the modeled classification confirms the original with a high rate of agreement--94%. The complementary map of classification uncertainty (entropy) gave us more information on the areas where the classification should be checked, and the analysis of the variable importance provided insight into the differentiation between types. Although the selection of the exclusively climatic variables seemed unusual at first, we were able to understand "the computer's logic" and support geographical explanations for the model. We conclude that the approach can enhance the explanation and evaluation of natural landscape classifications and can be transparently transferred to other areas.

Karst landscapes have an abundance of enclosed depressions. Many studies have detected depressions and have calculated geomorphometric characteristics with computer techniques. These outcomes are somewhat determined by the methods and data used. We aim to highlight the applicability of high-resolution relief laser scanning data in geomorphological studies of karst depressions. We set two goals: geomorphometrically to characterize depressions in different karst plateaus and to examine the influence of data preprocessing and detection methods on the results. The study was performed in three areas of the Slovene Dinaric Karst using the following steps: preprocessing digital elevation models (DEMs), enclosed depression detection, calculating geomorphometric characteristics, and comparing the characteristics of selected areas. We discovered that different combinations of methods influenced the number and geomorphometric characteristics of depressions. The range of detected depressions in the three areas were 442–491, 364–403, and 366–504, and the share of the depressions’ area confirmed with all the approaches was 23%, 29%, and 47%, which resulted in different geomorphometric properties. Comparisons between the study areas were also influenced by the methods, which was confirmed by the Mann–Whitney test. We concluded that preprocessing of high-resolution relief data and the detection methods in karst environments significantly impact analyses and must be taken into account when interpreting geomorphometric results.

One of the methods of water resource management is to construct small retention ponds. Within the framework of the “Possible ecological control of flood hazard in the hilly regions of Hungary and Slovenia“ project the management of small ponds and their impact on flood prevention were studied in selected catchments. Data on pond management were gathered from interviews with pond owners. In a pilot study, we conducted an inventarisation and classification of all retention ponds. Primarily they were constructed for more specific use: fishing, irrigation, watering livestock. These functions have been gradually replaced by leisure-time activities, aesthetics, and tourism. Spring, stream and rainfall-fed ponds prevail in the pilot area and reduce the flood risk. Due to the increased variability of precipitation patterns ponds are also becoming an important measure to limit drought consequences at a local level.

Many countries around the world are facing increasing impacts of natural disasters. This is primarily attributed to climate change, accompanied by an increase in the intensity of meteorological and hydro-geomorphological natural hazards. However, is climate change really responsible for this increased damage and low resilience, or should the cause be sought elsewhere? Based on the case of Slovenia, it is shown that social irresponsibility (e.g., inadequate spatial planning, lack of supervision, insufficient insurance policies, and a mix of politics and capital influences) could be a factor more responsible than climate change for the “catastrophic” consequences of natural disasters.

Supervised and unsupervised classification methods can be a useful tool in determining various geographical spatial divisions, especially regionalizations and typifications. Because Slovenia is geographically very diverse, its divisions are a particularly significant and interesting research challenge. The main objective of this article is to determine the effectiveness of unsupervised classification methods, and therefore we compare the well-established landscape typology of Slovenia from 1996 with landscape typologies that were modeled using various unsupervised classification methods. Our results show that landscape typologies modeled using unsupervised classification methods deviate more from the original landscape typology of Slovenia than landscape typologies modeled using random and expert-supervised classification methods.

In the first part of the analysis we tried to define places in Europe with higher diversity according to different natural landscape types or landscape regions. In order to get such “hotspots” four geographical classifications of Europe were analyzed (Environmental stratification of Europe [21]; European landscape classification [24]; Biogeographical regions [3]; Terrestrial ecoregions of the World [26]). At first maps of variety of landscapes were defined based on each classification that we took into account. This step was done by calculating a number of different unique natural landscape types or regions in radius of 50 km for each cell. Each map of variety of landscapes was then weighted (cell values were divided by a number of all unique types or regions in a division). At the final stage of this part all the maps were synthesized (averaged) into one map showing landscape diversity for the Europe. After that step we defined Europe's landscape hotspots and pointed out the most naturally heterogeneous countries. We found that among all of the European countries, Slovenia has the highest average landscape diversity. Such result gives the country some advantages in the field of tourism based on the natural values of landscape. One of the benefits of having high landscape diversity is making it possible to advertise Slovenia as a tourist destination, offering a "pan-European experience."

The main purpose of this analysis is to identify places in Europe that can be described as very diverse according to various natural landscape types or landscape regions. In order to obtain these “hotspots,” several geographical divisions of Europe were examined. The analysis was performed for most of Europe at 5 km resolution. First, maps of landscape variety were produced based on each division of Europe taken into account. This step was carried out for each cell by counting the number of different unique natural landscape types or regions that are present in a radius of 50 km around the cell. Several maps of landscape diversity were produced using this method. Each of them was then weighted; the cell values were divided by the number of all unique types or regions in a division. In the final stage, all of the maps were synthesized (averaged) into one map showing landscape diversity for Europe. With this data it was possible to determine Europe’s landscape hotspots and to define the most naturally heterogeneous countries. Among all of the European countries, Slovenia has the highest average landscape diversity; the highest absolute landscape diversity is located in the Norwegian part of southern Scandinavia.

Based on digital data on relief, rock, and vegetation, the most significant elements of the internal structure of Slovenian landscapes, and their external appearance, a geographic information system was used to calculate landscape diversity of Slovenia. Areas with high landscape diversity are landscape hotspots, and areas with low landscape diversity are landscape coldspots. One-tenth of Slovenia with the highest landscape diversity was defined as landscape hotspots, and one-tenth of Slovenia with the lowest landscape diversity was defined as landscape coldspots. Most landscape hotspots are located in the Alpine part of Slovenia (more than two-thirds of their total area), and most landscape coldspots in the Dinaric part of Slovenia (almost half of their total area).

This article presents central settlements in Slovenia and their main characteristics in 2016. We defined central settlements based on services of general interest and the population of an individual settlement, and developed the analysis further by using competitiveness indicators. We defined 360 central settlements at six levels of centrality, among which the significance of Ljubljana as a national center of international importance and the significance of intermunicipal, local, and rural centers are increasing. The significance of certain regional centers at the second and third levels of centrality is decreasing. The level of services of general interest supplied to Slovenian territory is relatively appropriate, but it should be improved by promoting competitiveness, especially in centers of national and regional importance.

Cultivated terraces distinctively mark the landscape and are a result of human adaptation to steep areas. Terraces were studied with regard to their morphometric qualities, ownership structure, and land use at eight pilot sites in various landscape types in Slovenia. Twenty-six detailed interviews were carried out with local residents and experts. In current agricultural practice, terraces mostly represent obstacles, and for owners they create a loss rather than profit; however, they represented an advantage in the past, when they were cultivated manually. Land use is intensifying on economically profitable terraces. Among those examined, the Jeruzalem terraces stand out because these are the youngest ones (created in socialist Yugoslavia around 1965). Because of their aesthetic value, they are the best known among the public. Profitability in particular will be an important driving force for the future maintenance of terraces.

The proposed European Union indicators for defining areas less suitable for agriculture in Slovenia are not entirely appropriate because taking them into account would omit some distinctly and clearly unsuitable areas–for example, Suha krajina (Dry Carniola) and Bela krajina (White Carniola)–and farmers would be unjustifiably financially harmed. In such a case, every European Union member state has the right to propose an additional indicator to reduce such discrepancies. With regard to actual natural conditions, in Slovenia especially some karst landscapes would be unjustifiably omitted, and so we have proposed a karst indicator as an additional criterion based on the distribution of karst (i.e., carbonate) rocks. Through spatial coverage of karst rocks and soils, we determined whether more reasonable and less strict application of European criteria regarding soil could be satisfactory for better results in defining areas less suitable for agriculture in Slovenia.

This paper estimates the information gain and the information gain ratio, which are usually used in machine-learning processes, to assess which data layer – absolute elevation or elevation difference – better reflects the topoclimatic characteristics (especially the thermal belt). Both attributes are compared based on their information value in explaining the locations of vineyards, which depend largely on the thermal belt. The analysis is performed on 9,000 cells covering various winegrowing districts. In general, elevation difference proves to be a better attribute, but certain differences can be observed between individual areas, especially between the continental and submediterranean parts of Slovenia.

Načrtovanje raznih dejavnosti v prostoru je zahtevno in odgovorno. Terja dobro poznavanje naravnih in družbenih razmer, poleg tega pa morajo biti rezultati v procesu načrtovanja podani čim bolj nazorno. V prispevku smo na primeru občine Kočevje skušali določiti najbolj primerne nepozidane površine za morebitno širjenje poselitve z vidika naravnih in družbenih dejavnikov. Pri tem smo uporabili metode geografskih informacijskih sistemov.

Based on digital data on relief, rock, and vegetation, the most significant elements of the internal structure of Slovenian landscapes and at the same time of their external appearance, a geographic information system and verification in the field were used to create several natural landscape typologies of Slovenia with a varying number of types. The most generalized typology is based on the spatial overlap of four relief, seven lithological, and seven vegetation units. It has twenty-four landscape types: four flat, eleven low hilly, six hilly, and three mountainous types.