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Dolines are concave circular karst landforms that are clearly presented by topography data (topographic maps), especially on high-resolution LiDAR digital terrain models (DTM). In the karst landscape, man has reshaped natural dolines through centuries by collecting rocks and soil to increase the flat area of tillable (cultivated) land at the bottom of the doline. By this human-induced process, the natural doline was reshaped into a cultivated doline. Cultivated dolines have a rich historical legacy of use for local agricultural production, high geomorphological value for geodiversity and present an important habitat supporting biodiversity. They are an element of agro-karstic landscape (paysage agro-karstiques) and are distinctive of Mediterranean karst landscapes like Dinaric karst, Central massive, Apulia etc. Most of the cultivated dolines have been recently abandoned, and covered by forest, thus the human impact is not evident anymore so clearly.In most studies on natural characteristics and processes in dolines, there is no distinct separation between natural and cultivated dolines and no consideration of past agricultural land use. Thus, the main goal of this study/presentation is to provide a geoinformatics methodology to separate cultivated dolines from natural dolines based on differences in micro-topography by using recent very high-resolution LiDAR topography data and historical cadastral maps (19th century).Using visualized LiDAR DTM the most evident morphometric differences between the natural and cultivated doline landforms were recognized. Cultivated dolines were characterized by (1) a circular concave landform with a flat bottom (2) the presence of anthropogenic elements, such as circular stonewalls at the upper doline edge, which provides evidence of stone-removal from the doline slopes (smooth surface). Additionally, in the 19th-century cadastral maps, only individual dolines with important land use were marked as special lots. Given the rural character of the landscape during that time, the only land use recorded in the concentric lots of the dolines was agricultural use (arable fields, gardens, meadows, and pastures). As a result, the number, location and surface coverage of cultivated dolines were precisely defined for classical karst regions in SW Slovenia. Based on Lidar data, bowl-shaped cultivated dolines with flat bottoms were separated from non-cultivated funnel-shaped dolines.

Increasingly severe hydrological extremes are predicted for the Pannonian Basin as one of the consequences of climate change. The challenges of extreme droughts require the adaptation of agriculture especially during the intense growth phase of crops. For dryland farming, the selections of the optimal land use type and sustainable agricultural land management are potential adaptation tools for facing the challenges posed by increased aridity. To this end, it is indispensable to understand soil moisture (SM) dynamics under different land use types over drought-affected periods. Within the framework of a Slovenian–Hungarian project, soil moisture, matric potential and rainfall time series have been collected at three pilot sites of different land use types (pasture, orchards and a ploughland) in SW Hungary since September 2018. Experiments were carried out in soils of silt, silt loam and clay loam texture. In the summers (June 1 to August 31) of 2019 and 2022, we identified normal and dry conditions, respectively, with regard to differences in water balance. Our results demonstrated that soil moisture is closely controlled by land use. Marked differences of the moisture regime were revealed among the three land use types based on statistical analyses. Soils under pasture had the most balanced regime, whereas ploughland soils indicated the highest amplitude of moisture dynamics. The orchard, however, showed responses to weather conditions in sharp contrast with the other two sites. Our results are applicable for loamy soils under humid and subhumid temperate climates and for periods of extreme droughts, a condition which is expected to be the norm for the future.

The retention of surface runoff and the preservation of soil moisture are among the most important water-related ecosystem services. In addition to field monitoring, advanced remote sensing techniques have been devised to reveal soil moisture dynamics on agricultural land. In our study we compare two soil moisture indices, TWI and SAVI, in three agricultural areas with different land use types. The SAVI has been found suitable to point out spatial variation on the moisture conditions of the vadose zone.

Geoscience has been devoting increased attention to understanding the complex pathways and flows of material, energy, and the multidimensional coupling between various geological systems. This understanding includes the “concept of connectivity”, which provides an overall framework better to investigate hydrological systems. So far, the concept has largely been used for fluvial geomorphic systems, whereas we intend to use it within the karst system. In relation to the concept of connectivity between the karst surface and subsurface, hydrological, sediment, and geochemical connectivities are the most relevant from the perspective of geoscience and to measuring human impacts through a long time span.Our main interest is to study the direct flow between enclosed karst depressions (solution dolines) and near-surface caves (50 m below the surface) that are prone to human influence. The doline-cave coupling zone represents the upper part of a karst aquifer for which specific connectivity characteristics between dolines and near-surface caves can be identified. Polina peč Cave (NW Dinaric Karst) was selected as a case study cave. We used geoinformatic methods (three-dimensional (3D) laser scanning) and available data (Registry of maps, Lidar DEM 1x1m, optical remote sensing data), geomorphometric analyse, geological mapping and surveying. With precise georeferencing (using the GNSS system), we placed the 3D point cloud of the cave in a geographical coordinate system, compared 3D cave map with the surface map (using existing national aero-laser scanning data – Lidar DEM 1x1m), and selected dolines that are most directly connected to cave. The results were controlled and further improved by geophysical methods (electrical resistivity tomography/ERT).

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.

In several European countries, land use changes can be analysed on the basis of the Franciscan Cadastre. Present land use data is defined on the basis of orthophotos, but the historical data is available only at a parcel level. Therefore, a question arose as to how reliable results about land use changes can be. The main aim of the paper was to analyse land use dynamics with the Franciscan Cadastre and to test the compatibility of detailed and parcel level of modern data. The study was carried out by calculating land use structure and landscape metrics for a part of the Pannonian low-hills area in Slovenia. We have observed that the calculation of the land use type structure mostly provided similar results regardless of the level of detail. On the other hand, the results of landscape metrics analysis were highly affected by the level of detail. The analysis at the parcel level showed that the forest area expanded, and fields and vineyards areas diminished. In general, today’s landscape is made of less patches, but they are larger and of more irregular shapes. We can conclude that a comparison of modern data and historical data based on Franciscan Cadastre must include generalisation to a parcel level.

This paper assesses the effects of agricultural payments on changes in farmland bird diversity in Slovenia. Diversity was measured by Shannon index, while the impacts were estimated with the first-difference estimator on panel data for municipalities with and without special protection areas for birds. The effects of agricultural payments on farmland biodiversity require that the balance of financial instruments be taken into account when the agricultural policy is being drafted. The effects of payments in municipalities with and without special protection areas indicate the need to consider the landscape perspective and adapt schemes to landscape type while preparing the national agricultural policy.

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.

Acta geographica Slovenica je znanstvena revija za vsa področja geografije in sorodnih ved. Izdaja jo Geografski inštitut Antona Melika ZRC SAZU, zalaga Založba ZRC in sozalaga Slovenska akademija znanosti in umetnosti. Med letoma 1952 in 1976 je revija izhajala občasno, nato enkrat letno, od leta 2003 dvakrat letno, od leta 2019 pa izhaja trikrat letno. Od leta 1995 revija izhaja tudi na spletu. Od leta 1981 je revija vključena v Scopus, od leta 2003 pa v Web of Science. Je med najbolj citiranimi slovenskimi znanstvenimi revijami v tujini. Leta 2020 je izšel njen šestdeseti letnik in tej obletnici je posvečen ta prispevek. // Acta geographica Slovenica is a scientific journal for papers covering all fields of geography and related disciplines. It is issued by the ZRC SAZU Anton Melik Geographical Institute, published by Založba ZRC, and co-published by the Slovenian Academy of Sciences and Arts. From 1952 to 1976, the journal was published periodically, then once a year, twice a year from 2003, and three times a year since 2019. The online version of the journal has been available since 1995. The journal has been included in Scopus since 1981 and in Web of Science since 2003. It is one of the Slovenian scholarly journals most cited abroad. The 60th volume was published in 2020 and this article is dedicated to the milestone anniversary.

V knjigi je stirinajst poglavij s podrocja naravnih nesrec. V poglavjih so opisana raziskovalna spoznanja ter primeri uporabe sodobnih tehnologij v primeru naravnih nesrec, s poudarkom na domacih odzivih na globalne izzive. Knjiga vsebuje razlicne teme, kot so na primer potresi, suse, vrocinski valovi, poplave, snežni plazovi ter odzivanje in komuniciranje v primeru naravnih nesrec.

Field mapping is an accurate but also time consuming method of detailed mapping of habitat types. Levels of habitat types are usually hierarchically nested at several levels. Our main research question therefore is: ‘How detailed can be modelling of habitat types with decision trees and digital data in karst landscape?’ Similar to studies in other (non-karst) environments we explored the basic properties of the habitats in Dinaric Karst study region (Classical Karst in Southwest Slovenia) and tested modelling of habitat types at three different levels of detail. To seek for the best set of predictor variables we used Rapid-Eye satellite images, airborne images and digital elevation model. We prepared more than 60 explanatory variables and divided habitat polygons into training and testing samples to validate the results. The results proved that modelling with decision trees in Dinaric Karst landscape does not result in high accuracy at high detailed levels. Due to the presence of mine fields in the large area of Dinaric Karst (e.g. in Croatia and Bosnia and Herzegovina) the field mapping in this area is difficult therefore the findings from this study can be used for further development of mapping through remote sensing.

Landscape researchers have described different options for landscape classifications and have suggested the approximate size of landscape units for various scale levels of study and the most suitable data layers (representing biophysical characteristics) for differentiating them. The literature already contains examples of evaluating data layers with regard to their information value, their correlation with one another, and so on, but less research has been done on the suitability of data layers from the perspective of the scale of landscape research. The objective of this paper is to propose a quantitative method to assess different data layers by landscape classification scale. The proposed method is based on systematic sequential multilevel division of the study area, calculating the average moderate coefficient of variation for each scale level, and comparing calculations between scale levels. It can be used to objectively determine which raster data layers are more suitable for defining large landscape units and which are more suitable for defining small ones. We tested the method for Slovenia, a small country at the junction of the Alps, Pannonian Basin, Mediterranean, and Dinaric Alps with a high landscape diversity. To test the method, we systematically divided the country into smaller units using ten differently structured grids (for the case of Slovenia, we used squares with a baseline of 1, 10, 20 km, and so on up to 100 km). For each data layer, we calculated the average moderate coefficient of variation for each division and compared it with the average coefficient of variation for the highest level, which represented the country as one whole unit. The ratios allowed us to classify the data layers into categories and assess which data layers are more important in landscape classification at a small scale, which ones are more important at a large scale, and which ones function as noise. As expected, variation diminishes with a smaller baseline in all cases, but the gradient of decreasing variation is different. We also studied the categorization of data layers using a hierarchical classification method. Following to the proposed method, it is possible to create various categories of data layers by the landscape classification scale for a certain area. The method can be used for any area and is an option for reducing subjectivity in selecting data layers for landscape analysis classification for the most general purposes (e.g., production of landscape classifications for education).

Preucevanje intenzivnosti erozijskih procesov spada med temeljne in pogosto obravnavane geomorfoloske dejavnosti ter obicajno vkljucuje tako terenske meritve kot tudi racunalnisko modeliranje. V Sloveniji so terenske meritve redke, zato prevladuje modeliranje erozijskih procesov. Pri slednjem je zaradi svoje preprostosti kljub pomanjkljivostim zelo priljubljena Gavriloviceva enacba v vec razlicicah. V prispevku predstavljamo uporabnost geografskih informacijskih sistemov pri izracunu posameznih clenov Gavriloviceve enacbe. Z njeno pomocjo smo za panonska gricevja severovzhodne Slovenije ocenili intenzivnost erozije. // The study of the intensity of erosion processes is one of the fundamental and often treated geomorphological activities. It usually involves both field measurements, as well as computer modelling. In Slovenia, field measurements are rare, so modelling of erosion processes prevail. Due to its simplicity the Gavrilovic equation (and its derivatives) is very popular for the calculations of erosion; despite its shortcomings. The paper presents the usefulness of geographic information systems in the calculation of individual parameters of Gavrilovic equation. The Gavrilovic equation was used to calculate the intensity of erosion in Pannonian low-hills of north-eastern Slovenia.

Researchers analyse land use status and its rates of change and try to define the most appropriate structure that suits the environmental characteristics. The article focuses on an analysis of the naturalness level of land use in three hilly regions in north-eastern Slovenia (Slovenske Gorice, Haloze, and Goricko) with the help of geoinformation tools. Land use structure is one of the best indicators of human presence in the landscape. The aim was to expose those parts of catchments that can be regarded as less natural or more natural. We divided the catchments into hydrogeographical areas and analysed them by calculating the urbanity index. The least natural areas in 2018 were located in Slovenske Gorice Hills and the most natural were those in Haloze. The urbanity index diminished between 2002 and 2018 for all the areas except two. The main reason for a higher average of naturalness level is overgrowth – changing agricultural areas into areas with bushes and trees. Natural disasters, e.g. floods and intensive erosion can be mitigated with suitable land use. // Raziskovalci analizirajo stanje rabe tal in trende spreminjanja ter skusajo ugotoviti, kaksna struktura je okoljsko najbolj sprejemljiva. V prispevku smo se osredotocili na analizo rabe tal treh gricevnatih obmocij severovzhodne Slovenije (Slovenske gorice, Haloze in Goricko) z vidika stopnje naravnosti s pomocjo geoinformacijskih metod. Raba tal je namrec eden najbolj nazornih pokazateljev clovekovega delovanja v pokrajini. Dolociti smo želeli posamezna obmocja porecij, ki jih lahko oznacimo za bolj naravna, in obmocja, ki so manj naravna. Porecja smo razdelili na hidrogeografska obmocja in jih analizirali glede na indeks urbanosti. Glede na izracunane indekse so bila v povprecju leta 2018 najmanj naravna obmocja v Slovenskih goricah, najbolj pa v Halozah. Indeks urbanosti se je od leta 2002 do 2018 sicer povsod zmanjsal, razen na dveh obmocjih. Vzrok za povecanje stopnje naravnosti v povprecju gre predvsem na racun zarascanja oziroma spreminjanja nekoc kmetijskih zemljisc v zemljisca v zarascanju. Z ustrezno rabo tal lahko omilimo naravne nesrece, na primer pojav poplav in povecane erozije.

Geographers have produced four landscape typologies of Slovenia to date. The best-established typology is the one from 1996, which relies on natural landscape elements and divides Slovenia into nine landscape types. Great landscape diversity in a small territory is the main geographical feature of Slovenia, and it also has an important impact on its economic and other activities. The population increasingly perceives it as an element of identity. The importance of landscape diversity is also highlighted in certain EU documents.

Geographers have produced many regionalizations of Slovenia to date. The most widely used geographical regionalization is based on a 1996 landscape typology and divides Slovenia into 48 regions and 4 macroregions. The average size of a region is 422 km2. According to the EU classification of territorial units (Nomenclature of Territorial Units for Statistics, NUTS), Slovenia is divided into 2 NUTS 2 regions and 12 NUTS 3 regions and after that into 212 municipalities. The average size of a NUTS 3 region is 1689 km2, and the average size of a municipality is 96 km2. However, the division that continues to be most deeply rooted among Slovenians is the division into the former Austro-Hungarian provinces.

Slovenia is one of the youngest countries in the world. It has been independent since 1991, but at the same time, it is strongly dependent on its geography. Most of its natural, economic, and cultural features result from its location in the center of Europe, where completely different geographical units intersect. It is exposed to South Slavic influences via the karstified plateaus and intermediate lowlands of the Dinaric Alps to the southeast, Hungarian influences from the continental Pannonian Basin to the northeast, Romance influences from the warm Mediterranean to the southwest, and Germanic influences via the steep mountains and deep valleys of the Alps to the northwest. Because most of the territory of what is now Slovenia belonged to Germanic states for over a thousand years, Germanic influences have left the most traces in the Slovenian cultural landscapes and among its residents. Due to its great landscape diversity and despite its smallness, Slovenia is well known for being a European landscape hotspot, and among other things the young country is increasingly using this geographical fact to strengthen its identity.

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.

After the independence of Slovenia and Croatia in 1991, the former internal Yugoslav border between the two countries became an international border (today a Schengen border), of which over two-fifths follows rivers (the Drava, Sotla, Kolpa, Dragonja, and others). Rivers are natural geographical dividers whose shifting courses hamper permanent administrative demarcation, especially in flat areas exposed to frequent flooding and meandering. Thus, rivers as borders may cause problems because they are not static. Moreover, they are very dynamic and tend to change their courses; for example, one country may claim that the “old” course is the border and the other that the “new” course is the border. Practically, all rivers and streams on the Slovenian–Croatian border are such examples. Applied geography and geospatial technologies, especially geographic information systems, have played an important role in the preparation of geographical bases for the arbitration procedure to determine the Slovenian–Croatian border. The final decision, which was announced on June 29, 2017 by The Hague-based Permanent Court of Arbitration, will affect the lives of many people along the border. To analyze the dynamics of changing river courses along the Slovenian–Croatian border, we used geographic information systems and multitemporal analysis of cartographic and other pictorial sources: historical maps, historical aerial images, satellite images, and precise digital elevation models (LiDAR).

With supervised classification methods, we can determine classification rules for landscape types of existing landscape typologies. In this article, we analyse whether supervised classification methods could also define adequate rules for landscape types determination in the case of poorly designed typologies. We tried to model two Slovenian intentionally distorted natural landscape typologies. We noted that due to the incongruity of the distorted typologies, decision tree methods were not capable of forming rules for determination of landscape types. Although we did manage to create modelled distorted typologies with minimum distance to means method, maximum likelihood method, and k -nearest neighbours method, they matched the basic distorted typology only slightly. Z metodami nadzorovane klasifikacije lahko za obstojece naravnopokrajinske tipizacije dolocimo klasifikacijska pravila za posamezne pokrajinske tipe. V prispevku razpravljamo, ali bi tudi v primeru zelo slabo zasnovanih tipizacij z metodami nadzorovane klasifikacije lahko izdelali dovolj natancna pravila za dolocanje pokrajinskih tipov. Poskusili smo modelirati dve namenoma popaceni naravnopokrajinski tipizaciji Slovenije. Opazili smo, da zaradi nesmiselnosti popacenih tipizacij metode odlocitvenih dreves sploh niso bile sposobne izdelati pravil za dolocanje pokrajinskih tipov. Z metodami najmanjse razdalje, najvecje verjetnosti in k najbližjih sosedov pa smo sicer uspeli izdelati modelirane popacene tipizacije, a so se te z osnovno popaceno tipizacijo le malo ujemale.

Pokrajina v visoki locljivosti ('The Landscape in High Resolution') is the fourteenth volume in the series GIS v Sloveniji (GIS in Slovenia). The goal of this volume is to present the wide variety of research findings on geographical information systems in Slovenia in recent years. Powerful geoinformatic tools and precise digital data facilitate research on processes and phenomena with a high level of accuracy. This makes it possible to affirm that the landscape and its components are being analyzed in high resolution. The volume clearly presents project outputs and research results in areas such as seismology, geomorphology, natural hazards, environmental protection, geography, surveying, archaeology, transport, agriculture, remote sensing, and others. Readers will discover new features regarding the applicability of geographical information systems and will learn about interesting findings in many area