25 research outputs found

    Factors affecting the persistence of traditional agricultural landscapes in Slovakia during the collectivization of agriculture

    Get PDF
    Collectivization of agriculture (1950s-1970s) was one of the most important periods in landscape development in Slovakia. Traditionally managed agricultural landscapes, that covered more than half of the Slovak territory, were transformed into large-scale fields and only fragments of traditional agricultural landscapes survived. We mapped the remaining traditional agricultural landscapes using aerial photos and historical maps. We then statistically analyzed the various geographical factors and their influence on the transformation process of traditional and collectivized fields, i.e., slope steepness, soil fertility, distance from settlements and isolation from regional capital cities. The comparison was performed using classification tree analysis. We constructed a set of decision rules that explain why fields were managed traditionally or collectivized. Our findings show that traditional agricultural fields were more likely to persist on steep terrain, less fertile soils, and on locations that were closer to the settlements, but more isolated from the regional capital cities. Steepness played the most important role: small-scale fields located on steep areas were not accessible to heavy machinery and therefore, frequently survived the collectivization. We show that the selected geographical factors are good explanatory variables for the collectivization of arable fields and orchards. For vineyards and grasslands, however, the explanatory power of the selected geographical factors is lower, and we suspect that other factors, not depicted in the analysis play an important role

    Abandonment and Recultivation of Agricultural Lands in Slovakia—Patterns and Determinants from the Past to the Future

    Get PDF
    Central and Eastern Europe has experienced fundamental land use changes since the collapse of socialism around 1990. We analyzeanalyzed the patterns and determinants of agricultural land abandonment and recultivation in Slovakia during the transition from a state-controlled economy to an open-market economy (1986 to 2000) and the subsequent accession to the European Union (2000 to 2010). We quantified agricultural land-use change based on available maps derived from 30-m multi-seasonal Landsat imagery and analyzeanalyzed the socioeconomic and biophysical determinants of the observed agricultural land-use changes using boosted regression trees. We used a scenario-based approach to assess future agricultural land abandonment and recultivation until 2060. The maps of agricultural land use analysis reveal that cropland abandonment was the dominant land use process on 11% of agricultural land from 1986 to 2000, and on 6% of the agricultural land from 2000 to 2010. Recultivation occurred on approximately 2% of agricultural land in both periods. Although most abandoned land was located in the plains, the rate of abandonment was twice as high in the mountainous landscapes. The likelihood of abandonment increased with increased distance from the national capital (Bratislava), decreased with an increase of annual mean temperatures and was higher in proximity to forest edges and on steeper slopes. Recultivation was largely determined by the opposite effects. The scenario for 2060 suggests that future agricultural land abandonment and recultivation may largely be determined by climate and terrain conditions and, to a lesser extent, by proximity to economic centers. Our study underscores the value of synergetic use of satellite data and land-use modeling to provide the input for land planning, and to anticipate the potential effects of changing environmental and policy conditions

    The Potential and Implications of Automated Pre-Processing of LiDAR-Based Digital Elevation Models for Large-Scale Archaeological Landscape Analysis

    Full text link
    LiDAR-derived digital elevation models (DEMs) have transformed the archaeological study of landscape features, broadened our technical capabilities, and enhanced the accuracy with which terrain relief is described. These models also place demands on how researchers and analysts interpret DEM content in the context of the modern landscape. LiDAR-based DEMs contain modern man-made structures that can significantly influence model properties. Although data are usually filtered and some of these artificial features are removed during bare-earth classification, many terrain interventions remain visible. This large-scale case study applies established methods to a freely available DEM of the Czech Republic in an attempt to evaluate differences between original and filtered DEMs. It applies a fully automated filtering procedure using vector topographic maps to avoid manual corrections that would make the procedure problematic when used on a macro scale. The results of our archaeological GIS analysis demonstrate that this procedure, despite its relative simplicity, can achieve a significantly better representation of a landscape compared to that offered by an unfiltered DEM. Finally, we propose a series of future steps with a view to developing a more comprehensive and accurate model and overcoming its limitations

    Fuzzy Similarity and Fuzzy Inclusion Measures in Polyline Matching: A Case Study of Potential Streams Identification for Archaeological Modelling in GIS

    Full text link
    When combining spatial data from various sources, it is often important to determine similarity or identity of spatial objects. Besides the differences in geometry, representations of spatial objects are inevitably more or less uncertain. Fuzzy set theory can be used to address both modelling of the spatial objects uncertainty and determining the identity, similarity, and inclusion of two sets as fuzzy identity, fuzzy similarity, and fuzzy inclusion. In this paper, we propose to use fuzzy measures to determine the similarity or identity of two uncertain spatial object representations in geographic information systems. Labelling the spatial objects by the degree of their similarity or inclusion measure makes the process of their identification more efficient. It reduces the need for a manual control. This leads to a more simple process of spatial datasets update from external data sources. We use this approach to get an accurate and correct representation of historical streams, which is derived from contemporary digital elevation model, i.e. we identify the segments that are similar to the streams depicted on historical maps

    ALS application in the landscape protection of protected heritage zone in Kremnica

    Full text link
    Kremnica bola v minulosti významným uhorským banským mestom. Vzhľadom na ťažbu zlata, sa stala už v stredoveku sídlom kráľovskej mincovne, ktorá pracuje dodnes. Mincovňa je, s výnimkou drobnej ťažby v štôlni Andrej, posledným z fungujúcich komponentov, na ktorých bolo postavené hospodárstvo a význam mesta. Relikty banskej činnosti prešli procesom sukcesie a splynuli s lesnatou krajinou v okolí mesta. Napriek tomu, že toto územie je pamiatkovo chránené ako pamiatková zóna krajinného typu už od roku 1999, kvôli členitému terénu a sukcesii neboli doteraz jeho hodnotné krajinné komponenty dostatočne známe a chránené. To sa prejavilo okrem iného aj v tom, ako bola stanovená hranica chráneného územia. Tá v mnohých miestach pretína priebeh zachovaného banského poľa, či ponecháva cenné krajinné relikty tesne za svojou hranicou. Na území Slovenskej Republiky je od roku 2017 sprístupňované letecké laserové skenovanie (LLS) krajiny. LLS vyniká vysokou hustotou skenovania a aj výškovou a polohovou presnosťou. Zdrojové dáta LLS, preto umožňujú vytvárať digitálny model povrchu (DMP) vo veľmi vysokom rozlíšení 25 cm/px, ktoré je 4-násobne vyššie ako väčšina bežne prístupných dát. DMP je vizualizovaný špecializovaným postupom zvýrazňujúcim relikty prvkov kultúrneho dedičstva. LLS terénu prišlo práve v čase, kedy bolo nutné pristúpiť k aktualizácii zásad ochrany pamiatkového územia. To pomohlo k nastaveniu nového prístupu k vyhodnoteniu tejto lokality založenej na kombinácii interpretácie LLS, historických máp a podrobného terénneho prieskumu. Na prezentáciu poznatkov a praktické účely výkonu štátnej správy bol vytvorený účelný GIS model a pripravuje sa interaktívny 3D model územia, ktorý bude dôležitým nástrojom najmä pre navrhovanie a posudzovanie nových stavebných vstupov v chránenom území.Kremnica was an important mining town in the kingdom. Because of the gold mining it has become since the Middle Ages the seat of the royal mint, which works until today. The mint is the last of the working components with the exception of minor mining in the Andrej shaft upon which the economy and the importance of the town were built. The remnants of the mining activities went through the process of natural succession and blended into the wooded landscape. Despite the area is a protected heritage zone since 1999 its valuable landscape components were not sufficiently known and protected because of broken topography and natural succession. It became visible among others in the way the border of the heritage zone was established. In several places it leaves valuable relicts without protection. Slovakia's landscape is gradually airborne laser scanned (ALS). The source data allow to create a digital surface model (DMP) in very high resolution, which is 4 times higher than most of the commonly available data. DMP is visualized by a specialized workflow highlighting relics of cultural heritage. Full-area ALS of Slovak landscape came just when the regulations of the protected heritage zone needed to be updated. This facilitated the configuration of a new assessment approach for this site using a combination of LLS interpretation, historical maps and field surveys. For presentation and practical use of state administration a practical GIS model was created and an interactive 3D model of the area is being prepared as an important tool mainly for consideration of new building inputs in the protected zone

    Photogrammetric Measurement of Grassland Fire Spread: Techniques and Challenges with Low-Cost Unmanned Aerial Vehicles

    Full text link
    The spread of natural fires is a complex issue, as its mathematical modeling needs to consider many parameters. Therefore, the results of such modeling always need to be validated by comparison with experimental measurements under real-world conditions. Remote sensing with the support of satellite or aerial sensors has long been used for this purpose. In this article, we focused on data collection with an unmanned aerial vehicle (UAV), which was used both for creating a digital surface model and for dynamic monitoring of the spread of controlled grassland fires in the visible spectrum. We subsequently tested the impact of various processing settings on the accuracy of the digital elevation model (DEM) and orthophotos, which are commonly used as a basis for analyzing fire spread. For the DEM generated from images taken during the final flight after the fire, deviations did not exceed 0.1 m compared to the reference model from LiDAR. Scale errors in the model with only approximal WGS84 exterior orientation parameters did not exceed a relative accuracy of 1:500, and possible deformations of the DEM up to 0.5 m in height had a minimal impact on determining the rate of fire spread, even with oblique images taken at an angle of 45°. The results of the experiments highlight the advantages of using low-cost SfM photogrammetry and provide an overview of potential issues encountered in measuring and performing photogrammetric processing of fire spread
    corecore