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Předkládaná studie hodnotí vliv environmentálních podmínek na dlouhodobé změny krajinného pokryvu ve dvou horských obcích na středním Slovensku, a to s využitím krabicových grafů, jednoduché logistické regrese a generalizovaných lineárních modelů (GLM). S využitím klasifikace CORINE Land Cover je analyzován krajinný pokryv na historických katastrálních mapách a leteckých snímcích v pěti historických horizontech od r. 1860 do současnosti. Hypotéza, že větší sklon, nadmořská výška a vzdálenost k sídlům je příčinou menší intenzity využívání krajiny byla do značné míry potvrzena, avšak k významným faktorům patřilo i geologické podloží. Modely nejlépe vysvětlitelnou třídou krajinného pokryvu byly lesy; lokalizace orné půdy a travních porostů byla v některých zkoumaných obdobích rovněž značně ovlivněna zkoumanými podmínkami, zatímco lesokřoviny na nich byly prakticky nezávislé. Velikosti ploch změn krajinného pokryvu byli pomocí GLM relativně méně vysvětlitelné.

This paper tests the use of various barrier and corridor effects in cost distance calculation, which often serves as a proxy for accessibility in Land-Use and Land-Cover Change (LUCC) models. The most suitable friction coefficients for barrier effects of slope and water, and corridor effect of roads, are identified by empirical sensitivity analysis. The influence of accessibility on urbanisation, agricultural intensification, and extensification, afforestation, and deforestation in Slovakia is modelled in the present study. The most significant improvement was achieved using the corridor effect of roads for accessibility to the nearest district town, while the barrier of slope significantly improved the effect of accessibility to the nearest commune. Different optimal friction coefficients were identified for different land cover changes; however, only some of them were sensitive to the change of coefficients. [ABSTRACT FROM AUTHOR]

Most land use/cover change (LUCC) models use socioeconomic predictors which spatially approximate human influence on the landscape. According to our meta-analysis, the simplest spatial approximations – the minimal Euclidean distance and indicators based on administrative areas – are used most often. We argue that these approximators are theoretically unjustified for a significant portion of LUCC research designs, mainly because the Euclidean distance ignore other factors influencing transportation costs and the administrative areas often have insufficient spatial resolution or unrepresentative shape. We introduce improvements which overcome these theoretical challenges: improved slope-based cost distance and exposure to human influence as a variant of potential accessibility. The exposure is modified to be measured in activity-per-area units (e.g., population/km2), which are easier to interpret and compare with other socioeconomic indicators (e.g., population density) than standard potential accessibility units. Logistic regression was used to quantify the predictive power of these alternative approximators within different LUCCs in Slovakia, across three time periods. Their performance (AUC) was compared with standard predictors in polynomial models, and their contribution when combined with biophysical predictors was evaluated using hierarchical partitioning. In line with the study's theoretical assumptions, cost distance and exposure significantly surpassed the standard approximators of human influence in most comparisons. They achieved a relatively good performance even for some LUCCs (pastures, permanent cultures, forests, agricultural extensification and intensification, afforestation) where standard socioeconomic indicators were weak. These indicators thus showed potential to improve the precision of LUCC models, particularly in mountainous regions. [Display omitted] • Exposure integrates slope-based cost distance into potential accessibility concept. • Our potential accessibility uniquely uses same units as population density. • "Half-cost" is more intuitive than usual distance decay parameters. • Exposure performed better than population density by 10% and 7% on average. • Cost distance performed better than Euclidean distance by 14% and 7% on average. [ABSTRACT FROM AUTHOR]

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