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A new spatial variable for the land use and land cover change modelling is introduced, approximating the intensity of human influence on the landscape. The 'exposure' simulates the dilution of human activity from settlements (source points with information about population size or other human activity quantification) to landscape, based on the accessibility. Exposure to a settlement is directly proportional to its population size and inversely proportional to the cost distance from the settlement. Cost distance uses the sine of the slope angle as a cost raster to simulate a barrier effect of the terrain. Overall exposure to human influence summates exposure to all individual settlements in a region. The resultant raster field created for Slovakia achieves observable resemblance to the actual intensity of land use derived from Corine Land Cover map. The ArcGIS tool developed for the exposure calculation is supplemented. [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]

Monitoring of land cover (LC) provides important information of actual land use (LU) and landscape dynamics. LC research results depend on the size of the area, purpose and applied methodology. CORINE Land Cover (CLC) data is one of the most important sources of LU data from a European perspective. Our research compares official CLC data (third hierarchical level of nomenclature at a scale of 1:100,000) and national statistics (NS) of LU in Slovakia between 2000 and 2018 at national, county, and local levels. The most significant differences occurred in arable land and permanent grassland, which is also related to the recording method and the development of agricultural land management. Due to the abandonment of agricultural areas, a real recorded increase in forest cover due to forest succession was not introduced in the official records of Land register. New modification of CLC methodology for identifying LC classes at a scale of 1:10,000 and fifth hierarchical level of CLC is firstly applied for local case studies representing lowland, basin, and mountain landscape. The size of the least identified and simultaneously recorded area was established at 0.1 ha the minimum width of a polygon was established at 10 m, the minimum recorded width of linear elements such as communications was established at 2 m. The use of the fifth CLC level in the case studies areas generated average boundary density 17.2 km/km2, comparing to the 2.6 km/km2 of the third level. Therefore, when measuring the density of spatial information by the polygon boundary lengths, the fifth level carries 6.6 times more information than the third level. Detailed investigation of LU affords better verification of national statistics data at a local level. This study also contributes to a more detailed recording of the current state of the Central European landscape and its changes. [ABSTRACT FROM AUTHOR]