Published April 29, 2026 | Version v1
Figure Open

Figure 9 from: Ziółkowska E, Jaśkowiec B, Groom GB, Topping CJ (2026) Development of a spatio-temporal representation of agricultural landscapes as the modelling environment for spatially explicit agent-based models in the Animal Landscape and Man Simulation System (ALMaSS). Agricultural and Environmental Modelling 8: e167439. https://doi.org/10.3897/aem.8.167439

  • 1. Institute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland|Institute of Geography and Spatial Management, Faculty of Geography and Geology, Jagiellonian University, Kraków, Poland|Social-Ecological Systems Simulation Centre, Department of Agroecology, Aarhus University, Aarhus, Denmark
  • 2. Institute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland
  • 3. Social-Ecological Systems Simulation Centre, Department of Agroecology, Aarhus University, Aarhus, Denmark

Description

Figure 9 Exemplary landscapes 10 × 10 km from Poland mapped using landscape model generation algorithms for ALMaSS. The presented landscapes exhibit variations in structural and farming heterogeneity. These differences are quantified through various landscape- and class-level metrics, providing insights into the complexity and diversity of the mapped areas. ALMaSS types of landscape elements (TOLEs) were generalised to six main classes: built-up areas (with transport infrastructure); semi-natural herbaceous areas, including meadows, extensively managed grasslands, field margins, and road verges; semi-natural woody areas, including forests, coppices, shrubs, individual trees, tree lines, and hedgerows; water; arable (with individual fields); and other. Each analysed landscape was coded with the first two letters of the main town within or on the border of its area (LU – Lubicz, RE – Redło, KR – Krotoszyn, DO – Domaniów, LI – Lipno, WI – Wieluń, WA – Warnice, NG – Nowy Gołębin, SK – Skulsk). Details about the landscapes are provided in Ziółkowska et al. (2021).

Files

big_1613431.jpg

Files (808.1 kB)

Name Size Download all
md5:433acdd3951b12612bdedf1391169b03
808.1 kB Preview Download

Linked records

Additional details

Related works

Is part of
Journal article: 10.3897/aem.8.167439 (DOI)
Journal article: https://zenodo.org/record/19942199 (URL)