Published April 29, 2026
| Version v1
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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)
Authors/Creators
- 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
The model environment constitutes the core component of the Animal, Landscape, and Man Simulation System (ALMaSS). ALMaSS was developed to evaluate the effects of changes in landscape structure and management on key animal species within agroecosystems. Consequently, it is designed to work with representations of actual agricultural landscape areas, capturing both spatial and temporal landscape heterogeneity to fulfil the specific requirements of the ALMaSS species models.
This article presents the methodology for describing the land-use/land-cover of agricultural landscapes and generating detailed landscape representations for use in ALMaSS landscape simulations. We outline the external data requirements and data handling procedures necessary to prepare the final set of input files for an ALMaSS run. We provide a mapping algorithm to generate a landscape (land-use/land-cover) raster map and describe the methods for classifying and defining ALMaSS farm types and crop rotations. We present exemplary results and discuss potential applications beyond the ALMaSS modelling framework. Finally, we examine the ALMaSS landscape model generation process in the context of input data quality, accessibility, and data processing challenges and offer a perspective on future developments.
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