A methodological Markov-CA projection of the greening agricultural landscape-a case study from 2005 to 2017 in southwestern Finland

Environ Monit Assess. 2018 Jun 19;190(7):411. doi: 10.1007/s10661-018-6796-y.

Abstract

The aim of the reformed EU Common Agricultural Policy (CAP) 2014-2020 is to enhance greening via an ecological focus area, arable crop diversification, and the maintenance of permanent grasslands. This study tests the greening process in the case of agricultural landscape in southwestern Finland by projecting land use between 2005 and 2017. The study method integrates the quantitative results of Markov chains and spatial features of a cellular automata model. Initially, land use change was recognized by appropriate metrics. The trend of greening following the CAP policy indicated that permanent grassland patches were more persistent with forest patches than agricultural land that lost its vegetated strips to neighboring land use patches. The modeling approach was demonstrated to provide acceptable performance when used as a spatial assessment tool for observing critical patch level changes reflecting the greening agricultural policy.

Keywords: Agricultural landscape; CAP; Finland; Greening; Markov-CA.

MeSH terms

  • Agriculture / methods*
  • Conservation of Natural Resources / methods*
  • Ecology
  • Ecosystem
  • Environmental Monitoring / methods
  • Finland
  • Forecasting
  • Forests
  • Models, Statistical*