Predicting land cover changes using a CA Markov model under different shared socioeconomic pathways in Greece
Creators: name: Gemitzi, Alexandra
Publisher: name: Taylor & Francis
Year: 2021
Subjects: subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: FOS: Earth and related environmental sciences
subject: Ecology
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: 20199 Astronomical and Space Sciences not elsewhere classified
subject: FOS: Physical sciences
subject: FOS: Physical sciences
subject: 69999 Biological Sciences not elsewhere classified
subject: 80699 Information Systems not elsewhere classified
subject: FOS: Computer and information sciences
subject: FOS: Computer and information sciences
subject: Science Policy
subject: Plant Biology

description: Land change modeling (LCM) is a complex GIS procedure aiming at predicting land cover changes in the future, contributing thus to the design of interventions that help maintain ecosystem services and mitigate climate change impacts. In the present work, the land change model for Greece, a typical Mediterranean country, has been developed, based on historical information from remotely sensed land cover data. Land cover types based on the International Geosphere-Biosphere Program (IGBP) classification were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product, i.e. MCD12Q1, provided annually from 2001 to 2018 at a spatial resolution of 500 m. Initially, the dominant land cover changes and their driving variables for the decade of 2001 to 2011 were determined and the transition potential of land was mapped using a multi-layer perceptron (MLP) neural network. Four dominant land-cover transformations were found in Greece from 2001 to 2011, i.e. land transformation from Savannas to Woody Savannas, from Savannas to Grasslands, from Grasslands to Savannas, and from Croplands to Grasslands. Driving variables were found to be the Evidence Likelihood of Land Cover, i.e. the relative frequency with which different land cover categories occurred within the areas that transitioned, the Altitude as realized in the Digital Elevation Model of Greece from ASTER GDEM, the Distance from previously changed land and two climate variables i.e. Mean Annual Precipitation and Mean Annual Minimum Temperature. After the model was calibrated, its predictive ability was tested for land cover prediction for 2018 and was found to be 96.7%. Future land cover projections up to 2030 were developed incorporating CMIP6 climate data under two Shared Socioeconomic Pathways (SSPs), i.e SSP126 corresponding to a sustainable future and SSP585, which describes the future world based on fossil-fueled development. The results indicate that major historical land transformations in Greece, do not correspond to land degradation or desertification, as it has been reported in previous works. On the contrary, the land cover transitions indicate that the Woody Savannas gain areas constantly, whereas Grasslands and Croplands lose areas, and forested areas of all types demonstrate moderate gains. Concerning future land cover, the present work indicates that the direction of historical changes will also prevail in the next decade, with the most severe scenario, i.e. SSP585 slowing down the rate of changes and the most sustainable one, i.e. SSP126, accelerating the rate of expansion of woody vegetation land cover type.