Abstract
This chapter makes an attempt to model the land cover changes of Hungary and create predictions for the future. To perform the modelling task, the Land Change Modeler v2.0 for ArcGIS software was used. From the available options, the Multi-Layer Perceptron method was selected. The 1990 and 2006 Corine Land Cover maps were served as basemaps for the modelling. Explanatory variables describing physical environment, relative location, socio-economic attributes was used to generate transition potential maps between each land cover category. Two types of forecasts were prepared: a soft prediction displaying the probability of transition in a given location, and a hard prediction, which describes the most probable land cover pattern in Hungary for 2030. This paper presents two scenarios, a base and an enhanced one, in which elements of spatial planning, future climatic and demographic changes were also introduced as spatial constraints and incentives. The results indicate a significant future increase of the area of forests and a moderate expansion of artificial surfaces and vineyards and orchards, while the share of arable lands, grasslands and heterogeneous agricultural areas will probably decrease.
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Notes
- 1.
In order to estimate the accuracy of the generated MLP network, the software divides the sample of the actual sub-model to learning and testing database. After every iteration, the cells of the testing sample are divided into classes of transition and persistence, and the software compares the results to the real occurrences, and calculates the percentage of accuracy.
- 2.
The value of the Skill Measure can vary between −1 and 1, with the zero value indicating only random matches. Therefore the model has an explanatory power only if the Skill Measure is different than zero.
- 3.
To evaluate the land use models, the Kappa simulation method is also frequently used, which specifically concentrates to the accuracy of the transition forecast with regard to the location (KTransLoc) and the quantity (KTransition).
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Acknowledgements
The results are based on the project Long-term socio-economic forecasting for Hungary (EEA-C12-11), funded by the EEA Grants, within the frame of Adaptation to Climate Change Programme.
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Farkas, J.Z., Lennert, J. (2019). Future Prospects of Land Cover Change in Hungary: Modelling and Forecasts. In: Bański, J. (eds) Three Decades of Transformation in the East-Central European Countryside. Springer, Cham. https://doi.org/10.1007/978-3-030-21237-7_14
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