GIS-Based Land Cover Analysis and Prediction Based on Open-Source Software and Data

Dawid Wojciech () and Bielecka Elżbieta
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Dawid Wojciech: Faculty of Civil Engineering and Geodesy, Military University of Technology, Warsaw, Poland
Bielecka Elżbieta: Faculty of Civil Engineering and Geodesy, Military University of Technology, Warsaw, Poland

Quaestiones Geographicae, 2022, vol. 41, issue 3, 75-86

Abstract: The study aims at land cover prediction based on cellular automata and artificial neural network (CA-ANN) method implemented in the Methods Of Land Use Change Evaluation (MOLUSCE) tool. The Tricity region and the neighbouring counties of Gdański and Kartuzy were taken as the research areas, and coordination of information on the environment (CORINE Land Cover, CLC, CLMS 2022) data for 2006, 2012 and 2018 were used to analyse, simulate and predict land cover for 2024, the next reference year of the CORINE inventory. The results revealed an increase in artificial surfaces, with the highest value during the period 2006–2012 (86.56 km2). In total, during the period 2006–2018, the growth in urbanised area amounted to 95.37 km2. The 2024 prediction showed that artificial surfaces increased by 9.19 km2, resulting in a decline in agricultural land.

Keywords: land cover change; prediction; MOLUSCE; CA-ANN; open data (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:quageo:v:41:y:2022:i:3:p:75-86:n:1

DOI: 10.2478/quageo-2022-0026

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