GIS-based land cover analysis and prediction based on open-source software and data

• Authors: Wojciech Dawid , Elżbieta Bielecka

Abstracts

EN

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

EN

land cover change; prediction; MOLUSCE; CA-ANN; open data

• Publisher: Uniwersytet im. Adama Mickiewicza w Poznaniu
• Journal: Quaestiones Geographicae
• Year: 2022
• Volume: 41
• Issue: 3
• Pages: 75-86

Dates

published

2022

Contributors

author

Wojciech Dawid

• Faculty of Civil Engineering and Geodesy, Military University of Technology, Warsaw, Poland

• https://orcid.org/0000000179645706

author

Elżbieta Bielecka

• Faculty of Civil Engineering and Geodesy, Military University of Technology, Warsaw, Poland

• https://orcid.org/0000000332551264

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Identifiers

DOI

10.2478/quageo-2022-0026

Biblioteka Nauki

15805022