<abstract xmlns="http://www.w3.org/1999/xhtml">

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.
</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.

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

Quaestiones Geographicae

This work is licensed under the Creative Commons Attribution 4.0 International License.

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...

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

Data publikacji: 16 lip 2022

Zakres stron: 75 - 86

Otrzymano: 14 lut 2022

DOI: https://doi.org/10.2478/quageo-2022-0026

Słowa kluczowe
land cover change, prediction, MOLUSCE, CA-ANN, open data

© 2022 Wojciech Dawid et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Data publikacji: 16 lip 2022

Zakres stron: 75 - 86

Otrzymano: 14 lut 2022

DOI: https://doi.org/10.2478/quageo-2022-0026

Słowa kluczoweland cover change, prediction, MOLUSCE, CA-ANN, open data

© 2022 Wojciech Dawid et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
land cover change, prediction, MOLUSCE, CA-ANN, open data