Opis

• Tytuł:
  GIS-based land cover analysis and prediction based on open-source software and data
• Twórca:
  Dawid, Wojciech;
  Bielecka, Elżbieta
• Opis:
  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.
• Dostępność obiektu:
  Dostęp otwarty
• Prawa: https://creativecommons.org/licenses/by/4.0/ ;
  Prawa autorskie (c) 2022 Wojciech Dawid, Elżbieta Bielecka
• Data:
  2022.09.30
• Typ:
  info:eu-repo/semantics/article;
  info:eu-repo/semantics/publishedVersion;
  Recenzowany artykuł
• Język:
  angielski
• Źródło:
  Quaestiones Geographicae; Vol. 41 No. 3 (2022); 75-86;
  Quaestiones Geographicae; Tom 41 Nr 3 (2022); 75-86;
  2081-6383;
  0137-477X
• Format:
  application/pdf
• Wydawca:
  Adam Mickiewicz University Poznan
• Relacja: http://pressto.amu.edu.pl/index.php/qg/article/view/36444/31164
• Temat i słowa kluczowe:
  land cover change;
  prediction;
  MOLUSCE;
  CA-ANN;
  open data
• Identyfikator: http://pressto.amu.edu.pl/index.php/qg/article/view/36444
• Dostawca danych:
  Platforma Otwartych Czasopism Naukowych UAM
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