{"title":"GIS-Based Land Cover Analysis and Prediction Based on Open-Source Software and Data","authors":"Wojciech Dawid, E. Bielecka","doi":"10.2478/quageo-2022-0026","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":46433,"journal":{"name":"Quaestiones Geographicae","volume":"41 1","pages":"75 - 86"},"PeriodicalIF":1.0000,"publicationDate":"2022-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quaestiones Geographicae","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/quageo-2022-0026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 2
Abstract
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.
摘要研究了基于元胞自动机和人工神经网络(CA-ANN)的土地覆盖预测方法，并将其应用于土地利用变化评价方法(Methods Of land Use Change Evaluation, MOLUSCE)工具中。以Tricity地区及其邻近的Gdański和Kartuzy县为研究区，利用2006年、2012年和2018年的环境信息(CORINE Land Cover, CLC, CLMS 2022)数据对2024年(CORINE清单的下一个参考年)的土地覆盖进行分析、模拟和预测。结果表明:人工地表面积呈增加趋势，以2006-2012年为最大值(86.56 km2);总体而言，2006-2018年期间，城市化面积增长了95.37平方公里。2024年预测人工地表面积增加9.19 km2，导致农业用地减少。
期刊介绍：
Quaestiones Geographicae was established in 1974 as an annual journal of the Institute of Geography, Adam Mickiewicz University, Poznań, Poland. Its founder and first editor was Professor Stefan Kozarski. Initially the scope of the journal covered issues in both physical and socio-economic geography; since 1982, exclusively physical geography. In 2006 there appeared the idea of a return to the original conception of the journal, although in a somewhat modified organisational form. Quaestiones Geographicae publishes research results of wide interest in the following fields: •physical geography, •economic and human geography, •spatial management and planning,
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
