%T Article monitoring land use changes and their future prospects using gis and ann-ca for perak river basin, malaysia
%A M.T. Zeshan
%A M.R.U. Mustafa
%A M.F. Baig
%I MDPI AG
%V 13
%K Agricultural robots; Cellular automata; Cellular neural networks; Climate change; Forecasting; Forestry; Geographic information systems; Image classification; Information systems; Information use; Maximum likelihood; Remote sensing; Rivers; Satellite imagery; Water conservation; Water management; Watersheds, Anthropogenic activity; Land use and land cover; LANDSAT satellite images; Management practices; Maximum likelihood supervised classifications; Natural landscapes; Population expansion; Significant patterns, Land use
%X Natural landscapes have changed significantly through anthropogenic activities, particularly in areas that are severely impacted by climate change and population expansion, such as countries in Southeast Asia. It is essential for sustainable development, particularly efficient water management practices, to know about the impact of land use and land cover (LULC) changes. Geographic information systems (GIS) and remote sensing were used for monitoring land use changes, whereas artificial neural network cellular automata (ANN-CA) modeling using quantum geographic information systems (QGIS) was performed for prediction of LULC changes. This study investigated the changes in LULC in the Perak River basin for the years 2000, 2010, and 2020. The study also provides predictions of future changes for the years 2030, 2040, and 2050. Landsat satellite images were utilized to monitor the land use changes. For the classification of Landsat images, maximum-likelihood supervised classification was implemented. The broad classification defines four main classes in the study area, including (i) waterbodies, (ii) agricultural lands, (iii) barren and urban lands, and (iv) dense forests. The outcomes revealed a considerable reduction in dense forests from the year 2000 to 2020, whereas a substantial increase in barren lands (up to 547.39 km2 ) had occurred by the year 2020, while urban land use has seen a rapid rise. The kappa coefficient was used to assess the validity of classified images, with an overall kappa coefficient of 0.86, 0.88, and 0.91 for the years 2000, 2010, and 2020, respectively. In addition, ANN-CA simulation results predicted that barren and urban lands will expand in the future at the expense of other classes in the years 2030, 2040, and 2050. However, a considerable decrease will occur in the area of dense forests in the simulated years. The study successfully presents LULC changes and future predictions highlighting significant pattern of land use change in the Perak River basin. This information could be helpful for land use administration and future planning in the region. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
%D 2021
%R 10.3390/w13162286
%N 16
%O cited By 23
%L scholars14580
%J Water (Switzerland)