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Modeling land cover dynamics using Markov chain and cellular automata in Batang Regency

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Land cover change is one of the impacts of the economic development process, also marked by urbanization. One form of urbanization is industrialization. Batang Regency is an area currently carrying out much industrial development, such as the steam power plant and the Batang integrated industrial area (KITB), which can become a centre of economic growth. Accessibility in Batang Regency is currently passed by the Toll Road and National Road, which can be one of the attractions for changes in land cover. This study aims to predict land-cover changes due to economic activities and compare the prediction results with applicable regulations. The method used is the cellular automata algorithm for 2032 and 2039. Land cover modelling is carried out based on data from 2015 to 2023. The selection of years is based on the Batang Regency spatial planning (RTRW) regulations. Accuracy test results using the relative operating characteristic (ROC) method show that the number is 0.86. The results of land cover predictions show that open land and agriculture tend to decline. Changes in land cover tend to occur in areas close to economic centres and highways. The agricultural area in the prediction results is lower than the planned area, indicating that the program to maintain agricultural land has been considered in the RTRW. The conversion of land that tends to be used as settlements is done in non-agriculture fields, such as forest areas and plantation areas.
Twórcy
  • Department of Geography, Faculty of Social and Political Science, Universitas Negeri Semarang, Indonesia
  • Department of Geography, Faculty of Social and Political Science, Universitas Negeri Semarang, Indonesia
autor
  • Department of Geography, Faculty of Social and Political Science, Universitas Negeri Semarang, Indonesia
Bibliografia
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c88e5673-fa8d-453c-addc-943a0bde47c8
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