Modeling of Land Cover Changes in Banjarbaru City South Kalimantan Province
Urban areas often experience land cover changes. Banjarbaru is one of several cities in Indonesia that has experienced land changes. The relocation of the administrative center of Banjarmasin City to Banjarbaru City led to the development of settlements. One spatial analysis carried out to examine t...
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Published in | Jurnal Geografi (Medan) (Online) Vol. 16; no. 1; pp. 89 - 100 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Universitas Negeri Medan
18.03.2024
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Online Access | Get full text |
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Summary: | Urban areas often experience land cover changes. Banjarbaru is one of several cities in Indonesia that has experienced land changes. The relocation of the administrative center of Banjarmasin City to Banjarbaru City led to the development of settlements. One spatial analysis carried out to examine the phenomenon of land change is remote sensing techniques. The method that can be used is the Land Change Modeler from MOLUSCE in QGIS. This model uses the CAM (Cellular Automata Markov) method to identify land cover change and predict land cover distribution. CAM can understand and predict land change patterns by considering land use, vegetation, and cell spatial interactions. This modeling is based on land cover data for 2015 and 2020 and several supporting parameters such as DEM data and distance to roads. Based on the modeling results from 2015 and 2020, Banjarbaru City experienced a change in built-up land, with most of it occurring in the center of Banjarbaru City. Based on the Markov Chain method by looking at land changes in the previous year, the development of built-up land increased by about 8% of the Banjarbaru City area of 32917.41 hectares. Based on the prediction results, the development of built-up land is centered in the middle of Banjarbaru City, such as North and South Banjarbaru Districts, due to the development of residential development.Keywords: Land Cover, Land Change Modeller, Cellular Automata, Markov Chain |
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ISSN: | 2085-8167 2549-7057 |
DOI: | 10.24114/jg.v16i1.48121 |