Abstract: Diminishing of vegetation is the main issue in Indonesia as a country with second largest forest in the world. It invites the increasing of global temperature and climate change. In local scale (province and regency level), the conversion from vegetation into another land type could lower the quality of life in such area. To prevent the decrease of vegetation, local governments have been trying to stop the conversion but it is difficult to ensure in daily activity with million people in those areas. Therefore, the objective mean is needed to monitor the numbers of vegetation in a region, e.g. satellite imagery and geographic information system. Satellite imageries can be used to analyse land cover change, especially the conversion from vegetation to other land covers. In this study, a land change modeler using two different dates of map was implemented after hard classification using iterative self-organising clustering in IDRISI Selva software. Decreasing vegetation trend and the direction of change can be seen after comparing two dates of land cover classification map.
Keywords: Satellite Imagery, Multispectral, ISOCLUST, Hard Classification
| DOI: 10.17148/IJARCCE.2021.10814