Abstract
Citarum Watershed is one of critical watershed that must be restored which included in five priority watersheds. Land use change is one of the problems that occurred in Citarum Watershed for several years. Information about land use change is required as considerationin order to plan policies regarding of revitalization of Citarum Watershed. Remote Sensing is widely well-known of its use for environmental monitoring, especially for land use change detection. Remote Sensing application is commonly use optical image to derive information about land use change in Citarum Watershed beside its limitation related to cloud cover. Sentinel 1A produces SAR data which obtain free cloud information in Citarum Watershed, and it can be used to cover optical satellite weakness. This research utilizes training samplesfromimage in 2016 and 2018 then using random forest to classify land use in 2016 and 2018.Both classification results can be used togenerate new image to see the land use change. Purpose of this research is to understand the potential of Sentinel-1Adata to detect land use change. Result of this research shown that Sentinel-1A could generate land use change even the confidence level is still below 70 percent and still need many improvements.
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