Quantifying the impact of industrialization on blue carbon storage in the coastal area of Metropolitan Semarang, Indonesia

This study investigated the impact of the coastal industrialization policy which began in 2015 in Indonesia. Because this policy has effected physical change on the environment, it requires quantification to determine its driving factors, and to formulate solutions to its problems. In doing so, this research used remote sensing and machine learning techniques. Satellite data from Sentinel-2A were acquired for the years 2015 and 2019 for LULC model, and Landsat 8 OLI for industrial growth model in coastal area. The data were processed using QGIS 3.8 software with machine learning techniques, the Random Forest algorithm, and sci-kit learn library from Dzetsaka tools. The results showed that changes in land use and land cover areas significantly contributed to the loss of blue carbon storage of more than 20%. This finding confirms that the industrialization policy on the coastal area needs to be reviewed, and land use monitoring must be more strictly regulated.