PEMODELAN POTENSI PERSEBARAN IKAN BERDASARKAN KAWASAN UPWELLING (STUDI KASUS: PELABUHAN RATU)

• Main Author: Mubinan, Fathan
• Format: Final Project
• Language: Indonesia
• Subjects: Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
• Online Access: https://digilib.itb.ac.id/gdl/view/55392
• Institution: Institut Teknologi Bandung

Indonesia has a water and jurisdiction territory of 5.9 million km2 so that Indonesia has great potential in the marine and fisheries sector. This potential needs to be maintained and improved by managing and supervising the sector. One of the steps that can be taken is to model the distribution of fish found in water areas in Indonesia. The modeling can be done by identifying the areas where upwelling and fronts occur. The purpose of this study was to determine the factors, methods, and relationships between each parameter forming the potential area for fish distribution and to map out the area. The research methodology of this final project includes literature study, method determination, data acquisition, data processing, data validation and presentation of processed data. Data processing is carried out by extracting sea surface temperature and chlorophyll-a data from Landsat-8 images using an algorithm to estimate sea surface temperature and chlorophyll-a values from these images. After that, the upwelling estimation for the potential area of fish distribution was carried out using the classification weighting method and the non-weighted method. In addition, wind and current data are also used as indicators of the occurrence of upwelling in an area and an estimation of the front area is carried out based on the thermal gradient of sea surface temperature. The results of the estimation and upwelling parameters were then tested for correlation of upwelling indicators and validated using fish production results per month. The results of the average correlation test between upwelling-forming parameters such as sea surface temperature with the highest chlorophyll-a are found in algorithm 10, which is -0.452 or moderately correlated and inversely. The upwelling estimation without weighting shows a higher correlation value for the upwelling indicator and the Indian Ocean Dipole (DMI IOD) mode index than using weighting. The front area in this study is only found in data that has cloud data so that it is assumed to be invalid because the thermal gradient formed occurs due to the relationship between sea level and clouds or clouds with clouds. The validation tests carried out showed various relationships from the results of the estimation of the potential area of fish distribution with the production of fish catches. The mapping of potential fish distribution areas based on the classification weighting method shows that upwelling with very strong criteria occurred in January, April, and September in 2019 and in January and September in 2020 while strong criteria dominated in 2019 and in 2020 only occurs from June to October. The unweighted method shows that upwelling occurs in January to March and October to November 2019 and in June, October to November 2020.