SPATIAL TEMPORAL ANALYSIS OF PREDICTED FISHING ZONES (ZPPI) IN RIAU WATERS USING R STUDIO COMPUTATIONS (2018–2023)

Abstract

Coastal fisheries in Riau Province, particularly in the regions surrounding Dumai and the Bengkalis Strait, continue to serve as a significant source of livelihood. However, local fishers predominantly depend on intuition rather than empirical data to identify fishing grounds, a practice that results in inefficient fuel use and reduced catch efficiency. This study conducted a spatial-temporal mapping of Fish Catch Prediction Zones (ZPPI) in Riau waters from 2018 to 2023, utilizing sea surface temperature (SST) and chlorophyll-a concentration data derived from Aqua MODIS Level 3 satellite imagery. The data, obtained from the NASA Ocean Color portal, featured a 4 km spatial resolution in NetCDF format. The entire data processing workflow, from extraction to thematic map visualization, was executed in R Studio using the sf, raster, and tmap packages, without reliance on additional software. The results indicate that ZPPI density consistently concentrated along the coast over the six-year period, with the highest point densities observed around Bengkalis, Sungai Pakning, and Dumai. Aggregation zones near Bengkalis Island and river mouths exhibited stability across the years, a pattern attributed to organic nutrient input from river runoff that supports high biological productivity. This spatial consistency provides fishers with a dependable basis for planning fishing routes and minimizing fuel expenses. Furthermore, the study demonstrates that R Studio can function as a comprehensive tool for the entire geospatial fisheries workflow, encompassing satellite data processing, statistical analysis, and cartographic output, thereby integrating tasks typically distributed across separate GIS, spreadsheet, and statistical software. These findings advocate for the use of long-term, satellite-derived environmental data as a practical foundation for fisheries management policy in Riau's coastal waters.