Understanding coastal dynamics is critical for effective shoreline management and environmental planning. This study presents a multi-temporal analysis of shoreline changes along India’s western coast, specifically for the coast of Karnataka state, often referred to as Karavali region, using PlanetScope, Sentinel-2, and Landsat satellite imageries. The combination of automated image processing and remote sensing techniques are employed for the extraction of shoreline dynamics with higher spatial accuracy and efficient temporal analysis. The study uses a Python-based shoreline extraction toolkit and spectral water indices to delineate water boundaries and identify shorelines temporally. By comparing remote sensing imagery across varying spatial resolutions, the study evaluates the limitations, and scope of each satellite sensor in capturing fine-scale coastal dynamics. The higher temporal availability of PlanetScope and the spectral richness of Sentinel-2, in addition with the long-term datasets of Landsat mission, enabled a deeper understanding of shoreline trends and their causation. The results reveal substantial spatiotemporal variability in coastal erosion and accretion patterns influenced by geomorphological features, anthropogenic interventions, and seasonal changes. The analysis using PlanetScope imagery having superior spatial resolution indicated a 15% improvement in shoreline extraction compared to coarser images from Landsat or Sentinel-2 observations. In contrast, long-term analysis of Landsat data revealed an average shoreline accretion rate of 0.36 m/year and an erosion rate of − 1.37 m/year over 35 years across two selected transects along the coastline. The outcomes serve as a valuable input for coastal vulnerability assessments and can assist in formulating adaptive management strategies under climate-induced sea-level rise scenarios. The study contributes directly to sustainable development goals (SDG) 13 and 14.