<![CDATA[The coastal area of Palu Bay experienced rapid geomorphic dynamics, pressure on space utilization, and changes after the 2018 tsunami. Evaluation of land capabilities is important to uncover this potential, but conventional field methods are cost-intensive, time-consuming, and labor-intensive, and less effective—especially in dynamic and disaster-prone coastal areas such as Palu Bay (earthquakes, tsunamis, liquefaction, underwater landslides). Development without considering coastal typology risks triggering repeated disasters. This study utilizes SPOT-6 satellite imagery, Geographic Information System to efficiently compile coastal typology classification. Supporting data includes terrain maps, thematic maps, and secondary data; object-based classification from satellite imagery followed by field verification based on BSN Land Cover Classification. Measurement of land parameters is carried out through rapid measurements and soil sampling. The integration of spatial data and attributes with overlay techniques results in six classes of land capabilities. The analysis showed changes in post-tsunami land capacity, with two classes requiring further evaluation. In addition, the study identified nine coastal typologies that reflect the biophysical conditions of the Palu Bay coast, confirming that land capabilities affect coastal physical conditions. These findings provide a scientific basis for the preparation of setback zones, ecosystem rehabilitation priorities, and directions for the use of coastal space that are aligned with risk. This study confirms the role of high-resolution remote sensing as an important tool in resilient and sustainable coastal planning]]>
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