Multi-source remote sensing workflow (PlanetScope and Sentinel-1/2) applied to LULCC analysis (2016–2024) in the SDERM-CGSM Ramsar Site, Colombia

The Ramsar site “Sistema Delta Estuarino del Río Magdalena Ciénaga Grande de Santa Marta” (SDERM-CGSM), located in the Colombian Caribbean, is a wetland of international importance due to its ecological and environmental value. However, the available thematic cartography to support territorial decision-making is limited, and alternative approaches for land cover monitoring and assessment are required. For this reason, a multi-source remote sensing methodology is presented, integrating PlanetScope (PS), Sentinel-1 (S1), and Sentinel-2 (S2) satellite data for land use and land cover change (LULCC) analysis over the 2016–2024 period in the SDERM-CGSM. Data processing was conducted using Google Colab (GC), ArcGIS Pro, and Google Earth Engine (GEE). Synthetic SWIR 1 (∼1610 nm) and RedEdge 1 (∼740 nm) bands were estimated for each PS image using multiple linear regressions (MLR) based on S2 data, achieving R 2 values between 0.85 and 0.96. The classification workflow was performed through variable selection using a Genetic Algorithm (GA) and the application of a Random Forest (RF) model with a three-stage temporal cross-validation training approach, achieving an overall accuracy (OA) of 92.99% and a Kappa index (K) of 92.36%. Finally, the LULCC diagnosis was carried out through the design and implementation of the Directional Spatial Similarity Index (DSSI), which highlights potential anomalous changes in the classified time series by considering the proportional spatial relationship between the evaluated land covers. It was found that approximately 8% of the Ramsar site may correspond to areas exhibiting unusual changes. In this way, a methodological workflow is presented that enables multitemporal analysis using multi-source data and provides foundational inputs for understanding land cover trajectories in a specific site, offering an initial tool for the development of territorial planning instruments.