The EroTrack tool was developed to assess shoreline dynamics and coastal erosion trends along the West African coastline through the integration of cloud-based remote sensing, geospatial analysis, and shoreline change modeling. The tool focused on key segments of the West African coastline.

Study Area and Data Collection

Areas of Interest (AOIs) were delineated using custom polygon to define coastal zone of the countries under study. Historical satellite imagery was accessed from Google Earth Engine covering the period 2000 to 2024. The datasets included Landsat 7 and 8, as well as Sentinel-2 surface reflectance imagery.

The images were filtered for cloud cover and shadow contamination. Only cloud-free images within the AOIs were retained for further processing.

Water Index Analysis

The Normalized Difference Water Index (NDWI) was calculated using the green and shortwave infrared (SWIR) bands. The NDWI enhances the land-water contrast, making it suitable for shoreline detection.

An annual median NDWI composite was then generated for each year to reduce the influence of seasonal variability and tidal fluctuations. These composites provided stable reference images from which shoreline positions were extracted.

Shoreline Extraction Process

Shoreline extraction was performed using thresholding on the NDWI composites. The resulting binary water masks were converted to raster layers representing approximate shoreline positions for each year.

These shoreline raster datasets were exported from GEE as GeoTIFFs into ArcGIS Pro for further analysis.

Shoreline Change Analysis

In ArcGIS Pro, each annual shoreline raster was vectorized using raster-to-polygon conversion tools. The resulting vector layers were cleaned, standardized, and assigned date attributes to facilitate time-series shoreline change analysis.

Using the Digital Shoreline Analysis System (DSAS), a fixed inland baseline was established for each country, based on data availability and coastal configuration. From this baseline, transects were generated at 100-meter intervals, oriented perpendicular to the shoreline.

DSAS was then used to calculate key shoreline change metrics, including Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR). These metrics quantified both the magnitude and direction of shoreline change over time, highlighting zones of intense erosion and significant accretion along the West African coast.

Impact Assessment

These shorelines change data were integrated with population distribution and land use datasets to assess the broader implications of coastal erosion within the region. This enabled estimates of land area lost, and the number of people potentially affected by shoreline retreat over the study period.

Technical Implementation and Visualization

The final outputs were published as feature services on ArcGIS Server, and an interactive dashboard was developed to visualize shoreline trends, risk hotspots, and population exposure. The dashboard supported the exploration of shoreline change metrics, visualizing erosion and accretion trends.

Users can interactively filter data by country, district, and view time-series charts. API endpoints were automatically generated, allowing external applications to access and query the data dynamically.

These endpoints were then embedded into the ROC DataHub platform, enabling seamless integration with its web-based interface.