Reliable assessment of shorelines extracted from medium-resolution satellite imagery requires independent high-resolution reference data and statistical methods that account for spatial dependence. This study compared three conventional analyst-assisted shoreline-extraction workflows—histogram thresholding, band ratio, and the Normalised Difference Water Index (NDWI)—at Coronation Park, Lake Ontario, Canada, using Sentinel-2 Level-2A imagery. A manually digitised shoreline derived from a UAV-based orthomosaic acquired approximately 27 h before the Sentinel-2 scene served as the independent reference. The UAV-based reference and each Sentinel-2-derived shoreline were divided into 31 ordered segments. For each Sentinel-2-derived segment midpoint, the shortest planar Euclidean distance to the nearest UAV-based reference midpoint was calculated and used to derive mean absolute error (MAE) and root mean square error (RMSE). Residual spatial autocorrelation was assessed using Moran’s I with 9999 permutations. Because the paired differences departed from normality, the Friedman test was treated as the primary overall comparison, while contiguous spatial-block permutation tests across block sizes of two to eight shoreline locations assessed robustness to local spatial dependence. NDWI achieved the highest positional agreement (MAE = 5.645 m; RMSE = 6.429 m), followed by band ratio (MAE = 14.303 m; RMSE = 14.797 m) and histogram thresholding (MAE = 26.167 m; RMSE = 26.910 m). Significant positive residual spatial autocorrelation was identified for all three methods (Moran’s I = 0.587–0.832, all p < 0.001). The Friedman test confirmed a significant extraction-method effect, χ2(2) = 49.226, p < 0.001, Kendall’s W = 0.794, and the effect remained significant across all tested spatial-block sizes, with empirical p-values ranging from 0.000007 to 0.004630. Among the three conventional methods tested at this large-lake site, NDWI provided the highest positional agreement and therefore offers a defensible baseline for evaluating future Sentinel-2 image-enhancement approaches.
Shoreline determination is fundamental to coastal research, spatial planning, and legal boundary delineation but remains challenging in low-relief coastal areas where small sea-level variations can produce substantial horizontal shoreline displacements. This study compares shoreline determination methods based on tide...
Ivar Kapsi, Tarmo Kall, K. Türk et al.· Geomatics· 0 citations
Abstract. Monitoring dynamic alluvial rivers is essential for safe inland navigation, yet traditional bathymetric surveys are costly and infrequent. This paper presents an automated method for detecting migrating sandbars by integrating Sentinel-2 satellite imagery with daily water gauge data. Implemented in Google Ear...
M. Smiarowski· The International Archives o...· 0 citations
Satellite-derived bathymetry (SDB) provides a remote-sensing approach for characterizing spatial variations in water depth-related information without requiring complete conventional hydrographic coverage. This study developed a relative satellite-derived bathymetry map of Kopa Dam, Tafa Local Government Area, Niger St...
M. Abdulmumin, A. Sunusi, D. Abdullahi et al.· African Journal of Environme...· 0 citations
Consistent monitoring of wetland Ecosystem Functional Groups (EFGs) over large areas and long periods remains challenging owing to uneven availability, varying spatial resolutions, and spectral similarity of some EFGs. A Google Earth Engine (GEE)-based Earth Observation workflow was developed to map and quantify change...
Philani Apleni, L. Naidoo, Philemon Tsele et al.· MethodsX· 0 citations
A semi-automated remote sensing approach for mapping water-level-specific shoreline contours in waterbodies lacking shoreline bathymetric data offers a rapid, remote and cost-effective tool for screening potential exposure risk of reservoir drawdowns on littoral-dependent fish populations.
Marie-Joëlle Lauzier, Olivier Morissette, Maxime Gillet et al.· Frontiers in Ecology and Evo...· 0 citations
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