Abstract
The explosive rate of population growth demands a revision of existing protective measures to address water scarcity that urges water body monitoring models to be developed using satellite image-based change detection approaches. And the main objective of this proposed work was to investigate the spectral indices for spatial object extraction in satellite images with respect to water body extraction. The Landsat 8 coastal/aerosol band (0.433–0.453 μm) is still an unexplored band with spectral signatures that favor water extraction, and it has been used in the proposed deep blue normalized difference water index (DBNDWI). The multi-temporal Landsat 8 data products of three lakes with distinct geographical importance from India and Iran are chosen for assessment. Widely used spectral indices for water body extraction such as the normalized difference water index (NDWI), modified normalized difference water index, and automated water extraction index are the benchmark results used for comparative assessment. Along with these conventional water indices, the most recent water indices weighted normalized difference water index (WNDWI) and Wavelet-based normalized difference water index (WAWI) are also compared for extended validation. The use of standard image quality analysis and statistical histogram distance measures justifies the significance of coastal band in extracting water bodies. The experimental results tabulated show that proposed DBNDWI outperforms the most recent WNDWI and WAWI with higher accuracy, even in moderate-resolution images.
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Aroma, R.J., Raimond, K., Estrela, V.V. et al. A coastal band spectral combination for water body extraction using Landsat 8 images. Int. J. Environ. Sci. Technol. 21, 1767–1784 (2024). https://doi.org/10.1007/s13762-023-05027-z
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DOI: https://doi.org/10.1007/s13762-023-05027-z