Field-Spectroradiometric Characterisation of Three Seagrass Species (Halophila stipulacea, Halodule uninervis, and Halophila ovalis) and Their Differentiation in the Arabian Gulf, Kingdom of Bahrain

Seagrass meadows support critical coastal ecosystems, but corresponding species-level remote sensing data remain limited, particularly in the Arabian Gulf, where field spectral data for dominant taxa are extremely limited. We present the first multi-species spectral characterisation of three dominant seagrass species in the Kingdom of Bahrain—Halophila stipulacea (n = 46 spectra, 25 stations), Halodule uninervis (n = 34, 19 stations), and Halophila ovalis (n = 17, 8 stations)—measured with an ASD FieldSpec® 4 Hi-Res spectroradiometer (Malvern Panalytical, Malvern, UK; 350–2500 nm) from samples collected across 29 geographic stations (52 species–station sampling units). All sample counts reported here underwent quality control. Kruskal–Wallis tests with Benjamini–Hochberg (BH) correction, Jeffries–Matusita (JM) distance, Hedges’ g, and linear discriminant analysis (LDA) were used to characterise inter-species differences. H. ovalis was clearly distinguished from both co-occurring species: the Hd. uninervis–H. ovalis pair showed a discriminating window of 692–1394 nm (mean |g| = 1.31, BH q = 0.000046), and that for the H. stipulacea–H. ovalis pair was 700–1376 nm (mean |g| = 1.21, BH q = 0.000285); the JM distances were 1.60–1.67. A secondary shortwave-infrared discriminating window (1607–1755 nm; mean |g| = 0.90, BH q = 0.006) was also identified for the Hd. uninervis–H. ovalis pair. The H. stipulacea–Hd. uninervis pair showed meaningful geometric separation (JM = 0.994) but no individually significant wavelengths at the available sample size. ASentinel-2-proxy LDA achieved 85.6% overall accuracy (balanced accuracy = 87.3%; macro area under the curve = 0.917), outperforming a Landsat-proxy model by 20 percentage points. For each species, both a best-overall index and a visible-range alternative optimised for submerged satellite remote sensing are reported. The primary indices achieved balanced accuracies of 0.877–0.924; the visible-range alternatives achieved 0.818–0.907. Performance degraded substantially under noise (σ ≥ 0.002: −7.5 percentage points [pp]) and wavelength misregistration (±2–3 nm shifts caused losses of 5.5–15.7 pp), calling for stringent calibration requirements. These results constitute the first multi-species spectral library for Kingdom of Bahrain seagrasses, supporting Sentinel-2-based species mapping in the Arabian Gulf.