Dube, TimothyMashala, Makgabo JohannaAyisi, Kingsley Kwabena2026-05-142026-05-142026Mashala, M.J., Dube, T. and Ayisi, K.K., 2026. Quantifying Land Use and Land Cover Influences on Surface Water Quality through Sentinel-2 Observations in the Letaba Catchment, South Africa. Science of Remote Sensing, p.100424.https://doi.org/10.1016/j.srs.2026.100424https://hdl.handle.net/10566/22443This study evaluates the association between land use and land cover (LULC) and surface water quality in the Letaba Catchment, South Africa, by integrating in-situ physicochemical measurements with Sentinel-2 Multispectral Instrument (MSI) data. Water quality parameters including temperature, pH, dissolved oxygen (DO), electrical conductivity (EC), total dissolved solids (TDS), and salinity (SAL) were measured using a multi-parameter probe. Sentinel-2 spectral bands and derived water indices were analysed using Pearson's and Spearman's correlation coefficients and stepwise multiple linear regression. Statistically significant relationship (p < 0.05) was observed in the visible and red-edge bands with EC and TDS exhibiting strong predictive performance (R2 = 0.84 and 0.87, respectively). Models for DO, SAL, temperature, and pH showed more variable performance, reflecting parameter-specific optical sensitivities. Weak model performance for pH is attributed to its limited spectral expression in the visible-near infrared (VNIR) region. Overall, the results indicate that LULC patterns are significantly associated with spatial variations in water quality, particularly in areas dominated by built up and plantation land uses. The study demonstrates the utility and limitations of Sentinel 2 data for catchment scale water quality monitoring in semi-arid environments.enCatchment healthEnvironmental securityPopulation growthRemote sensingWater qualityArticle