A Classification-Based, Semianalytical Approach for Estimating Water Clarity From a Hyperspectral Sensor Onboard the ZY1-02D Satellite

Water clarity ( $Z_{\mathrm {sd}}$ ) is a widely used quality indicator that can be estimated from remote sensing imagery. China’s newest generation advanced hyperspectral imager (AHSI) onboard the ZY1-02D satellite is expected to enable accurate water clarity retrieval for inland waters, since AHSI can provide abundant band choices, while its 30-m spatial resolution is advantageous for monitoring small inland water bodies. In this study, to retrieve $Z_{\mathrm {sd}}$ from the ZY1-02D imagery for inland waters with varying turbidities, we propose a classification-based, semianalytical method, in which the red/blue band ratio is employed to distinguish clear to moderately turbid water and highly turbid waters. Two quasi-analytical algorithms (QAAs), QAA _v5 and QAA _m14 , are used to estimate the total absorption coefficient [ $a(\lambda)$ ] and the backscattering coefficient [ $b_{b}(\lambda)$ ] for clear to moderately turbid water and highly turbid waters, respectively. The estimated $a(\lambda)$ and $b_{b}(\lambda)$ are utilized to obtain the diffuse attenuation coefficient $K_{d}$ , followed by the $Z_{\mathrm {sd}}$ calculations. Compared with 70 matchups of in situ measured $Z_{\mathrm {sd}}$ values (0–6.5 m), the ZY1-02D image-derived $Z_{\mathrm {sd}}$ achieved an $R^{2}$ of 0.98, with an average unbiased relative error and root mean square error of 29.1% and 0.52 m, respectively. In addition, the proposed method can yield $Z_{\mathrm {sd}}$ with higher accuracies than that of optimized empirical models. Therefore, the ZY1-02D AHSI imagery can retrieve reliable $Z_{\mathrm {sd}}$ for both clear (>3 m) and turbid waters (0–3.0 m), thereby serving as a useful satellite data source for monitoring the water clarity of large-scale inland water bodies.