Publications

Lu, XM; Situ, CY; Wang, JJ; Zhou, LG; Ma, WC; Li, LN (2022). Remote Estimation of the Chlorophyll-a Concentration in Lake Dianshan, China Using High-Spatial-Resolution Satellite Imagery. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 50(12), 2465-2477.

Abstract
The high spatial resolution of satellite data and the capability of physics-based approaches are considered highly suitable for testing the integration of remote sensing technologies into the water quality monitoring of small and medium-sized inland lakes. This research thus aimed to investigate an operational algorithm for chlorophyll-a (Chla) estimation based on China's recently launched high-spatial-resolution GF-1 satellite data for Lake Dianshan, a eutrophic lake in Shanghai city, eastern China. For the calibration of the empirical model, an enhanced three-band model and an improved four-band model (IFB) developed by model derivation and statistical analysis based on in situ water sampling and satellite reflectance data were proposed. The IFB model could account for more than 90% of the Chla variation in the GF-1 satellite data. For the calibration of the semi-empirical model, the performance of Delta phi and an improved NCI model (NCI') were analyzed and validated with field spectral measurements and GF-1 satellite data. The corresponding GF-1 satellite Delta phi model and NCI' model reached high estimation accuracies of R-2 = 0.80 and 0.76, respectively. The good estimated results indicate that the established GF-1 satellite models are promising and applicable to estimating Chla in small and medium-sized eutrophic inland lakes.

DOI:
10.1007/s12524-022-01614-8

ISSN:
0974-3006