Water quality parameters retrieval of coastal mariculture ponds based on UAV multispectral remote sensing - Zhang, Yumeng; Jing, Wenlong; Deng, Yingbin; Zhou, Wenneng; Yang, Ji; Li, Yong; Cai, Yanpeng; Hu, Yiqiang; Peng, Xiaoyan; Lan, Wenlu; Peng, Mengwei; Tang, Yimin (Frontiers in Environmental Science, 2023)
The rapid expansion of aquaculture in coastal areas is typically associated with ecological negligence and low water quality owing to the economic exploitation of these areas. However, evaluation of these water bodies tends to be laborious, time-consuming, and costly. Therefore, to overcome these limitations, in this study, we evaluated water bodies in the Beibu Gulf of Guangxi, obtained spectral reflectance by unmanned aerial vehicle with multispectral sensors, and constructed inverse models of 11 water quality parameters, namely, ammonia nitrogen (NH3-N), chemical oxygen demand (COD), active phosphate (PO4−), dissolved oxygen, nitrate nitrogen (NO3-N), nitrite nitrogen (NO2-N), inorganic nitrogen, total nitrogen, total phosphorus, suspended solids (SS), and chlorophyll a (chl-a), based on the partial least squares method to invert the water quality distribution of regional aquaculture. Furthermore, we compared the retrieval accuracy of different water quality parameters. The following results were obtained: 1) the constructed model’s results showed that the retrieval models for COD, NO3-N, SS, and chl-a had good accuracy; 2) application of the model to the validation set data yielded a correlation coefficient of 0.93 between the measured and predicted SS values, with a mean absolute error of prediction of 4.65 mg·L−1; this parameter constructed the best prediction model. This study provides a reference for remote sensing monitoring of water quality in mariculture in cloudy and rainy areas.