Noise Removal Method for Unmanned Aerial Vehicle Data to Estimate Water Quality of Miharu Dam Reservoir, Japan

Abstract

Lake Sakurako is a reservoir of the Miharu Dam in Fukushima Prefecture, Japan. The water quality of the small lake becomes significantly worse during the summer owing to the occurrence of blue-green algae. Therefore, water quality management is a serious problem. Because the primary method of water quality analysis is direct collection from the target water area, the analysis range is limited, and the analysis of the entire water area is very difficult. Therefore, performing a wider range of analyses by remote sensing is a possible solution. In this study, we analyze near infrared (NIR) data acquired by unmanned aerial vehicles (UAVs). A fuzzy regression analysis is conducted on the UAV data and water measurements. Based on the experimental results of data from August 2015, the NIR data is confirmed to be useful in estimating the water quality conditions in Lake Sakurako. Furthermore, we investigate the noise removal process using a nonlocal mean filter and demonstrate that the process provides more detailed information regarding the lake’s water quality.