Blue-green algae blooms caused by eutrophication in closed water bodies affect various issues such as scenery, odor, and water utilization. It has been reported that the cyanobacteria that form blue-green algae are capable of active vertical migration due to the balance between photosynthesis and respiration, and that they accumulate in the surface layer in the early morning and diffuse during the daytime. However, because of the difficulty of continuous and long-term observation and analysis, the long-term response characteristics to meteorological and other changes are still largely unknown. Therefore, water managers must constantly observe water bodies and take appropriate actions when signs of abnormal growth are observed. In recent years, with the spread of relatively inexpensive cameras that meet various needs and the advancement of open source libraries with image processing and analysis functions, such as OpenCV, it has become possible to observe and analyze field phenomena that have been difficult in the past.
Blue-green algae floating on the surface of the water
When dealing with continuous images of field phenomena, it is necessary to deal with changes in image brightness caused by weather variations. In addition, when quantifying a phenomenon using continuous images, binarization by dynamic thresholding in response to weather variations is also required. However, there are few examples of research on dynamic thresholding, especially for continuous images, and currently no method has been established to enable long-term monitoring of blue-green algae phenomena.This study aims to quantify the long-term time series of blue-green algae phenomena using time-lapse images of the water surface acquired by a fixed-point camera installed in a closed water body, to elucidate the response of blue-green algae to meteorological changes in detail, and to analyze the water body flow regime by tracing the flow trajectory of blue-green algae to elucidate the detailed distribution of blue-green algae within the water body. The objective of this project is to elucidate the detailed distribution of blue-green algae in a water body by tracing their flow trajectory.
Binarization of blue-green algae by image processing
Long-term time-series changes in the percentage of blue-green algae on the water surface
