Multi-source remote sensing big data mining reveals cross-regional correlation between aquaculture and Enteromorpha disaster outbreaks

Abstract

Marine aquaculture is one of the most important marine resource utilization types, widely distributed in seashore areas. Because mass marine aquaculture development will lead to the eutrophication disaster of macroalgae blooms (green tide), it is imperative to discover the latent relationship. Inspired by the big data analysis theory, the spatiotemporal correlation change in 2017 and 2019 of the marine aquaculture and macroalgae blooms in Jiangsu Shoal in the West of the Yellow Sea and its adjacent seas were monitored and extracted respectively based on multi-source remote sensing images. Through optical and Synthetic Aperture Radar (SAR) images, the imaging characteristics of marine aquaculture in different growth cycles and sea conditions are analyzed. The relationship between the green tide and marine aquaculture harvest was explored from the early green algae distribution and spatiotemporal distribution changes. The earliest harvest area of marine aquaculture is the exact location of the outbreak of green tide. Along with the rapid reduction of aquaculture area, the distribution range of green tide gradually increased. The two showed opposite trends through many multi-source remote sensing data statistical analyses. Therefore, they have a strong correlation, which can be utilized to offer a significant value for the balance of marine environmental protection and resource development.

Keywords

• Marine aquaculture
• Enteromorpha disaster
• long-time monitoring
• spatiotemporal correlation
• multi-source remote sensing
• big data