Remote sensing method for detecting green tide using HJ-CCD top-of-atmosphere reflectance
Hailong Zhang, Yibo Yuan, Yongjiu Xu, Xiaojing Shen, Deyong Sun, Zhongfeng Qiu, Shengqiang Wang, Yijun He
Abstract
Accurate and rapid monitoring of green macroalgae blooms (GMB; also known as green tide) provide valuable information in decision making for mitigating its environmental impacts and economic losses. Plenty of spectral-based algorithms mainly rely on Rayleigh-corrected or atmospherically-corrected reflectance. However, this inherently requires additional information beyond satellite observations for atmospheric correction. This work developed a new method for detecting GMB just by using satellite top-of-atmosphere reflectance (Rtoa) without any atmospheric correction scheme based on Tasseled-cap-like transformation (TCT-like). Here we conducted a case study on Chinese four-band HJ-CCD sensor for illustrating the reliability and sensitivity of this method for detecting GMB of Ulva prolifera. The performance of the method was validated statistically via cross-sensor and cross-index comparisons with existing algorithms from atmospherically-corrected reflectance. Results showed that the Rtoa-based method can effectively detect GMB with high accuracy, and achieved high robustness against observing conditions such as various background water conditions, thin cloud cover and sun-glint. In addition to the findings presented here, this study may provide a promising way to detect massive macroalgae blooms of other species using optical satellite data.