International Journal of Applied Earth Observations and Geoinformation | |
Remote sensing method for detecting green tide using HJ-CCD top-of-atmosphere reflectance | |
Xiaojing Shen1  Yongjiu Xu2  Deyong Sun3  Yijun He4  Hailong Zhang4  Zhongfeng Qiu4  Shengqiang Wang4  Yibo Yuan5  | |
[1] Corresponding author.;Fisheries College, Zhejiang Ocean University, Zhoushan, China;Institute of Applied Meteorology Beijing, Beijing, China;School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, China;Shanghai Investigation, Design and Research Institute Co., Ltd, Shanghai, China; | |
关键词: Ulva prolifera; Macroalgae bloom; TCG; Top-of-atmosphere reflectance; TCT-like; | |
DOI : | |
来源: DOAJ |
【 摘 要 】
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.
【 授权许可】
Unknown