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Inland water chlorophyll-a retrieval based on ZY-1 02D satellite hyperspectral observations

  • role： First author第一作者
  • Affiliation：

    Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, China

  • Email：liuyao@lasac.cn
  • Introduction：刘瑶，1988年生，女，高级工程师，研究方向为国产高光谱卫星的数据处理与内陆水体应用。E-mail： liuyao@lasac.cn
LIU Yao1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：lijs@radi.ac.cn
  • Introduction：李俊生，1979年生，男，研究员，研究方向为水环境遥感。E-mail： lijs@radi.ac.cn
LI Junsheng23*,  
  • Affiliation：

    Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, China

XIAO Chenchao1,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

ZHANG Fangfang2,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

WANG Shenglei2

resumen

China’s ZY-1 02D satellite was successfully launched on September 12, 2019. It carries the new-generation Advanced Hyperspectral Imager (AHSI), which has 166 bands in the visible to short-wave infrared bands. AHSI can acquire images at 30 m spatial resolution with a 60 km swath. ZY-1 02D satellite shows great potential for inland water quality monitoring application, owing to its abundant narrow bands and relatively high spatial resolution. However, this satellite has been launched for a short period, and the applicability of this data needs to be further analyzed and tested.Taihu Lake (eutrophic), Yuqiao reservoir (eutrophic), and Xiaolangdi Reservoir (mesotrophic) in China were used as study areas for the Chlorophyll-a (Chla) retrieval based on the ZY-1 02D hyperspectral images. Within one day of the ZY-1 02D satellite overpass, in situ spectra, and Chla concentrations were collected at sampling sites in these study areas. We selected five typical Chla semi-empirical models based on spectral indices, namely, Band Ratio (BR), Normalized Difference Chlorophyll Index (NDCI), Three-Band Index (TBI), Enhanced Three-Band Index (ETBI), and the Baseline Height (BH). We used in situ measured Chla concentration at 46 sampling sites in the three study areas and simultaneously acquired ZY-1 02D images to optimize the parameters in these models. We evaluated the accuracies of image-derived Rrs at sampling sites, and then conducted accuracy analysis for estimated Chla concentrations using optimized empirical models.ZY-1 02D image-derived Rrs were consistent with in situ measured Rrs in the 671 and 705 nm, whereas the 731 and 748 nm band Rrs had greater uncertainties because they were more likely to be affected by the image noise. In addition, the accuracy analysis for the estimated Chla concentrations shows that the model based on the 705 to 671 nm band ratio achieves the highest accuracy, with an R2 of 0.78. In addition, the mean unbiased relative error (AURE) and Root Mean Square Error (RMSE) are 13.5% and 4.5 mg/m3, respectively. On the contrary, models based on the ETBI and BH yield Chla concentration estimates with low accuracies.In conclusion, ZY-1 02D hyperspectral data show good potential in terms of accurate retrieval of Chla concentration for inland waters. We plan to conduct more in situ experiment when the ZY-1 02D satellite overpasses to improve the Chla concentration retrieval model applied on the ZY-1 02D data. In the future, the monitoring capacity should be improved through establishing a hyperspectral satellite constellation, and noise reduction and atmospheric correction methods should be developed for ZY-1 02D’s inland water application.

palabra clave

ZY-1 02D satellite;hyperspectral remote sensing;inland water;Chlorophyll-a retrieval;lake remote sensing

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