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Remote sensing retrieval of chlorophyll-a concentration in Dianchi lake based on orbita hyperspectral imagery

  • role： First author第一作者
  • Affiliation：

    School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou 341000, China

  • Email：zhengzhubin@gnnu.edu.cn
  • Introduction：郑著彬，研究方向为水色遥感与环境遥感。E-mail：zhengzhubin@gnnu.edu.cn
ZHENG Zhubin1,  
  • Affiliation：

    School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou 341000, China

    School of Geography, Nanjing Normal University, Nanjing 210023, China

ZHANG Runfei12,  
  • Affiliation：

    School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou 341000, China

    School of Geography, Nanjing Normal University, Nanjing 210023, China

LI Jianzhong12,  
  • Affiliation：

    School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou 341000, China

LIN Lin1,  
  • Affiliation：

    School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou 341000, China

YANG Hong1

résumé

The chlorophyll-a (Chla) concentration that refers to the content of Chla contained in per unit volume water, is a key indicator describing the eutrophication degree of lake waters. Accurate quantification of Chla concentration is of great significance for water environment assessment and water quality monitoring and has become a focus on the study of watercolor remote sensing. Orbita hyperspectral (OHS) satellite is a new generation of hyperspectral satellites launched by Zhuhai Orbita Aerospace Technology Co., Ltd. in 2018, which covers spectral range of 400~1000 nm and 32 spectral channels with both high spectral and high spatial resolution (2.5 nm and 10 m, respectively), showing great potential for inland water quality monitoring application. However, this satellite has a short operating period from launch, and the applicability of the generated images needs to be further investigated and validated.Dianchi Lake, a typical eutrophic plateau lake, was used as the study area for Chla concentration retrieval based on the OHS hyperspectral imagery. We collected in-situ spectra and Chla concentration from two cruise surveys in Dianchi Lake and acquired the satellite-ground synchronization data within one day of the OHS satellite overpass. Data from two field campaigns including 72 sampling sites were used for model calibration and validation, and ground data matched with satellite overpass including 10 sampling sites was used to further validate the retrieval results after the calibrated model was applied to the OHS imagery. We first utilized all 72 in-situ spectra to explore the relationship between all possible combinations of band ratio and Chla concentrations to seek the optimal band ratio model. Immediately after we used the spectral response function of the OHS imagery to resample the in-situ spectra to the band configuration of the OHS imagery, the OHS-based band ratio model was calibrated using 48 field-measured data according to the optimal band ratio combination of in-situ spectra, and the remaining 24 data were used to evaluate model accuracy. We further validated the retrieval results using the Chla concentrations at 10 sampling points synchronized with the OHS image after the OHS-based band ratio model was applied to the OHS image, and the spatial pattern of Chla concentration in Dianchi Lake was revealed.The band ratio Rrs(716)/Rrs(595) had the highest correlation with Chla concentration in terms of the in-situ spectra with R2=0.819, and the corresponding OHS-based band ratio model (B17/B9) was suitable for remote sensing retrieval of Chla concentration in Dianchi Lake with R2 of 0.804, the root-mean-square error (RMSE) of 6.99 μg/L and the mean absolute percentage error (MAPE) of 6.32%. The retrieval results of the OHS-based band ratio model applied to the OHS image and the spatial pattern of Chla concentration were reasonable with acceptable errors (RMSE=12.47 μg/L, MAPE=22.53%). The spatial pattern of Chla concentration in Dianchi Lake showed a decreasing trend from the lakeshore to the center of the lake on April 2, 2019, the northeast and southeast decrease fitted a power function, whereas the northwest decrease described a linear function. The pixel reflectance of the nearshore waters may be higher than that of the normal waters due to the land adjacency effect, which may lead to a high concentration of retrieved Chla along the coast. In the OHS imagery of Dianchi Lake, four nearshore water pixels could be easily influenced by the land adjacency effect, so these four pixels needed to be masked to eliminate the influence. In addition, compared with the existing Chla concentration retrieval algorithms, the band ratio model (B17/B9) proposed in this study improved the retrieval accuracy of Chla concentration.In conclusion, the OHS-based band ratio model works efficiently and reliably for retrieving Chla concentration in Dianchi Lake. OHS hyperspectral data show great potential in terms of accurate retrieval of Chla concentration for inland waters, providing a new means for remote sensing monitoring of Chla concentration. However, whether the OHS-based band ratio model developed in this study applies to other water bodies with different optical properties still needs to be further investigated and tested. In future studies, the performance of the model will be further examined by collecting more field data in different lakes.

mots-clés

Orbita hyperspectral imagery;chlorophyll-a;Dianchi Lake;Land adjacency effect

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