高分六号影像在内陆水体叶绿素a反演中的应用潜力分析

GF-6 WFV影像具有宽覆盖、高时空分辨率、高光谱分辨率等特点,目前在农业和林业遥感领域都有一定应用,但是在水质遥感中的应用潜力还缺乏系统的评估。本文以潘家口和大黑汀水库为研究区,采用2019年9月24—25日获取的潘家口和大黑汀水库叶绿素a浓度、实测遥感反射率和准同步GF-6 WFV影像,构建了潘家口和大黑汀水库叶绿素a浓度经验反演模型,探索GF-6 WFV在内陆水体叶绿素a浓度遥感监测中的应用潜力。研究结果表明,基于GF-6 WFV模拟光谱构建的潘家口和大黑汀水库叶绿素a浓度经验模型决定系数均在0.90以上,GF-6 WFV影像在水体叶绿素a遥感监测中具有应用潜力,尤其是新增的黄波段和红边波段1,有助于提高GF-6 WFV影像叶绿素a浓度遥感监测能力;GF-6 WFV影像大气校正误差降低了叶绿素a浓度遥感监测精度,GF-6 WFV影像水体大气校正精度有待改进,以提升GF-6 WFV影像水质遥感监测能力。

Application Potential Analysis on Chlorophyll-a Retrieval for Inland Water based on a Gaofen-6 WFV Imagery

Gaofen-6 wide field of view (GF-6 WFV) imagery, with wide coverage, high temporal, spatial, and spectral resolution, has been applied in the fields of remote sensing of agriculture and forestry. However, the application potential of GF-6 imagery in the field of remote sensing of water quality lacks a systematic assessment. In this study, four empirical models of single-band model, band-ratio model, partial least squares model, and support vector machine model were developed to retrieve Chlorophyll-a (Chl-a) in Panjiakou and Daheiting reservoirs. The retrieval was based on measured Chl-a concentration and in situ remote sensing reflectance of 37 samples acquired in September 24 and 25, 2019, as well as a quasi-synchronous GF-6 WFV imagery. The application potential of GF-6 imagery in the field of remote sensing of water quality was evaluated according to the performance of four empirical models for Chl-a retrieval in Panjiakou and Daheiting reservoirs. The determination coefficients and comprehensive errors of four empirical models based on GF-6 WFV reflectance simulated by in situ reflectance were above 0.9 and less than 15% for Chl-a retrieval in Panjiakou and Daheiting reservoirs, respectively. The partial least squares model had the highest accuracy among the four empirical models, with a determination coefficient of 0.96 and a comprehensive error of 13.22%. Finally, the partial least squares model was applied to retrieve the spatial distribution of Chl-a concentration in Panjiakou and Daheiting reservoirs based on the GF-6 WFV imagery acquired on September 26, 2019. The Chl-a retrieval result indicated that Chl-a concentration was less than 10 µg/L in Panjiakou reservoir but more than 10 µg/L in Daheiting reservoir. The trophic states of Panjiakou reservoir and Daheiting reservoir were respectively mesotrophic and eutrophic according to trophic level index calculated by Chl-a concentration. GF-6 WFV imagery, with eight bands in visible and near-infrared, has application potential in remote sensing of Chl-a concentration in inland water. In particular, the newly added yellow band and red-edge band 1 in GF-6 WFV imagery contribute to improving the performance of Chl-a retrieval. The band reflectance of the GF-6 WFV imagery, derived from atmospheric correction, has obvious systematic deviations and correction errors, especially for band 4 (Near Infrared, NIR) and band 6 (Red-edge 2). Atmospheric correction error reduces the performance of the GF-6 WFV imagery in Chl-a retrieval in Panjiakou and Daheiting reservoirs. In order to improve the capability of GF-6 WFV imagery in remote sensing of water quality in inland water, the atmospheric correction accuracy of GF-6 WFV imagery needs to be further improved.