Atmospheric correction of inland lake water based on Sentinel-2 satellite data

doi:10.13474/j.cnki.11-2246.2021.0265

Abstract

Abstract: Referring to the historical measured remote sensing reflectance data, the atmospheric correction of inland lake water acquired by Sentinel-2 satellite is carried out by correction algorithms Acolite, FLAASH and C2RCC. The experimental results show that, numerically, the correction results of C2RCC are in the same order of magnitude as the measured results, and the correction results of Acolite and FLAASH are overestimated. In terms of the variation trend of spectral curve, the correction results of C2RCC are similar to the measured data, and the correction results of Acolite and FLAASH are abnormal. Therefore, it is recommended to use C2RCC atmospheric correction for Sentinel-2 inland water data. If only the first five wavebands are considered, the curve trend of the correction result of Acolite is close to the measured spectrum. As the correction result is overestimated, it is recommended to use the band ratio to eliminate the overestimation.

Key words: Sentinel-2 satellite, inland lake, atmospheric correction, remote sensing reflectance, East Lake

CLC Number:

P237

MU Chao, LIU Zhenyu, MENG Dan. Atmospheric correction of inland lake water based on Sentinel-2 satellite data[J]. Bulletin of Surveying and Mapping, 2021, 0(9): 9-14.

References

[1] 曾群,张海东,陈晓玲,等.MERIS影像水环境遥感大气校正算法评价:以鄱阳湖叶绿素a浓度反演为例[J].湖泊科学,2016,28(6):1306-1315.
[2] DONG B L, QIN B Q, GAO G, et al. Submerged macro-phyte communities and the controlling factors in large, shallow Lake Taihu (China):sediment distribution and water depth[J]. Journal of Great Lakes Research, 2014, 40(3):646-655.
[3] CHEN J, ZHU W, TIAN Y Q, et al. Remote estimation of colored dissolved organic matter and chlorophyll-a in Lake Huron using Sentinel-2 measurements[J]. Journal of Applied Remote Sensing, 2017, 11(3):1-15
[4] SAKUNO Y,YAJIMA H,YOSHIOKA Y, et al. Evalua-tion of unified algorithms for remote sensing of chlorophyll-a and turbidity in Lake Shinji and Lake Nakaumi of Japan and the Vaal Dam reservoir of South Africa under eutrophic and ultra-turbid conditions[J]. Water, 2018, 10(618):1-18.
[5] 赵丽娜.基于哨兵-2(Sentinel-2)影像的藻毒素遥感估算初步研究[D].南京:南京师范大学,2016.
[6] 李亭亭, 田礼乔, 李建,等. 基于Sentinel卫星的浑浊水体叶绿素反演对比研究——以鄱阳湖为例[J]. 华中师范大学学报(自然科学版), 2017,51(6):858-864.
[7] 曾群,赵越,田礼乔,等.HJ-1A/1B卫星CCD影像水环境遥感大气校正方法评价研究:以鄱阳湖为例[J].光谱学与光谱分析,2013,33(5):1320-1326.
[8] STEFANI N, DAVID D, ANOUCK O, et al. Atmospheric corrections and multi-conditional algorithm for multi-sensor remote sensing of suspended particulate matter in low-to-high turbidity levels coastal waters[J]. Remote Sensing, 2017,61(9):1-31.
[9] 苏伟,张明政,蒋坤萍,等. Sentinel-2卫星影像的大气校正方法[J]. 光学学报,2018,38(1):322-331.
[10] 蒋丹丹, 原娟, 武文娟,等. 基于Sentinel-2卫星影像的面向对象城市水体提取[J]. 地理空间信息, 2019, 17(5):21-24.
[11] 郑阳,吴炳方,张淼.Sentinel-2数据的冬小麦地上干生物量估算及评价[J].遥感学报,2017,21(2):318-328.
[12] VANHELLEMONT Q, RUDDICK K. Turbid wakes associated with offshore wind turbines observed with Landsat 8[J]. Remote Sensing of Environment, 2014, 145(8):105-115.
[13] CAI L, BU J, TANG D, et al. Geosynchronous satellite GF-4 observations of chlorophyll-a distribution details in the Bohai Sea, China[J]. Sensors, 2020, 20(5471):1-17.
[14] WANG M, SHI W. The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing[J]. Optics Express, 2007, 15(24):15722-15733.
[15] DOERFFER R, SCHILLER H. The MERIS case 2 water algorithm[J]. International Journal of Remote Sensing, 2007, 28(3-4):517-535.
[16] BROCKMANN C, DOERFFER R, PETERS M, et al. Evolution of the C2RCC neural network for Sentinel 2 and 3 for the retrieval of ocean colour products in normal and extreme optically complex waters[C]//Proceedings of the Living Planet Symposium. Prague:[s.n.], 2016:9-13.
[17] VITOR M, CLAUDIO B, LINO D C, et al. Assessment of atmospheric correction methods for Sentinel-2 MSI images applied to amazon floodplain lakes[J]. Remote Sensing, 2017, 322(9):1-23.
[18] 张莹,高玚,祝善友,等.近30a中国上空臭氧总量时空变化遥感监测分析[J].地球信息科学学报,2014,16(6):971-978.
[19] 杨煜,李云梅,王桥,等.富营养化的太湖水体叶绿素a浓度模型反演[J]. 地球信息科学学报,2009,11(5):5597-5603.
[20] 谢婷婷, 陈芸芝, 卢文芳. 基于三波段生物光学模型反演闽江下游叶绿素a[J]. 激光与光电子学进展, 2020, 57(7):248-255.