Remote Sensing Technology and Application, Volume. 39, Issue 1, 110(2024)
Inversion of Beibu Gulf Chlorophyll a Concentration based on Sentinel-3A Satellite
[1] X G XING, D Z ZHAO, Y G LIU et al. An overview of remote sensing of chlorophyll fluorescence. Ocean Science Journal, 42, 49-59(2007).
[2] S KOPONEN, J PULLIAINEN, K KALLIO et al. Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data. Remote Sensing of Environment, 79, 51-59(2002).
[3] H R GORDON, A Y MOREL. Remote assessment of ocean color for interpretation of satellite visible imagery: A review. Springer Science & Business Media(2012).
[4] A MOREL, L PRIEUR. Analysis of variations in ocean color 1. Limnology and oceanography, 22, 709-722(1977).
[5] S SATHYENDRANATH, A MOREL. Light emerging from the sea—interpretation and uses in remote sensing. Remote Sensing Applications in Marine Science and Technology, 323-357(1983).
[6] Chuqun CHEN, Ping SHI, Qingwen MAO. Study on the model of chlorophyll concentration in the surface water of coastal waters using TM data. Remote Environment Sensing, 168-176(1996).
[7] Z HU, H LIU, L ZHU et al. Quantitative inversion model of water chlorophyll-a based on spectral analysis. Procedia Environmental Sciences, 10, 523-528(2011).
[8] Q CHEN, M HUANG, R WANG. Genetic algorithm–Back Propagation (Ga-BP) neural network for chlorophyll-a concentration inversion using Landsat-8 OLI data, 143(2020).
[9] F WATANABE, E ALCÂNTARA, N IMAI et al. Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters. Remote Sensing, 10, 227(2018).
[10] Lin WANG, Qinghui MENG, Yujuan MA. Remote sensing inversion of chlorophyll a concentration in the Qinhuangdao sea area based on Sentinel-2 MSI images. Marine Environmental Science, 42, 309-314(2023).
[11] Zhifeng LI, Bin HAN, Di JIA et al. Evaluation of remote sensing inversion algorithm for chlorophyll a concentration in the Northern South China Sea and construction of COCTS Inversion Algorithm. Journal of Ocean Technology, 41, 1-7(2022).
[12] J VERRELST, L ALONSO et al. Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and-3. Remote Sensing of Environment, 118, 127-139(2012).
[13] Junwu TANG, Guoliang TIAN, Xiaoyong WANG et al. Spectral measurement and analysis of water Ⅰ: Above-water surface measurement method. Journal of Remote Sensing, 8, 37-44(2004).
[14] Xuwen LI, Sheng JIANG, Yue ZHANG et al. Study on the retrieval of chlorophyll a and algae from Taihu Lake based on MPH algorithm of OLCI image from Sentinel-3 satellite. Environmental Monitoring and Early Warning, 11, 59-65(2019).
[15] B STURM. The atmospheric correction of remotely sensed data and the quantitative determination of suspended matter in marine water surface layers. Remote sensing in meteorology, oceanography and hydrology, 147, 163-197(1981).
[16] G ZHOU, W XU, C NIU et al. The polarization patterns of skylight reflected off wave water surface. Optics express, 21, 32549-32565(2013).
[17] L DE KEUKELAERE, S STERCKX, S ADRIAENSEN et al. atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: Validation for coastal and inland waters. European Journal of Remote Sensing, 51, 525-542(2018).
[18] B C GAO. NDWI—a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257-266(1996).
[19] D A LANDGREBE. Signal theory methods in multispectral remote sensing(2005).
[20] S Sarthyendranath. Remote sensing of ocean colour in coastal, and other optically-complex,waters, 3(2000).
[21] A GITELSON, G GARBUZOV, F SZILAGYI et al. Quantitative remote sensing methods for real-time monitoring of inland waters quality. International Journal of Remote Sensing, 14, 1269-1295(1993).
[22] Runyuan KUANG, Wei LUO, Meng ZHANG. Optical classification of Poyang Lake water based on measured data and remote sensing images. Yangtze River Basin Resources and Environment, 24, 773-780(2015).
[23] Chengfei JIANG. High-score remote sensing inversion and monitoring of eutrophication Zhanjiang's key water quality elements(2017).
[24] J PULLIAINEN, K KALLIO, K ELOHEIMO et al. a semi-operative approach to lake water quality retrieval from remote sensing data. Science of the Total Environment, 268, 79-93(2021).
[25] Tingting LI, Liqiao TIAN, Jian LI et al. Comparative study on chlorophyll inversion of Turbid water based on Sentinel satellite——A case study of Poyang Lake. Journal of Central China Normal University (Natural Science Edition), 51, 858-864(2017).
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Juan SHEN, Zhigang ZHOU, Tonghui ZHANG, Dazhao LIU. Inversion of Beibu Gulf Chlorophyll a Concentration based on Sentinel-3A Satellite[J]. Remote Sensing Technology and Application, 2024, 39(1): 110
Category: Research Articles
Received: Jun. 25, 2023
Accepted: --
Published Online: Jul. 22, 2024
The Author Email: SHEN Juan (jshen@scut.edu.cn)