Monitoring and understanding chlorophyll-a concentration changes in lakes in northeastern China using MERIS and OLCI satellite data

References

• Ahlgren, P., and B. Jarneving. 2003. “Requirements for a Cocitation Similarity Measure, with Special Reference to Pearson’s Correlation Coefficient.” Journal of the American Society for Information Science and Technology 54 (6): 550–19. https://doi.org/10.1002/asi.10242.
   Web of Science ®Google Scholar
• Aptoula, E., and S. Ariman. 2021. “Chlorophyll-A Retrieval from Sentinel-2 Images Using Convolutional Neural Network Regression.” IEEE Geoscience and Remote Sensing Letters 19:1–5. https://doi.org/10.1109/LGRS.2021.3070437.
   Web of Science ®Google Scholar
• Attila, J., P. Kauppila, K. Y. Kallio, H. Alasalmi, V. Keto, E. Bruun, and S. Koponen. 2018. “Applicability of Earth Observation Chlorophyll-A Data in Assessment of Water Status via MERIS — with Implications for the Use of OLCI Sensors.” Remote Sensing of Environment 212:273–287. https://doi.org/10.1016/j.rse.2018.02.043.
   Web of Science ®Google Scholar
• Bao, W., Y. Yang, T. Fu, and G. H. Xie. 2019. “Estimation of Livestock Excrement and Its Biogas Production Potential in China.” Journal of Cleaner Production 229:1158–1166. https://doi.org/10.1016/j.jclepro.2019.05.059.
   Web of Science ®Google Scholar
• Binding, C. E., T. A. Greenberg, and R. P. Bukata. 2011. “Time Series Analysis of Algal Blooms in Lake of the Woods Using the MERIS Maximum Chlorophyll Index.” Journal of Plankton Research 33 (12): 1847–1852. https://doi.org/10.1093/plankt/fbr079.
   Web of Science ®Google Scholar
• Cannizzaro, J. P., and K. L. Carder. 2006. “Estimating Chlorophyll a Concentrations from Remote-Sensing Reflectance in Optically Shallow Waters.” Remote Sensing of Environment 101 (1): 13–24. https://doi.org/10.1016/j.rse.2005.12.002.
   Web of Science ®Google Scholar
• Carlson, R. E. 1977. “A Trophic State Index for Lakes.” Limnology and Oceanography 22 (2): 361–369. https://doi.org/10.4319/lo.1977.22.2.0361.
   Web of Science ®Google Scholar
• Chen, Q., M. Huang, and X. Tang. 2020. “Eutrophication Assessment of Seasonal Urban Lakes in China Yangtze River Basin Using Landsat 8-Derived Forel-Ule Index: A Six-Year (2013-2018) Observation.” Science of the Total Environment 745:135392. https://doi.org/10.1016/j.scitotenv.2019.135392.
   PubMed Web of Science ®Google Scholar
• Dall’olmo, G., and A. A. Gitelson. 2005. “Effect of Bio-Optical Parameter Variability on the Remote Estimation of Chlorophyll-A Concentration in Turbid Productive Waters: Experimental Results.” Applied Optics 44 (3): 412–422. https://doi.org/10.1364/AO.44.000412.
   PubMed Web of Science ®Google Scholar
• Duan, H., R. Ma, X. Xu, F. Kong, S. Zhang, W. Kong, J. Hao, and L. Shang. 2009. Two-Decade Reconstruction of Algal Blooms in China’s Lake Taihu 43 (10): 3522–3528. https://doi.org/10.1021/es8031852.
   Google Scholar
• Duan, H., Y. Zhang, B. Zhang, K. Song, Z. Wang, D. Liu, and F. Li. 2007. “Estimation of Chlorophyll-A Concentration and Trophic States for Inland Lakes in Northeast China from Landsat TM Data and Field Spectral Measurements.” International Journal of Remote Sensing 29 (3): 767–786. https://doi.org/10.1080/01431160701355249.
   Web of Science ®Google Scholar
• Du, Y., K. Song, G. Liu, Z. Wen, C. Fang, Y. Shang, F. Zhao, Q. Wang, J. Du, and B. Zhang. 2020. “Quantifying Total Suspended Matter (TSM) in Waters Using Landsat Images During 1984-2018 Across the Songnen Plain, Northeast China.” Journal of Environmental Management 262:110334. https://doi.org/10.1016/j.jenvman.2020.110334.
   PubMed Web of Science ®Google Scholar
• Fang, C., K. Song, L. Li, Z. Wen, G. Liu, J. Du, Y. Shang, and Y. Zhao. 2018. “Spatial Variability and Temporal Dynamics of HABs in Northeast China.” Ecological Indicators 90:280–294. https://doi.org/10.1016/j.ecolind.2018.03.006.
   Web of Science ®Google Scholar
• Feng, L., X. Hou, and Y. Zheng. 2019. “Monitoring and Understanding the Water Transparency Changes of Fifty Large Lakes on the Yangtze Plain Based on Long-Term MODIS Observations.” Remote Sensing of Environment 221:675–686. https://doi.org/10.1016/j.rse.2018.12.007.
   Web of Science ®Google Scholar
• Feng, L., C. Hu, X. Han, X. Chen, and L. Qi. 2014. “Long-Term Distribution Patterns of Chlorophyll-A Concentration in China’s Largest Freshwater Lake: MERIS Full-Resolution Observations with a Practical Approach.” Remote Sensing 7 (1): 275–299. https://doi.org/10.3390/rs70100275.
   Web of Science ®Google Scholar
• François, S., D. Pierre-Yves, and R. Didier. 2011. “Atmospheric Correction in Presence of Sun Glint: Application to MERIS.” Optics Express 19 (10): 9783–9800. https://doi.org/10.1364/OE.19.009783.
   PubMed Web of Science ®Google Scholar
• Gao, J., G. Deng, H. Jiang, Y. Wen, S. Zhu, C. He, C. Shi, and Y. Cao. 2023. “Water Quality Pollution Assessment and Source Apportionment of Lake Wetlands: A Case Study of Xianghai Lake in the Northeast China Plain.” Journal of Environmental Management 344:118398. https://doi.org/10.1016/j.jenvman.2023.118398.
   PubMed Web of Science ®Google Scholar
• García-Nieto, P. J., E. García-Gonzalo, J. R. Alonso Fernández, and C. Díaz Muñiz. 2020. “A New Predictive Model for Evaluating Chlorophyll-A Concentration in Tanes Reservoir by Using a Gaussian Process Regression.” Water Resources Management 34 (15): 4921–4941. https://doi.org/10.1007/s11269-020-02699-x.
   Web of Science ®Google Scholar
• Giannini, F., B. P. V. Hunt, D. Jacoby, and M. Costa. 2021. “Performance of OLCI Sentinel-3A Satellite in the Northeast Pacific Coastal Waters.” Remote Sensing of Environment 256:112317. https://doi.org/10.1016/j.rse.2021.112317.
   Web of Science ®Google Scholar
• Gitelson, A. A., G. Dall’olmo, W. Moses, D. C. Rundquist, T. Barrow, T. R. Fisher, D. Gurlin, and J. Holz. 2008. “A Simple Semi-Analytical Model for Remote Estimation of Chlorophyll-A in Turbid Waters: Validation.” Remote Sensing of Environment 112 (9): 3582–3593. https://doi.org/10.1016/j.rse.2008.04.015.
   Web of Science ®Google Scholar
• Gower, J. F. R., R. Doerffer, and G. A. Borstad. 2010. “Interpretation of the 685 Nm Peak in Water-Leaving Radiance Spectra in Terms of Fluorescence, Absorption and Scattering, and Its Observation by MERIS.” International Journal of Remote Sensing 20 (9): 1771–1786. https://doi.org/10.1080/014311699212470.
   Google Scholar
• Gower, J., S. King, G. Borstad, and L. Brown. 2005. “Detection of Intense Plankton Blooms Using the 709 nm Band of the MERIS Imaging Spectrometer.” International Journal of Remote Sensing 26 (9): 2005–2012. https://doi.org/10.1080/01431160500075857.
   Web of Science ®Google Scholar
• Guan, Q., L. Feng, X. Hou, G. Schurgers, Y. Zheng, and J. Tang. 2020. “Eutrophication Changes in Fifty Large Lakes on the Yangtze Plain of China Derived from MERIS and OLCI Observations.” Remote Sensing of Environment 246:111890. https://doi.org/10.1016/j.rse.2020.111890.
   Web of Science ®Google Scholar
• Guo, J., C. Zhang, G. Zheng, J. Xue, and L. Zhang. 2018. “The Establishment of Season-Specific Eutrophication Assessment Standards for a Water-Supply Reservoir Located in Northeast China Based on Chlorophyll-A Levels.” Ecological Indicators 85:11–20. https://doi.org/10.1016/j.ecolind.2017.09.056.
   Web of Science ®Google Scholar
• Han, X., L. Feng, X. Chen, and H. Yesou. 2014. “MERIS Observations of Chlorophyll-A Dynamics in Erhai Lake Between 2003 and 2009.” International Journal of Remote Sensing 35 (24): 8309–8322. https://doi.org/10.1080/01431161.2014.985395.
   Web of Science ®Google Scholar
• He, J., Y. Chen, J. Wu, D. A. Stow, and G. Christakos. 2020. “Space-Time Chlorophyll-A Retrieval in Optically Complex Waters That Accounts for Remote Sensing and Modeling Uncertainties and Improves Remote Estimation Accuracy.” Water Research 171:115403. https://doi.org/10.1016/j.watres.2019.115403.
   PubMed Web of Science ®Google Scholar
• Ho, J. C., A. M. Michalak, and N. Pahlevan. 2019. “Widespread Global Increase in Intense Lake Phytoplankton Blooms Since the 1980s.” Nature 574 (7780): 667–670. https://doi.org/10.1038/s41586-019-1648-7.
   PubMed Web of Science ®Google Scholar
• Hsu, C. W., C. C. Chang, and C. J. Lin. 2003. A Practical Guide to Support Vector Classification. Taipei. Accessed February 21, 2021. https://www.csie.ntu.edu.tw/~cjlin/papers/guide/guide.pdf.
   Google Scholar
• Huovinen, P., J. Ramirez, L. Caputo, and I. Gomez. 2019. “Mapping of Spatial and Temporal Variation of Water Characteristics Through Satellite Remote Sensing in Lake Panguipulli, Chile.” Science of the Total Environment 679:196–208. https://doi.org/10.1016/j.scitotenv.2019.04.367.
   PubMed Web of Science ®Google Scholar
• Ji, Z.-G. 2017. Hydrodynamics and Water Quality: Modeling Rivers, Lakes, and Estuaries. America: John Wiley & Sons.
   Google Scholar
• Jiang, G., S. A. Loiselle, D. Yang, R. Ma, W. Su, and C. Gao. 2020. “Remote Estimation of Chlorophyll a Concentrations Over a Wide Range of Optical Conditions Based on Water Classification from VIIRS Observations.” Remote Sensing of Environment 241:241. https://doi.org/10.1016/j.rse.2020.111735.
   Web of Science ®Google Scholar
• Ji, Z.-G., and K.-R. Jin. 2006. “Gyres and Seiches in a Large and Shallow Lake.” Journal of Great Lakes Research 32 (4): 764–775. https://doi.org/10.3394/0380-1330(2006)32[764:GASIAL]2.0.CO;2.
   Web of Science ®Google Scholar
• Kotsiantis, S. B., I. D. Zaharakis, and P. E. Pintelas. 2007. “Machine Learning: A Review of Classification and Combining Techniques.” Artificial Intelligence Review 26 (3): 159–190. https://doi.org/10.1007/s10462-007-9052-3.
   Web of Science ®Google Scholar
• Kravitz, J., M. Matthews, S. Bernard, and D. Griffith. 2020. “Application of Sentinel 3 OLCI for Chl-A Retrieval Over Small Inland Water Targets: Successes and Challenges.” Remote Sensing of Environment 237:237. https://doi.org/10.1016/j.rse.2019.111562.
   Web of Science ®Google Scholar
• Li, Z., Z. Jiang, Y. Qu, Y. Cao, F. Sun, and Y. Dai. 2022. “Analysis of Landscape Change and Its Driving Mechanism in Chagan Lake National Nature Reserve.” Sustainability 14 (9): 5675. https://doi.org/10.3390/su14095675.
   Web of Science ®Google Scholar
• Li, S., K. Song, G. Mu, Y. Zhao, J. Ma, and J. Ren. 2016. “Evaluation of the Quasi-Analytical Algorithm (QAA) for Estimating Total Absorption Coefficient of Turbid Inland Waters in Northeast China.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9 (9): 4022–4036. https://doi.org/10.1109/JSTARS.2016.2549026.
   Web of Science ®Google Scholar
• Li, S., K. Song, S. Wang, G. Liu, Z. Wen, Y. Shang, L. Lyu, et al. 2021. “Quantification of Chlorophyll-A in Typical Lakes Across China Using Sentinel-2 MSI Imagery with Machine Learning Algorithm.” Science of the Total Environment 778:146271. https://doi.org/10.1016/j.scitotenv.2021.146271.
   PubMed Web of Science ®Google Scholar
• Liu, Y., L. Li, L. Liang, and J. Li. 2011. “Study on the Non-Point Source Pollution in the Upper and Middle Reaches of the Taoer River Basin.” Chinese Journal of Population Resources and Environment 9 (1): 48–54. https://doi.org/10.1080/10042857.2011.10685018.
   Google Scholar
• Liu, G., S. G. H. Simis, L. Li, Q. Wang, Y. Li, K. Song, H. Lyu, Z. Zheng, and K. Shi. 2018. “A Four-Band Semi-Analytical Model for Estimating Phycocyanin in Inland Waters from Simulated MERIS and OLCI Data.” IEEE Transactions on Geoscience and Remote Sensing 56 (3): 1374–1385. https://doi.org/10.1109/TGRS.2017.2761996.
   Web of Science ®Google Scholar
• Liu, D., C. Song, C. Fang, Z. Xin, J. Xi, and Y. Lu. 2021. “A Recommended Nitrogen Application Strategy for High Crop Yield and Low Environmental Pollution at a Basin Scale.” Science of the Total Environment 792:148464. https://doi.org/10.1016/j.scitotenv.2021.148464.
   PubMed Web of Science ®Google Scholar
• Liu, R., J. Wang, J. Shi, Y. Chen, C. Sun, P. Zhang, and Z. Shen. 2014. “Runoff Characteristics and Nutrient Loss Mechanism from Plain Farmland Under Simulated Rainfall Conditions.” Science of the Total Environment 468-469:1069–1077. https://doi.org/10.1016/j.scitotenv.2013.09.035.
   PubMed Web of Science ®Google Scholar
• Liu, X., G. Zhang, G. Sun, Y. Wu, and Y. Chen. 2019. “Assessment of Lake Water Quality and Eutrophication Risk in an Agricultural Irrigation Area: A Case Study of the Chagan Lake in Northeast China.” Water 11 (11): 2380. https://doi.org/10.3390/w11112380.
   Web of Science ®Google Scholar
• Matthews, M. W., S. Bernard, and K. Winter. 2010. “Remote Sensing of Cyanobacteria-Dominant Algal Blooms and Water Quality Parameters in Zeekoevlei, a Small Hypertrophic Lake, Using MERIS.” Remote Sensing of Environment 114 (9): 2070–2087. https://doi.org/10.1016/j.rse.2010.04.013.
   Web of Science ®Google Scholar
• MEP. 2002. Environmental Quality Standards for Surface Water (GB 3838–2002) (In Chinese). https://www.mee.gov.cn/ywgz/fgbz/bz/bzwb/shjbh/shjzlbz/200206/W020061027509896672057.pdf.
   Google Scholar
• Mishra, D. R., B. A. Schaeffer, and D. Keith. 2014. “Performance Evaluation of Normalized Difference Chlorophyll Index in Northern Gulf of Mexico Estuaries Using the Hyperspectral Imager for the Coastal Ocean.” GIScience & Remote Sensing 51 (2): 175–198. https://doi.org/10.1080/15481603.2014.895581.
   Web of Science ®Google Scholar
• Mograne, M., C. Jamet, H. Loisel, V. Vantrepotte, X. Mériaux, and A. Cauvin. 2019. “Evaluation of Five Atmospheric Correction Algorithms Over French Optically-Complex Waters for the Sentinel-3A OLCI Ocean Color Sensor.” Remote Sensing 11 (6): 668. https://doi.org/10.3390/rs11060668.
   Web of Science ®Google Scholar
• Mohebzadeh, H., E. Mokari, P. Daggupati, and A. Biswas. 2021. “A Machine Learning Approach for Spatiotemporal Imputation of MODIS Chlorophyll a.” International Journal of Remote Sensing 42 (19): 7381–7404. https://doi.org/10.1080/01431161.2021.1957513.
   Web of Science ®Google Scholar
• Moore, T. S., J. W. Campbell, and M. D. Dowell. 2009. “A Class-Based Approach to Characterizing and Mapping the Uncertainty of the MODIS Ocean Chlorophyll Product.” Remote Sensing of Environment 113 (11): 2424–2430. https://doi.org/10.1016/j.rse.2009.07.016.
   Web of Science ®Google Scholar
• Moses, W. J., A. A. Gitelson, S. Berdnikov, and V. Povazhnyy. 2009. “Satellite Estimation of Chlorophyll-A Concentration Using the Red and NIR Bands of MERIS—The Azov Sea Case Study.” IEEE Geoscience and Remote Sensing Letters 6 (4): 845–849. https://doi.org/10.1109/LGRS.2009.2026657.
   Web of Science ®Google Scholar
• Mueller, J. L., A. Morel, R. Frouin, C. Davis, R. Arnone, K. Carder, Z. Lee, R. Steward, S. Hooker, and C. Mobley. 2003. “Ocean optics protocols for satellite ocean color sensor validation, revision 4.” Volume III: Radiometric Measurements and Data Analysis Protocols. https://oceancolor.gsfc.nasa.gov/docs/technical/
   Google Scholar
• NIGLAS. 2019. National Lake Survey Report in China (In Chinese). Nanjing: Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences.
   Google Scholar
• Pahlevan, N., S. K. Chittimalli, S. V. Balasubramanian, and V. Vellucci. 2019. “Sentinel-2/Landsat-8 Product Consistency and Implications for Monitoring Aquatic Systems.” Remote Sensing of Environment 220:19–29. https://doi.org/10.1016/j.rse.2018.10.027.
   Web of Science ®Google Scholar
• Pastor-Guzman, J., L. Brown, H. Morris, L. Bourg, P. Goryl, S. Dransfeld, and J. Dash. 2020. “The Sentinel-3 OLCI Terrestrial Chlorophyll Index (OTCI): Algorithm Improvements, Spatiotemporal Consistency and Continuity with the MERIS Archive.” Remote Sensing 12 (16): 2652. https://doi.org/10.3390/rs12162652.
   Web of Science ®Google Scholar
• Qin, G., J. Liu, S. Xu, and T. Wang. 2020. “Water Quality Assessment and Pollution Source Apportionment in a Highly Regulated River of Northeast China.” Environmental Monitoring and Assessment 192 (7): 446. https://doi.org/10.1007/s10661-020-08404-0.
   PubMed Web of Science ®Google Scholar
• Smith, M. E., L. Robertson Lain, and S. Bernard. 2018. “An Optimized Chlorophyll a Switching Algorithm for MERIS and OLCI in Phytoplankton-Dominated Waters.” Remote Sensing of Environment 215:217–227. https://doi.org/10.1016/j.rse.2018.06.002.
   Web of Science ®Google Scholar
• Sun, D., Y. Li, and Q. Wang. 2009. “A Unified Model for Remotely Estimating Chlorophyll a in Lake Taihu, China, Based on SVM and in situ Hyperspectral Data.” IEEE Transactions on Geoscience and Remote Sensing 47 (8): 2957–2965. https://doi.org/10.1109/TGRS.2009.2014688.
   Web of Science ®Google Scholar
• Su, M. M., G. Wall, and Z. Ma. 2014. “Assessing Ecotourism from a Multi-Stakeholder Perspective: Xingkai Lake National Nature Reserve, China.” Environmental Management 54 (5): 1190–1207. https://doi.org/10.1007/s00267-014-0360-5.
   PubMed Web of Science ®Google Scholar
• Tilstone, G. H., S. Pardo, G. Dall’olmo, R. J. W. Brewin, F. Nencioli, D. Dessailly, E. Kwiatkowska, T. Casal, and C. Donlon. 2021. “Performance of Ocean Colour Chlorophyll a Algorithms for Sentinel-3 OLCI, MODIS-Aqua and Suomi-VIIRS in Open-Ocean Waters of the Atlantic.” Remote Sensing of Environment 260:112444. https://doi.org/10.1016/j.rse.2021.112444.
   Web of Science ®Google Scholar
• Tzortziou, M., A. Subramaniam, J. R. Herman, C. L. Gallegos, P. J. Neale, and L. W. Harding. 2007. “Remote Sensing Reflectance and Inherent Optical Properties in the Mid Chesapeake Bay.” Estuarine, Coastal and Shelf Science 72 (1–2): 16–32. https://doi.org/10.1016/j.ecss.2006.09.018.
   Web of Science ®Google Scholar
• USEPA. 2000. “Chapter: The Basis for Lake and Reservoir Nutrient Criteria.“ In Nutrient Criteria Technical Guidance Manual-Lakes and Reservoirs, 1–16. Washington, DC: Office of water, office of science and technology.
   Google Scholar
• Vanhellemont, Q., and K. Ruddick. 2021. “Atmospheric Correction of Sentinel-3/OLCI Data for Mapping of Suspended Particulate Matter and Chlorophyll-A Concentration in Belgian Turbid Coastal Waters.” Remote Sensing of Environment 256:112284. https://doi.org/10.1016/j.rse.2021.112284.
   Web of Science ®Google Scholar
• Wang, R., T. Xu, L. Yu, J. Zhu, and X. Li. 2013. “Effects of Land Use Types on Surface Water Quality Across an Anthropogenic Disturbance Gradient in the Upper Reach of the Hun River, Northeast China.” Environmental Monitoring and Assessment 185 (5): 4141–4151. https://doi.org/10.1007/s10661-012-2856-x.
   PubMed Web of Science ®Google Scholar
• Warren, M. A., S. G. H. Simis, and N. Selmes. 2021. “Complementary Water Quality Observations from High and Medium Resolution Sentinel Sensors by Aligning Chlorophyll-A and Turbidity Algorithms.” Remote Sensing of Environment 265:112651. https://doi.org/10.1016/j.rse.2021.112651.
   PubMed Web of Science ®Google Scholar
• Yang, W., B. Matsushita, J. Chen, T. Fukushima, and R. Ma. 2010. “An Enhanced Three-Band Index for Estimating Chlorophyll-A in Turbid Case-II Waters: Case Studies of Lake Kasumigaura, Japan, and Lake Dianchi, China.” IEEE Geoscience and Remote Sensing Letters 7 (4): 655–659. https://doi.org/10.1109/LGRS.2010.2044364.
   Web of Science ®Google Scholar
• Yu, S., X. Li, B. Wen, G. Chen, A. Hartleyc, M. Jiang, and X. Li. 2021. “Characterization of Water Quality in Xiao Xingkai Lake: Implications for Trophic Status and Management.” CHINESE GEOGRAPHICAL SCIENCE 31 (3): 558–570. https://doi.org/10.1007/s11769-021-1199-3.
   Web of Science ®Google Scholar
• Zhang, M., C. Hu, J. Cannizzaro, D. English, B. B. Barnes, P. Carlson, and L. Yarbro. 2018. “Comparison of Two Atmospheric Correction Approaches Applied to MODIS Measurements Over North American Waters.” Remote Sensing of Environment 216:442–455. https://doi.org/10.1016/j.rse.2018.07.012.
   Web of Science ®Google Scholar