Mapping river turbidity at a large basin-scale with a spatially transferable ensemble model using Landsat 8 multispectral imagery

References

• Baughman, C., B. Jones, K. Bartz, D. Young, and C. Zimmerman. 2015. “Reconstructing Turbidity in a Glacially Influenced Lake Using the Landsat TM and ETM+ Surface Reflectance Climate Data Record Archive, Lake Clark, Alaska.” Remote Sensing 7 (10): 13692–13710.
   Web of Science ®Google Scholar
• Beck, R., S. Zhan, H. Liu, S. Tong, B. Yang, X. Min, Y. Zhaoxia, Y. Huang, S. Shu, and W. Qiusheng. 2016. “Comparison of Satellite Reflectance Algorithms for Estimating Chlorophyll-A in a Temperate Reservoir Using Coincident Hyperspectral Aircraft Imagery and Dense Coincident Surface Observations.” Remote Sensing of Environment 178:15–30. https://doi.org/10.1016/j.rse.2016.03.002.
   Web of Science ®Google Scholar
• Breiman, L., J. H. Friedman, R. A. Olshen, and C. J. Stone. 1984. Classification and Regression Trees. 1st ed. Routledge. https://doi.org/10.1201/9781315139470.
   Google Scholar
• Dogliotti, A. I., K. G. Ruddick, B. Nechad, D. Doxaran, and E. Knaeps. 2015. “A Single Algorithm to Retrieve Turbidity from Remotely-Sensed Data in All Coastal and Estuarine Waters.” Remote Sensing of Environment 156:157–168. https://doi.org/10.1016/j.rse.2014.09.020.
   Web of Science ®Google Scholar
• Effler, S. W. 1988. “Secchi Disc Transparency and Turbidity.” Journal of Environmental Engineering 114 (6): 1436–1447. https://doi.org/10.1061/(ASCE)0733-9372(1988)114:6(1436).
   Web of Science ®Google Scholar
• Gippel, C. J. 1995. “Potential of Turbidity Monitoring for Measuring the Transport of Suspended Solids in Streams.” Hydrological Processes 9 (1): 83–97. https://doi.org/10.1002/hyp.3360090108.
   Web of Science ®Google Scholar
• Grayson, R. B., B. L. Finlayson, C. J. Gippel, and B. T. Hart. 1996. “The Potential of Field Turbidity Measurements for the Computation of Total Phosphorus and Suspended Solids Loads.” Journal of Environmental Management 47 (3): 257–267. https://doi.org/10.1006/jema.1996.0051.
   Web of Science ®Google Scholar
• Gunn, J. M., E. D. Snucins, N. D. Yan, and M. T. Arts. 2001. “Use of Water Clarity to Monitor the Effects of Climate Change and Other Stressors on Oligotrophic Lakes.” Environmental Monitoring and Assessment 67 (1–2): 69–88. https://doi.org/10.1023/A:1006435721636.
   PubMed Web of Science ®Google Scholar
• Kloiber, S. M., P. L. Brezonik, L. G. Olmanson, and M. E. Bauer. 2002. “A Procedure for Regional Lake Water Clarity Assessment Using Landsat Multispectral Data.” Remote Sensing of Environment 82 (1): 38–47. https://doi.org/10.1016/S0034-4257(02)00022-6.
   Web of Science ®Google Scholar
• Liu, Y., H. Liu, L. Wang, X. Min, S. Cohen, and K. Liu. 2021. “Derivation of Spatially Detailed Lentic Habitat Map and Inventory at a Basin Scale by Integrating Multispectral Sentinel-2 Satellite Imagery and USGS Digital Elevation Models.” Journal of Hydrology 603:126876. https://doi.org/10.1016/j.jhydrol.2021.126876.
   Web of Science ®Google Scholar
• Matthews, M. W. 2011. “A Current Review of Empirical Procedures of Remote Sensing in Inland and Near-Coastal Transitional Waters.” International Journal of Remote Sensing 32 (21): 6855–6899. https://doi.org/10.1080/01431161.2010.512947.
   Web of Science ®Google Scholar
• Mobley, C. D. 2015. “Polarized Reflectance and Transmittance Properties of Windblown Sea Surfaces.” Applied Optics 54 (15): 4828–4849. https://doi.org/10.1364/AO.54.004828.
   PubMed Web of Science ®Google Scholar
• Odermatt, D., A. Gitelson, V. E. Brando, and M. Schaepman. 2012. “Review of Constituent Retrieval in Optically Deep and Complex Waters from Satellite Imagery.” Remote sensing of environment 118: 116126.
   Web of Science ®Google Scholar
• Olmanson, L. G., P. L. Brezonik, and M. E. Bauer. 2015. “Remote Sensing for Regional Lake Water Quality Assessment: Capabilities and Limitations of Current and Upcoming Satellite Systems.” In Advances in Watershed Science and Assessment, 111–140. Springer International Publishing. https://doi.org/10.1007/978-3-319-14212-8_5.
   Google Scholar
• Pahlevan, N., J. R. Schott, B. A. Franz, G. Zibordi, B. Markham, S. Bailey, C. B. Schaaf, M. Ondrusek, S. Greb, and C. M. Strait. 2017. “Landsat 8 Remote Sensing Reflectance (Rrs) Products: Evaluations, Intercomparisons, and Enhancements.” Remote Sensing of Environment 190:289–301. https://doi.org/10.1016/j.rse.2016.12.030.
   Web of Science ®Google Scholar
• Politi, E., M. E. Cutler, and J. S. Rowan. 2015. “Evaluating the Spatial Transferability and Temporal Repeatability of Remote-Sensing-Based Lake Water Quality Retrieval Algorithms at the European Scale: A Meta-Analysis Approach.” International Journal of Remote Sensing 36 (11): 2995–3023. https://doi.org/10.1080/01431161.2015.1054962.
   Web of Science ®Google Scholar
• Ross, M. R., S. N. Topp, A. P. Appling, X. Yang, C. Kuhn, D. Butman, M. Simard, and T. M. Pavelsky. 2019. “AquaSat: A Data Set to Enable Remote Sensing of Water Quality for Inland Waters.” Water Resources Research 55 (11): 10012–10025. https://doi.org/10.1029/2019WR024883.
   Web of Science ®Google Scholar
• Roy, D. P., M. A. Wulder, T. R. Loveland, C. E. Woodcock, R. G. Allen, M. C. Anderson, D. Helder, J. R. Irons, D. M. Johnson, and R. Kennedy. 2014. “Landsat-8: Science and Product Vision for Terrestrial Global Change Research.” Remote Sensing of Environment 145:154–172. https://doi.org/10.1016/j.rse.2014.02.001.
   Web of Science ®Google Scholar
• Smith, D., and R. Davis-Colley. 2001. “Turbidity Suspended Sediment and Water Clarity.” Journal of the American Water Resources Association / AWRA 37 (5): 1085–1101. https://doi.org/10.1111/j.1752-1688.2001.tb03624.x.
   Web of Science ®Google Scholar
• Soil, Alabama, and Water Conservation Committee. 2009. “Alabama Handbook for Erosion Control, Sediment Control and Stormwater Management on Construction Sites and Urban Areas.” Montgomery, AL.
   Google Scholar
• Vanhellemont, Q. 2019. “Adaptation of the Dark Spectrum Fitting Atmospheric Correction for Aquatic Applications of the Landsat and Sentinel-2 Archives.” Remote Sensing of Environment 225:175–192. https://doi.org/10.1016/j.rse.2019.03.010.
   Web of Science ®Google Scholar
• Warren, M. A., S. G. Simis, V. Martinez-Vicente, K. Poser, M. Bresciani, K. Alikas, E. Spyrakos, C. Giardino, and A. Ansper. 2019. “Assessment of Atmospheric Correction Algorithms for the Sentinel-2A MultiSpectral Imager Over Coastal and Inland Waters.” Remote Sensing of Environment 225:267–289. https://doi.org/10.1016/j.rse.2019.03.018.
   Web of Science ®Google Scholar
• Xu, M., H. Liu, R. Beck, J. Lekki, B. Yang, Y. Liu, S. Shu, et al. 2021. “Implementation Strategy and Spatiotemporal Extensibility of Multipredictor Ensemble Model for Water Quality Parameter Retrieval with Multispectral Remote Sensing Data.” IEEE Transactions on Geoscience & Remote Sensing 60:1–16. https://doi.org/10.1109/TGRS.2020.3045921.
   Google Scholar
• Xu, M., H. Liu, R. Beck, J. Lekki, B. Yang, S. Shu, E. L. Kang, R. Anderson, R. Johansen, and E. Emery. 2018. “A Spectral Space Partition Guided Ensemble Method for Retrieving Chlorophyll-A Concentration in Inland Waters from Sentinel-2A Satellite Imagery.” Journal of Great Lakes Research 45 (3): 454–465. https://doi.org/10.1016/j.jglr.2018.09.002.
   Web of Science ®Google Scholar
• Xu, M., H. Liu, R. Beck, J. Lekki, B. Yang, S. Shu, Y. Liu, et al. 2019. “Regionally and Locally Adaptive Models for Retrieving Chlorophyll-A Concentration in Inland Waters from Remotely Sensed Multispectral and Hyperspectral Imagery.” IEEE Transactions on Geoscience & Remote Sensing 57 (7): 4758–4774. https://doi.org/10.1109/TGRS.2019.2892899.
   Web of Science ®Google Scholar