Hyperspectral and Multispectral Retrieval of Suspended Sediment in Shallow Coastal Waters Using Semi-Analytical and Empirical Methods

Natural lagoons and estuaries worldwide are experiencing accelerated ecosystem degradation due to increased anthropogenic pressure. As a key driver of coastal zone dynamics, suspended sediment concentration (SSC) is difficult to monitor with adequate spatial and temporal resolutions both in the field and using remote sensing. In particular, the spatial resolutions of currently available remote sensing data generated by satellite sensors designed for ocean color retrieval, such as MODIS (Moderate Resolution Imaging Spectroradiometer) or SeaWiFS (Sea-Viewing Wide Field-of-View Sensor), are too coarse to capture the dimension and geomorphological heterogeneity of most estuaries and lagoons. In the present study, we explore the use of hyperspectral (Hyperion) and multispectral data, i.e., the Landsat TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), and ALOS (Advanced Land Observing Satellite), to estimate SSC through semi-analytical and empirical approaches in the Venice lagoon (Italy). Key parameters of the retrieval models are calibrated and cross-validated by matching the remote sensing estimates of SSC with in situ data from a network of water quality sensors. Our analysis shows that, despite the higher spectral resolution, hyperspectral data provide limited advantages over the use of multispectral data, mainly due to information redundancy and cross-band correlation. Meanwhile, the limited historical archive of hyperspectral data (usually acquired on demand) severely reduces the chance of observing high turbidity events, which are relatively rare but critical in controlling the coastal sediment and geomorphological dynamics. On the contrary, retrievals using available multispectral data can encompass a much wider range of SSC values due to their frequent acquisitions and longer historical archive. For the retrieval methods considered in this study, we find that the semi-analytical method outperforms empirical approaches, when applied to both the hyperspectral and multispectral dataset. Interestingly, the improved performance emerges more clearly when the data used for testing are kept separated from those used in the calibration, suggesting a greater ability of semi-analytical models to “generalize” beyond the specific data set used for model calibration.

[1]  Andrew N. Tyler,et al.  Remote sensing of the water quality of shallow lakes: A mixture modelling approach to quantifying phytoplankton in water characterized by high‐suspended sediment , 2006 .

[2]  Maria Adamo,et al.  Assessing water quality in the northern Adriatic Sea from HICO™ data , 2013 .

[3]  L. Han,et al.  Applications of Landsat‐5 TM imagery in assessing and mapping water quality in Reelfoot Lake, Tennessee , 2006 .

[4]  C. Long,et al.  Remote sensing of suspended sediment concentration and hydrologic connectivity in a complex wetland environment. , 2013 .

[5]  C. Mobley,et al.  Hyperspectral remote sensing for shallow waters. I. A semianalytical model. , 1998, Applied optics.

[6]  Marcos J. Montes,et al.  Water and bottom properties of a coastal environment derived from Hyperion data measured from the EO-1 spacecraft platform , 2007 .

[7]  M. Kirwan,et al.  Tidal wetland stability in the face of human impacts and sea-level rise , 2013, Nature.

[8]  Lian Feng,et al.  Dynamic range and sensitivity requirements of satellite ocean color sensors: learning from the past. , 2012, Applied optics.

[9]  Andrea Rinaldo,et al.  Biologically‐controlled multiple equilibria of tidal landforms and the fate of the Venice lagoon , 2007 .

[10]  M. Marani,et al.  Spatial response of coastal marshes to increased atmospheric CO2 , 2015, Proceedings of the National Academy of Sciences.

[11]  Harry H. Roberts,et al.  Drowning of the Mississippi Delta due to insufficient sediment supply and global sea-level rise , 2009 .

[12]  Fred A. Kruse,et al.  Comparison of EO-1 Hyperion and airborne hyperspectral remote sensing data for geologic applications , 2002, Proceedings, IEEE Aerospace Conference.

[13]  Arnold G. Dekker,et al.  Retrieval of chlorophyll and suspended matter from imaging spectrometry data by matrix inversion , 1998 .

[14]  Eric Vermote,et al.  Atmospheric correction for the monitoring of land surfaces , 2008 .

[15]  John Shepanski,et al.  Hyperion, a space-based imaging spectrometer , 2003, IEEE Trans. Geosci. Remote. Sens..

[16]  S. Lawrence Dingman,et al.  Effective sea-level rise and deltas: Causes of change and human dimension implications , 2006 .

[17]  Vittorio E. Brando,et al.  Assessment of water quality in Lake Garda (Italy) using Hyperion , 2007 .

[18]  C. Mobley,et al.  Hyperspectral remote sensing for shallow waters. 2. Deriving bottom depths and water properties by optimization. , 1999, Applied optics.

[19]  Richard L. Miller,et al.  Using MODIS Terra 250 m imagery to map concentrations of total suspended matter in coastal waters , 2004 .

[20]  S. Boudjelas,et al.  The distribution of fine suspended sediments in the surface waters of the Irish Sea and its relation to tidal stirring , 1998 .

[21]  J. Kämäri,et al.  Detection of water quality using simulated satellite data and semi-empirical algorithms in Finland. , 2001, The Science of the total environment.

[22]  C. Mobley.  Light and Water: Radiative Transfer in Natural Waters , 1994 .

[23]  T. J. Petzold.  Volume Scattering Functions for Selected Ocean Waters , 1972 .

[24]  R. Bukata,et al.  Suspended particulate matter in Lake Erie derived from MODIS aquatic colour imagery , 2010 .

[25]  E. Fry,et al.  Absorption spectrum (380-700 nm) of pure water. II. Integrating cavity measurements. , 1997, Applied optics.

[26]  Tim R. McVicar,et al.  Preprocessing EO-1 Hyperion hyperspectral data to support the application of agricultural indexes , 2003, IEEE Trans. Geosci. Remote. Sens..

[27]  Junwu Tang,et al.  Backscattering ratio variation and its implications for studying particle composition: A case study in Yellow and East China seas , 2010 .

[28]  Patricia L. Wiberg,et al.  Stability and bistability of seagrass ecosystems in shallow coastal lagoons: Role of feedbacks with sediment resuspension and light attenuation , 2010 .

[29]  Giuseppe Zibordi,et al.  Assessment of satellite ocean color products at a coastal site , 2007 .

[30]  B. Nechad,et al.  Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters , 2010 .

[31]  Serwan Mj Baban,et al.  Environmental Monitoring of Estuaries; Estimating and Mapping Various Environmental Indicators in Breydon Water Estuary, U.K., Using Landsat TM Imagery , 1997 .

[32]  Wensheng Jiang,et al.  Study on the seasonal variation of the suspended sediment distribution and transportation in the East China Seas based on SeaWiFS data , 2008 .

[33]  Luca Carniello,et al.  Dynamic response of marshes to perturbations in suspended sediment concentrations and rates of relative sea level rise , 2011 .

[34]  B. Nechad,et al.  Mapping total suspended matter from geostationary satellites: a feasibility study with SEVIRI in the Southern North Sea. , 2009, Optics express.

[35]  David Doxaran,et al.  Role of measurement uncertainties in observed variability in the spectral backscattering ratio: a case study in mineral-rich coastal waters. , 2009, Applied optics.

[36]  M. Marani,et al.  Evaluation of sediment properties using wind and turbidity observations in the shallow tidal areas of the Venice Lagoon , 2014 .

[37]  Sindy Sterckx,et al.  In situ evidence of non-zero reflectance in the OLCI 1020 nm band for a turbid estuary , 2012 .

[38]  T Platt,et al.  Effect of the particle-size distribution on the backscattering ratio in seawater. , 1994, Applied optics.

[39]  P. V. Sundareshwar,et al.  RESPONSES OF COASTAL WETLANDS TO RISING SEA LEVEL , 2002 .

[40]  X. Wang,et al.  Application of Remote Sensing Techniques in Monitoring and Assessing the Water Quality of Taihu Lake , 2001, Bulletin of environmental contamination and toxicology.

[41]  Michael Corson,et al.  Hyperspectral Imager for the Coastal Ocean: instrument description and first images. , 2011, Applied optics.

[42]  Menghua Wang,et al.  An assessment of the black ocean pixel assumption for MODIS SWIR bands , 2009 .

[43]  Luca Carniello,et al.  Modeling sand-mud transport induced by tidal currents and wind waves in shallow microtidal basins: Application to the Venice Lagoon (Italy) , 2012 .

[44]  Martti Hallikainen,et al.  A case study of airborne and satellite remote sensing of a spring bloom event in the Gulf of Finland , 2007 .

[45]  Carlo A. Furia,et al.  User manual , 2023, International Transport Forum Policy Papers.

[46]  J. Ehn,et al.  Optical characterisation of suspended particles in the Mackenzie River plume (Canadian Arctic Ocean) and implications for ocean colour remote sensing , 2012 .

[47]  C. Binding,et al.  The optical properties of mineral suspended particles: A review and synthesis , 2006 .

[48]  E. Vermote,et al.  Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part I: path radiance. , 2006, Applied optics.

[49]  R. Lucke,et al.  Impact of signal-to-noise ratio in a hyperspectral sensor on the accuracy of biophysical parameter estimation in case II waters. , 2012, Optics express.

[50]  D. Doxaran,et al.  Spectral signature of highly turbid waters: Application with SPOT data to quantify suspended particulate matter concentrations , 2002 .

[51]  François Cauneau,et al.  Optical Remote Sensing of Shallow-Water Environmental Parameters , 2000 .

[52]  C. Binding,et al.  Estimating suspended sediment concentrations from ocean colour measurements in moderately turbid waters; the impact of variable particle scattering properties , 2005 .

[53]  Luca Carniello,et al.  Sediment dynamics in shallow tidal basins: In situ observations, satellite retrievals, and numerical modeling in the Venice Lagoon , 2014 .

[54]  F. R. Schiebe,et al.  Remote sensing of Lake Chicot, Arkansas: Monitoring suspended sediments, turbidity, and Secchi depth with Landsat MSS data , 1992 .

[55]  Luca Carniello,et al.  Morphological evolution of the Venice lagoon: Evidence from the past and trend for the future , 2009 .

[56]  Anatoly A. Gitelson,et al.  Estimation of chlorophyll-a concentration in case II waters using MODIS and MERIS data—successes and challenges , 2009 .

[57]  A. Goetz,et al.  Column atmospheric water vapor and vegetation liquid water retrievals from Airborne Imaging Spectrometer data , 1990 .

[58]  Stefano Pignatti,et al.  A two-step optimization procedure for assessing water constituent concentrations by hyperspectral remote sensing techniques: An application to the highly turbid Venice lagoon waters , 2010 .

[59]  Young-Heon Jo,et al.  Future Retrievals of Water Column Bio-Optical Properties using the Hyperspectral Infrared Imager (HyspIRI) , 2013, Remote. Sens..

[60]  Paul V. Zimba,et al.  Remote Sensing Techniques to Assess Water Quality , 2003 .

[61]  P. Groves,et al.  Methodology For Hyperspectral Band Selection , 2004 .

[62]  David A. Landgrebe,et al.  The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon , 1994, IEEE Trans. Geosci. Remote. Sens..

[63]  David Bowers,et al.  The optical efficiency of flocs in shelf seas and estuaries , 2011 .

[64]  K. Ali,et al.  Application of empirical and semi-analytical algorithms to MERIS data for estimating chlorophyll a in Case 2 waters of Lake Erie , 2014, Environmental Earth Sciences.

[65]  I. Overeem,et al.  Sinking deltas due to human activities , 2009 .

[66]  Wojciech M. Klonowski,et al.  Intercomparison of shallow water bathymetry, hydro‐optics, and benthos mapping techniques in Australian and Caribbean coastal environments , 2011 .

[67]  M. Claverie,et al.  Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. , 2016, Remote sensing of environment.

[68]  David Doxaran,et al.  Estimating turbidity and total suspended matter in the Adour River plume (South Bay of Biscay) using MODIS 250-m imagery , 2010 .

[69]  J. Milliman,et al.  50,000 dams later: Erosion of the Yangtze River and its delta , 2011 .

[70]  Yoshiki Saito,et al.  Recent changes of sediment flux to the western Pacific Ocean from major rivers in East and Southeast Asia , 2011 .

[71]  Dariusz Stramski,et al.  Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration , 2003 .

[72]  David Doxaran,et al.  Dynamics of the turbidity maximum zone in a macrotidal estuary (the Gironde, France): Observations from field and MODIS satellite data , 2009 .

[73]  David Doxaran,et al.  Use of reflectance band ratios to estimate suspended and dissolved matter concentrations in estuarine waters , 2005 .

[74]  Marco Marani,et al.  Vegetation engineers marsh morphology through multiple competing stable states , 2013, Proceedings of the National Academy of Sciences.

[75]  M. He,et al.  Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments , 2007, Sensors.

[76]  Sindy Sterckx,et al.  Retrieval of Suspended Sediment from Advanced Hyperspectral Sensor Data in the Scheldt Estuary at Different Stages in the Tidal Cycle , 2007 .

[77]  A. Smirnov,et al.  AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .

[78]  Fred A. Kruse,et al.  Comparison of airborne hyperspectral data and EO-1 Hyperion for mineral mapping , 2003, IEEE Trans. Geosci. Remote. Sens..

[79]  Zhongping Lee,et al.  Effect of spectral band numbers on the retrieval of water column and bottom properties from ocean color data. , 2002, Applied optics.

[80]  G. Ferrari,et al.  On the accuracy of determining light absorption by “yellow substance” through measurements of induced fluorescence , 1991 .

[81]  Thomas M. Lillesand,et al.  Monitoring water quality and river plume transport in Green Bay, Lake Michigan with SPOT-1 imagery , 1989 .

[82]  S. Silvestri,et al.  Remote sensing retrieval of suspended sediment concentration in shallow waters , 2011 .

[83]  M. Matthews.  A current review of empirical procedures of remote sensing in inland and near-coastal transitional waters , 2011 .

[84]  Chuanmin Hu,et al.  Aquatic color radiometry remote sensing of coastal and inland waters: Challenges and recommendations for future satellite missions , 2015 .

[85]  Paul J. Curran,et al.  The form of the relationship between suspended sediment concentration and spectral reflectance: its implications for the use of Daedalus 1268 data , 1991 .

[86]  Vittorio E. Brando,et al.  Satellite hyperspectral remote sensing for estimating estuarine and coastal water quality , 2003, IEEE Trans. Geosci. Remote. Sens..

[87]  David A. Landgrebe,et al.  Information Extraction Principles and Methods for Multispectral and Hyperspectral Image Data , 1999 .

[88]  Richard W. Gould,et al.  From Meters to Kilometers: A Look at Ocean-Color Scales of Variability, Spatial Coherence, and the Need for Fine-Scale Remote Sensing in Coastal Ocean Optics , 2004 .

[89]  F. L. Hellwegera,et al.  Use of satellite imagery for water quality studies in New York Harbor , 2004 .

[90]  Dariusz Stramski,et al.  Variations in the light absorption coefficients of phytoplankton, nonalgal particles, and dissolved organic matter in coastal waters around Europe , 2003 .

[91]  M. Schaepman,et al.  Review of constituent retrieval in optically deep and complex waters from satellite imagery , 2012 .

[92]  松山 洋.  「Statistical Methods in the Atmospheric Sciences(2nd edition), International Geophysics Series 91」, Daniel S. Wilks著, Academic Press, 2005年11月, 648頁, $94.95, ISBN978-0-12-751966-1(本だな) , 2010 .