Modeling and Multi-Temporal Characterization of Total Suspended Matter by the Combined Use of Sentinel 2-MSI and Landsat 8-OLI Data: The Pertusillo Lake Case Study (Italy)

The total suspended matter (TSM) variability plays a crucial role in a lake’s ecological functioning and its biogeochemical cycle. Sentinel-2A MultiSpectral Instrument (MSI) and Landsat 8 Operational Land Instrument (OLI) data offer unique opportunities for investigating certain in-water constituents (e.g., TSM and chlorophyll-a) owing to their spatial resolution (10–60 m). In this framework, we assessed the potential of MSI–OLI combined data in characterizing the multi-temporal (2014–2018) TSM variability in Pertusillo Lake (Basilicata region, Southern Italy). We developed and validated a customized MSI-based TSM model (R2 = 0.81) by exploiting ground measurements acquired during specific measurement campaigns. The model was then exported as OLI data through an intercalibration procedure (R2 = 0.87), allowing for the generation of a TSM multi-temporal MSI–OLI merged dataset. The analysis of the derived multi-year TSM monthly maps showed the influence of hydrological factors on the TSM seasonal dynamics over two sub-regions of the lake, the west and east areas. The western side is more influenced by inflowing rivers and water level fluctuations, the effects of which tend to longitudinally decrease, leading to less sediment within the eastern sub-area. The achieved results can be exploited by regional authorities for better management of inland water quality and monitoring systems.

[1]  Vincent Marieu,et al.  Monitoring spatio-temporal variability of the Adour River turbid plume (Bay of Biscay, France) with MODIS 250-m imagery , 2014 .

[2]  P. McIntyre,et al.  Global threats to human water security and river biodiversity , 2010, Nature.

[3]  Zhi-Gang Yao,et al.  Heavy metal research in lacustrine sediment: a review , 2007 .

[4]  C. Giardino,et al.  Sensitivity analysis of a bio-optical model for Italian lakes focused on Landsat-8, Sentinel-2 and Sentinel-3 , 2015 .

[5]  David Doxaran,et al.  Monitoring the maximum turbidity zone and detecting fine‐scale turbidity features in the Gironde estuary using high spatial resolution satellite sensor (SPOT HRV, Landsat ETM+) data , 2006 .

[6]  D. Hering,et al.  Drivers and stressors of freshwater biodiversity patterns across different ecosystems and scales: a review , 2012, Hydrobiologia.

[7]  Bryan A. Franz,et al.  Sentinel-2 MultiSpectral Instrument (MSI) data processing for aquatic science applications: Demonstrations and validations , 2017 .

[8]  Zhongping Lee,et al.  Remote Sensing of Secchi Depth in Highly Turbid Lake Waters and Its Application with MERIS Data , 2019, Remote. Sens..

[9]  Olga Yu. Lavrova,et al.  River plumes investigation using Sentinel-2A MSI and Landsat-8 OLI data , 2016, Remote Sensing.

[10]  John R. Schott,et al.  On-orbit radiometric characterization of OLI (Landsat-8) for applications in aquatic remote sensing , 2014 .

[11]  G. Weyhenmeyer,et al.  Lakes as sentinels of climate change , 2009, Limnology and oceanography.

[12]  Tiziana Simoniello,et al.  A first assessment of the Sentinel-2 Level 1-C cloud mask product to support informed surface analyses , 2018, Remote Sensing of Environment.

[13]  T. Parsons,et al.  A practical handbook of seawater analysis , 1968 .

[14]  R. Coluzzi,et al.  Land cover changes and forest landscape evolution (1985–2009) in a typical Mediterranean agroforestry system (high Agri Valley) , 2014 .

[15]  G. Zibordi,et al.  Protocols for Satellite Ocean Color Data Validation : In situ Optical Radiometry , 2018 .

[16]  P. J. Werdell,et al.  A multi-sensor approach for the on-orbit validation of ocean color satellite data products , 2006 .

[17]  Xiaohan Liu,et al.  Long-term remote monitoring of total suspended matter concentration in Lake Taihu using 250 m MODIS-Aqua data , 2015 .

[18]  Frank Canters,et al.  Dating lava flows of tropical volcanoes by means of spatial modeling of vegetation recovery , 2018 .

[19]  C. Justice,et al.  The Harmonized Landsat and Sentinel-2 surface reflectance data set , 2018, Remote Sensing of Environment.

[20]  Tiit Kutser,et al.  First Experiences in Mapping Lake Water Quality Parameters with Sentinel-2 MSI Imagery , 2016, Remote. Sens..

[21]  N. Oppelt,et al.  Remote sensing for lake research and monitoring – Recent advances , 2016 .

[22]  Mati Kahru,et al.  Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4, Volume IV: Inherent Optical Properties: Instruments, Characterizations, Field Measurements and Data Analysis Protocols , 2013 .

[23]  Menghua Wang Remote sensing of the ocean contributions from ultraviolet to near-infrared using the shortwave infrared bands: simulations. , 2007, Applied optics.

[24]  Zhongfeng Qiu,et al.  Light beam attenuation and backscattering properties of particles in the Bohai Sea and Yellow Sea with relation to biogeochemical properties , 2016 .

[25]  Menghua Wang,et al.  Remote Sensing of Inherent Optical Properties : Fundamentals , 2009 .

[26]  N. Oppelt,et al.  Analysis of mineral-rich suspended matter in glacial lakes using simulations and satellite data , 2016 .

[27]  Nima Pahlevan,et al.  Sentinel-2/Landsat-8 product consistency and implications for monitoring aquatic systems , 2019, Remote Sensing of Environment.

[28]  Valeria Satriano,et al.  On the Potential of Robust Satellite Techniques Approach for SPM Monitoring in Coastal Waters: Implementation and Application over the Basilicata Ionian Coastal Waters Using MODIS-Aqua , 2016, Remote. Sens..

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

[30]  Kevin Ruddick,et al.  Acolite for Sentinel-2: Aquatic Applications of MSI Imagery , 2016 .

[31]  David Doxaran,et al.  Shellfish Aquaculture from Space: Potential of Sentinel2 to Monitor Tide-Driven Changes in Turbidity, Chlorophyll Concentration and Oyster Physiological Response at the Scale of an Oyster Farm , 2017, Front. Mar. Sci..

[32]  R. Coluzzi,et al.  Satellite data and soil magnetic susceptibility measurements for heavy metals monitoring: findings from Agri Valley (Southern Italy) , 2018, Environmental Earth Sciences.

[33]  M. Présing,et al.  Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10 years of MERIS observations , 2015 .

[34]  Teodosio Lacava,et al.  The VIIRS-Based RST-FLARE Configuration: The Val d'Agri Oil Center Gas Flaring Investigation in Between 2015-2019 , 2020, Remote. Sens..

[35]  Emiliana Valentini,et al.  Airborne hyperspectral data to assess suspended particulate matter and aquatic vegetation in a shallow and turbid lake , 2015 .

[36]  Thomas L. Crisman,et al.  The role of water-level fluctuations in shallow lake ecosystems – workshop conclusions , 2003, Hydrobiologia.

[37]  John P. Smol,et al.  Lakes and reservoirs as sentinels, integrators, and regulators of climate change , 2009 .

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

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

[40]  C. Binding,et al.  Long term water clarity changes in North America's Great Lakes from multi‐sensor satellite observations , 2015 .

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

[42]  Natascha Oppelt,et al.  Water Constituents and Water Depth Retrieval from Sentinel-2A - A First Evaluation in an Oligotrophic Lake , 2016, Remote. Sens..

[43]  Daniela Stroppiana,et al.  Optical remote sensing of lakes: an overview on Lake Maggiore , 2013 .

[44]  Quinten Vanhellemont,et al.  Atmospheric correction of metre-scale optical satellite data for inland and coastal water applications , 2018, Remote Sensing of Environment.

[45]  John R. Schott,et al.  Leveraging EO-1 to Evaluate Capability of New Generation of Landsat Sensors for Coastal/Inland Water Studies , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[46]  D. Odermatt,et al.  Application of remote sensing for the optimization of in-situ sampling for monitoring of phytoplankton abundance in a large lake. , 2015, The Science of the total environment.

[47]  Stephanie C. J. Palmer,et al.  Remote sensing of inland waters: Challenges, progress and future directions , 2015 .

[48]  Menghua Wang,et al.  Retrieval of the seawater reflectance for suspended solids monitoring in the East China Sea using MODIS, MERIS and GOCI satellite data , 2014 .

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

[50]  Quinten Vanhellemont,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 , 2017, Remote. Sens..

[51]  Quinten Vanhellemont,et al.  Adaptation of the dark spectrum fitting atmospheric correction for aquatic applications of the Landsat and Sentinel-2 archives , 2019, Remote Sensing of Environment.

[52]  Valeria Satriano,et al.  Evaluation of MODIS - Aqua Chlorophyll-a Algorithms in the Basilicata Ionian Coastal Waters , 2018, Remote. Sens..

[53]  T. Lacava,et al.  A satellite-based analysis of the Val d'Agri Oil Center (southern Italy) gas flaring emissions , 2014 .

[54]  Julius T. Tou,et al.  Pattern Recognition Principles , 1974 .

[55]  Chuanmin Hu,et al.  Influence of the Three Gorges Dam on total suspended matters in the Yangtze Estuary and its adjacent coastal waters: Observations from MODIS , 2014 .

[56]  Wei Li,et al.  Estimation of the algal-available phosphorus pool in sediments of a large, shallow eutrophic lake (Taihu, China) using profiled SMT fractional analysis. , 2013, Environmental pollution.

[57]  Menghua Wang,et al.  Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: a preliminary algorithm. , 1994, Applied optics.

[58]  John R. Schott,et al.  Landsat 8 Remote Sensing Reflectance (Rrs) Products: Evaluations, Intercomparisons, and Enhancements , 2017 .

[59]  Qingquan Li,et al.  Application of Sentinel 2 MSI Images to Retrieve Suspended Particulate Matter Concentrations in Poyang Lake , 2017, Remote. Sens..

[60]  Manel Leira,et al.  Effects of water-level fluctuations on lakes: an annotated bibliography , 2008, Hydrobiologia.

[61]  David P. Roy,et al.  A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring , 2017, Remote. Sens..

[62]  Á. Borja,et al.  The European Water Framework Directive at the age of 10: a critical review of the achievements with recommendations for the future. , 2010, The Science of the total environment.

[63]  G. Chiaudani,et al.  Lake management in Italy: the implications of the Water Framework Directive , 2003 .

[64]  J. Osán,et al.  Heavy metals in Lake Balaton: water column, suspended matter, sediment and biota. , 2005, The Science of the total environment.

[65]  Steven L. Rhodes,et al.  Great Lakes toxic sediments and climate change: Implications for environmental remediation , 1993 .

[66]  Marten Scheffer,et al.  Assessing ecological quality of shallow lakes: Does knowledge of transparency suffice? , 2009 .

[67]  Gabriele Bitelli,et al.  Preliminary Comparison of Sentinel-2 and Landsat 8 Imagery for a Combined Use , 2016, Remote. Sens..

[68]  Zhe Zhu,et al.  Harmonizing Landsat 8 and Sentinel-2: A time-series-based reflectance adjustment approach , 2019 .