441
Views
6
CrossRef citations to date
0
Altmetric
Research Articles

Assessment of PRISMA Level-2 Hyperspectral Imagery for Large Scale Satellite-Derived Bathymetry Retrieval

, & ORCID Icon
Pages 251-273 | Received 19 Jun 2021, Accepted 18 Jan 2022, Published online: 04 Feb 2022

References

  • Albert, A. 2004. Inversion technique for optical remote sensing in shallow water. Optische Fernerkundung von Flachwasserzonen. PhD diss., SUB Hamburg. https://ediss.sub.uni-hamburg.de/handle/ediss/812.
  • Albert, A., and C. D. Mobley. 2003. An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters. Optics Express 11 (22):2873–90.
  • Agencia Spatiale Italiana. 2020. PRISMA products specification document, Issue 2.3 Date 12/03/2020. Accessed on April 01, 2021. http://prisma.asi.it/missionselect/docs/PRISMA%20Product%20Specifications_Is2_3.pdf.
  • Atwater, B. F., U. S. ten Brink, M. Buckley, R. S. Halley, B. E. Jaffe, A. M. López-Venegas, E. G. Reinhardt, M. P. Tuttle, S. Watt, and Y. Wei. 2012. Geomorphic and stratigraphic evidence for an unusual tsunami or storm a few centuries ago at Anegada, British Virgin Islands. Natural Hazards 63 (1):51–84.
  • Caballero, I., and R. P. Stumpf. 2019. Retrieval of nearshore bathymetry from Sentinel-2A and 2B satellites in South Florida coastal waters. Estuarine, Coastal and Shelf Science 226:106277.
  • Castillo-López, E., J. A. Dominguez, R. Pereda, J. M. de Luis, R. Pérez, and F. Piña. 2017. The importance of atmospheric correction for airborne hyperspectral remote sensing of shallow waters: Application to depth estimation. Atmospheric Measurement Techniques 10 (10):3919–29.
  • De Keukelaere, L., S. Sterckx, S. Adriaensen, E. Knaeps, I. Reusen, C. Giardino, M. Bresciani, P. Hunter, C. Neil, D. Van der Zande, et al. 2018. 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 (1):525–42.
  • Defoin‐Platel, M., and M. Chami. 2007. How ambiguous is the inverse problem of ocean color in coastal waters? Journal of Geophysical Research 112 (C3), 2006JC003847.
  • Dekker, A. G., S. R. Phinn, J. Anstee, P. Bissett, V. E. Brando, B. Casey, P. Fearns, J. Hedley, W. Klonowski, Z. P. Lee, et al. 2011. Intercomparison of shallow water bathymetry, hydro-optics, and benthos mapping techniques in Australian and Caribbean coastal environments. Limnology and Oceanography: Methods 9 (9):396–425.
  • Dierssen, H. M., R. C. Zimmerman, R. A. Leathers, T. V. Downes, and C. O. Davis. 2003. Ocean color remote sensing of seagrass and bathymetry in the Bahamas Banks by high-resolution airborne imagery. Limnology and Oceanography 48 (1part2):444–55.
  • Dominey-Howes, D., A. Dawson, and D. Smith. 1998. Late Holocene coastal tectonics at Falasarna, western Crete: A sedimentary study. Geological Society Special Publication, 146 (1):343–352. https://doi.org/https://doi.org/10.1144/GSL.SP.1999.146.01.20.
  • Dörnhöfer, K., A. Göritz, P. Gege, B. Pflug, and N. Oppelt. 2016. Water constituents and water depth retrieval from sentinel-2A—A first evaluation in an oligotrophic lake. Remote Sensing 8 (11):941.
  • European Space Agency. n.d. SNAP software. Accessed April 10, 2021. https://step.esa.int/main/download/snap-download/.
  • Eugenio, F., J. Marcello, J. Martin, and D. Rodríguez-Esparragón. 2017. Benthic habitat mapping using multispectral high-resolution imagery: Evaluation of shallow water atmospheric correction techniques. Sensors 17 (11):2639.
  • Frouin, R. J., B. A. Franz, A. Ibrahim, K. Knobelspiesse, Z. Ahmad, B. Cairns, J. Chowdhary, H. M. Dierssen, J. Tan, O. Dubovik, et al. 2019. Atmospheric correction of satellite ocean-color imagery during the PACE era. Frontiers in Earth Science 7:145.
  • Gao, B.-C., M. J. Montes, C. O. Davis, and A. F. H. Goetz. 2009. Atmospheric correction algorithms for hyperspectral remote sensing data of land and ocean. Remote Sensing of Environment 113:S17–S24.
  • Gao, J. 2009. Bathymetric mapping by means of remote sensing: Methods, accuracy and limitations. Progress in Physical Geography: Earth and Environment 33 (1):103–16.
  • Garcia, R. A. 2015. Uncertainty in hyperspectral remote sensing: Analysis of the potential and limitation of shallow water bathymetry and benthic classification. Thesis, Curtin University.
  • Garcia, R. A., Z. Lee, and E. J. Hochberg. 2018. Hyperspectral shallow-water remote sensing with an enhanced benthic classifier. Remote Sensing 10 (1):147.
  • Gege, P. 2014a. WASI-2D: A software tool for regionally optimized analysis of imaging spectrometer data from deep and shallow waters. Computers & Geosciences 62:208–15.
  • Gege, P. 2014b. A case study at starnberger see for hyperspectral bathymetry mapping using inverse modeling. In 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). Presented at the 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 1–4. Lausanne, Switzerland: IEEE.
  • Gege, P., and A. Albert. 2006. A tool for inverse modeling of spectral measurements in deep and shallow waters. In Remote sensing of aquatic coastal ecosystem processes, remote sensing and digital image processing, eds. L. L. Richardson, and E. F. LeDrew, 81–109. Dordrecht: Springer Netherlands.
  • Geyman, E. C., and A. C. Maloof. 2019. A simple method for extracting water depth from multispectral satellite imagery in regions of variable bottom type. Earth and Space Science 6 (3):527–37.
  • Gholamalifard, M., T. Kutser, A. Esmaili-Sari, A. A. Abkar, and B. Naimi. 2013. Remotely sensed empirical modeling of bathymetry in the southeastern Caspian sea. Remote Sensing 5 (6):2746–62.
  • Gómez, R. A. 2014. Spectral Reflectance Analysis of the Caribbean Sea. Geofísica Internacional 53: 385–398.
  • Hamylton, S. 2012. A comparison of spatially explicit and classic regression modelling of live coral cover using hyperspectral remote-sensing data in the Al Wajh lagoon, Red Sea. International Journal of Geographical Information Science 26 (11):2161–75.
  • Hedley, J. D., C. M. Roelfsema, I. Chollett, A. R. Harborne, S. F. Heron, S. Weeks, W. J. Skirving, A. E. Strong, C. M. Eakin, T. R. L. Christensen, et al. 2016. Remote sensing of coral reefs for monitoring and management: A review. Remote Sensing 8 (2):118.
  • Johnson, L. 2015. The underwater optical channel. https://doi.org/https://doi.org/10.13140/RG.2.1.1295.7283
  • Kay, S., J. D. Hedley, and S. Lavender. 2009. Sun glint correction of high and low spatial resolution images of aquatic scenes: A review of methods for visible and near-infrared wavelengths. Remote Sensing 1 (4):697–730.
  • Kibele, J., and N. T. Shears. 2016. Nonparametric empirical depth regression for bathymetric mapping in coastal waters. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9 (11):5130–8.
  • Kobryn, H. T., K. Wouters, L. E. Beckley, and T. Heege. 2013. Ningaloo reef: Shallow marine habitats mapped using a hyperspectral sensor. Plos One 8 (7):e70105.
  • Kutser, T., I. Miller, and D. L. B. Jupp. 2006. Mapping coral reef benthic substrates using hyperspectral space-borne images and spectral libraries. Estuarine, Coastal and Shelf Science 70 (3):449–60.
  • Kutser, T., E. Vahtmäe, and J. Praks. 2009. A sun glint correction method for hyperspectral imagery containing areas with non-negligible water leaving NIR signal. Remote Sensing of Environment 113 (10):2267–74.
  • Lee, Z., K. L. Carder, C. D. Mobley, R. G. Steward, and J. S. Patch. 1999. Hyperspectral remote sensing for shallow waters. 2. Deriving bottom depths and water properties by optimization. Applied Optics 38 (18):3831–43.
  • Lee, Z., K. L. Carder, C. D. Mobley, R. G. Steward, and J. S. Patch. 1998. Hyperspectral remote sensing for shallow waters. I. A semianalytical model. Applied Optics 37 (27):6329–38.
  • Lee, Z., B. Casey, R. A. Arnone, A. D. Weidemann, R. Parsons, M. J. Montes, B.-C. Gao, W. Goode, C. O. Davis, and J. Dye. 2007. Water and bottom properties of a coastal environment derived from Hyperion data measured from the EO-1 spacecraft platform. Journal of Applied Remote Sensing 1 (1):011502.
  • Leiper, I. A., S. R. Phinn, C. M. Roelfsema, K. E. Joyce, and A. G. Dekker. 2014. Mapping coral reef benthos, substrates, and bathymetry, using compact airborne spectrographic imager (CASI) data. Remote Sensing 6 (7):6423–45.
  • Liu, S., Y. Gao, W. Zheng, and X. Li. 2015. Performance of two neural network models in bathymetry. Remote Sensing Letters 6 (4):321–30.
  • Loizzo, R., C. Ananasso, R. Guarini, E. Lopinto, L. Candela, and A. R. Pisani. 2016. The Prisma hyperspectra mission. Living Planet Symposium 740:415.
  • Loncan, L.,. L. B. de Almeida, J. M. Bioucas-Dias, X. Briottet, J. Chanussot, N. Dobigeon, S. Fabre, W. Liao, G. A. Licciardi, M. Simões, et al. 2015. Hyperspectral pansharpening: A review. IEEE Geoscience and Remote Sensing Magazine 3 (3):27–46.
  • Lyzenga, D. R. 1978. Passive remote sensing techniques for mapping water depth and bottom features. Applied Optics 17 (3):379–83.
  • Ma, S., Z. Tao, X. Yang, Y. Yu, X. Zhou, and Z. Li. 2014. Bathymetry retrieval from hyperspectral remote sensing data in optical-shallow water. IEEE Transactions on Geoscience and Remote Sensing 52 (2):1205–12.
  • McIntyre, M. L., D. F. Naar, K. L. Carder, B. T. Donahue, and D. J. Mallinson. 2006. Coastal bathymetry from hyperspectral remote sensing data: Comparisons with high resolution multibeam bathymetry. Marine Geophysical Researches 27 (2):129–36.
  • Mobley, C. D., L. K. Sundman, C. O. Davis, J. H. Bowles, T. V. Downes, R. A. Leathers, M. J. Montes, W. P. Bissett, D. D. R. Kohler, R. P. Reid, et al. 2005. Interpretation of hyperspectral remote-sensing imagery by spectrum matching and look-up tables. Applied Optics 44 (17):3576–92.
  • Niroumand-Jadidi, M., F. Bovolo, L. Bruzzone, and P. Gege. 2020. Physics-based bathymetry and water quality retrieval using planetscope imagery: Impacts of 2020 COVID-19 lockdown and 2019 extreme flood in the Venice lagoon. Remote Sensing 12 (15):2381.
  • Pinnel, N. 2007. A method for mapping submerged macrophytes in lakes using hyperspectral remote sensing. https://mediatum.ub.tum.de/doc/604557/document.pdf.
  • Purkis, S. J. 2018. Remote sensing tropical coral reefs: The view from above. Annual Review of Marine Science 10:149–68.
  • Purkis, S. J., A. C. R. Gleason, C. R. Purkis, A. C. Dempsey, P. G. Renaud, M. Faisal, S. Saul, and J. M. Kerr. 2019. High-resolution habitat and bathymetry maps for 65,000 sq. km of earth’s remotest coral reefs. Coral Reefs 38 (3):467–88.
  • Roelfsema, C., E. Kovacs, J. C. Ortiz, N. H. Wolff, D. Callaghan, M. Wettle, M. Ronan, S. M. Hamylton, P. J. Mumby, and S. Phinn. 2018. Coral reef habitat mapping: A combination of object-based image analysis and ecological modelling. Remote Sensing of Environment 208:27–41.
  • Stumpf, R. P., K. Holderied, and M. Sinclair. 2003. Determination of water depth with high-resolution satellite imagery over variable bottom types. Limnology and Oceanography 48 (1part2):547–56.
  • Sun, W., B. Chen, and D. Messinger. 2014. Nearest-neighbor diffusion-based pan-sharpening algorithm for spectral images. Optical Engineering 53 (1):013107.
  • Traganos, D., D. Poursanidis, B. Aggarwal, N. Chrysoulakis, and P. Reinartz. 2018. Estimating satellite-derived bathymetry (SDB) with the google earth engine and sentinel-2. Remote Sensing 10 (6):859.
  • Wang, L., H. Liu, H. Su, and J. Wang. 2019. Bathymetry retrieval from optical images with spatially distributed support vector machines. GIScience & Remote Sensing 56 (3):323–37. https://doi.org/https://doi.org/10.1080/15481603.2018.1538620.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.