Evaluating ACOMP, FLAASH and QUAC on Worldview-3 for satellite derived bathymetry (SDB) in shallow water
Abstract
Bathymetry map is instrumental for monitoring marine ecosystem and supporting marine transportation. Optical satellite imagery has been widely utilised as an alternative method to derive bathymetry map in shallow water. Nonetheless, interactions between electromagnetic energy and Earth’s atmosphere causing the atmosphere effects pose a significant challenge in satellite-derived bathymetry (SDB) application. In this study, Worldview-3 imagery was used to obtain bathymetry map in shallow water. Three atmospheric correction models (ACOMP, FLAASH and QUAC) were employed to eliminate atmospheric effects on Worldview-3 imagery. Three simple band ratios involving coastal blue, blue, green and yellow band were used to test the performance of atmospheric correction models. ACOMP combined with blue and green band ratio efficaciously provided the best performance where it explained 77% of model values. Bathymetry map obtained from Worldview-3 was also validated using bathymetry data acquired from bathymetric survey over the study area. The estimated depths shared aggregable results with measured depths (depth < 20 m) with accuracy of 2.07 m. This study shows that robust atmospheric correction combined with suitable simple band combinations offered bathymetry map retrieval with relatively high accuracy.
Keyword : bathymetry, SDB, Worldview-3, ACOMP, FLAASH
How to Cite
Basith, A., & Prastyani, R. (2020). Evaluating ACOMP, FLAASH and QUAC on Worldview-3 for satellite derived bathymetry (SDB) in shallow water. Geodesy and Cartography, 46(3), 151-158. https://doi.org/10.3846/gac.2020.11426
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Bernstein, L. S., Jin, X., Gregor, B., & Adler-Golden, S. M. (2012b). Quick atmospheric correction code: algorithm description and recent upgrades. Optical Engineering, 51(11), 111719. https://doi.org/10.1117/1.oe.51.11.111719
Cooley, T., Anderson, G. P., Felde, G. W., Hoke, M. L., Ratkowski, A. J., Chetwynd, J. H., Gardner, J. A., Adler-Golden, S. M., Matthew, M. W., Berk, A., Bernstein, L. S., Acharya, P. K., Miller, D., & Lewis, P. (2002). FLAASH, a MODTRAN4based atmospheric correction algorithm, its applications and validation. International Geoscience and Remote Sensing Symposium (IGARSS), (pp. 1414–1418). IEEE. https://doi.org/10.1109/IGARSS.2002.1026134
Delegido, J., Verrelst, J., Alonso, L., & Moreno, J. (2011). Evaluation of sentinel-2 red-edge bands for empirical estimation of green LAI and chlorophyll content. Sensors, 11(7), 7063–7081. https://doi.org/10.3390/s110707063
Digital Globe. (2010). The Benefits of the eight spectral bands of Worldview-2 (pp. 1–12). https://dg-cms-uploads-production.s3.amazonaws.com/uploads/document/file/35/DG-8SPEC-TRAL-WP_0.pdf
Eugenio, F., Marcello, J., Martin, J., & Rodríguez-Esparragón, D. (2017). Benthic habitat mapping using multispectral highresolution imagery: Evaluation of shallow water atmospheric correction techniques. Sensors, 17(11), 2639. https://doi.org/10.3390/s17112639
Giardino, C., Brando, V. E., Gege, P., Pinnel, N., Hochberg, E., Knaeps, E., Reusen, I., Doerffer, R., Bresciani, M., Braga, F., Foerster, S., Champollion, N., & Dekker, A. (2019). Imaging spectrometry of Inland and Coastal waters: State of the art, achievements and perspectives. Surveys in Geophysics, 40(3), 401–429. https://doi.org/10.1007/s10712-018-9476-0
Harris Geospatial. (2009). Atmospheric correction module: QUAC and FLAASH User’ s guide. Atmospheric Correction Module: QUAC and FLAASH User’s Guide (pp. 20–21). https://www.harrisgeospatial.com/portals/0/pdfs/envi/Flaash_Module.pdf
Hell, B., Broman, B., Jakobsson, L., Jakobsson, M., Magnusson, Å., & Wiberg, P. (2012). The use of bathymetric data in society and science: A review from the Baltic Sea. Ambio, 41(2), 138–150. https://doi.org/10.1007/s13280-011-0192-y
Hernandez, W. J., & Armstrong, R. A. (2016). Deriving bathymetry from multispectral remote sensing data. Journal of Marine Science and Engineering, 4(1), 8. https://doi.org/10.3390/jmse4010008
Ilori, C. O., Pahlevan, N., & Knudby, A. (2019). Analyzing performances of different atmospheric correction techniques for Landsat 8: Application for coastal remote sensing. Remote Sensing, 11(4), 1–20. https://doi.org/10.3390/rs11040469
Jawak, S. D., Vadlamani, S. S., & Luis, A. J. (2015). A synoptic review on deriving bathymetry information using remote sensing technologies: Models, methods and comparisons. Advances in Remote Sensing, 4(2), 147–162. https://doi.org/10.4236/ars.2015.42013
Kotchenova, S. Y., & Vermote, E. F. (2007). Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part II. Homogeneous Lambertian and anisotropic surfaces. Applied Optics, 46(20), 4455–4464. https://doi.org/10.1364/AO.46.004455
Liang, S., Li, X., & Wang, J. (Eds.). (2012). Atmospheric correction of optical imagery. In Advanced Remote Sensing (p. 117). https://doi.org/10.1016/B978-0-12-385954-9.00005-8
Lyzenga, D. R. (1981). Remote sensing of bottom reflectance and water attenuation parameters in shallow water using aircraft and landsat data. International Journal of Remote Sensing, 2(1), 71–82. https://doi.org/10.1080/01431168108948342
Lyzenga, D. R., Malinas, N. P., & Tanis, F. J. (2006). Multispectral bathymetry using a simple physically based algorithm. IEEE Transactions on Geoscience and Remote Sensing, 44(8), 2251–2259. https://doi.org/10.1109/TGRS.2006.872909
Mavraeidopoulos, A., Pallikaris, A., & Oikonomou, E. (2018). Satellite Derived Bathymetry (SDB) and safety of navigation. The International Hydrographic Review, (17), 7–19.
McFeeters, S. K. (1996). The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7), 1425– 1432. https://doi.org/10.1080/01431169608948714
Mishra, D. R., Narumalani, S., Rundquist, D., Lawson, M., & Perk, R. (2007). Enhancing the detection and classification of coral reef and associated benthic habitats: A hyperspectral remote sensing approach. Journal of Geophysical Research: Oceans, 112(8), 1–18. https://doi.org/10.1029/2006JC003892
Nuha, M. U. (2019). Optimization of analytical parameters to derive bathymetry with high resolution satellite imagery on shallow water. Univeristas Gadjah Mada.
Parente, C., & Pepe, M. (2018). Bathymetry from worldview-3 satellite data using radiometric band ratio. Acta Polytechnica, 58(2), 109–117. https://doi.org/10.14311/AP.2018.58.0109
Philpot, W. D. (1989). Bathymetric mapping with passive multispectral imagery. Applied Optics, 28(8), 1569. https://doi.org/10.1364/ao.28.001569
Richter, R., & Schläpfer, D. (2002). Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/ topographic correction. International Journal of Remote Sensing, 23(13), 2631–2649. https://doi.org/10.1080/01431160110115834
Said, N. M., Mahmud, M. R., & Hasan, R. C. (2017). Satellitederived bathymetry: Accuracy assessment on depths. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII(October), 159–164. https://doi.org/10.5194/isprs-archives-XLII-4-W5-159-2017
Sánchez-Carnero, N., Ojeda-Zujar, J., Rodríguez-Pérez, D., & Marquez-Perez, J. (2014). Assessment of different models for bathymetry calculation using SPOT multispectral images in a high-turbidity area: The mouth of the Guadiana Estuary. International Journal of Remote Sensing, 35(2), 493–514. https://doi.org/10.1080/01431161.2013.871402
Shi, L., Mao, Z., & Wang, Z. (2018). Retrieval of total suspended matter concentrations from high resolution WorldView-2 imagery: A case study of inland rivers. IOP Conference Series: Earth and Environmental Science, 121(3), 032036. https://doi.org/10.1088/1755-1315/121/3/032036
Smith, M. J. (2015). A comparison of DG AComp, FLAASH and QUAC atmospheric compensation algorithms using WorldView-2 IMagery. https://digitalglobe-marketing.s3.amazonaws.com/files/blog/MichaelSmith_Masters_Report_ACOMP_Assessment.pdf
Stumpf, R. P., Holderied, K., & Sinclair, M. (2003). Determination of water depth with high-resolution satellite imagery over variable bottom types. Limnology and Oceanography, 48(1 II), 547–556. https://doi.org/10.4319/lo.2003.48.1_part_2.0547
Vanhellemont, Q., & Ruddick, K. (2016). Acolite for Sentinel-2: Aquatic applications of MSI imagery. ESA Special Publication SP-740, 9–13. http://odnature.naturalsciences.be/downloads/publications/2016_Vanhellemont_ESALP.pdf