Heavy Metals Estimation in Coastal Areas Using Remote Sensing, Field Sampling and Classical and Robust Statistic
Sediments are an important source of accumulation of toxic contaminants within the aquatic environment. Bioassays are a powerful tool for the study of sediments in relation to their toxicity, but they can be expensive. This article presents a methodology to estimate the main physical property of intertidal sediments in coastal zones: heavy metals concentration. This study, which was developed in the Bay of Santander (Spain), applies classical and robust statistic to CASI-2 hyperspectral images to estimate heavy metals presence and ecotoxicity (TOC). Simultaneous fieldwork (radiometric and chemical sampling) allowed an appropriate atmospheric correction to CASI-2 images.
[1] Castillo, E., Pereda, R., de Luis, J.M., Medina, R. and Viguri, J. Sediment grain size estimation using airborne remote sensing, field sampling and robust statistic. Environmental Monitoring and Assessment, 181: 431-444, 2011.
[2] Salomons, W., and Brils, J. Contaminated sediments in European River Basins. European Sediment.2004.
[3] Alvarez-Guerra, M., San-Martín, D., and Viguri, J. Predicting toxicity from sediment chemistry using artificial neural networks: Screening tools for sustainable sediment management. In J.R. 11th Mediterranean Congress of Chemical Engineering, 2008.
[4] Del Valls, T. A., Andres, A., Belzunce, M. J., Buceta, J. L., Casado-Martínez, M. C., Castro, R., Riba, I., Viguri, J.R. and Blasco, J. Chemical and Ecotoxicological Guidelines for Managing Disposal of Dredged Material, 23, 819-828, 2004.
[5] Alvarez-Guerra, M., Viguri, J. R., Casado-Martínez, Carmen, M., & DelValls, A. T. Sediment quality assessment and dredged material management in Spain: Part II, analysis of action levels for dredged material management and application to the Bay of Cádiz. Integrated Environmental Assessment and Management, 3(4), 539–551, 2007.
[6] Alvarez-Guerra, M., Viguri, J. R., Casado-Martínez, M. C., & DelValls, T. A. Sediment quality assessment and dredged material management in Spain: Part I, application of sediment quality guidelines in the Bay of Santander. Integrated Environmental Assessment and Management, 3, 529–538, 2007.
[7] Campbell, N. A. The decorrelation stretch transformation. International Journal Remote Sensing, 10, 1939–1949. Canadian Council of Ministers of the Environment (2001).
[8] Van der Wal, D., & Herman, P. M. J. Regression based on synergy of optical, shortwave infrared and microwave remote sensing for monitoring the grain-size of intertidal sediments. Remote Sensing of Environment, 111, 89–106, 2007.
[9] Folving, S. The Danish Wadden Sea: Thematic mapping by means of remote sensing. Folia Geographica Danica, 15(2), 1–56, 1984.
[10] Bartholdy, J., & Folving, S. Sediment classification and surface type mapping in the Danish Wadden Sea by remote sensing. Netherlands Journal of Sea Research, 20, 337–345, 1986.
[11] Yachts, M. G., Jones, A. R.,
[12] McGrorty, S., & Goss-Custard, J. D. The uses of satellite imagery to determine the distribution of intertidal surface sediments of The Wash, England. Marine. Coastal and Shelf Science, 36, 333–344, 1993.
[13] Populus, J., Moreau, F., Coquelet, D., & Xavier, J. P. An assessment of environmental sensitivity to marine pollutions: Solutions with remote sensing and geographical information systems. International Journal of Remote Sensing, 16(1), 3–15., 1995.
[14] Populus, J., et al. Remote sensing as a tool for diagnostic of water quality in Indonesian seas. Ocean and Coastal Management, 27(3), 197–215, 1995.
[15] Ortega, J. Formación y Desarrollo de una Economía Moderna. Santander, España, 1986.
[16] ICANE, Cantabria. https://www.icane.es/.
[1] Castillo, E., Pereda, R., de Luis, J.M., Medina, R. and Viguri, J. Sediment grain size estimation using airborne remote sensing, field sampling and robust statistic. Environmental Monitoring and Assessment, 181: 431-444, 2011.
[2] Salomons, W., and Brils, J. Contaminated sediments in European River Basins. European Sediment.2004.
[3] Alvarez-Guerra, M., San-Martín, D., and Viguri, J. Predicting toxicity from sediment chemistry using artificial neural networks: Screening tools for sustainable sediment management. In J.R. 11th Mediterranean Congress of Chemical Engineering, 2008.
[4] Del Valls, T. A., Andres, A., Belzunce, M. J., Buceta, J. L., Casado-Martínez, M. C., Castro, R., Riba, I., Viguri, J.R. and Blasco, J. Chemical and Ecotoxicological Guidelines for Managing Disposal of Dredged Material, 23, 819-828, 2004.
[5] Alvarez-Guerra, M., Viguri, J. R., Casado-Martínez, Carmen, M., & DelValls, A. T. Sediment quality assessment and dredged material management in Spain: Part II, analysis of action levels for dredged material management and application to the Bay of Cádiz. Integrated Environmental Assessment and Management, 3(4), 539–551, 2007.
[6] Alvarez-Guerra, M., Viguri, J. R., Casado-Martínez, M. C., & DelValls, T. A. Sediment quality assessment and dredged material management in Spain: Part I, application of sediment quality guidelines in the Bay of Santander. Integrated Environmental Assessment and Management, 3, 529–538, 2007.
[7] Campbell, N. A. The decorrelation stretch transformation. International Journal Remote Sensing, 10, 1939–1949. Canadian Council of Ministers of the Environment (2001).
[8] Van der Wal, D., & Herman, P. M. J. Regression based on synergy of optical, shortwave infrared and microwave remote sensing for monitoring the grain-size of intertidal sediments. Remote Sensing of Environment, 111, 89–106, 2007.
[9] Folving, S. The Danish Wadden Sea: Thematic mapping by means of remote sensing. Folia Geographica Danica, 15(2), 1–56, 1984.
[10] Bartholdy, J., & Folving, S. Sediment classification and surface type mapping in the Danish Wadden Sea by remote sensing. Netherlands Journal of Sea Research, 20, 337–345, 1986.
[11] Yachts, M. G., Jones, A. R.,
[12] McGrorty, S., & Goss-Custard, J. D. The uses of satellite imagery to determine the distribution of intertidal surface sediments of The Wash, England. Marine. Coastal and Shelf Science, 36, 333–344, 1993.
[13] Populus, J., Moreau, F., Coquelet, D., & Xavier, J. P. An assessment of environmental sensitivity to marine pollutions: Solutions with remote sensing and geographical information systems. International Journal of Remote Sensing, 16(1), 3–15., 1995.
[14] Populus, J., et al. Remote sensing as a tool for diagnostic of water quality in Indonesian seas. Ocean and Coastal Management, 27(3), 197–215, 1995.
[15] Ortega, J. Formación y Desarrollo de una Economía Moderna. Santander, España, 1986.
[16] ICANE, Cantabria. https://www.icane.es/.
@article{"International Journal of Earth, Energy and Environmental Sciences:76380", author = "Elena Castillo-López and Raúl Pereda and Julio Manuel de Luis and Rubén Pérez and Felipe Piña", title = "Heavy Metals Estimation in Coastal Areas Using Remote Sensing, Field Sampling and Classical and Robust Statistic", abstract = "Sediments are an important source of accumulation of toxic contaminants within the aquatic environment. Bioassays are a powerful tool for the study of sediments in relation to their toxicity, but they can be expensive. This article presents a methodology to estimate the main physical property of intertidal sediments in coastal zones: heavy metals concentration. This study, which was developed in the Bay of Santander (Spain), applies classical and robust statistic to CASI-2 hyperspectral images to estimate heavy metals presence and ecotoxicity (TOC). Simultaneous fieldwork (radiometric and chemical sampling) allowed an appropriate atmospheric correction to CASI-2 images.
", keywords = "Remote sensing, intertidal sediment, airborne sensors, heavy metals, ecotoxicity, robust statistic, estimation.", volume = "11", number = "9", pages = "834-5", }
