Eurasian Journal of Soil Science

Volume 3, Issue 2, Oct 2014, Pages 82 - 88
DOI: 10.18393/ejss.84540
Stable URL: http://ejss.fess.org/10.18393/ejss.84540
Copyright © 2014 The authors and Federation of Eurasian Soil Science Societies



Mapping soil salinity in irrigated land using optical remote sensing data

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Lhissou ,R., El-Harti ,A., Chokmani,K., 2014. Mapping soil salinity in irrigated land using optical remote sensing data. Eurasian J Soil Sci 3(2):82 - 88. DOI : 10.18393/ejss.84540
Lhissou ,R.El-Harti ,A.,,& Chokmani,K. Mapping soil salinity in irrigated land using optical remote sensing data Eurasian Journal of Soil Science, DOI : 10.18393/ejss.84540
Lhissou ,R.El-Harti ,A.,, and ,Chokmani,K."Mapping soil salinity in irrigated land using optical remote sensing data" Eurasian Journal of Soil Science, DOI : 10.18393/ejss.84540
Lhissou ,R.El-Harti ,A.,, and ,Chokmani,K. "Mapping soil salinity in irrigated land using optical remote sensing data" Eurasian Journal of Soil Science, DOI : 10.18393/ejss.84540
R,Lhissou .A,El-Harti .K,Chokmani "Mapping soil salinity in irrigated land using optical remote sensing data" Eurasian J. Soil Sci, vol., no., pp., DOI : 10.18393/ejss.84540
Lhissou ,Rachid ;El-Harti ,Abderrazak ;Chokmani,Karem Mapping soil salinity in irrigated land using optical remote sensing data. Eurasian Journal of Soil Science,. DOI : 10.18393/ejss.84540

How to cite

Lhissou , R., El-Harti , A., Chokmani, K., 2014. Mapping soil salinity in irrigated land using optical remote sensing data. Eurasian J. Soil Sci. 3(2): 82 - 88. DOI : 10.18393/ejss.84540

Author information

Rachid Lhissou , Team of Remote Sensing and GIS Applied to Geosciences and Environment, Faculty of Sciences and Techniques, Beni Mellal, Morocco
Abderrazak El-Harti , Team of Remote Sensing and GIS Applied to Geosciences and Environment, Faculty of Sciences and Techniques, Beni Mellal, Morocco
Karem Chokmani , Institut National de la Recherche Scientifique, Centre- Eau, Terre & Environnement 490, Canada

Publication information

Issue published online: 30 Oct 2014
Article first published online : 27 Oct 2014
Manuscript Accepted : 26 Oct 2014
Manuscript Received: 01 May 2014
DOI: 10.18393/ejss.84540
Stable URL: http://ejss.fesss.org/10.18393/ejss.84540

Abstract

Soil salinity caused by natural or human-induced processes is certainly a severe environmental problem that already affects 400 million hectares and seriously threatens an equivalent surface. Salinization causes negative effects on the ground; it affects agricultural production, infrastructure, water resources and biodiversity. In semi-arid and arid areas, 21% of irrigated lands suffer from waterlogging, salinity and/or sodicity that reduce their yields. 77 million hectares are saline soils induced by human activity, including 58% in the irrigated areas. In the irrigated perimeter of Tadla plain (central Morocco), the increased use of saline groundwater and surface water, coupled with agricultural intensification leads to the deterioration of soil quality. Experimental methods for monitoring soil salinity by direct measurements in situ are very demanding of time and resources, and also very limited in terms of spatial coverage. Several studies have described the usefulness of remote sensing for mapping salinity by its synoptic coverage and the sensitivity of the electromagnetic signal to surface soil parameters. In this study, we used an image of the TM Landsat sensor and field measurements of electrical conductivity (EC), the correlation between the image data and field measurements allowed us to develop a semi-empirical model allowing the mapping of soil salinity in the irrigated perimeter of Tadla plain. The validation of this model by the ground truth provides a correlation coefficient r² = 0.90. Map obtained from this model allows the identification of different salinization classes in the study area.

Keywords

Soil salinity, Electric conductivity, spectral indices, principle component analysis

Corresponding author

References

Abbas, A., Khan, S., Hussain, N., Hanjra, M.A., Akbar, S., 2013. Characterizing soil salinity in irrigated agriculture using a remote sensing approach. Physics and Chemistry of Earth, Parts A/B/C, 55-57, 43-52.

Al-khaier, F., 2003. Soil Salinity detection using satellite Remote Sensing. International Institute for Geo-Information Science and Earth Observation, Enschede, The Netherlands. 61 p.

Bachaoui, B., Bachaoui, E., Maimouni, S., Lhissou, R., El Harti, A., El Ghmari, A., 2014. The use of spectral and geomorphometric data for water erosion mapping in El Ksiba region in the central High Atlas Mountains of Morocco. Applied Geomatics 6(3), 159-169.

Bannari, A., Guedon, A.M., El-Harti, A., Cherkaoui, F.Z., El-Ghmari, A., 2008. Characterization of slightly and moderately saline and sodic soils in irrigated agricultural land using simulated data of advanced land imaging (EO-1) sensor. Communications in Soil Science and Plant Analysis 39 (19), 2795–2811

Bonn, F., Rochon, G. 1992. Précis de télédétection. Vol. 1 : Principes et méthodes. Presses de l’Université du Québec et l’AUPELF, Sainte-Foy et Montréal, 485 p.

Burgess, D. W., Lewis, P., Muller, J. P., 1995. Topographic Effects in AVHRR NDVI Data. Remote Sensing of Environment, 45, 223-232.

Caloz, R., Collet, C., 2001. Traitements numériques d'images de télédétection. Presses de l'université du Québec/AUPELF, Québec, 380p.

Chen, H. S., 1997.Remote Sensing Calibration Systems: An Introduction. DEEPAK.

Douaoui, A.K., Herve´ , N., Walter, C., 2006. Detecting salinity hazards within a semiarid context by means of combining soil and remotesensing data. Geodema, 134, 217–230.

FAO, 2002. Le The salt of the earth: hazardous for food production. Word Food Summit. Five years later. 10-13 June 2012. Available at: http://www.fao.org/worldfoodsummit/english/newsroom/focus/focus1.htm

Farifteh, J., Farshad, A., George, R.J., 2006. Assessing salt-affected soils using remote sensing, solute modelling, and geophysics. Geoderma 130 (3-4), 191-206.

Frans E.P., Schowengerdt, R.A. 1997. Spatial-Spectral Unmixing Using the sensor PSF, Proc. SPIE, Vol. 3118, Imaging Spectrometry III, San Diego,CA.

IDNP, 2003. Indo-Dutch Network Project: A Methodology for Identification of Waterlogging and Soil Salinity Conditions Using Remote Sensing. Central Soil Salinity Research Institute, Karnal, India, 78 pages.

Jenson, J., 2007. Remote Sensing of the environnement, an earth resource perspective. 2ème edition. 591 p.

Khan, N.M., Rastoskuev, V.V., Shalina E.V., Sato, Y., 2001. Mapping salt affected soils using remote sensing indicators: A simple approach with the use of GIS IDRISI. In: Proceedings of the 22nd Asian Conference on Remote Sensing. 5 - 9 November 2001, Singapore.

Metternichet, G.I., Zinck, J.A., 2003. Remote sensing of soil salinity: potential and constraints. Remote Sensing of Environment 85, 1-20.

Mougenot, B., Pouget, M., 1993. Remote sensing of salt-affected soil. Remote Sensing Reviews 7, 241-259.

Rhoades, J.D., Corwin, D.L., 1990. Soil electrical conductivity: effects of soil properties and application to soil salinity appraisal. Communication in Soil Science and Plant Analyses 21: 836-860.

Richards, J. A., 1993. Remote Sensing Digital Image Analysis (2nd Edition). Springer-Verlag, New York, 340 p.

Richards, L.A., 1954. Diagnosis and improvements of saline and alkali soils. U.S. Salinity Laboratory. US Dept. of Agronmy Handbook 60, 160 p.

Staenz, K., Secker, J., Gao, B.C., Davis, C., Nadeau, C., 2002. Radiative transfer codes applied to hyperspectral data for theretrieval of surface reflectance. ISPRS Journal of Photogrammetric Engineering and Remote Sensing, 57(3), 194-203.

Abstract

Soil salinity caused by natural or human-induced processes is certainly a severe environmental problem that already affects 400 million hectares and seriously threatens an equivalent surface. Salinization causes negative effects on the ground; it affects agricultural production, infrastructure, water resources and biodiversity. In semi-arid and arid areas, 21% of irrigated lands suffer from waterlogging, salinity and/or sodicity that reduce their yields. 77 million hectares are saline soils induced by human activity, including 58% in the irrigated areas. In the irrigated perimeter of Tadla plain (central Morocco), the increased use of saline groundwater and surface water, coupled with agricultural intensification leads to the deterioration of soil quality. Experimental methods for monitoring soil salinity by direct measurements in situ are very demanding of time and resources, and also very limited in terms of spatial coverage. Several studies have described the usefulness of remote sensing for mapping salinity by its synoptic coverage and the sensitivity of the electromagnetic signal to surface soil parameters. In this study, we used an image of the TM Landsat sensor and field measurements of electrical conductivity (EC), the correlation between the image data and field measurements allowed us to develop a semi-empirical model allowing the mapping of soil salinity in the irrigated perimeter of Tadla plain. The validation of this model by the ground truth provides a correlation coefficient r² = 0.90. Map obtained from this model allows the identification of different salinization classes in the study area.

Keywords: Soil salinity, Electric conductivity, spectral indices, principle component analysis

References

Abbas, A., Khan, S., Hussain, N., Hanjra, M.A., Akbar, S., 2013. Characterizing soil salinity in irrigated agriculture using a remote sensing approach. Physics and Chemistry of Earth, Parts A/B/C, 55-57, 43-52.

Al-khaier, F., 2003. Soil Salinity detection using satellite Remote Sensing. International Institute for Geo-Information Science and Earth Observation, Enschede, The Netherlands. 61 p.

Bachaoui, B., Bachaoui, E., Maimouni, S., Lhissou, R., El Harti, A., El Ghmari, A., 2014. The use of spectral and geomorphometric data for water erosion mapping in El Ksiba region in the central High Atlas Mountains of Morocco. Applied Geomatics 6(3), 159-169.

Bannari, A., Guedon, A.M., El-Harti, A., Cherkaoui, F.Z., El-Ghmari, A., 2008. Characterization of slightly and moderately saline and sodic soils in irrigated agricultural land using simulated data of advanced land imaging (EO-1) sensor. Communications in Soil Science and Plant Analysis 39 (19), 2795–2811

Bonn, F., Rochon, G. 1992. Précis de télédétection. Vol. 1 : Principes et méthodes. Presses de l’Université du Québec et l’AUPELF, Sainte-Foy et Montréal, 485 p.

Burgess, D. W., Lewis, P., Muller, J. P., 1995. Topographic Effects in AVHRR NDVI Data. Remote Sensing of Environment, 45, 223-232.

Caloz, R., Collet, C., 2001. Traitements numériques d'images de télédétection. Presses de l'université du Québec/AUPELF, Québec, 380p.

Chen, H. S., 1997.Remote Sensing Calibration Systems: An Introduction. DEEPAK.

Douaoui, A.K., Herve´ , N., Walter, C., 2006. Detecting salinity hazards within a semiarid context by means of combining soil and remotesensing data. Geodema, 134, 217–230.

FAO, 2002. Le The salt of the earth: hazardous for food production. Word Food Summit. Five years later. 10-13 June 2012. Available at: http://www.fao.org/worldfoodsummit/english/newsroom/focus/focus1.htm

Farifteh, J., Farshad, A., George, R.J., 2006. Assessing salt-affected soils using remote sensing, solute modelling, and geophysics. Geoderma 130 (3-4), 191-206.

Frans E.P., Schowengerdt, R.A. 1997. Spatial-Spectral Unmixing Using the sensor PSF, Proc. SPIE, Vol. 3118, Imaging Spectrometry III, San Diego,CA.

IDNP, 2003. Indo-Dutch Network Project: A Methodology for Identification of Waterlogging and Soil Salinity Conditions Using Remote Sensing. Central Soil Salinity Research Institute, Karnal, India, 78 pages.

Jenson, J., 2007. Remote Sensing of the environnement, an earth resource perspective. 2ème edition. 591 p.

Khan, N.M., Rastoskuev, V.V., Shalina E.V., Sato, Y., 2001. Mapping salt affected soils using remote sensing indicators: A simple approach with the use of GIS IDRISI. In: Proceedings of the 22nd Asian Conference on Remote Sensing. 5 - 9 November 2001, Singapore.

Metternichet, G.I., Zinck, J.A., 2003. Remote sensing of soil salinity: potential and constraints. Remote Sensing of Environment 85, 1-20.

Mougenot, B., Pouget, M., 1993. Remote sensing of salt-affected soil. Remote Sensing Reviews 7, 241-259.

Rhoades, J.D., Corwin, D.L., 1990. Soil electrical conductivity: effects of soil properties and application to soil salinity appraisal. Communication in Soil Science and Plant Analyses 21: 836-860.

Richards, J. A., 1993. Remote Sensing Digital Image Analysis (2nd Edition). Springer-Verlag, New York, 340 p.

Richards, L.A., 1954. Diagnosis and improvements of saline and alkali soils. U.S. Salinity Laboratory. US Dept. of Agronmy Handbook 60, 160 p.

Staenz, K., Secker, J., Gao, B.C., Davis, C., Nadeau, C., 2002. Radiative transfer codes applied to hyperspectral data for theretrieval of surface reflectance. ISPRS Journal of Photogrammetric Engineering and Remote Sensing, 57(3), 194-203.



Eurasian Journal of Soil Science