NDLI: Empirical model for soil salinity mapping from SAR data

Content Provider	IEEE Xplore Digital Library
Author	Grissa, M. Abdelfattah, R. Mercier, G. Zribi, M. Chahbi, A. Lili-Chabaane, Z.
Copyright Year	2011
Description	Author affiliation: École Supérieure des Télécoms, Université de Carthage, Route de Raouèd, Km 3.5, 2083 El Ghazala - Tunisie (Grissa, M.; Abdelfattah, R.) \|\| Institut Telecom; Telecom Bretagne Technopole Brest-Iroise, CS 83818, 29238 Cedex 3 - France (Mercier, G.) \|\| Institut National Agronomique de Tunisie, 43 Avenue Charles Nicolle, 1082 - Tunisie (Lili-Chabaane, Z.) \|\| Institut de recherche pour le développement, IRD, B.P. 4345, impasse Chahrazède, 1004 El Menzah IV -Tunis, Tunisie (Zribi, M.; Chahbi, A.)
Abstract	Soil salinization is one of the most hazardous phenomenon accelerating the land degradation processes. Mapping and tracking soil salinity changes is fundamental for anticipating natural disaster, such as desertification, in arid and semi-arid regions. In this work, we establish an empirical model for soil salinity mapping based on a gaussian mixture and using field electrical conductivity (EC) measures. The developed model is tested on saline soil samples collected from the semi-arid region of Kairouan located in central Tunisia. It is based on statistical moments derived from multiband (HH and VV) intensity synthetic aperture radar (SAR) data of the Envisat satellite. The resulting salinity map is composed of three classes of salinity (Low, Medium and High) with respect to the EC measurements. The developed model is validated for low salinity distribution, whereas, it needs more samples to be generalized for medium and high soil salinity content.
Starting Page	1099
Ending Page	1102
File Size	1141252
Page Count	4
File Format	PDF
ISBN	9781457710032
ISSN	21537003
e-ISBN	9781457710056
DOI	10.1109/IGARSS.2011.6049388
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Soil Soil measurements Remote sensing Support vector machines Conductivity Synthetic aperture radar mapping SAR mixture model soil salinity electrical conductivity
Content Type	Text
Resource Type	Article

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