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https://hdl.handle.net/1959.11/15984
Title: | Assessing soil salinity using soil salinity and vegetation indices derived from IKONOS high-spatial resolution imageries: Applications in a date palm dominated region | Contributor(s): | Allbed, Amal (author); Kumar, Lalit (author) ; Aldakheel, Yousef Y (author) | Publication Date: | 2014 | DOI: | 10.1016/j.geoderma.2014.03.025 | Handle Link: | https://hdl.handle.net/1959.11/15984 | Abstract: | In saline soils, the spectral reflectance of either salt features at the surface or of vegetation that was negatively affected by salt varies with different salinity levels. Thus, several indices for vegetation and soil salinity have been developed. This study was conducted to assess the soil salinity levels in the Al-Hassa Oasis, which is dominated by date palm vegetation, in the eastern province of Saudi Arabia. Ground and remote sensing data were used to determine if any existing vegetation and soil salinity indices could be used to assess the soil salinity of communities vegetated with date palm. A systematic regular grid-sampling approach was used to collect a total of 149 composite soil samples from the study area. Thirteen broadband indices, which encompassed vegetation and soil salinity indices, were extracted from IKONOS satellite images. The predictive power of these indices for soil salinity was examined. The study area was dominated by areas of high salinity. Among the investigated indices, the Soil-Adjusted Vegetation Index (SAVI), Normalized Differential Salinity Index (NDSI) and Salinity Index (SI-T) yielded the best results for assessing the soil salinity of cultivated lands with dense and uniform vegetation. In contrast, the NDSI and SI-T exhibited the highest significant correlation with salinity for less densely vegetated lands and bare soils. Generally, the soil salinity in the areas that were dominated by date palms was successfully assessed by broadband vegetation and soil salinity indices that were extracted from the IKONOS satellite images. | Publication Type: | Journal Article | Source of Publication: | Geoderma, v.230-231, p. 1-8 | Publisher: | Elsevier BV | Place of Publication: | Netherlands | ISSN: | 1872-6259 0016-7061 |
Fields of Research (FoR) 2008: | 050206 Environmental Monitoring 090905 Photogrammetry and Remote Sensing 090903 Geospatial Information Systems |
Fields of Research (FoR) 2020: | 410599 Pollution and contamination not elsewhere classified 401304 Photogrammetry and remote sensing 401302 Geospatial information systems and geospatial data modelling |
Socio-Economic Objective (SEO) 2008: | 960904 Farmland, Arable Cropland and Permanent Cropland Land Management 960504 Ecosystem Assessment and Management of Farmland, Arable Cropland and Permanent Cropland Environments 960510 Ecosystem Assessment and Management of Sparseland, Permanent Grassland and Arid Zone Environments |
Socio-Economic Objective (SEO) 2020: | 180607 Terrestrial erosion 180603 Evaluation, allocation, and impacts of land use 180601 Assessment and management of terrestrial ecosystems |
Peer Reviewed: | Yes | HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
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Appears in Collections: | Journal Article |
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