TY - JOUR
T1 - Mapping soil salinity in arid and semi-arid regions using Landsat 8 OLI satellite data
AU - Abuelgasim, Abdelgadir
AU - Ammad, Rubab
N1 - Funding Information:
This work was funded by a grant from the Research and Sponsored Projects Office of the United Arab Emirates University under startup grant number 31H106 -Research Start-up (4) 2015.
Publisher Copyright:
© 2018 The Authors
PY - 2019/1
Y1 - 2019/1
N2 - Soil salinity, whether natural or human induced, is a major geo-hazard in arid and semi-arid landscapes. In agricultural lands, it negatively affects plant growth, crop yields, whereas in semi-arid and arid non-agricultural areas it affects urban structures due to subsidence, corrosion and ground water quality, leading to further soil erosion and land degradation. Accurately mapping soil salinity through remote sensing techniques has been an active area of research in the past few decades particularly for agricultural lands. Most of this research has focused on the utilization and development of salinity indices for properly mapping and identifying saline agricultural soils. This research develops a soil salinity index and model using Landsat 8 OLI image data from the near infra-red and shortwave infra-red spectral information with emphasis on soil salinity mapping and assessment in non-agricultural desert arid and semi-arid surfaces. The developed index when integrated into a semi-empirical model outperformed in its soil salinity mapping overall accuracy (60%) in comparison to other salinity indices (~50%). The newly developed index further outperformed other indices in its accuracy in mapping and identifying high saline soils (67%) and excessively high saline soils (90%).
AB - Soil salinity, whether natural or human induced, is a major geo-hazard in arid and semi-arid landscapes. In agricultural lands, it negatively affects plant growth, crop yields, whereas in semi-arid and arid non-agricultural areas it affects urban structures due to subsidence, corrosion and ground water quality, leading to further soil erosion and land degradation. Accurately mapping soil salinity through remote sensing techniques has been an active area of research in the past few decades particularly for agricultural lands. Most of this research has focused on the utilization and development of salinity indices for properly mapping and identifying saline agricultural soils. This research develops a soil salinity index and model using Landsat 8 OLI image data from the near infra-red and shortwave infra-red spectral information with emphasis on soil salinity mapping and assessment in non-agricultural desert arid and semi-arid surfaces. The developed index when integrated into a semi-empirical model outperformed in its soil salinity mapping overall accuracy (60%) in comparison to other salinity indices (~50%). The newly developed index further outperformed other indices in its accuracy in mapping and identifying high saline soils (67%) and excessively high saline soils (90%).
KW - Arid
KW - Landsat 8 OLI
KW - Semi-arid
KW - Soil salinity
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U2 - 10.1016/j.rsase.2018.12.010
DO - 10.1016/j.rsase.2018.12.010
M3 - Article
AN - SCOPUS:85059510989
SN - 2352-9385
VL - 13
SP - 415
EP - 425
JO - Remote Sensing Applications: Society and Environment
JF - Remote Sensing Applications: Society and Environment
ER -