ORIGINAL RESEARCH
Monitoring Soil Salinity Changes, Comparison
of Different Maps and Indices Extracted
from Landsat Satellite Images
(Case Study: Atabieh, Khuzestan)
More details
Hide details
1
Department of Soil Sciences, Khuzestan Science and Research Branch, Islamic Azad University, Ahvaz, Iran
2
Department of Soil Sciences, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
3
Department of Geology, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
Submission date: 2020-02-18
Final revision date: 2020-05-29
Acceptance date: 2020-06-03
Online publication date: 2020-10-16
Publication date: 2021-01-20
Corresponding author
Ahad Nazarpour
Department of Geology, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran, Iran
Pol. J. Environ. Stud. 2021;30(2):1139-1154
KEYWORDS
TOPICS
ABSTRACT
Soil salinity is the dominant process in the degradation of arid and semi-arid soils, which in turn
reduces crop yields, increases erosion, and exacerbates desertification. In recent years, soil salinity has
affected much of the land in the Atabieh area located in the west of Khuzestan province in Iran. The
purpose of this study was thus to evaluate and map soil salinity changes in the region over 15 years
using Landsat 7 and 8 satellite images. To that end, the spectra of saline soils in the study area were
extracted from the satellite data, and after the initial pre-processing in EVNI software version 5.3, the
SI1, SI2, SI3, BI, NDVI, and NDSI indices were prepared. Using the supervised classification method,
the salinity map with four different classes was then plotted in Arc GIS version 10.2, and the changes in
saline soil area were investigated. Moreover, field surveys, surface soil sampling, soil EC measurement
and identification of available minerals were performed by X-ray diffraction (XRD) technique and
satellite images. Among the studied indices, the BI index with the highest correlation (0.71) was
considered as the best index, and NDVI with the correlation coefficient of 0.35 at the 95% confidence
level, was the best index for vegetation cover. Examination of changes in BI index by Landsat 7 images
showed that the non-saline land area decreased from 1023.54 ha in 2000 to 143.43 ha in 2010, while the
area with medium salinity increased by 14.57%. Besides, the salinity severity in the NDVI index had
a growth rate of 72.86%. In turn, XRD studies confirmed the presence of abundant evaporate minerals
(Halites, Calcite and Dolomite) corresponding to the values (real numbers) of salinity and mineralogical
maps obtained from the Landsat 8 images.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
CITATIONS (12):
1.
Baseline-Based Soil Salinity Index (BSSI): A Novel Remote Sensing Monitoring Method of Soil Salinization
Zhimei Zhang, Yanguo Fan, Aizhu Zhang, Zhijun Jiao
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2.
Predicting the spatial distribution of salt-affected soil using Sentinel-2 in coastal area of Demak Regency
Pronika Kricella, Projo Danoedoro, Sandy Budi Wibowo
IOP Conference Series: Earth and Environmental Science
3.
Spatial Distribution of Uranium and Thorium in the Soils of North Macedonia
Trajče Stafilov, Robert Šajn
Minerals
4.
Comparative study on pollution characteristics of heavy metals and polycyclic aromatic hydrocarbons in coking solid wastes
Kezhou Yan, Yangxu Guo, Kaizhi Yang, Mingmin Bao, Kun Jin, Dan Li, Yanxia Guo
Environmental Progress & Sustainable Energy
5.
Evaluation of Geogenic Enrichment Using Satellite, Geochemical, and Aeromagnetic Data in the Central Anti-Atlas (Morocco): Implications for Soil Enrichment
Mouna Id-Belqas, Said Boutaleb, Fatima Zahra Echogdali, Mustapha Ikirri, Hasna El Ayady, Mohamed Abioui
Earth
6.
Evaluation of the Use of the 12 Bands vs. NDVI from Sentinel-2 Images for Crop Identification
Adolfo Lozano-Tello, Guillermo Siesto, Marcos Fernández-Sellers, Andres Caballero-Mancera
Sensors
7.
Advances in soil salinity diagnosis for mangrove swamp rice production in Guinea Bissau, West Africa
Gabriel Garbanzo, Jesus Céspedes, Marina Temudo, Maria do Rosário Cameira, Paula Paredes, Tiago Ramos
Science of Remote Sensing
8.
Integration of Machine Learning and Remote Sensing to Evaluate the Effects of Soil Salinity, Nitrate, and Moisture on Crop Yields and Economic Returns in the Semi-Arid Region of Ethiopia
Gezimu Gelu Otoro, Katsuaki Komai
Agriculture
9.
Preparing soil maps in Mansourieh City-Diyala-Iraq using remote sensing and GIS
Mohamed Rabah Abdel-Qader, Raad Abdel Karim Hamdan, Ahmed Bahjat Khalaf
2ND INTERNATIONAL CONFERENCE ON APPLIED RESEARCH AND ENGINEERING (ICARAE2022)
10.
Soil degradation in andean watersheds: a case study using remote sensing
Fernando Oñate-Valdivieso, Arianna Oñate-Paladines, Ricardo Díaz
Frontiers in Earth Science
11.
Multi-hazard Vulnerability Assessment Through RS-GIS and AHP: A Geo-Spatial Study of Keleghai River Basin in India
Anirban Roy, Sarbendu Bikash Dhar
International Journal of Environmental Research
12.
Fusion level of satellite and UAV image data for soil salinity inversion in the coastal area of the Yellow River Delta
Ying Ma, Weiya Zhu, Zan Zhang, Hongyan Chen, Gengxing Zhao, Peng Liu
International Journal of Remote Sensing