Methodology for mapping soil salinity and halophyte cover using remote sensing data in Kerkennah, Tunisia

• Published in: Euro-Mediterranean journal for environmental integration 2021-09, Vol.6 (2), p.51, Article 51
• Main Authors: Kurbatova, Anna Igorevna, Bouchhima, Rim Attya, Grigorets, Elizaveta Andreevna, Tsymbarovich, Petr Romanovich, Ksibi, Mohamed
• Format: Article
• Language: English
• Subjects: Agricultural production; Agriculture; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Coasts; Decision trees; Earth and Environmental Science; Earth Sciences; Environmental Chemistry; Environmental Management; Environmental Science and Engineering; Fossil fuels; Groundwater; Halophytes; Islands; Land cover; Landsat; Mapping; Normalized difference vegetative index; Oceans; Original Paper; Population density; Regression models; Remote sensing; Salinity; Salinity effects; Salinization; Satellite imagery; Seawater; Soil characteristics; Soil degradation; Soil dynamics; Soil erosion; Soil mapping; Soil salinity; Spectral classification; Vegetation; Waste Management/Waste Technology; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 2365-6433; 2365-7448
• DOI: 10.1007/s41207-021-00257-4

A global increase in average annual temperatures above land and oceans has led to increasing sea levels, which has in turn caused flooding along the coastlines of the Kerkennah Islands, Sfax Governorate, Central-East Tunisia. Seawater actively seeps into the groundwater of these islands. This groundwater is used for crop irrigation, which has resulted in rapid salinization and degradation of the soil cover. Thus, the environment in the Kerkennah Islands is characterized by hypersaline soil that is densely populated by halophytes. The halophyte distribution can be studied by mapping and monitoring using a remote sensing approach. In this work, we focused on determining the normalized difference vegetation index, the automated water extraction index, and the salinity index (NDVI, AWEI, and SI, respectively) in images obtained by Landsat 8 in order to map the soil salinity and halophyte cover in this region using the QGIS, GDAL, and SAGA GIS software packages. To achieve accurate land cover mapping of the Kerkennah Islands, we devised a scheme for identifying halophytes according to a decision tree based on a spectral classification approach that exploits several spectral indices. A regression model was used to detect significant relationships between spectral indices and soil characteristics such as pH and EC. The dynamics of the soil salinity in the study region were estimated using SI 9 , as this approach is known to give accurate results. The results confirm the methodology for mapping salinity by halophytes.