Open AccessCartographie De La Salinite A La Surface Du Sol Dans Une Zone Du Prerif. Cas De La Region De L’ouergha
Author(s) -
Mohamed Sarwat,
Amal Markhi,
Hicham Elbelrhiti,
S. Mrabet
Publication year - 2016
Publication title -
european scientific journal
Language(s) - English
Resource type - Journals
eISSN - 1857-7881
pISSN - 1857-7431
DOI - 10.19044/esj.2016.v12n3p197
Subject(s) - soil salinity , environmental science , arid , salinity , vegetation (pathology) , thematic map , hydrology (agriculture) , soil water , normalized difference vegetation index , thematic mapper , geology , remote sensing , soil science , satellite imagery , climate change , geography , cartography , medicine , paleontology , oceanography , geotechnical engineering , pathology
The soil and groundwater salinization phenomenon in semi-arid to arid climate is considered as a real threat to safety and food quality. There are several factors that present soil salinity, some factors are purely climatic (temperature, rainfall levels, lack of drainage, composition of the rock) or human-induced (using salt water to irrigation). The aim of the work is to take stock of the surface condition at a specified scale of soil salinity by taking satellite images Landsat TM 2009 and ASTER 2003 with 15 m and 30 m of resolution respectively. This study allows us to detect the potential of remote sensing data to see a set of thematic maps that distinguish, evaluate and locate their extended saline soils on the surface of the study area. The methods of satellite image processing are for understanding of soil salinization process, assess their extensive and locate areas vulnerable to soil and water salinization. Evaluation of the results of applying this method on Landsat TM gave an accuracy of 87%. This study also allows us to highlight spectral indices that again demonstrate the natural origin, related to the lithology of groundwater salinity in the study area. These various indices largely exploit the difference spectral response of vegetation and soils in the red band (R) and near infrared band (PIR) which is related to the density of green vegetation the NDSI and NDVI which allows a very good distinction between areas of salinity and vegetation area.