Use of Geographic Information Systems and Remote Sensing for Crop Analysis in a Saharan Environment: A Case Study of El Oued Province
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جامعة الوادي university of eloued
Abstract
The Oued Souf region in southeastern Algeria has experienced significant agricultural
expansion relying on center pivot irrigation, leading to severe groundwater depletion (a 30 m
drop in the water table) and increased soil salinization. Although the Oued Righ region no
longer administratively belongs to Oued Souf, it remains one of southern Algeria’s most
important agricultural areas due to its oasis system and date palm groves. This study aimed to
employ remote sensing and GIS techniques to monitor barley as a strategic crop and to
analyze the spatiotemporal dynamics of vegetation cover over the period 2016–2026, while
testing the reliability of the Normalized Difference Vegetation Index (NDVI) for agricultural
decision support.
The methodology integrated weekly field measurements of barley plant height from an
experimental plot in Debila (February–May 2026) with NDVI values derived from Sentinel-2
imagery, together with a long-term time-series analysis of vegetation cover using seven
spectral classes.
The results showed a strong relationship between NDVI and barley vertical growth (R²
= 0.905). NDVI peaked at 0.67 in week nine, coinciding with maximum vegetative
development, then declined as physiological maturity began. At the regional level, the 10-year
analysis revealed that drought periods (2017–2025) caused a contraction of higher NDVI
classes (>0.4) and an expansion of lower classes, while the exceptionally wet year 2026
showed marked recovery. The moderate vegetation class (0.2–0.4) peaked in 2021 with 6.15
million pixels, and the dense vegetation class (0.4–0.6) peaked in 2025 with 2.05 million
pixels.
The study concludes that remote sensing and Geographic Information System GIS
constitute an accurate and reliable alternative to costly field surveys. It recommends their
adoption for agricultural and environmental monitoring, and the use of class-based frequency
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Plant Production
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master ,2026. production végétale . Faculte des Sciences de La Nature et de La Vie . Université d'El-Oued