Assessment of agricultural suitability through remote sensing: A Google Earth Engine and GIS-based approach for integrated urban planning

Authors

  • MAYA BENOUMELDJADJ Larbi Ben Mhidi University Oum El Bouaghi, Department of Architecture, Earth Sciences and Architecture Faculty, AUTES Research Laboratory, University of Constantine 3, Salah Boubnider, Constantine City, Algeria.
  • IMEN GUECHI Department of Architecture, Earth Sciences and Architecture Faculty, Laboratory of Evaluation of Quality in Architecture and In-built Environment. University of Larbi Ben M’hidi, Oum El Bouaghi, Algeria
  • AMDJED LAKEHAL Agronomy Engineer in Spa CEVITAL Company, Algiers, Algeria
  • ABDELOUAHAB BOUCHAREB AUTES Research Laboratory, University of Constantine 3, Salah Boubnider, Constantine City, Algeria

DOI:

https://doi.org/10.54386/jam.v27i3.3067

Keywords:

Google earth engine, Crop phenology, Analytic Hierarchy Process (AHP), Sentinel-2, Maize

Abstract

This study utilizes remote sensing (Sentinel-2 images via Google Earth Engine) to analyze maize growth in the El Meniaa region, Algeria, and assess agricultural land suitability. Using vegetation indices (NDVI, EVI, NDPI), growth cycles were characterized, showing a cyclical NDVI evolution (0.51 at the start, peaking at 0.71, and dropping to 0.06-0.09 at season end). A multi-criteria approach (AHP method) revealed that the topographic criterion (weight 0.413, notably aspect) is the most influential for agricultural suitability, followed by climatic data (weight 0.327, including temperature) and vegetation indices (weight 0.216, including NDVI). This research demonstrates the effectiveness of integrating remote sensing and multi-criteria analysis to accurately model crop phenology and map areas of high agricultural suitability, offering a transferable methodological framework for arid regions of Algeria.

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Published

01-09-2025

How to Cite

BENOUMELDJADJ, M., IMEN GUECHI, AMDJED LAKEHAL, & ABDELOUAHAB BOUCHAREB. (2025). Assessment of agricultural suitability through remote sensing: A Google Earth Engine and GIS-based approach for integrated urban planning. Journal of Agrometeorology, 27(3), 299–306. https://doi.org/10.54386/jam.v27i3.3067

Issue

Vol. 27 No. 3 (2025): September

Section

Research Paper

Categories

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Copyright (c) 2025 MAYA BENOUMELDJADJ, IMEN GUECHI, AMDJED LAKEHAL, ABDELOUAHAB BOUCHAREB

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