Work

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

Year: 2025

Type: article

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.

Source: Journal of Agrometeorology

DOI: 10.54386/jam.v27i3.3067

Authors: MAYA BENOUMELDJADJ, IMEN GUECHI, AMDJED LAKEHAL, ABDELOUAHAB BOUCHAREB

Institutions: Larbi Ben M'hidi University of Oum El Bouaghi, University of Constantine 3

Language: English

Topic: Remote Sensing in Agriculture

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDGs: Zero hunger, Life on land

Open Access status: diamond

Funder: Direction Générale de la Recherche Scientifique et du Développement Technologique