Remote Sensing Technologies for Monitoring Argane Forest Stands: A Comprehensive Review

Mohamed Mouafik (), Abdelghani Chakhchar, Mounir Fouad and Ahmed El Aboudi
Additional contact information
Mohamed Mouafik: Botany, Mycology and Environment Laboratory, Department of Biology, Faculty of Sciences, Mohammed V University, Rabat 10050, Morocco
Abdelghani Chakhchar: École Normale Supérieure Marrakech, Cadi Ayyad University, Marrakech 40000, Morocco
Mounir Fouad: National Forestry School of Engineers, Sale 11000, Morocco
Ahmed El Aboudi: Botany, Mycology and Environment Laboratory, Department of Biology, Faculty of Sciences, Mohammed V University, Rabat 10050, Morocco

Geographies, 2024, vol. 4, issue 3, 1-21

Abstract: This comprehensive review explores the ecological significance of the Argane stands ( Argania spinosa ) in southwestern Morocco and the pivotal role of remote sensing technology in monitoring forest ecosystems. Argane stands, known for their resilience in semi-arid and arid conditions, serve as a keystone species, preventing soil erosion, maintaining ecological balance, and providing habitat and sustenance to diverse wildlife species. Additionally, they produce an extremely valuable Argane oil, offering economic opportunities and cultural significance to local communities. Remote sensing tools, including satellite imagery, LiDAR, drones, radar, and GPS precision, have revolutionized our capacity to remotely gather data on forest health, cover, and responses to environmental changes. These technologies provide precise insights into canopy structure, density, and individual tree health, enabling assessments of Argane stand populations and detection of abiotic stresses, biodiversity, and conservation evaluations. Furthermore, remote sensing plays a crucial role in monitoring vegetation health, productivity, and drought stress, contributing to sustainable land management practices. This review underscores the transformative impact of remote sensing in safeguarding forest ecosystems, particularly the Argane forest stands, and highlights its potential for continued advancements in ecological research and conservation efforts.

Keywords: Argania spinosa; remote sensing; satellite imagery; forest monitoring; drone; vegetation health; drought stress (search for similar items in EconPapers)
JEL-codes: Q1 Q15 Q5 Q53 Q54 Q56 Q57 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2673-7086/4/3/24/pdf (application/pdf)
https://www.mdpi.com/2673-7086/4/3/24/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jgeogr:v:4:y:2024:i:3:p:24-461:d:1443343

Access Statistics for this article

Geographies is currently edited by Ms. Fannie Xu

More articles in Geographies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().