Journal of Natural Environment

Journal of Natural Environment

Comparative analysis of vegetation indices (NDVI, SAVI, NDPI) for assessing Phenological events of Mangrove forests in Southern Iran

Document Type : Research Paper

Authors
Azin Balouchestan asl 1
Hossein Moradi 2
Sedighe Abdollahi 1
Zahra Najjar Khodabakhsh 3
Saeid Pourmanafi 1
1 Department of Natural Resources, Isfahan University of Technology, Isfahan, Iran.
2 Department of Environment, Faculty of Natural Resources, University College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran.
3 School of Forest Resources, University of Maine, 5755 Nutting Hall, Orono, ME 04469-5755, USA.
10.22059/jne.2026.415057.2917
Abstract
Mangrove forests, as one of the most vital coastal ecosystems, play a crucial role in the environmental sustainability of Iran’s southern regions. Investigating the phenological patterns of these ecosystems, particularly through remote sensing, enables continuous and efficient monitoring of vegetation health and dynamics. Vegetation indices are primary tools for extracting phenological information; however, their relative accuracy and efficiency in marginal and complex environments like the mangroves of southern Iran require rigorous comparative evaluation. This study aimed to compare the performance of three indices: NDVI, SAVI, and NDPI, in assessing the phenological components of mangrove forests in southern Iran. To do this, changes in three main phenological events—start of grow season (SOS), end of grow season (EOS), and length of grow season (LOS)—were extracted and analyzed over a 30-year period (1993–2023) across seven selected mangrove sites. A mixed-linear model in R software was employed to evaluate temporal trends of these events and to compare differences arising from various indices and regions. The results indicated that all three indices exhibited an upward trend over the past 30 years, suggesting a gradual increase in mangrove greenness and canopy density, and that the type of vegetation index did not have a significant impact (P>0.05) on the phenological components. These findings provide a framework for more effective monitoring and management of mangrove ecosystems in Iran’s coastal areas, facilitating the identification of regions with specific conservation or management needs.
Keywords
;">Avicennia marina, ;">Mangrove phenology cycle, Mixed-linear model, ;">Remote sensing, ;">Vegetation indices.
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Journal of Natural Environment
Volume 79, Issue 2
Summer 2026
Pages 407-425