Integrating Vegetation Indices and PRISMA Hyperspectral Imagery for Forest Risk Assessment in Northern Iran
Abstract
In recent years, the forests of northern Iran have experienced increasing ecological stress due to climate change and human activities, highlighting the need for effective forest health monitoring. This study evaluates the applicability of PRISMA hyperspectral imagery for assessing forest risk in this region during 2024. Leveraging the sensor’s high spectral resolution, several vegetation indices were extracted and grouped into three categories: greenness, pigment, and canopy water/light use efficiency. These indices were combined and classified into five risk levels using multi-index integration and weighting techniques in a GIS environment. Validation of the classification results revealed a high level of accuracy, with an overall accuracy of 93.73% and a Kappa coefficient of 0.9157. The combined indices outperformed individual indices in identifying vegetation stress patterns. Results indicated that the central and western forest areas are in healthy condition, while the eastern, northeastern, and southeastern regions exhibit notable stress, likely linked to water deficit or pest and disease pressures. The findings underscore the effectiveness of integrating hyperspectral data and vegetation indices for forest risk assessment and offer valuable insights for improving spatiotemporal forest health monitoring strategies.
Keywords
References
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Details
Primary Language
English
Subjects
Photogrammetry and Remote Sensing
Journal Section
Research Article
Authors
Early Pub Date
August 25, 2025
Publication Date
October 1, 2025
Submission Date
February 15, 2025
Acceptance Date
July 18, 2025
Published in Issue
Year 2026 Volume: 11 Number: 1
APA
Ebadi, R., Karımzadeh, S., Valizadeh Kamran, K., & Mahdavifard, M. (2025). Integrating Vegetation Indices and PRISMA Hyperspectral Imagery for Forest Risk Assessment in Northern Iran. International Journal of Engineering and Geosciences, 11(1), 163-182. https://doi.org/10.26833/ijeg.1640355
AMA
1.Ebadi R, Karımzadeh S, Valizadeh Kamran K, Mahdavifard M. Integrating Vegetation Indices and PRISMA Hyperspectral Imagery for Forest Risk Assessment in Northern Iran. IJEG. 2025;11(1):163-182. doi:10.26833/ijeg.1640355
Chicago
Ebadi, Roghayyeh, Sadra Karımzadeh, Khalil Valizadeh Kamran, and Mostafa Mahdavifard. 2025. “Integrating Vegetation Indices and PRISMA Hyperspectral Imagery for Forest Risk Assessment in Northern Iran”. International Journal of Engineering and Geosciences 11 (1): 163-82. https://doi.org/10.26833/ijeg.1640355.
EndNote
Ebadi R, Karımzadeh S, Valizadeh Kamran K, Mahdavifard M (October 1, 2025) Integrating Vegetation Indices and PRISMA Hyperspectral Imagery for Forest Risk Assessment in Northern Iran. International Journal of Engineering and Geosciences 11 1 163–182.
IEEE
[1]R. Ebadi, S. Karımzadeh, K. Valizadeh Kamran, and M. Mahdavifard, “Integrating Vegetation Indices and PRISMA Hyperspectral Imagery for Forest Risk Assessment in Northern Iran”, IJEG, vol. 11, no. 1, pp. 163–182, Oct. 2025, doi: 10.26833/ijeg.1640355.
ISNAD
Ebadi, Roghayyeh - Karımzadeh, Sadra - Valizadeh Kamran, Khalil - Mahdavifard, Mostafa. “Integrating Vegetation Indices and PRISMA Hyperspectral Imagery for Forest Risk Assessment in Northern Iran”. International Journal of Engineering and Geosciences 11/1 (October 1, 2025): 163-182. https://doi.org/10.26833/ijeg.1640355.
JAMA
1.Ebadi R, Karımzadeh S, Valizadeh Kamran K, Mahdavifard M. Integrating Vegetation Indices and PRISMA Hyperspectral Imagery for Forest Risk Assessment in Northern Iran. IJEG. 2025;11:163–182.
MLA
Ebadi, Roghayyeh, et al. “Integrating Vegetation Indices and PRISMA Hyperspectral Imagery for Forest Risk Assessment in Northern Iran”. International Journal of Engineering and Geosciences, vol. 11, no. 1, Oct. 2025, pp. 163-82, doi:10.26833/ijeg.1640355.
Vancouver
1.Roghayyeh Ebadi, Sadra Karımzadeh, Khalil Valizadeh Kamran, Mostafa Mahdavifard. Integrating Vegetation Indices and PRISMA Hyperspectral Imagery for Forest Risk Assessment in Northern Iran. IJEG. 2025 Oct. 1;11(1):163-82. doi:10.26833/ijeg.1640355