Maple Species Identification Based On Hyperspectral Imaging Time Series

Pavel Dmitriev; Boris Kozlovsky; Anastasiya Dmitrieva

doi:10.33904/ejfe.1516227

EN

Maple Species Identification Based On Hyperspectral Imaging Time Series

Abstract

The aim of the study was to identify Acer campestre L., A. negundo L., and A. saccharinum L. from time-series hyperspectral data. Maple leaves were subjected to Hyperspectral Imaging (HSI) in laboratory conditions every 7-10 days for two years. Random forest (RF), correlation analysis, principal component analysis (PCA), PCA-RF and Gini index were used to determine significant spectral bands for species classification. This paper demonstrates that maple species can be accurately classified during specific periods of the growing season with a success rate exceeding 90%. These periods can vary from year to year. Research has demonstrated that using seven spectral bands is adequate for classifying maple species, while using twenty spectral bands can maximize accuracy. The repeatability of the obtained results confirms their representativeness over time and when using different methods of data processing.

Keywords

Spectral bands , Acer , photosynthetic pigments , remote sensing , random forest

References

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Details

Primary Language

English

Subjects

Photogrammetry and Remote Sensing

Journal Section

Research Article

Authors

Pavel Dmitriev ^*
0000-0001-5740-5146
Russian Federation

Boris Kozlovsky
0000-0001-9410-1854
Russian Federation

Anastasiya Dmitrieva
0000-0002-7419-793X
Russian Federation

Early Pub Date

August 26, 2025

Publication Date

December 25, 2025

Submission Date

July 14, 2024

Acceptance Date

December 19, 2024

Published in Issue

Year 2025 Volume: 11 Number: 2

DOI

https://doi.org/10.33904/ejfe.1516227

IZ

https://izlik.org/JA38ES46ET

APA

Dmitriev, P., Kozlovsky, B., & Dmitrieva, A. (2025). Maple Species Identification Based On Hyperspectral Imaging Time Series. European Journal of Forest Engineering, 11(2), 81-94. https://doi.org/10.33904/ejfe.1516227

Creative Commons License

The works published in European Journal of Forest Engineering (EJFE) are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Maple Species Identification Based On Hyperspectral Imaging Time Series

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Maple Species Identification Based On Hyperspectral Imaging Time Series

Abstract

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Subjects

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Early Pub Date

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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