Whiteboard photography: A field method with automated image processing to measure vertical vegetation features for ecological research in open habitats

Accurate measurement of vertical vegetation structure is essential for modeling habitat variation and species interactions. The study's objective to present an improved whiteboard photography method combined with a semi-automated image processing pipeline to standardize vegetation measurements in open habitats. The workflow includes whiteboard localization using a neural network for real-time object detection; geometric correction based on reference points; pixel-level vegetation classification; and calculation of structural metrics such as leaf area (LA: total leaf surface), maximum height of vegetation (MHV: tallest point), height of closed vegetation (HCV: lowest continuous cover), and foliage height diversity (FHD: height variation). All steps are integrated into a web interface that enables both user-controlled and fully automated image processing within seconds per image. Geometric transformation accuracy and noise sensitivity were evaluated using 120 calibration images. Object-detection precision was high (mAP₅₀ ≈ 0.995, where mAP₅₀ represents mean average precision at 50 % intersection-over-union). Over 92.9 % of cases exhibited geometric error ≤ 5 cm, regardless of whiteboard or image quality. Results indicated that renewing the board and using higher-resolution images improved measurement consistency, while moderate occlusion had minimal impact on transformation accuracy. The method was applied to 99 Hungarian grassland plots to model Balkan Wall Lizard density using N-mixture models. Lizard density increased with greater MHV and HCV but decreased with higher LA after accounting for temperature-dependent detectability. This low-cost, non-destructive, and replicable approach provides a reliable tool for measuring vertical vegetation structure and supports ecological monitoring and habitat modeling in open landscapes. • Whiteboard: quick and precise way to gather data about vertical vegetation structure • Free, user friendly web application to do automated or manual processing • Structure encoded by the parameters influences the density of the Balkan wall lizard.

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Publication Details

Journal
Ecological Informatics
Published
2025-12-02
DOI
https://doi.org/10.1016/j.ecoinf.2025.103540
Primary Topic
Amphibian and Reptile Biology
Type
article
Field-Weighted Citation Impact
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article

Whiteboard photography: A field method with automated image processing to measure vertical vegetation features for ecological research in open habitats

George Olah, Edvárd Mizsei, Miklós Bán, Mátyás Budai
Ecological Informatics
Amphibian and Reptile Biology
article

Whiteboard photography: A field method with automated image processing to measure vertical vegetation features for ecological research in open habitats

George Olah, Edvárd Mizsei, Miklós Bán, Mátyás Budai
article en

Abstract

Accurate measurement of vertical vegetation structure is essential for modeling habitat variation and species interactions. The study's objective to present an improved whiteboard photography method combined with a semi-automated image processing pipeline to standardize vegetation measurements in open habitats. The workflow includes whiteboard localization using a neural network for real-time object detection; geometric correction based on reference points; pixel-level vegetation classification; and calculation of structural metrics such as leaf area (LA: total leaf surface), maximum height of vegetation (MHV: tallest point), height of closed vegetation (HCV: lowest continuous cover), and foliage height diversity (FHD: height variation). All steps are integrated into a web interface that enables both user-controlled and fully automated image processing within seconds per image. Geometric transformation accuracy and noise sensitivity were evaluated using 120 calibration images. Object-detection precision was high (mAP₅₀ ≈ 0.995, where mAP₅₀ represents mean average precision at 50 % intersection-over-union). Over 92.9 % of cases exhibited geometric error ≤ 5 cm, regardless of whiteboard or image quality. Results indicated that renewing the board and using higher-resolution images improved measurement consistency, while moderate occlusion had minimal impact on transformation accuracy. The method was applied to 99 Hungarian grassland plots to model Balkan Wall Lizard density using N-mixture models. Lizard density increased with greater MHV and HCV but decreased with higher LA after accounting for temperature-dependent detectability. This low-cost, non-destructive, and replicable approach provides a reliable tool for measuring vertical vegetation structure and supports ecological monitoring and habitat modeling in open landscapes. • Whiteboard: quick and precise way to gather data about vertical vegetation structure • Free, user friendly web application to do automated or manual processing • Structure encoded by the parameters influences the density of the Balkan wall lizard.

Ecological InformaticsVol. 93
Openalex Percentile: Top 65%
Amphibian and Reptile Biology
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