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dataset_info:
features:
- name: bands
dtype: binary
- name: bands_shape
list: int64
- name: bands_dtype
dtype: string
- name: band_metadata
dtype: string
- name: band_order
list: string
- name: site
dtype: string
- name: sample_id
dtype: string
splits:
- name: train
num_bytes: 196618624
num_examples: 48
download_size: 196528243
dataset_size: 196618624
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
size_categories:
- n<1K
---
# Dune Plant Functional Trait
This dataset provides real-world multispectral imagery of coastal dune vegetation collected in the field at Sant'Andrea, Grado, and Marano lagoons, Italy. Captured using a ground-based Micasense RedEdge camera with five spectral bands, the images deliver detailed spectral information for analyzing plant functional traits in natural dune environments. The dataset contains 48 images with no classification, segmentation, or bounding-box annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{trotta2025capturing,
title={Capturing plant functional traits in coastal dunes using close-range remote sensing},
author={Trotta, Giacomo and Vuerich, Marco and Petrussa, Elisa and Asquini, Edoardo and Cingano, Paolo and Boscutti, Francesco},
journal={Ecological Informatics},
volume={88},
pages={103159},
year={2025},
publisher={Elsevier}
}
```
Trotta, Giacomo (2025), “Data from Capturing functional trait response of dune plants using close-range remote sensing ”, Mendeley Data, V3, doi: 10.17632/n2bp3ppr77.3
*This dataset was reformatted from its original format to match HuggingFace standards.*
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