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Update README.md
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README.md
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---
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configs:
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- config_name: labeled_all
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data_files: "labeled_all/all.csv"
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# data_files:
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# - split: all
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# path:
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# - "50_all_traits.csv"
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default: true
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description: "Labeled spectra data with trait measurements for supervised learning."
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- config_name: unlabeled
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data_files: "unlabeled/*.csv"
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description: "Unlabeled spectra data for semi-supervised or self-supervised learning."
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- config_name: labeled_splits
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data_files:
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- split: train
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path:
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- "labeled_splits/train.csv"
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- split: test
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path: "labeled_splits/test.csv"
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description: "A stratified splitting of the labeled data."
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---
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# 🌱 GreenHySpectra: A multi-source hyperspectral dataset for global vegetation trait prediction 🌱
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GreenHySpectra is a collection of hyperspectral reflectance data of vegetation from different sources. It is intended for Regression machine learning task for plant trait prediction with self and semi-supervised learning.
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## 📁 Configurations
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### 1. `GreenHySpectra: Unlabeled Set`
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- Files: all CSVs under `unlb/`
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- Contains:
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- Sample ID
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- Spectral bands (400-2450 nm) >> 1721 bands
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| Column | Description |
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|----------------|-----------------------------------------|
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| 400 | Reflectance at 400nm |
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| ... | More spectral bands |
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| 2450 | Reflectance at 2450nm |
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---
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### 2. `Labeled set`
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- File: `50_all_traits.csv`
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- Contains:
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- Sample ID
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- Dataset ID
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- Spectral bands (400-2450 nm) >> 1721 bands
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- Trait measurements (e.g., leaf chlorophyll, nitrogen content etc.)
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| Column | Description |
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|----------------|-----------------------------------------|
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| dataset | Reference to the source of the dataset |
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| 400 | Reflectance at 400nm |
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| ... | More spectral bands |
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| 2450 | Reflectance at 2450nm |
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| Cp | Nitrogen content (g/m²) |
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| Cm | Leaf mass per area (g/m²) |
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| Cw | Leaf water content (cm) |
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| LAI | Leaf area index (m²/m²) |
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| Cab | Leaf chrolophyll content (µg/m²) |
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| Car | Leaf carotenoids content (µg/m²) |
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| Anth | Leaf anthocynins content (µg/m²) |
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---
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license: cc-by-nc-4.0
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---
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