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--- |
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configs: |
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- config_name: labeled_all |
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data_files: "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: "unlb/*.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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- "lb/train.csv" |
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- split: test |
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path: "lb/test.csv" |
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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: mit |
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--- |
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