# Data Directory

## Required files

### 1. `test_site_raw_2024.csv` — Raw satellite observations

Sparse NDVI observations with date-named columns. This is the primary input:
- The **streaming driver** RBF-smooths it at runtime for incremental fine-tuning
- The **MAE notebook** uses it as ground truth for evaluation

```
FID,avND20240301,avND20240315,avND20240402,...
grid_001,0.12,0.18,0.25,...
grid_002,0.11,0.17,0.23,...
```

- **Columns**: `FID` + one column per satellite observation date (YYYYMMDD or prefixed like `avNDYYYYMMDD`)
- **Values**: Raw NDVI float values
- **Dates need not be evenly spaced** — the RBF smoother interpolates to a daily grid

### 2. `test_site_NDVI_2024.csv` — Pre-smoothed ground truth

Used by the streaming driver to provide future labels beyond the currently observed horizon (for rollout-gated evaluation).

```
FID,0,1,2,...,126
grid_001,0.12,0.13,0.14,...,0.31
grid_002,0.11,0.12,0.13,...,0.28
```

- **Columns**: `FID` + 127 DAP columns (0–126)
- **Values**: Float in [0.0, 1.0], preprocessed and smoothed

**Important**: Both files must contain the same FIDs.

## For training from scratch (optional)

Place the full training datasets:

- `train_site_NDVI_2020.csv`
- `train_site_NDVI_2021.csv`
- `train_site_NDVI_2022.csv`

These follow the same format as the ground truth CSV above. Uncomment the training appendix in the notebook to use.
