Metadata-Version: 2.1
Name: geoflexforecast
Version: 0.1.0
Summary: Flexible raster time-series forecasting using native and aggregated spatial grids
Author: Zainab Khan
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: rasterio
Requires-Dist: statsmodels
Requires-Dist: tqdm


# geoflexforecast

geoflexforecast is a Python package for flexible raster time-series forecasting.

The package allows users to:

- Forecast rasters at native pixel level
- Aggregate pixels into user-defined blocks
- Reduce computational load for massive raster datasets
- Apply ARIMA forecasting across raster time series

## Forecasting Modes

### Native Mode

Forecast every raster pixel independently.

### Aggregate Mode

Aggregate raster pixels into blocks such as:

- 2x2
- 5x5
- 10x10

before forecasting.

This is useful for large rasters and limited computational resources.

## Example

```python
from geoflexforecast import forecast_raster_series

forecast_raster_series(
    raster_paths=[
        "NDVI_2001.tif",
        "NDVI_2002.tif",
        "NDVI_2003.tif"
    ],
    output_path="forecast.tif",
    mode="aggregate",
    block_size=10,
    aggregation="mean",
    order=(1, 1, 1),
    min_obs=3
)
