PyVPP

Python package to download and preprocess High Resolution Vegetation Phenology and Productivity products (HR-VPP) from Copernicus Land Monitoring Service.

⚠️ IMPORTANT - VPP_Index Dataset Currently Unavailable (January 2025)

The VPP_Index dataset (EO:EEA:DAT:CLMS_HRVPP_VI) currently returns 404 errors on WEkEO.

This dataset, which contained daily vegetation indices (LAI, FAPAR, NDVI, PPI), appears to have been discontinued or moved since 2024.

✅ Datasets that ARE working:

• VPP_ST (Seasonal Trajectories): Contains PPI, QFLAG
• VPP_Pheno (Phenology & Productivity): Contains SOSD, MAXD, EOSD, LENGTH, AMPL, TPROD, etc.

🔧 If you needed VPP_Index:

• For PPI → Use VPP_ST
• For phenology parameters → Use VPP_Pheno
• For LAI, FAPAR, NDVI → Currently not available via PyVPP (see alternatives below)

See DATASETS_AVAILABLE.md for more details.

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Installation

pip install pyvpp

Quick Start

1. Configure your WEkEO credentials

import pyvpp

# Create .hdarc file with your credentials
pyvpp.create_hdarc("your_wekeo_username", "your_wekeo_password")

2. Download data

Option A: Phenology parameters (RECOMMENDED - WORKING)

import pyvpp

# Download phenology parameters (annual products)
downloader = pyvpp.wekeo_download(
    dataset='VPP_Pheno',  # ✅ Working
    shape='path/to/your/area.shp',  # or DEIMS ID
    dates=['2020-01-01', '2020-12-31'],
    products=['SOSD', 'MAXD', 'EOSD', 'LENGTH']
)

downloader.run()

Option B: Seasonal Trajectories - PPI (RECOMMENDED - WORKING)

import pyvpp

# Download PPI (Plant Phenology Index) every 10 days
downloader = pyvpp.wekeo_download(
    dataset='VPP_ST',  # ✅ Working
    shape='path/to/your/area.shp',
    dates=['2020-01-01', '2020-12-31'],
    products=['PPI', 'QFLAG']
)

downloader.run()

Option C: Vegetation Indices (⚠️ CURRENTLY NOT AVAILABLE)

import pyvpp

# ⚠️ WARNING: This dataset is currently returning 404 errors
# VPP_Index (LAI, FAPAR, NDVI) is not available as of January 2025
downloader = pyvpp.wekeo_download(
    dataset='VPP_Index',  # ⚠️ Returns 404 error
    shape='path/to/your/area.shp',
    dates=['2020-01-01', '2020-12-31'],
    products=['LAI', 'FAPAR']  # Not available
)

# This will fail with: 404 Client Error

Available Datasets & Products

✅ VPP_Pheno (Vegetation Phenology & Productivity)

Status: Working
Products:

• SOSD (Start of Season Date)
• EOSD (End of Season Date)
• MAXD (Maximum Date)
• MINV (Minimum Value)
• MAXV (Maximum Value)
• AMPL (Amplitude)
• LENGTH (Length of Season)
• LSLOPE (Left Slope)
• RSLOPE (Right Slope)
• SPROD (Seasonal Productivity)
• TPROD (Total Productivity)
• SOSV (Start of Season Value)
• EOSV (End of Season Value)

✅ VPP_ST (Seasonal Trajectories)

Status: Working
Products:

• PPI (Plant Phenology Index)
• QFLAG (Quality Flag)

⚠️ VPP_Index (Vegetation Indices)

Status: NOT AVAILABLE (404 Error as of January 2025)
Products (no longer accessible):

• ~~LAI (Leaf Area Index)~~
• ~~FAPAR (Fraction of Absorbed Photosynthetically Active Radiation)~~
• ~~NDVI (Normalized Difference Vegetation Index)~~
• ~~PPI (now available in VPP_ST)~~

✅ SLSTR (Sentinel-3 Land Surface Temperature)

Status: Working
Products: SL_2_LST___

Using DEIMS IDs

You can use DEIMS site IDs instead of shapefiles:

downloader = pyvpp.wekeo_download(
    dataset='VPP_Pheno',
    shape='deimsid:https://deims.org/bcbc866c-3f4f-47a8-bbbc-0a93df6de7b2',
    dates=['2020-01-01', '2020-12-31'],
    products=['SOSD', 'MAXD']
)

Step-by-step workflow

PyVPP performs the following operations:

1. Downloads all Sentinel-2 tiles that intersect your area of interest
2. Filters tiles by UTM zone
3. Creates mosaics for each date and product
4. Clips mosaics to your exact boundaries
5. Saves final products as mosaic_YYYYMMDD_PRODUCT_rec.tif
6. Cleans up intermediate files

Advanced Usage

Use credentials directly (without .hdarc)

downloader = pyvpp.wekeo_download(
    dataset='VPP_Pheno',
    shape='area.shp',
    dates=['2020-01-01', '2020-12-31'],
    products=['SOSD'],
    user='your_username',      # Direct credentials
    password='your_password'
)

Clean old .hdarc format

If you have an old .hdarc file (pre-March 2024):

import pyvpp
pyvpp.clean_old_hdarc()  # Removes obsolete 'url:' line

Step-by-step execution

# Execute steps individually
downloader.download()        # Only download
downloader.mosaic_and_clip() # Only mosaic and clip
downloader.clean()           # Only clean intermediate files

Alternatives for LAI, FAPAR, NDVI

Since VPP_Index is currently unavailable, here are alternatives:

1. Google Earth Engine (Recommended)

// Calculate NDVI from Sentinel-2
var s2 = ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')
  .filterDate('2020-01-01', '2020-12-31')
  .filterBounds(geometry);

var addNDVI = function(image) {
  var ndvi = image.normalizedDifference(['B8', 'B4']).rename('NDVI');
  return image.addBands(ndvi);
};

2. Sentinel Hub

https://www.sentinel-hub.com/

• Pre-computed LAI, FAPAR, NDVI available

3. Copernicus Global Land Service

https://land.copernicus.eu/global/products/

• 300m resolution (not 10m like HR-VPP)

4. Calculate from Sentinel-2 directly

import rasterio
import numpy as np

# NDVI = (NIR - Red) / (NIR + Red)
with rasterio.open('sentinel2.tif') as src:
    red = src.read(4)  # Band 4
    nir = src.read(8)  # Band 8
    ndvi = (nir - red) / (nir + red)

Troubleshooting

Error 404: Dataset not found

If you get a 404 error with VPP_Index:

requests.exceptions.HTTPError: 404 Client Error: Not Found for url: 
https://gateway.prod.wekeo2.eu/hda-broker/api/v1/datasets/EO:EEA:DAT:CLMS_HRVPP_VI

Solution: Use VPP_Pheno or VPP_ST instead (see examples above).

Authentication failed

# Recreate your .hdarc file
import pyvpp
pyvpp.create_hdarc("username", "password")

No matches found

This usually means:

1. Date range is outside available data
2. Area of interest has no coverage
3. Product name is misspelled

Check the official documentation for data availability.

Requirements

• Python >= 3.8
• hda >= 2.18
• geopandas >= 0.8.2
• rasterio >= 1.3
• deims >= 4.0

Documentation & Support

• HR-VPP Documentation: https://land.copernicus.eu/pan-european/biophysical-parameters/high-resolution-vegetation-phenology-and-productivity
• WEkEO Help Center: https://help.wekeo.eu/
• PyVPP Repository: https://github.com/Digdgeo/PyVPP
• Report Issues: https://github.com/Digdgeo/PyVPP/issues

Citation

If you use PyVPP in your research, please cite:

García-Díaz, D. (2025). PyVPP: Python package for HR-VPP data access and processing.
https://github.com/Digdgeo/PyVPP

License

MIT License - see LICENSE file for details

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Changelog

v0.1.9 (Current)

• Updated .hdarc format for new HDA API (March 2024+)
• Added direct credential support
• Improved error handling
• Added helper functions: create_hdarc(), clean_old_hdarc(), delete_hdarc()
• Note: VPP_Index dataset currently unavailable (404 error)

v0.1.8

• Previous stable version
• Works with old HDA API (pre-March 2024)

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Last updated: January 2025
Status: VPP_ST ✅ | VPP_Pheno ✅ | VPP_Index ⚠️ (unavailable)