Urban Green Monitoring for the Municipality of Athens

This repository contains the processing stack used to monitor urban green areas in Athens from Earth Observation data (Sentinel-2). It combines:

• an actinia + GRASS GIS processing backend,
• custom GRASS add-ons for Sentinel-2 scene filtering, Sentinel-2 scene download and STAC publishing,
• process chain templates for NDVI/NDWI production and classification.

The main output is a set of geospatial products (NDVI/NDWI and classified versions) plus STAC item updates for catalog publication.

Note: This workflow was designed to be integrated with the satellite.cityofathens.gr repository. Adding STAC items of processed raster layers to STAC collection might not work properly if running this worklow independently (needs correct STAC catalog setup).

What this workflow does

The workflow in this repository is designed to:

1. Filter Sentinel-2 scenes by date range, AOI, tile id, and cloud cover.
2. Download and import selected scenes into GRASS GIS.
3. Use L2A cloud probability layer to mask out clouds. Cloud proabability threshold is set to 65 %. (Could be changed in processing/templates/template_S2_download_import.json). See also i.sentinel.import.
4. Compute NDVI and NDWI maps.
5. Classify NDVI/NDWI outputs using configured categories for vegetation health assessment. The threshold for the categorization is set in processing/input/index_classification/*classes.
6. Export raster outputs as COG.
7. Create and publish STAC items to an existing STAC catalog/collection and update collection extent metadata.

Main components

Custom GRASS Addons

In ./grass-gis-addons/

• i.s2_id.filter
  • Module to query Sentinel-2 metadata via EODAG and return scene IDs based on filters (date, AOI, tile id, cloud cover).
• i.s2_id.download
  • Module to download selected Sentinel-2 scenes using EODAG. Imports bands using i.sentinel.import for processing.
• i.create.stac
  • Module to create a STAC item from exported assets and publish it to an existing STAC catalog/collection. Also updates collection extents. Uses pystac and rio-stac.

Scripts

In ./processing/scripts/

• create_export_subfolders.py
  • utility script to create export directory for exported COGs. Directory is parsed in process chain template.
• remove_data.py
  • cleanup script to remove downloaded Sentinel-2 SAFE files.
• rename_bands.py
  • utility script to rename imported raster bands in GRASS location for further processing.

Actinia Process Chains

Jinja2 templates in ./processing/templates/. Variables are parsed in run_service.py and rendered as JSON before submission to actinia.

• process_chain_filter_S2_scenes.json.j2
  • process chain to run i.s2_id.filter and return filtered scene ids.
• process_chain_S2_processing.json.j2
  • process chain to trigger processing for parsed Sentinel-2 scene ids.

Actinia Process Templates

Actinia module templates in ./processing/templates/ are used by process_chain_S2_processing.json.j2.

• template_S2_processing.json
  • process template to run the main processing steps for a Sentinel-2 scene: import, NDVI/NDWI calculation, classification, export, and STAC item creation. Calls the following templates for specific steps:
  • template_S2_download_import.json
    • process template to download Sentinel-2 scenes using i.s2_id.download and to import bands using i.sentinel.import.
  • template_calc_NDVI.json
    • process template to calculate NDVI and categorize it. Exports layers as COG.
  • template_calc_NDWI.json
    • process template to calculate NDWI and categorize it. Exports layers as COG.

Start service script

• processing/run_service.py
  • script to run the whole workflow. Parses parameters, renders process chain templates, submits to actinia, and monitors execution.

How to use this workflow

All Docker commands below are run from the docker/ directory. For further docker instructions see docker/README.md.

1. Configure environment variables

Create docker/.env with actinia and CDSE credentials:

ACTINIA_USER=<your_user>
ACTINIA_PW=<your_password>
EODAG_USER=<your_CDSE_user>
EODAG_PW=<your_CDSE_password>

Do not commit real credentials in docker/.env.

2. Build the image

docker compose -f docker-compose.yml -p athen_urban-green build

For a full rebuild after dependency changes:

docker compose -f docker-compose.yml -p athen_urban-green build --no-cache

3. Start containers

For a Local Setup: you need to mount a local directory for data export. Add to volumes for actinia /path/to/local/export/dir:/src/export_dir, then:

docker compose -f docker-compose.yml -p athen_urban-green up

4. Verify API is up

• Version endpoint: http://localhost:8088/api/v3/version
• Locations endpoint: http://localhost:8088/api/v3/locations

5. Stop containers

docker compose -f docker-compose.yml -p athen_urban-green down

Run processing

Run Service

The script in processing/run_service.py starts the whole workflow.

From repository root folder:

python processing/run_service.py

Script parameters

Important script parameters to adapt before production runs:

Sentinel-2 query parameters:

• Time range (START_TIME, END_TIME, or automatic time range mode) for filtering Sentinel-2 scenes.

  Options:

  1. manual time range: Set START_TIME and END_TIME e.g. START_TIME = "2026-04-05" and END_TIME = "2026-04-10"
  2. automatic time range: Queries given STAC collection STAC_COLLECTION_URL for latest item and sets START_TIME accordingly and END_TIME to current time. For the current settings, the collection ndvi-ath is used which is updated with each workflow run. Check with names defined in STAC_COLLECTIONS.

• TILE_ID: Sentinel-2 tile identifier e.g. 34SGH for Athens area

• MAX_CLOUD_COVER: Max. cloud cover threshold

• AOI: By default, the script uses a predefined AOI for Athens in processing/input/athens_aoi.geojson.

  • To use a different AOI, replace this file with a new GeoJSON containing the desired AOI geometry (and rebuild image).
  • Or specify a bounding box by setting LONMIN, LONMAX, LATMIN, LATMAX.
    • Note: Currently -a flag is set for i.s2_id.filter in process chain. This enables AOI filtering based on predifined AOI. For bounding box filtering -a flag must be removed. --> TODO: implement automatic flag removal when bounding box parameters are set.

actinia process parameters:

It should not be necessary to change these parameters. To be able to reach actinia a correct actinia base URL (ACTINIA_BASE_URL) is required. The default of this setup is http://localhost:8088/.

STAC parameters:

• STAC_CATALOG_URL: Should link to the STAC catalog "http://pycsw:8000/stac/"
• STAC_COLLECTIONS: Names of the STAC collections, where the created items are registered. For this workflow four collections for each product are used: "ndvi-ath,ndvi-cat-ath,ndwi-ath,ndwi-cat-ath"
• PRODUCT_NAMES: Names used for the STAC items of the four products (same order as STAC_COLLECTIONS): "NDVI,NDVI_categorized,NDWI,NDWI_categorized"
• STAC_ITEM_ID_PREFIX: Defines a prefix for the STAC item IDs: e.g. "athen_urban_green" so the STAC item ID will be like this athen_urban_green_NDWI_categorized_20260218T091031 STAC_ITEM_TITLE: Title for STAC item. Additionally, product name and date are added to the title. E.g. Urban Green Monitoring Athens- NDWI_categorized - 2026-02-18 09:10:31+00:00 STAC_ITEM_DESCRIPTION: Description for STAC item. Currently it is the same text for all products.

Note for a local setup: Adding STAC item to a collection only works if you have write access to the collection.

Required python dependencies for run_service.py are listed in requirements.txt and include:

• requests
• dotenv
• jinja2

Output layers

The main output layers are exported as Cloud Optimized GeoTIFFs (COG):

• NDVI (Normalized Difference Vegetation Index)
• Categorized NDVI
• NDWI (Normalized Difference Water Index)
• Categorized NDWI

Categorization thresholds for NDVI and NDWI are defined in processing/input/index_classification/ndvi_4_classes and processing/input/index_classification/ndwi_3_classes.

Uses equations:

• NDVI = (NIR - Red) / (NIR + Red)
• NDWI = (( NIR - SWIR ) / ( NIR + SWIR ))

NDVI classes (raster values in brackets):

• no vegetation (1): -1 to 0.1
• bare soil (2): 0.1 to 0.2
• sparse/stressed vegetation (3): 0.2 to 0.5
• dense/healthy vegetation (4): 0.5 to 1.0

NDWI classes (raster values in brackets):

• barren soil (1): -1000 to -200
• strong water stress (2): -200 to 0
• medium water stress (3): 0 to 100
• low water stress (4): 100 to 200
• no water stress (5): 200 to 1000

Troubleshooting

• Authentication failures:
  • verify ACTINIA_USER, ACTINIA_PW, EODAG_USER, EODAG_PW in docker/.env.
• No scenes returned:
  • widen time window, increase cloud threshold, verify tile ID and AOI.
• Process polling errors:
  • inspect actinia status URL and container logs for detailed module errors.

Repository structure

.
├── docker
│   └── ...
├── grass-gis-addons
│   ├── i.create.stac
│   │   └── ...
│   ├── i.s2_id.download
│   │   └── ...
│   └── i.s2_id.filter
│       └── ...
├── LICENSES
│   └── GPL-3.0-or-later.txt
├── processing
│   ├── input
│   │   ├── aoi
│   │   │   └── Athens_aoi.geojson
│   │   └── index_classification
│   │       └── ...
│   ├── run_service.py
│   ├── scripts
│   │   ├── create_export_subfolders.py
│   │   ├── remove_data.py
│   │   └── rename_bands.py
│   └── templates
│       ├── process_chain_filter_S2_scenes.json
│       ├── process_chain_filter_S2_scenes.json.j2
│       ├── process_chain_S2_processing.json
│       ├── process_chain_S2_processing.json.j2
│       ├── template_calc_NDVI.json
│       ├── template_calc_NDWI.json
│       ├── template_S2_download_import.json
│       └── template_S2_processing.json
├── README.md
├── requirements.txt
└── ...

License

This project is licensed under GPL-3.0-or-later. See LICENSE and LICENSES/GPL-3.0-or-later.txt.