EODAG - A quick start with DEDL - DEDL Notebook Gallery

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Copyright: 2025 EUMETSAT
License: MIT
Authors: Serena Avolio (EUMETSAT/Starion)

EODAG - A quick start with DEDL¶

Prerequisites:

To search and access DEDL data a DestinE user account is needed

References:

EODAG - Earth Observation Data Access Gateway

EODAG - DEDL

EODAG API documentation

Credit:

Code used in this context takes inspiration from the Python API User Guide produced by CS Group.

EODAG is a command line tool and a Python package for searching and downloading earth observation data via a unified API.

This quickstart tutorial has the aim to show how to get DEDL data using the EODAG python API. It contains some help tools to select the dataset of interest, the bounding box and the time range for searching DEDL data.

Detailed information about the usage of EODAG can be found on the project documentation page.

Throughout this quickstart notebook, you will learn:

Setup: How to configure EODAG to use the provider DEDL.
Discover: How to discover DEDL datasets through EODAG.
Search products: How to search DEDL data through EODAG.
Download products: How to download DEDL data through EODAG.

In this notebook the word ‘collection’, ‘dataset’ and ‘product type’ have the same meaning.

Note:

Please note that the two factor authentication (2FA) is still not implemented in EODAG. The users who have enabled 2FA on DESP will not be able to run this notebook.

Setup¶

In this section, we set:

The output_dir, the directory where to store downloaded products.
The DEDL credentials, you’ll be asked to enter your DEDL credentials.
The search timeout, it is of 60 seconds to avoid any unexpected errors because of long running search queries.

import os
from getpass import getpass

workspace = 'eodag_workspace'
if not os.path.isdir(workspace):
    os.mkdir(workspace)
    
os.environ["EODAG__DEDL__DOWNLOAD__OUTPUT_DIR"] = os.path.abspath(workspace)

os.environ["EODAG__DEDL__SEARCH__TIMEOUT"]="60"
os.environ["DEFAULT_STREAM_REQUESTS_TIMEOUT"] = "15"
os.environ["EODAG__DEDL__PRIORITY"]="10"


DESP_USERNAME = input("Please input your DESP username or email: ")
DESP_PASSWORD = getpass("Please input your DESP password: ")

os.environ["EODAG__DEDL__AUTH__CREDENTIALS__USERNAME"]=DESP_USERNAME
os.environ["EODAG__DEDL__AUTH__CREDENTIALS__PASSWORD"]=DESP_PASSWORD

EODiscover¶

In this section, we:

import and instantiate an EODataAccessGateway object that will be used for all the operations in this tutorial.
discover DEDL collections. The collections are presented in a dropdown menu, selecting a collection its description will be prompted.
the collection selected will be used in the rest of the tutorial


from eodag import EODataAccessGateway, setup_logging
dag = EODataAccessGateway()

setup_logging(0)

import ipywidgets as widgets
from IPython.display import display, clear_output, HTML
from ipywidgets import Layout, Box
import json

#default values

DATASET_ID = 'EO.EUM.DAT.SENTINEL-3.OL_2_WFR___'


# Event listeners
def on_change(change):
    with output_area:
        clear_output()
        print(f'Selected: {change["new"]}')
        print('---------------------------------------------')
        delimiter=''
        global DATASET_ID
        DATASET_ID = delimiter.join(change["new"])
        product_types=dag.list_product_types("dedl")
        index = next((i for i, d in enumerate(product_types) if d.get('ID') == DATASET_ID), None)
        
        print("TITLE: "+product_types[index]['title'])
        print("ABSTRACT: "+product_types[index]['abstract'])
        print("KEYWORDS: "+product_types[index]['abstract'])

options=[product_type["ID"] for product_type in dag.list_product_types("dedl")]

# Widgets
output_area = widgets.Output()

dropdown = widgets.Dropdown(
    options=options,
    value=options[0],
    description="Datasets:",
    disabled=False,
) 

dropdown.observe(on_change, names='value')


# Layout
# Define the layout for the dropdown
dropdown_layout = Layout(display='space-between', justify_content='center', width='80%')
# Create a box to hold the dropdown with the specified layout
box = Box([dropdown, output_area], layout=dropdown_layout)
display( box)

EOSearch¶

In this section, we define the search criteria to find data inside the chosen dataset.

Bounding box can be modified using the text inputs, it will be visualized on the map. Once selected, to use it for the search we need to use the ‘save bbox’ button under the map.
Time range can be modified using the inputs for dates under the map.

# Import necessary libraries
import folium, datetime
from ipywidgets import interactive, HBox, VBox, FloatText, Button, Label

#default values

START_DATE = '2024-08-11'
END_DATE = '2024-08-13'

sw_lat = 37.0
sw_lng = 14.0
ne_lat = 38.0
ne_lng = 16.0

#functions to handle the chosen values
def on_date_change(change):
    with output_area:
        clear_output()
        global START_DATE
        global END_DATE
        t1 = start_date.value
        t2 = end_date.value
        START_DATE = t1.strftime('%Y-%m-%d')
        END_DATE = t2.strftime('%Y-%m-%d')

        
def update_map(sw_lat, sw_lng, ne_lat, ne_lng):
    # Clear the map
    m = folium.Map(location=[(sw_lat + ne_lat) / 2, (sw_lng + ne_lng) / 2], zoom_start=4, tiles=None)

    nasa_wms = folium.WmsTileLayer(
        url='https://gibs.earthdata.nasa.gov/wms/epsg4326/best/wms.cgi',
        name='NASA Blue Marble',
        layers='BlueMarble_ShadedRelief',
        format='image/png',
        transparent=True,
        attr='NASA'
    )
    nasa_wms.add_to(m)
    
    # Add the bounding box rectangle
    folium.Rectangle(
        bounds=[[sw_lat, sw_lng], [ne_lat, ne_lng]],
        color="#ff7800",
        fill=True,
        fill_opacity=0.3
    ).add_to(m)
    
    # Display the map
    display(m)
    return (sw_lat, sw_lng, ne_lat, ne_lng)

def save_bbox(button):
    global sw_lat 
    global sw_lng  
    global ne_lat 
    global ne_lng 

    sw_lat = sw_lat_input.value
    sw_lng = sw_lng_input.value
    ne_lat = ne_lat_input.value
    ne_lng = ne_lng_input.value
    
    with output:
        clear_output()
        print(f"BBox: sw_lat {sw_lat} sw_lng {sw_lng} ne_lat {ne_lat} ne_lng {ne_lng}")


# Create a base map
m = folium.Map(location=[40, 20], zoom_start=4)
        
        
# Widgets
output = widgets.Output()

# Widgets for bbox coordinates input
sw_lat_input = FloatText(value=sw_lat, description='SW Latitude:')
sw_lng_input = FloatText(value=sw_lng, description='SW Longitude:')
ne_lat_input = FloatText(value=ne_lat, description='NE Latitude:')
ne_lng_input = FloatText(value=ne_lng, description='NE Longitude:')

save_button = Button(description="Save BBox")


# Create DatePicker widgets
start_date = widgets.DatePicker(
    description='Start Date',value = datetime.date(2024,8,11),
    disabled=False
)

end_date = widgets.DatePicker(
    description='End Date',value = datetime.date(2024,8,13),
    disabled=False
)


ui = VBox([
   # HBox([sw_lat_input, sw_lng_input]),
  #  HBox([ne_lat_input, ne_lng_input]),
    save_button,
    output,
    start_date, 
    end_date
])

# Display the interactive map and UI
interactive_map = interactive(update_map, sw_lat=sw_lat_input, sw_lng=sw_lng_input,
                              ne_lat=ne_lat_input, ne_lng=ne_lng_input)


display(interactive_map, ui)

     
#Events

start_date.observe(on_date_change, names='value')
end_date.observe(on_date_change, names='value')
save_button.on_click(save_bbox)

Selected criteria:

search_criteria = {
    "productType": DATASET_ID,
    "start": START_DATE,
    "end": END_DATE,
    "geom": {"lonmin": sw_lng, "latmin": sw_lat, "lonmax": ne_lng, "latmax": ne_lat},
    "count": True
}

print(json.dumps(search_criteria, indent=2))

Use selected criteria to search data:

products_first_page = dag.search(**search_criteria)
print(f"Got {len(products_first_page)} products and an estimated total number of {products_first_page.number_matched} products.")
products_first_page

See the available metadata:


if(len(products_first_page)>0):
    one_product = products_first_page[0]
    print(one_product.properties.keys())

EODownload¶

In this section, we download one of the retrievied product.The first product is going to be downloaded.

if(len(products_first_page)>0):
    product_to_download = one_product
    product_path = dag.download(product_to_download)
    print(product_path)