EODAG - DestinE Data Lake Provider

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__DOWNLOAD__OUTPUTS_PREFIX"] = os.path.abspath(workspace)

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


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

from eodag import EODataAccessGateway
dag = EODataAccessGateway()

[product_type["ID"] + ", " + product_type["title"] for product_type in dag.list_product_types("dedl")]

search_criteria = {
    "provider":"dedl",
    "productType": "EO.ESA.DAT.SENTINEL-2.MSI.L2A",
    "start": "2024-07-04T07:00:00.00Z",
    "end": "2024-07-08T07:00:00.00Z",
    "geom": {"lonmin": 12, "latmin": 37, "lonmax": 16, "latmax": 39},
    "count": True,
    "items_per_page": 50
}

products_first_page = dag.search(**search_criteria)

products_first_page

one_product = products_first_page[0]
one_product.properties.keys()

one_product.properties['cloudCover']

from eodag.crunch import FilterProperty
from eodag.crunch import FilterOverlap
import shapely
import folium
from shapely.geometry import Polygon

small_geom = Polygon([[15.1, 37.7], [15.5, 37.7], [15.1, 37.75], [15.1, 37.75], [15.1, 37.7]])

smaller_area = {"lonmin": 15.1, "latmin": 37.7, "lonmax": 15.5, "latmax": 37.75}

search_geometry = shapely.geometry.box(
    smaller_area["lonmin"],
    smaller_area["latmin"],
    smaller_area["lonmax"],
    smaller_area["latmax"],
)

def create_search_result_map(search_results, extent):
    """Small utility to create an interactive map with folium
    that displays an extent in red and EO Producs in blue"""
    fmap = folium.Map([38, 14], zoom_start=7)
    folium.GeoJson(
        extent,
        style_function=lambda x: dict(color="red")
    ).add_to(fmap)
    folium.GeoJson(
        search_results
    ).add_to(fmap)
    return fmap

# Crunch the results
filtered_results = products_first_page.crunch(FilterProperty({"cloudCover": 20, "operator" : "lt"}))

print(f"Got now {len(filtered_results)} products after filtering by cloudCover.")

filtered_products = filtered_results.crunch(
    FilterOverlap(dict(contains=True)),
    geometry=small_geom
)
print(f"Got now {len(filtered_products)} products after filtering by geometry.")

fmap = create_search_result_map(products_first_page, search_geometry)
# Create a layer that represents the filtered products in green
folium.GeoJson(
    filtered_products,
    style_function=lambda x: dict(color="green")
).add_to(fmap)
fmap

import matplotlib.pyplot as plt
import matplotlib.image as mpimg

quicklooks_dir = os.path.join(workspace, "quicklooks")
if not os.path.isdir(quicklooks_dir):
    os.mkdir(quicklooks_dir)

fig = plt.figure(figsize=(20, 40))
for i, product in enumerate(filtered_products, start=1):

    # This line takes care of downloading the quicklook
    quicklook_path = product.get_quicklook()
    
    img = mpimg.imread(quicklook_path)
    ax = fig.add_subplot(8, 2, i)
    ax.set_title(product.properties['dedl:beginningDateTime'] + "TILE: " +product.properties['dedl:tileIdentifier'])
    plt.imshow(img)
plt.tight_layout()

product_to_download = filtered_products[-1]
product_path = dag.download(product_to_download)
product_path

product_to_download.location