Create time stacks of images

This example demonstrates how to aggregate the images returned from a Catalog image search by date.

from earthdaily.earthone.catalog import Product, properties as p
from earthdaily.earthone.utils import display

# Define a bounding box around Taos in a GeoJSON
taos = {
    "type": "Polygon",
    "coordinates": [
        [
            [-105.71868896484375, 36.33725319397006],
            [-105.2105712890625, 36.33725319397006],
            [-105.2105712890625, 36.73668306473141],
            [-105.71868896484375, 36.73668306473141],
            [-105.71868896484375, 36.33725319397006],
        ]
    ],
}

Create an ImageCollection.

search = (
    Product.get("usgs:landsat:oli-tirs:c2:l2:v0")
    .images()
    .intersects(taos)
    .filter("2018-01-01" <= p.acquired < "2018-12-31")
    .filter(p.cloud_fraction < 0.7)
    .sort("acquired")
    .limit(500)
)
images = search.collect()
print("There are {} images in the collection.".format(len(images)))

There are 80 images in the collection.

To create subcollections using the ImageCollection API, we have the built in methods ImageCollection.groupby and ImageCollection.filter.

If we want to create multiple subsets based on those properties, we can use the ImageCollection.groupby method.

for (year, month), month_images in images.groupby("acquired.year", "acquired.month"):
    print("{}: {} images".format(month, len(month_images)))

1: 8 images
2: 6 images
3: 6 images
4: 6 images
5: 6 images
6: 8 images
7: 8 images
8: 7 images
9: 6 images
10: 5 images
11: 6 images
12: 8 images

You can further group the subsets using the built in ImageCollection.filter method.

spring_images = images.filter(lambda i: i.acquired.month > 2 and i.acquired.month < 6)
fall_images = images.filter(lambda i: i.acquired.month > 8 and i.acquired.month < 12)

print(
    "There are {} Spring images & {} Fall images.".format(
        len(spring_images), len(fall_images)
    )
)

There are 18 Spring images & 17 Fall images.

Mosaic and display these two image collections.

spring_arr = spring_images.mosaic("red green blue", resolution=120)

fall_arr = fall_images.mosaic("red green blue", resolution=120)
display(spring_arr, fall_arr, size=4, title=["Spring", "Fall"])