Glossary in SDK

Overview

The glossary provides information on UP42 data offerings. It helps you create orders.

Collections serve as the higher-level category, containing one or more data products related to the actual configuration of data available for ordering.

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Class: ProductGlossary

A data class that represents product glossary in the system.

Methods

get_collections

Retrieves a list of geospatial collections. Returns Iterator[Collection]. Use itertools.islice to offset and limit the results.

Parameter Description

Parameter	Description
`collection_type`	Optional[CollectionType] The type of the collection.
`sort_by`	Optional[utils.SortingField] The results sorting method that arranges elements in ascending or descending order based on a chosen field.

collection_type

Optional[CollectionType]

The type of the collection.

sort_by

Optional[utils.SortingField]

The results sorting method that arranges elements in ascending or descending order based on a chosen field.

1
# Fetch collections
2
tasking_collections = up42.ProductGlossary.get_collections(
3
    collection_type = up42.CollectionType.TASKING,
4
    sort_by = up42.CollectionSorting.name.asc,
5
)
6

7
archive_collections = up42.ProductGlossary.get_collections(
8
    collection_type = up42.CollectionType.ARCHIVE,
9
    sort_by = up42.CollectionSorting.name.asc,
10
)
11

12
# Define output
9 collapsed lines
13
print(f"Tasking collections")
14
for collection in tasking_collections:
15
    print(f"    {collection.title}: {collection.name}")
16
    print(f"    {collection.description}\n")
17

18
print(f"Catalog collections")
19
for collection in archive_collections:
20
    print(f"    {collection.title}: {collection.name}")
21
    print(f"    {collection.description}\n")

Class: Collection

A data class that represents a collection in the system.

Attributes

Attribute	Description
`name`	str The name of the collection.
`title`	str The title of the collection.
`description`	str The description of the collection.
`type`	CollectionType The type of the collection.
`integrations`	list[IntegrationValue] Integration values.
`providers`	list[Provider] Providers.
`data_products`	list[DataProduct] Data products.
`metadata`	Optional[CollectionMetadata] The collection metadata.

1
from itertools import chain
2

3
# Fetch collections
11 collapsed lines
4
tasking_collections = up42.ProductGlossary.get_collections(
5
    collection_type = up42.CollectionType.TASKING,
6
    sort_by = up42.CollectionSorting.name.asc,
7
)
8

9
archive_collections = up42.ProductGlossary.get_collections(
10
    collection_type = up42.CollectionType.ARCHIVE,
11
    sort_by = up42.CollectionSorting.name.asc,
12
)
13

14
all_collections = chain(tasking_collections, archive_collections)
15

16
# Define output
17
for collection in all_collections:
18
    print(f"- Title:        {collection.title}")
19
    print(f"  Name:         {collection.name}")
20
    print(f"  Description:  {collection.description}")
21
    print(f"  Type:         {collection.type.value}")
22
    print("  Integrations:")
23
    for integration in collection.integrations:
24
        print(f"    {integration}")
25
    print("  Providers:")
26
    for provider in collection.providers:
27
        print(f"    {provider.name} ({', '.join(provider.roles)})")
28
    print("  Data products:")
29
    for product in collection.data_products:
30
        print(f"  - Title:  {product.title}")
31
        print(f"    Name:   {product.name}")
32
        print(f"    ID:     {product.id}")
33
    print("  Metadata:")
34
    print(f"    Product type:       {collection.metadata.product_type}")
35
    print(f"    Resolution class:   {collection.metadata.resolution_class}")
36
    print(f"    Min resolution:     {collection.metadata.resolution_value.minimum} m")
37
    if collection.metadata.resolution_value.maximum:
38
        print(f"    Max resolution: {collection.metadata.resolution_value.maximum} m")
39
    print()

Class: CollectionType

An enumeration class that defines types of geospatial collections.

Constants

Constant Description Value

Constant	Description	Value
`ARCHIVE`	str A catalog collection. Scenes from catalog collections are available for immediate purchase.	`ARCHIVE`
`TASKING`	str A tasking collection. Tasking is requesting a satellite or an aircraft to capture your designated area of interest.	`TASKING`

ARCHIVE

str

A catalog collection. Scenes from catalog collections are available for immediate purchase.

ARCHIVE

TASKING

str

A tasking collection. Tasking is requesting a satellite or an aircraft to capture your designated area of interest.

TASKING

1
# Fetch collections
2
tasking_collections = up42.ProductGlossary.get_collections(
3
    collection_type = up42.CollectionType.TASKING,
4
    sort_by = up42.CollectionSorting.name.asc,
5
)
6

7
archive_collections = up42.ProductGlossary.get_collections(
8
    collection_type = up42.CollectionType.ARCHIVE,
9
    sort_by = up42.CollectionSorting.name.asc,
10
)
11

12
# Define output
9 collapsed lines
13
print(f"Tasking collections")
14
for collection in tasking_collections:
15
    print(f"    {collection.title}: {collection.name}")
16
    print(f"    {collection.description}\n")
17

18
print(f"Catalog collections")
19
for collection in archive_collections:
20
    print(f"    {collection.title}: {collection.name}")
21
    print(f"    {collection.description}\n")

Class: CollectionSorting

A class that provides sorting options for collections.

Attributes

Attribute	Description
`name`	utils.SortingField Sorts by collection name. The default order is ascending.
`title`	utils.SortingField Sorts by collection title. The default order is ascending.
`description`	utils.SortingField Sorts by collection description. The default order is ascending.
`type`	utils.SortingField Sorts by collection type. The default order is ascending.

1
tasking_collections = up42.ProductGlossary.get_collections(
2
    collection_type = up42.CollectionType.TASKING,
3
    sort_by = up42.CollectionSorting.name.asc,
4
)
5

6
for collection in tasking_collections:
7
    print(f"{collection.name}")

Class: CollectionMetadata

A data class that contains metadata related to a collection.

Attributes

Attribute Description

Attribute	Description
`product_type`	Optional[Literal[“OPTICAL”, “SAR”, “ELEVATION”]] The type of product the collection delivers.
`resolution_class`	Optional[Literal[“VERY_HIGH”, “HIGH”, “MEDIUM”, “LOW”]] The nominal resolution class.
`resolution_value`	Optional[ResolutionValue] The level of detail achievable for the collection.

product_type

Optional[Literal[“OPTICAL”, “SAR”, “ELEVATION”]]

The type of product the collection delivers.

resolution_class

Optional[Literal[“VERY_HIGH”, “HIGH”, “MEDIUM”, “LOW”]]

The nominal resolution class.

resolution_value

Optional[ResolutionValue]

The level of detail achievable for the collection.

1
from itertools import chain
2

3
# Fetch collections
11 collapsed lines
4
tasking_collections = up42.ProductGlossary.get_collections(
5
    collection_type = up42.CollectionType.TASKING,
6
    sort_by = up42.CollectionSorting.name.asc,
7
)
8

9
archive_collections = up42.ProductGlossary.get_collections(
10
    collection_type = up42.CollectionType.ARCHIVE,
11
    sort_by = up42.CollectionSorting.name.asc,
12
)
13

14
all_collections = chain(tasking_collections, archive_collections)
15

16
# Define output
17
for collection in all_collections:
18
    print(f"- Title:    {collection.title}")
19
    print(f"  Name:     {collection.name}")
20
    print("  Metadata:")
21
    print(f"    Product type:       {collection.metadata.product_type}")
22
    print(f"    Resolution class:   {collection.metadata.resolution_class}")
23
    print(f"    Min resolution:     {collection.metadata.resolution_value.minimum} m")
24
    if collection.metadata.resolution_value.maximum:
25
        print(f"    Max resolution: {collection.metadata.resolution_value.maximum} m")
26
    print()

Class: ResolutionValue

A data class that represents the resolution of data within a collection.

Attributes

Attribute Description

Attribute	Description
`minimum`	float The best native resolution available for the collection, in meters.
`maximum`	Optional[float] The least detailed resolution available for the collection, in meters. The parameter is omitted if the collection has only one resolution value, specified in `minimum`.

minimum

float

The best native resolution available for the collection, in meters.

maximum

Optional[float]

The least detailed resolution available for the collection, in meters. The parameter is omitted if the collection has only one resolution value, specified in minimum.

1
from itertools import chain
2

3
# Fetch collections
11 collapsed lines
4
tasking_collections = up42.ProductGlossary.get_collections(
5
    collection_type = up42.CollectionType.TASKING,
6
    sort_by = up42.CollectionSorting.name.asc,
7
)
8

9
archive_collections = up42.ProductGlossary.get_collections(
10
    collection_type = up42.CollectionType.ARCHIVE,
11
    sort_by = up42.CollectionSorting.name.asc,
12
)
13

14
all_collections = chain(tasking_collections, archive_collections)
15

16
# Define output
17
for collection in all_collections:
18
    print(f"- Title:    {collection.title}")
19
    print(f"  Name:     {collection.name}")
20
    print("  Metadata:")
21
    print(f"    Product type:       {collection.metadata.product_type}")
22
    print(f"    Resolution class:   {collection.metadata.resolution_class}")
23
    print(f"    Min resolution:     {collection.metadata.resolution_value.minimum} m")
24
    if collection.metadata.resolution_value.maximum:
25
        print(f"    Max resolution: {collection.metadata.resolution_value.maximum} m")
26
    print()

Class: Provider

A data class that represents a provider in the system.

Attributes

Attribute	Description
`name`	str The name of the provider.
`title`	str The title of the provider. The default value is an empty string.
`description`	str The description of the provider. The default value is an empty string.
`roles`	list[Literal[“PRODUCER”, “HOST”]] Provider roles: `PRODUCER`: A provider that initially acquired and processed the source data. Data acquired by a producer can be distributed to various hosts. `HOST`: A provider that offers access to data acquired by a producer. The default value is `["HOST"]`.

1
# Fetch catalog collections
2
archive_collections = up42.ProductGlossary.get_collections(
3
    collection_type = up42.CollectionType.ARCHIVE,
4
    sort_by = up42.CollectionSorting.name.asc,
5
)
6

7
# Define output, return hosts and producers by collection
8
for collection in archive_collections:
9
    print(f"- Title:  {collection.title}")
10
    print(f"  Name:   {collection.name}")
11
    print("  Providers:")
12
    for provider in collection.providers:
13
        print(f"    {provider.name} ({', '.join(provider.roles)})")
14
    print()

Properties

is_host

Checks if the provider has the HOST role. Returns bool.

1
# Fetch catalog collections
2
archive_collections = up42.ProductGlossary.get_collections(
3
    collection_type = up42.CollectionType.ARCHIVE,
4
    sort_by = up42.CollectionSorting.name.asc,
5
)
6

7
# Define output, return only providers who are hosts
8
for collection in archive_collections:
9
    print(f"- Title:  {collection.title}")
10
    print(f"  Name:   {collection.name}")
11
    for provider in collection.providers:
12
        if getattr(provider, "is_host", False):
13
            print(f"  Host:   {provider.name}")
14
    print()

Methods

search

Searches the catalog and retrieves scenes. Returns Iterator[Scene]. Use itertools.islice to offset and limit the results.

Parameter	Description
`bbox`	Optional[BoundingBox] A search geometry in the GeoJSON format. Returns images that intersect with the defined rectangle and may not fully cover it. Use only if `intersects` isn’t specified.
`intersects`	Optional[geojson.Polygon] A polygon in the GeoJSON format.
`start_date`	Optional[str] Search for full scenes that were acquired after the given start date, in the `YYYY-MM-DD` format.
`end_date`	Optional[str] Search for full scenes that were acquired before the given end date, in the `YYYY-MM-DD` format.
`query`	Optional[dict] A STAC query object.
`collections`	Optional[list[str]] The names of the collections whose full scenes you want to include in search results.

1
import pandas as pd
2
import geojson
3
from itertools import islice
4

5
# Select the host
6
host = "oneatlas"
7

8
# Fetch catalog collections
7 collapsed lines
9
archive_collections = up42.ProductGlossary.get_collections(
10
    collection_type = up42.CollectionType.ARCHIVE,
11
    sort_by = up42.CollectionSorting.name.asc,
12
)
13

14
# Find the provider matching the host name that's marked as a host
15
host_provider = next((p for c in archive_collections for p in c.providers if p.name == host and getattr(p, "is_host", False)), None)
16

17
# Define search geometry
13 collapsed lines
18
geometry = {
19
    "type": "Polygon",
20
    "coordinates": [[
21
        [13.369713, 52.452327],
22
        [13.369713, 52.470760],
23
        [13.339159, 52.470760],
24
        [13.339159, 52.452327],
25
        [13.369713, 52.452327]
26
    ]]
27
}
28

29
# Wrap the geometry into a GeoJSON FeatureCollection
30
features = geojson.FeatureCollection(features=[geojson.Feature(geometry=geometry)])
31

32
# Search for scenes using the host
33
scenes = host_provider.search(
34
    collections=["SPOT", "phr"],
35
    intersects=geometry,
36
    start_date="2022-06-01",
37
    end_date="2022-12-31",
38
    query={
39
        "cloudCoverage": {"LT": 20}
40
    }
41
)
42

43
# Define output, return found scenes and their details
44
scene_ids = [scene.id for scene in islice(scenes, 0, 5)] # Print first 5 results
45
print(f"Displaying the first {len(scene_ids)} scenes found.")
46

47
# Display the table
48
df = pd.DataFrame(scene_ids, columns=["Scene ID"])
49
display(df)

Class: Scene

A data class that represents a scene in the system.

Attributes

Attribute	Description
`id`	str The scene ID.
`bbox`	Optional[BoundingBox] The bounding box.
`geometry`	Union[geojson.Polygon, geojson.MultiPolygon] The geometry in the GeoJSON format.
`datetime`	Optional[str] The date and time when the sensor acquired the data.
`start_datetime`	Optional[str] The date and time when the sensor started the acquisition process.
`end_datetime`	Optional[str] The date and time when the sensor finished the acquisition process.
`constellation`	str The name of the sensor.
`collection`	str The name of the collection.
`cloud_coverage`	Optional[float] The percentage of cloud coverage.
`resolution`	Optional[float] The nominal resolution, in meters.
`delivery_time`	Optional[Literal[“MINUTES”, “HOURS”, “DAYS”]] The unit of data delivery time.
`producer`	str The name of the producer. Data producers are companies that initially acquired and processed the source data. Data acquired by a producer can be distributed to various hosts.
`quicklook`	utils.ImageFile The quicklook file. Quicklooks are low-resolution scene previews.
`provider_properties`	dict Additional properties returned by the provider.

1
import geojson
2
from itertools import islice
3

4
# Select the host
5
host = "oneatlas"
6

7
# Fetch catalog collections
15 collapsed lines
8
archive_collections = up42.ProductGlossary.get_collections(
9
    collection_type = up42.CollectionType.ARCHIVE,
10
    sort_by = up42.CollectionSorting.name.asc,
11
)
12

13
# Find the provider matching the selected host name that's marked as a host
14
host_provider = next(
15
    (
16
        p
17
        for c in archive_collections
18
        for p in c.providers
19
        if p.name == host and getattr(p, "is_host", False)
20
    ),
21
    None,
22
)
23

24
# Define search geometry
15 collapsed lines
25
geometry = {
26
    "type": "Polygon",
27
    "coordinates": [
28
        [
29
            [13.369713, 52.452327],
30
            [13.369713, 52.470760],
31
            [13.339159, 52.470760],
32
            [13.339159, 52.452327],
33
            [13.369713, 52.452327],
34
        ]
35
    ],
36
}
37

38
# Wrap the geometry into a GeoJSON FeatureCollection
39
features = geojson.FeatureCollection(features=[geojson.Feature(geometry=geometry)])
40

41
# Search for scenes using the host
42
scenes = host_provider.search(
43
    collections=["SPOT", "phr"],
44
    intersects=geometry,
45
    start_date="2022-06-01",
46
    end_date="2022-12-31",
47
    query={"cloudCoverage": {"LT": 20}},
48
)
49

50
# Define output
51
for scene in islice(scenes, 0, 5): # Print first 5 results
52
    print(f"- Scene ID: {scene.id}")
53
    print(f"  Bounding box: {scene.bbox}")
54
    print(f"  Geometry: {scene.geometry}")
55
    print(f"  Acquisition date and time: {scene.datetime}")
56
    print(f"  Acquisition start: {scene.start_datetime}")
57
    print(f"  Acquisition end: {scene.end_datetime}")
58
    print(f"  Constellation: {scene.constellation}")
59
    print(f"  Collection: {scene.collection}")
60
    print(f"  Cloud coverage: {scene.cloud_coverage}%")
61
    print(f"  Resolution: {scene.resolution} m")
62
    print(f"  Delivery time: {scene.delivery_time}")
63
    print(f"  Producer: {scene.producer}")
64
    print(f"  Quicklook: {scene.quicklook}\n")

Class: DataProduct

A data class that represents a data product in the system.

Attributes

Attribute	Description
`name`	str The data product name.
`title`	str The title of the data product.
`description`	str The description of the data product.
`id`	Optional[str] The data product ID.
`eula_id`	Optional[str] The EULA ID.

1
from itertools import chain
2

3
# Fetch collections
18 collapsed lines
4
tasking_collections = up42.ProductGlossary.get_collections(
5
    collection_type = up42.CollectionType.TASKING,
6
    sort_by = up42.CollectionSorting.name.asc,
7
)
8

9
archive_collections = up42.ProductGlossary.get_collections(
10
    collection_type = up42.CollectionType.ARCHIVE,
11
    sort_by = up42.CollectionSorting.name.asc,
12
)
13

14
all_collections = chain(tasking_collections, archive_collections)
15

16
# Create a single generator for all data products
17
all_products = (
18
    product
19
    for collection in all_collections
20
    for product in collection.data_products
21
)
22

23
# Define output
24
def print_product_info(product):
25
    print(f"Name:         {product.name}")
26
    print(f"Title:        {product.title}")
27
    print(f"Description:  {(product.description or '').replace(chr(10), ' ').strip()}")
28
    print(f"ID:           {product.id}")
29
    print(f"EULA ID:      {product.eula_id}\n")
30

31
# Print information for data products
32
for product in all_products:
33
    print_product_info(product)

Properties

schema

Retrieves the schema of the data product. Returns Optional[dict].

1
from itertools import chain
2

3
# Select a data product
4
data_product_name="sentinel-2-level-2a"
5

6
# Fetch collections
11 collapsed lines
7
tasking_collections = up42.ProductGlossary.get_collections(
8
    collection_type = up42.CollectionType.TASKING,
9
    sort_by = up42.CollectionSorting.name.asc,
10
)
11

12
archive_collections = up42.ProductGlossary.get_collections(
13
    collection_type = up42.CollectionType.ARCHIVE,
14
    sort_by = up42.CollectionSorting.name.asc,
15
)
16

17
all_collections = chain(tasking_collections, archive_collections)
18

19
# Retrieve the first matching data product's schema
20
schema = None
21
all_products = (
22
    product
23
    for collection in all_collections
24
    for product in collection.data_products
25
)
26

27
# Look up the schema for the selected data product
28
for product in all_products:
29
    if product.name == data_product_name:
30
        schema = product.schema
31
        break
32
schema

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Glossary in SDK

Choose data offerings from the glossary using the SDK.

Overview

Class: ProductGlossary

Methods

get_collections

Class: Collection

Attributes

Class: CollectionType

Constants

Class: CollectionSorting

Attributes

Class: CollectionMetadata

Attributes

Class: ResolutionValue

Attributes

Class: Provider

Attributes

Properties

is_host

Methods

search

Class: Scene

Attributes

Class: DataProduct

Attributes

Properties

schema

Learn more