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: CollectionType

An enumeration class that defines types of geospatial collections.

Constants

Constant Description Value

Constant	Description	Value
`ARCHIVE`	str A catalog collection.	`ARCHIVE`
`TASKING`	str A tasking collection.	`TASKING`

ARCHIVE

str

A catalog collection.

ARCHIVE

TASKING

str

A tasking collection.

TASKING

1
# Fetch collections
2
tasking_collections = list(
3
    up42.ProductGlossary.get_collections(
4
        collection_type=up42.CollectionType.TASKING,
5
        sort_by=up42.CollectionSorting.name.asc,
6
    )
7
)
8

9
archive_collections = list(
10
    up42.ProductGlossary.get_collections(
11
        collection_type=up42.CollectionType.ARCHIVE,
12
        sort_by=up42.CollectionSorting.name.asc,
13
    )
14
)
15

16
# Define output
9 collapsed lines
17
print(f"Tasking collections")
18
for collection in tasking_collections:
19
    print(f"    {collection.title}: {collection.name}")
20
    print(f"    {collection.description}\n")
21

22
print(f"Catalog collections")
23
for collection in archive_collections:
24
    print(f"    {collection.title}: {collection.name}")
25
    print(f"    {collection.description}\n")

Class: ResolutionValue

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

Attributes

Attribute Description

Attribute	Description
`minimum`	float The best possible resolution available for the collection, in meters.
`description`	Optional[str] A description of the resolution.
`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 possible resolution available for the collection, in meters.

description

Optional[str]

A description of the resolution.

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
# Fetch collections
15 collapsed lines
2
tasking_collections = list(
3
    up42.ProductGlossary.get_collections(
4
        collection_type=up42.CollectionType.TASKING,
5
        sort_by=up42.CollectionSorting.name.asc,
6
    )
7
)
8

9
archive_collections = list(
10
    up42.ProductGlossary.get_collections(
11
        collection_type=up42.CollectionType.ARCHIVE,
12
        sort_by=up42.CollectionSorting.name.asc,
13
    )
14
)
15

16
all_collections = tasking_collections + archive_collections
17

18
# Define output
19
for collection in all_collections:
20
    print(f"- Title:    {collection.title}")
21
    print(f"  Name:     {collection.name}")
22
    print("  Metadata:")
23
    print(f"    Product type:       {collection.metadata.product_type}")
24
    print(f"    Resolution class:   {collection.metadata.resolution_class}")
25
    print(f"    Min resolution:     {collection.metadata.resolution_value.minimum} m")
26
    if collection.metadata.resolution_value.maximum:
27
        print(f"    Max resolution: {collection.metadata.resolution_value.maximum} m")
28
    print()

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 spatial 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 spatial resolution class.

resolution_value

Optional[ResolutionValue]

The level of detail achievable for the collection.

1
# Fetch collections
15 collapsed lines
2
tasking_collections = list(
3
    up42.ProductGlossary.get_collections(
4
        collection_type=up42.CollectionType.TASKING,
5
        sort_by=up42.CollectionSorting.name.asc,
6
    )
7
)
8

9
archive_collections = list(
10
    up42.ProductGlossary.get_collections(
11
        collection_type=up42.CollectionType.ARCHIVE,
12
        sort_by=up42.CollectionSorting.name.asc,
13
    )
14
)
15

16
all_collections = tasking_collections + archive_collections
17

18
# Define output
19
for collection in all_collections:
20
    print(f"- Title:    {collection.title}")
21
    print(f"  Name:     {collection.name}")
22
    print("  Metadata:")
23
    print(f"    Product type:       {collection.metadata.product_type}")
24
    print(f"    Resolution class:   {collection.metadata.resolution_class}")
25
    print(f"    Min resolution:     {collection.metadata.resolution_value.minimum} m")
26
    if collection.metadata.resolution_value.maximum:
27
        print(f"    Max resolution: {collection.metadata.resolution_value.maximum} m")
28
    print()

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 spatial 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

3
# Select the host
4
host = "oneatlas"
5

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

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# Find the provider instance matching the selected host name that is marked as a host
15
host_provider = next(
16
    (
17
        p
18
        for c in archive_collections
19
        for p in c.providers
20
        if p.name == host and getattr(p, "is_host", False)
21
    ),
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    None,
23
)
24

25
# Define search geometry
15 collapsed lines
26
geometry = {
27
    "type": "Polygon",
28
    "coordinates": [
29
        [
30
            [13.369713, 52.452327],
31
            [13.369713, 52.470760],
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            [13.339159, 52.470760],
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            [13.339159, 52.452327],
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            [13.369713, 52.452327],
35
        ]
36
    ],
37
}
38

39
# Wrap the geometry into a GeoJSON FeatureCollection
40
features = geojson.FeatureCollection(features=[geojson.Feature(geometry=geometry)])
41

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# Search for scenes using the host
43
scenes = list(
44
    host_provider.search(
45
        collections=["SPOT", "phr"],
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        intersects=geometry,
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        start_date="2022-06-01",
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        end_date="2022-12-31",
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        query={"cloudCoverage": {"LT": 20}},
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    )
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)
52

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# Define output, return found scenes and their details
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for scene in scenes:
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    print(f"- Scene ID: {scene.id}")
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    print(f"  Bounding box: {scene.bbox}")
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    print(f"  Geometry: {scene.geometry}")
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    print(f"  Acquisition date and time: {scene.datetime}")
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    print(f"  Acquisition start: {scene.start_datetime}")
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    print(f"  Acquisition end: {scene.end_datetime}")
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    print(f"  Constellation: {scene.constellation}")
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    print(f"  Collection: {scene.collection}")
63
    print(f"  Cloud coverage: {scene.cloud_coverage}%")
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    print(f"  Resolution: {scene.resolution} m")
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    print(f"  Delivery time: {scene.delivery_time}")
66
    print(f"  Producer: {scene.producer}")
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    print(f"  Quicklook: {scene.quicklook}\n")

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.
`description`	str The description of the provider.
`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.

1
# Fetch catalog collections
2
archive_collections = list(
3
    up42.ProductGlossary.get_collections(
4
        collection_type=up42.CollectionType.ARCHIVE,
5
        sort_by=up42.CollectionSorting.name.asc,
6
    )
7
)
8

9
# Define output, return hosts and producers by collection
10
for collection in archive_collections:
11
    print(f"- Title:  {collection.title}")
12
    print(f"  Name:   {collection.name}")
13
    print("  Providers:")
14
    for provider in collection.providers:
15
        print(f"    {provider.name} ({', '.join(provider.roles)})")
16
    print()

Properties

is_host

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

1
# Fetch catalog collections
2
archive_collections = list(
3
    up42.ProductGlossary.get_collections(
4
        collection_type=up42.CollectionType.ARCHIVE,
5
        sort_by=up42.CollectionSorting.name.asc,
6
    )
7
)
8

9
# Define output, return only providers who are hosts
10
for collection in archive_collections:
11
    print(f"- Title:  {collection.title}")
12
    print(f"  Name:   {collection.name}")
13
    for provider in collection.providers:
14
        if getattr(provider, "is_host", False):
15
            print(f"  Host:   {provider.name}")
16
    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

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

7
# Fetch catalog collections
9 collapsed lines
8
archive_collections = list(
9
    up42.ProductGlossary.get_collections(
10
        collection_type=up42.CollectionType.ARCHIVE,
11
        sort_by=up42.CollectionSorting.name.asc,
12
    )
13
)
14

15
# Find the provider instance matching the selected host name that is marked as a host
16
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)
17

18
# Define search geometry
13 collapsed lines
19
geometry = {
20
    "type": "Polygon",
21
    "coordinates": [[
22
        [13.369713, 52.452327],
23
        [13.369713, 52.470760],
24
        [13.339159, 52.470760],
25
        [13.339159, 52.452327],
26
        [13.369713, 52.452327]
27
    ]]
28
}
29

30
# Wrap the geometry into a GeoJSON FeatureCollection
31
features = geojson.FeatureCollection(features=[geojson.Feature(geometry=geometry)])
32

33
# Search for scenes using the host
34
scenes = list(host_provider.search(
35
    collections=["SPOT", "phr"],
36
    intersects=geometry,
37
    start_date="2022-06-01",
38
    end_date="2022-12-31",
39
    query={
40
        "cloudCoverage": {"LT": 20}
41
    }
42
))
43

44
# Define output, return found scenes and their details
45
print(f"Found {len(scenes)} scenes matching the criteria.")
46
scene_ids = [scene.id for scene in scenes]
47

48
# Display the table
49
df = pd.DataFrame(scene_ids, columns=["Scene ID"])
50
display(df)

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
# Fetch collections
15 collapsed lines
2
tasking_collections = list(
3
    up42.ProductGlossary.get_collections(
4
        collection_type=up42.CollectionType.TASKING,
5
        sort_by=up42.CollectionSorting.name.asc,
6
    )
7
)
8

9
archive_collections = list(
10
    up42.ProductGlossary.get_collections(
11
        collection_type=up42.CollectionType.ARCHIVE,
12
        sort_by=up42.CollectionSorting.name.asc,
13
    )
14
)
15

16
all_collections = tasking_collections + archive_collections
17

18
# Define output
19
def print_product_info(product):
20
    print(f"Name:         {product.name}")
21
    print(f"Title:        {product.title}")
22
    print(f"Description:  {(product.description or '').replace(chr(10), ' ').strip()}")
23
    print(f"ID:           {product.id}")
24
    print(f"EULA ID:      {product.eula_id}\n")
25

26
# Print information for all data products
27
for collection in all_collections:
28
    for product in collection.data_products:
29
        print_product_info(product)

Properties

schema

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

1
# Select a data product
2
data_product_name="sentinel-2-level-2a"
3

4
# Fetch collections
15 collapsed lines
5
tasking_collections = list(
6
    up42.ProductGlossary.get_collections(
7
        collection_type=up42.CollectionType.TASKING,
8
        sort_by=up42.CollectionSorting.name.asc,
9
    )
10
)
11

12
archive_collections = list(
13
    up42.ProductGlossary.get_collections(
14
        collection_type=up42.CollectionType.ARCHIVE,
15
        sort_by=up42.CollectionSorting.name.asc,
16
    )
17
)
18

19
all_collections = tasking_collections + archive_collections
20

21
# Create a dictionary of all data product names and their schemas
22
product_schemas = {
23
    product.name: product.schema
24
    for collection in all_collections
25
    for product in collection.data_products
26
}
27

28
# Look up the schema for the selected data product
29
schema = product_schemas.get(data_product_name)
30
schema

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
# Fetch collections
15 collapsed lines
2
tasking_collections = list(
3
    up42.ProductGlossary.get_collections(
4
        collection_type=up42.CollectionType.TASKING,
5
        sort_by=up42.CollectionSorting.name.asc,
6
    )
7
)
8

9
archive_collections = list(
10
    up42.ProductGlossary.get_collections(
11
        collection_type=up42.CollectionType.ARCHIVE,
12
        sort_by=up42.CollectionSorting.name.asc,
13
    )
14
)
15

16
all_collections = tasking_collections + archive_collections
17

18
# Define output
19
for collection in all_collections:
20
    print(f"- Title:        {collection.title}")
21
    print(f"  Name:         {collection.name}")
22
    print(f"  Description:  {collection.description}")
23
    print(f"  Type:         {collection.type.value}")
24
    print("  Integrations:")
25
    for integration in collection.integrations:
26
        print(f"    {integration}")
27
    print("  Providers:")
28
    for provider in collection.providers:
29
        print(f"    {provider.name} ({', '.join(provider.roles)})")
30
    print("  Data products:")
31
    for product in collection.data_products:
32
        print(f"  - Title:  {product.title}")
33
        print(f"    Name:   {product.name}")
34
        print(f"    ID:     {product.id}")
35
    print("  Metadata:")
36
    print(f"    Product type:       {collection.metadata.product_type}")
37
    print(f"    Resolution class:   {collection.metadata.resolution_class}")
38
    print(f"    Min resolution:     {collection.metadata.resolution_value.minimum} m")
39
    if collection.metadata.resolution_value.maximum:
40
        print(f"    Max resolution: {collection.metadata.resolution_value.maximum} m")
41
    print()

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
glossary = up42.glossary.ProductGlossary
2

3
tasking_collections = glossary.get_collections(
4
    collection_type = up42.glossary.CollectionType.TASKING,
5
    sort_by = up42.glossary.CollectionSorting.name.asc,
6
)
7

8
for collection in tasking_collections:
9
    print(f"{collection.name}")

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 = list(up42.ProductGlossary.get_collections(
3
    collection_type=up42.CollectionType.TASKING,
4
    sort_by = up42.CollectionSorting.name.asc,
5
))
6

7
archive_collections = list(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")

Glossary in SDK

Choose data offerings from the glossary using the SDK.

Overview

Class: CollectionType

Constants

Class: ResolutionValue

Attributes

Class: CollectionMetadata

Attributes

Class: Scene

Attributes

Class: Provider

Attributes

Properties

is_host

Methods

search

Class: DataProduct

Attributes

Properties

schema

Class: Collection

Attributes

Class: CollectionSorting

Attributes

Class: ProductGlossary

Methods

get_collections

Learn more

API docs | Glossary

Console docs | Collections