STAC Creation
Within this repo there is a directory called scripts. Within it is a jupyter notebook STAC_creation_latest.ipynb that has python code for creating STAC json and geojson files from crawling over imagery assets. The code primarily uses the pystac library to create the STAC metadata. The STAC creation code is in active development.
Here is what the code currently does:¶
-
Users manually input metadata about the geospatial imagery products. These include: Title of the collection, description of collection and items, provider name and info.
-
Users can specify the collection date with a single entry or they can provide a csv file that lists each of the assets and their date of collection.
-
The script crawls over a user defined directory (e.g., in Cyverse DataStore) and looks for geotiff and cloud optimized geotiff (COG) files.
-
It pulls out the projection, ground sampling distance (gsd) and footprint of the imagery asset. If an asset does not have a projection, the gsd will return 0.00 meters.
-
It will assign multiple assets to a single item. This is also based on a user provided csv file that lists which assets should belong to which item.
-
It can output a static STAC with the structure catalog>>collection>>items. These will have relative links. A static catalog can be browsed by the STAC browser but it has limited ability to be queried.
-
It can output a dynamic STAC that can be ingesting into a STAC API. The structure is: collection>>index.geojson. It has absolute links. The STAC API is a lot more powerful compared with the static catalog. STAC APIs can be queried by space or time within the STAC Browser.
Additional Functionality that is Needed¶
-
Find point clouds in a directory (laz, copc) and index them in STAC. There is a 'pointcloud' extension in pystac that should make it possible.
-
Link out to COPC Viewer for point cloud visualization
STAC json and geojson examples¶
collection.json - contains the relevant metadata which you want to be visible in a STAC Browser
collection.json
{
"id": "Open-Forest-Observatory",
"description": "The [Open Forest Observatory](https://openforestobservatory.org) Project",
"stac_version": "1.0.0",
"license": "public-domain",
"links": [
{
"rel": "license",
"href": "https://creativecommons.org/licenses/publicdomain/",
"title": "public domain"
}
],
"type": "Collection",
"extent": {
"spatial": {
"bbox": [
[
-106.79191589355467,
35.648927129774336,
-106.49803161621092,
35.95744398067361
]
]
},
"temporal": {
"interval": [
[
"2022-01-01T12:00:00Z",
"2023-02-25T12:00:00Z"
]
]
}
}
}
index.geojson - list of Features in a FeatureCollection that corresponds to the Collection
index.geojson
{
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"collection": "Open-Forest-Observatory",
"stac_version": "1.0.0",
"stac_extensions": [
"https://stac-extensions.github.io/projection/v1.0.0/schema.json",
"https://stac-extensions.github.io/raster/v1.1.0/schema.json",
"https://stac-extensions.github.io/eo/v1.0.0/schema.json"
],
"id": "chm_cog.tif",
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
-106.79191589355467,
35.648927129774336
],
[
-106.49803161621092,
35.648927129774336
],
[
-106.49803161621092,
35.95744398067361
],
[
-106.79191589355467,
35.95744398067361
],
[
-106.79191589355467,
35.648927129774336
]
]
]
},
"bbox": [
-106.79191589355467,
35.648927129774336,
-106.49803161621092,
35.95744398067361
],
"properties": {
"proj:epsg": 3857,
"proj:geometry": {
"type": "Polygon",
"coordinates": [
[
[
-11888021.698108606,
4252421.194589211
],
[
-11855306.65000255,
4252421.194589211
],
[
-11855306.65000255,
4294767.308259198
],
[
-11888021.698108606,
4294767.308259198
],
[
-11888021.698108606,
4252421.194589211
]
]
]
},
"proj:bbox": [
-11888021.698108606,
4252421.194589211,
-11855306.65000255,
4294767.308259198
],
"proj:shape": [
141824,
109568
],
"proj:transform": [
0.29858214173896974,
0,
-11888021.698108606,
0,
-0.29858214173896974,
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0,
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1
],
"proj:projjson": {
"$schema": "https://proj.org/schemas/v0.4/projjson.schema.json",
"type": "ProjectedCRS",
"name": "WGS 84 / Pseudo-Mercator",
"base_crs": {
"name": "WGS 84",
"datum": {
"type": "GeodeticReferenceFrame",
"name": "World Geodetic System 1984",
"ellipsoid": {
"name": "WGS 84",
"semi_major_axis": 6378137,
"inverse_flattening": 298.257223563
}
},
"coordinate_system": {
"subtype": "ellipsoidal",
"axis": [
{
"name": "Latitude",
"abbreviation": "lat",
"direction": "north",
"unit": "degree"
},
{
"name": "Longitude",
"abbreviation": "lon",
"direction": "east",
"unit": "degree"
}
]
},
"id": {
"authority": "EPSG",
"code": 4326
}
},
"conversion": {
"name": "unnamed",
"method": {
"name": "Popular Visualisation Pseudo Mercator",
"id": {
"authority": "EPSG",
"code": 1024
}
},
"parameters": [
{
"name": "Latitude of natural origin",
"value": 0,
"unit": "degree",
"id": {
"authority": "EPSG",
"code": 8801
}
},
{
"name": "Longitude of natural origin",
"value": 0,
"unit": "degree",
"id": {
"authority": "EPSG",
"code": 8802
}
},
{
"name": "False easting",
"value": 0,
"unit": "metre",
"id": {
"authority": "EPSG",
"code": 8806
}
},
{
"name": "False northing",
"value": 0,
"unit": "metre",
"id": {
"authority": "EPSG",
"code": 8807
}
}
]
},
"coordinate_system": {
"subtype": "Cartesian",
"axis": [
{
"name": "Easting",
"abbreviation": "",
"direction": "east",
"unit": "metre"
},
{
"name": "Northing",
"abbreviation": "",
"direction": "north",
"unit": "metre"
}
]
},
"id": {
"authority": "EPSG",
"code": 3857
}
},
"datetime": "2023-04-12T20:19:05.989194Z"
},
"links": [],
"assets": {
"data": {
"href": "https://data.cyverse.org/dav-anon/iplant/home/tswetnam/jemez/chm_cog.tif",
"type": "image/tiff; application=geotiff",
"raster:bands": [
{
"data_type": "uint8",
"scale": 1,
"offset": 0,
"sampling": "area",
"statistics": {
"mean": 37.61441723935138,
"minimum": 0,
"maximum": 255,
"stddev": 57.379448784450744,
"valid_percent": 96.65515013415404
},
"histogram": {
"count": 11,
"min": 0,
"max": 255,
"buckets": [
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]
}
},
{
"data_type": "uint8",
"scale": 1,
"offset": 0,
"sampling": "area",
"statistics": {
"mean": 46.35795866974706,
"minimum": 0,
"maximum": 255,
"stddev": 64.61711636383107,
"valid_percent": 96.65515013415404
},
"histogram": {
"count": 11,
"min": 0,
"max": 255,
"buckets": [
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]
}
},
{
"data_type": "uint8",
"scale": 1,
"offset": 0,
"sampling": "area",
"statistics": {
"mean": 40.6277738585321,
"minimum": 0,
"maximum": 212,
"stddev": 54.02405921611601,
"valid_percent": 96.65515013415404
},
"histogram": {
"count": 11,
"min": 0,
"max": 212,
"buckets": [
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]
}
}
],
"eo:bands": [
{
"name": "b1",
"description": "red"
},
{
"name": "b2",
"description": "green"
},
{
"name": "b3",
"description": "blue"
}
]
}
}
}
]
}
STAC Assets in Cyverse Datastore¶
CyVerse features a set of public datasets that are curated in the CyVerse DataStore.
The assets are primarily available from the DataStore over the public WebDAV.
https://data.cyverse.org/dav-anon/
All assets must be shared as read-only with the anonymous user in the iRODS environment (accessed via the Discovery Environment, Share Data feature) in order for them to be visible and downloadable.