Product Discovery#
Product Listings#
Once a datacube instance has been created, users can explore the products and measurements stored within.
The datacube instance’s list_products
method can be used to view a list of all products available in the datacube.
Products listed under name in the following table represent the product options available when querying the datacube. The table below provides some useful information about each product, including a brief product description, the data’s license, and the product’s default crs (coordinate reference system) and resolution if applicable.
[1]:
import datacube
dc = datacube.Datacube(app="my_analysis")
dc.list_products()
[1]:
name | description | license | default_crs | default_resolution | |
---|---|---|---|---|---|
name | |||||
ls5_sr | ls5_sr | USGS Landsat 5 Collection 2 Level-2 Surface Re... | CC-BY-4.0 | None | None |
ls7_sr | ls7_sr | USGS Landsat 7 Collection 2 Level-2 Surface Re... | CC-BY-4.0 | None | None |
ls8_sr | ls8_sr | USGS Landsat 8 Collection 2 Level-2 Surface Re... | CC-BY-4.0 | None | None |
ls9_sr | ls9_sr | USGS Landsat 9 Collection 2 Level-2 Surface Re... | CC-BY-4.0 | None | None |
Measurement Listings#
Most products are associated with a range of available measurements. These can be individual satellite bands (e.g. Landsat’s near-infrared band) or statistical product summaries.
The datacube instance’s list_measurements
method can be used to interrogate the measurements associated with a specific product.
The table below includes a range of technical information about each band in the ls9_sr
product (USGS Landsat 9 Collection 2 Level-2 Surface Reflectance). This includes the measurement name, data type (dtype), data units, nodata values, any aliases which can be used to load the measurements, and any flags definitions associated with the measurement (this information is used for tasks like cloud masking).
[2]:
dc.list_measurements()
[2]:
name | dtype | units | nodata | aliases | flags_definition | ||
---|---|---|---|---|---|---|---|
product | measurement | ||||||
ls9_sr | SR_B1 | SR_B1 | uint16 | 1 | 0.0 | [band_1, coastal_aerosol] | NaN |
SR_B2 | SR_B2 | uint16 | 1 | 0.0 | [band_2, blue] | NaN | |
SR_B3 | SR_B3 | uint16 | 1 | 0.0 | [band_3, green] | NaN | |
SR_B4 | SR_B4 | uint16 | 1 | 0.0 | [band_4, red] | NaN | |
SR_B5 | SR_B5 | uint16 | 1 | 0.0 | [band_5, nir] | NaN | |
SR_B6 | SR_B6 | uint16 | 1 | 0.0 | [band_6, swir_1] | NaN | |
SR_B7 | SR_B7 | uint16 | 1 | 0.0 | [band_7, swir_2] | NaN | |
QA_PIXEL | QA_PIXEL | uint16 | bit_index | 1.0 | [pq, pixel_quality] | {'snow': {'bits': 5, 'values': {'0': 'not_high... | |
QA_RADSAT | QA_RADSAT | uint16 | bit_index | 0.0 | [radsat, radiometric_saturation] | {'nir_saturation': {'bits': 4, 'values': {'0':... | |
SR_QA_AEROSOL | SR_QA_AEROSOL | uint8 | bit_index | 1.0 | [qa_aerosol, aerosol_qa] | {'water': {'bits': 2, 'values': {'0': False, '... |