Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2022-10-26 11:17:05	ga_s2am_ard_3-2-1_52HBG_2022-10-26_nrt.stac-item
2022-12-15 11:16:49	ga_s2am_ard_3-2-1_52HBH_2022-12-15_nrt.stac-item
2022-12-25 11:16:47	ga_s2am_ard_3-2-1_52HBH_2022-12-25_nrt.stac-item
2022-12-25 11:17:00	ga_s2am_ard_3-2-1_52HBG_2022-12-25_nrt.stac-item
2023-01-04 11:16:48	ga_s2am_ard_3-2-1_52HBH_2023-01-04_nrt.stac-item
2023-01-04 11:17:01	ga_s2am_ard_3-2-1_52HBG_2023-01-04_nrt.stac-item
2023-01-14 11:16:46	ga_s2am_ard_3-2-1_52HBH_2023-01-14_nrt.stac-item
2023-01-14 11:17:00	ga_s2am_ard_3-2-1_52HBG_2023-01-14_nrt.stac-item
2023-01-14 11:17:06	ga_s2am_ard_3-2-1_52HBF_2023-01-14_nrt.stac-item
2023-01-24 11:16:45	ga_s2am_ard_3-2-1_52HBH_2023-01-24_nrt.stac-item
2023-01-24 11:16:59	ga_s2am_ard_3-2-1_52HBG_2023-01-24_nrt.stac-item
2023-02-03 11:16:48	ga_s2am_ard_3-2-1_52HBH_2023-02-03_nrt.stac-item
2023-02-03 11:17:01	ga_s2am_ard_3-2-1_52HBG_2023-02-03_nrt.stac-item
2023-02-13 11:16:37	ga_s2am_ard_3-2-1_52HBH_2023-02-13_nrt.stac-item
2023-02-13 11:16:47	ga_s2am_ard_3-2-1_52HBH_2023-02-13_nrt.stac-item
2023-02-13 11:17:00	ga_s2am_ard_3-2-1_52HBG_2023-02-13_nrt.stac-item
2023-02-23 11:16:46	ga_s2am_ard_3-2-1_52HBH_2023-02-23_nrt
2023-02-23 11:17:00	ga_s2am_ard_3-2-1_52HBG_2023-02-23_nrt
2023-03-05 11:16:46	ga_s2am_ard_3-2-1_52HBH_2023-03-05_nrt
2023-03-05 11:16:59	ga_s2am_ard_3-2-1_52HBG_2023-03-05_nrt
2023-03-15 11:16:46	ga_s2am_ard_3-2-1_52HBH_2023-03-15_nrt
2023-03-15 11:16:59	ga_s2am_ard_3-2-1_52HBG_2023-03-15_nrt
2023-03-25 11:16:47	ga_s2am_ard_3-2-1_52HBH_2023-03-25_nrt
2023-03-25 11:17:01	ga_s2am_ard_3-2-1_52HBG_2023-03-25_nrt
2023-04-04 11:16:48	ga_s2am_ard_3-2-1_52HBH_2023-04-04_nrt
2023-04-04 11:17:02	ga_s2am_ard_3-2-1_52HBG_2023-04-04_nrt
2023-04-14 11:16:49	ga_s2am_ard_3-2-1_52HBH_2023-04-14_nrt
2023-04-14 11:17:02	ga_s2am_ard_3-2-1_52HBG_2023-04-14_nrt
2023-04-24 11:16:48	ga_s2am_ard_3-2-1_52HBH_2023-04-24_nrt
2023-04-24 11:17:01	ga_s2am_ard_3-2-1_52HBG_2023-04-24_nrt
2023-05-04 11:16:49	ga_s2am_ard_3-2-1_52HBH_2023-05-04_nrt
2023-05-04 11:17:02	ga_s2am_ard_3-2-1_52HBG_2023-05-04_nrt
2023-05-14 11:16:49	ga_s2am_ard_3-2-1_52HBH_2023-05-14_nrt
2023-05-14 11:17:02	ga_s2am_ard_3-2-1_52HBG_2023-05-14_nrt
2023-05-24 11:16:52	ga_s2am_ard_3-2-1_52HBH_2023-05-24_nrt
2023-05-24 11:17:05	ga_s2am_ard_3-2-1_52HBG_2023-05-24_nrt
2023-06-03 11:16:53	ga_s2am_ard_3-2-1_52HBH_2023-06-03_nrt
2023-06-03 11:17:07	ga_s2am_ard_3-2-1_52HBG_2023-06-03_nrt
2023-06-03 11:17:13	ga_s2am_ard_3-2-1_52HBF_2023-06-03_nrt
2023-06-13 11:16:53	ga_s2am_ard_3-2-1_52HBH_2023-06-13_nrt
2023-06-13 11:17:06	ga_s2am_ard_3-2-1_52HBG_2023-06-13_nrt
2023-06-23 11:16:52	ga_s2am_ard_3-2-1_52HBH_2023-06-23_nrt
2023-06-23 11:17:05	ga_s2am_ard_3-2-1_52HBG_2023-06-23_nrt
2023-07-03 11:16:54	ga_s2am_ard_3-2-1_52HBH_2023-07-03_nrt
2023-07-03 11:17:08	ga_s2am_ard_3-2-1_52HBG_2023-07-03_nrt
2023-07-03 11:17:14	ga_s2am_ard_3-2-1_52HBF_2023-07-03_nrt
2023-07-13 11:16:48	ga_s2am_ard_3-2-1_52HBH_2023-07-13_nrt
2023-07-13 11:16:55	ga_s2am_ard_3-2-1_52HBH_2023-07-13_nrt
2023-07-13 11:17:06	ga_s2am_ard_3-2-1_52HBG_2023-07-13_nrt
2023-07-23 11:16:53	ga_s2am_ard_3-2-1_52HBH_2023-07-23_nrt
2023-07-23 11:17:06	ga_s2am_ard_3-2-1_52HBG_2023-07-23_nrt
2023-08-02 11:16:54	ga_s2am_ard_3-2-1_52HBH_2023-08-02_nrt
2023-08-02 11:17:07	ga_s2am_ard_3-2-1_52HBG_2023-08-02_nrt
2023-08-12 11:16:54	ga_s2am_ard_3-2-1_52HBH_2023-08-12_nrt
2023-08-12 11:17:07	ga_s2am_ard_3-2-1_52HBG_2023-08-12_nrt
2023-08-22 11:16:55	ga_s2am_ard_3-2-1_52HBH_2023-08-22_nrt
2023-08-22 11:17:08	ga_s2am_ard_3-2-1_52HBG_2023-08-22_nrt
2023-09-01 11:16:54	ga_s2am_ard_3-2-1_52HBH_2023-09-01_nrt
2023-09-01 11:17:07	ga_s2am_ard_3-2-1_52HBG_2023-09-01_nrt
2023-09-11 11:16:54	ga_s2am_ard_3-2-1_52HBH_2023-09-11_nrt
2023-09-11 11:17:07	ga_s2am_ard_3-2-1_52HBG_2023-09-11_nrt
2023-09-21 11:16:51	ga_s2am_ard_3-2-1_52HBH_2023-09-21_nrt
2023-09-21 11:17:03	ga_s2am_ard_3-2-1_52HBG_2023-09-21_nrt
2023-10-01 11:16:51	ga_s2am_ard_3-2-1_52HBH_2023-10-01_nrt
2023-10-01 11:17:04	ga_s2am_ard_3-2-1_52HBG_2023-10-01_nrt
2023-10-11 11:16:48	ga_s2am_ard_3-2-1_52HBH_2023-10-11_nrt
2023-10-11 11:17:00	ga_s2am_ard_3-2-1_52HBG_2023-10-11_nrt
2023-10-21 11:16:49	ga_s2am_ard_3-2-1_52HBH_2023-10-21_nrt
2023-10-21 11:17:02	ga_s2am_ard_3-2-1_52HBG_2023-10-21_nrt
2023-10-31 11:16:48	ga_s2am_ard_3-2-1_52HBH_2023-10-31_nrt
2023-10-31 11:17:01	ga_s2am_ard_3-2-1_52HBG_2023-10-31_nrt
2023-11-10 11:16:48	ga_s2am_ard_3-2-1_52HBH_2023-11-10_nrt
2023-11-10 11:17:01	ga_s2am_ard_3-2-1_52HBG_2023-11-10_nrt
2023-11-20 11:16:46	ga_s2am_ard_3-2-1_52HBH_2023-11-20_nrt
2023-11-20 11:16:59	ga_s2am_ard_3-2-1_52HBG_2023-11-20_nrt
2023-11-30 11:16:40	ga_s2am_ard_3-2-1_52HBH_2023-11-30_nrt
2023-11-30 11:16:47	ga_s2am_ard_3-2-1_52HBG_2023-11-30_nrt
2023-11-30 11:16:47	ga_s2am_ard_3-2-1_52HBH_2023-11-30_nrt
2023-11-30 11:16:53	ga_s2am_ard_3-2-1_52HBG_2023-11-30_nrt
2023-12-10 11:16:44	ga_s2am_ard_3-2-1_52HBH_2023-12-10_nrt
2023-12-10 11:16:56	ga_s2am_ard_3-2-1_52HBG_2023-12-10_nrt
2023-12-20 11:16:45	ga_s2am_ard_3-2-1_52HBH_2023-12-20_nrt
2023-12-20 11:16:58	ga_s2am_ard_3-2-1_52HBG_2023-12-20_nrt
2023-12-30 11:16:59	ga_s2am_ard_3-2-1_52HBG_2023-12-30_nrt
2024-01-09 11:16:44	ga_s2am_ard_3-2-1_52HBH_2024-01-09_nrt
2024-01-09 11:16:57	ga_s2am_ard_3-2-1_52HBG_2024-01-09_nrt
2024-01-19 11:16:40	ga_s2am_ard_3-2-1_52HBH_2024-01-19_nrt
2024-01-19 11:16:53	ga_s2am_ard_3-2-1_52HBG_2024-01-19_nrt
2024-01-29 11:16:57	ga_s2am_ard_3-2-1_52HBG_2024-01-29_nrt.stac-item
2024-02-08 11:16:57	ga_s2am_ard_3-2-1_52HBG_2024-02-08_nrt
2024-02-18 11:17:00	ga_s2am_ard_3-2-1_52HBG_2024-02-18_nrt
2024-02-28 11:17:01	ga_s2am_ard_3-2-1_52HBG_2024-02-28_nrt
2024-03-09 11:17:02	ga_s2am_ard_3-2-1_52HBG_2024-03-09_nrt
2024-03-19 11:17:02	ga_s2am_ard_3-2-1_52HBG_2024-03-19_nrt
2024-03-29 11:17:02	ga_s2am_ard_3-2-1_52HBG_2024-03-29_nrt
2024-04-08 11:16:57	ga_s2am_ard_3-2-1_52HBG_2024-04-08_nrt
2024-04-08 11:17:01	ga_s2am_ard_3-2-1_52HBG_2024-04-08_nrt
2024-04-18 11:17:04	ga_s2am_ard_3-2-1_52HBG_2024-04-18_nrt
2024-04-28 11:17:04	ga_s2am_ard_3-2-1_52HBG_2024-04-28_nrt
2024-05-08 11:17:03	ga_s2am_ard_3-2-1_52HBG_2024-05-08_nrt

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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