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
2022-08-22 10:27:21	ga_s2am_ard_3-2-1_53HNA_2022-08-22_final
2022-09-01 10:27:21	ga_s2am_ard_3-2-1_53HNA_2022-09-01_final
2022-09-11 10:27:19	ga_s2am_ard_3-2-1_53HNA_2022-09-11_final
2022-09-21 10:27:16	ga_s2am_ard_3-2-1_53HNA_2022-09-21_final
2022-10-01 10:27:16	ga_s2am_ard_3-2-1_53HNA_2022-10-01_final
2022-10-11 10:27:14	ga_s2am_ard_3-2-1_53HNA_2022-10-11_final
2022-10-21 10:27:10	ga_s2am_ard_3-2-1_53HNA_2022-10-21_final
2022-10-31 10:27:12	ga_s2am_ard_3-2-1_53HNA_2022-10-31_final
2022-11-10 10:27:12	ga_s2am_ard_3-2-1_53HNA_2022-11-10_final
2022-11-20 10:27:09	ga_s2am_ard_3-2-1_53HNA_2022-11-20_final
2022-11-30 10:27:09	ga_s2am_ard_3-2-1_53HNA_2022-11-30_final
2022-12-10 10:27:09	ga_s2am_ard_3-2-1_53HNA_2022-12-10_final
2022-12-13 10:37:03	ga_s2am_ard_3-2-1_53HNA_2022-12-13_nrt.stac-item
2022-12-20 10:27:07	ga_s2am_ard_3-2-1_53HNA_2022-12-20_final
2022-12-23 10:37:01	ga_s2am_ard_3-2-1_53HNA_2022-12-23_nrt.stac-item
2022-12-30 10:27:07	ga_s2am_ard_3-2-1_53HNA_2022-12-30_final
2023-01-02 10:37:02	ga_s2am_ard_3-2-1_53HNA_2023-01-02_nrt.stac-item
2023-01-09 10:27:07	ga_s2am_ard_3-2-1_53HNA_2023-01-09_final
2023-01-12 10:37:01	ga_s2am_ard_3-2-1_53HNA_2023-01-12_nrt.stac-item
2023-01-19 10:27:03	ga_s2am_ard_3-2-1_53HNA_2023-01-19_final
2023-01-22 10:36:59	ga_s2am_ard_3-2-1_53HNA_2023-01-22_nrt.stac-item
2023-01-29 10:27:06	ga_s2am_ard_3-2-1_53HNA_2023-01-29_final
2023-02-01 10:37:01	ga_s2am_ard_3-2-1_53HNA_2023-02-01_nrt.stac-item
2023-02-08 10:27:07	ga_s2am_ard_3-2-1_53HNA_2023-02-08_final
2023-02-11 10:37:01	ga_s2am_ard_3-2-1_53HNA_2023-02-11_nrt.stac-item
2023-02-18 10:27:05	ga_s2am_ard_3-2-1_53HNA_2023-02-18_final
2023-02-21 10:37:00	ga_s2am_ard_3-2-1_53HNA_2023-02-21_nrt.stac-item
2023-02-28 10:27:06	ga_s2am_ard_3-2-1_53HNA_2023-02-28_final
2023-03-03 10:37:00	ga_s2am_ard_3-2-1_53HNA_2023-03-03_nrt
2023-03-10 10:27:03	ga_s2am_ard_3-2-1_53HNA_2023-03-10_final
2023-03-13 10:36:59	ga_s2am_ard_3-2-1_53HNA_2023-03-13_nrt
2023-03-20 10:27:07	ga_s2am_ard_3-2-1_53HNA_2023-03-20_final
2023-03-23 10:37:02	ga_s2am_ard_3-2-1_53HNA_2023-03-23_nrt
2023-03-30 10:27:00	ga_s2am_ard_3-2-1_53HNA_2023-03-30_final
2023-03-30 10:27:07	ga_s2am_ard_3-2-1_53HNA_2023-03-30_final
2023-04-02 10:37:02	ga_s2am_ard_3-2-1_53HNA_2023-04-02_nrt
2023-04-09 10:27:09	ga_s2am_ard_3-2-1_53HNA_2023-04-09_final
2023-04-12 10:37:03	ga_s2am_ard_3-2-1_53HNA_2023-04-12_nrt
2023-04-19 10:27:07	ga_s2am_ard_3-2-1_53HNA_2023-04-19_final
2023-04-22 10:37:01	ga_s2am_ard_3-2-1_53HNA_2023-04-22_nrt
2023-04-29 10:27:09	ga_s2am_ard_3-2-1_53HNA_2023-04-29_final
2023-05-02 10:37:02	ga_s2am_ard_3-2-1_53HNA_2023-05-02_nrt
2023-05-09 10:27:07	ga_s2am_ard_3-2-1_53HNA_2023-05-09_final
2023-05-09 10:27:13	ga_s2am_ard_3-2-1_53HNA_2023-05-09_final
2023-05-12 10:37:01	ga_s2am_ard_3-2-1_53HNA_2023-05-12_nrt
2023-05-19 10:27:11	ga_s2am_ard_3-2-1_53HNA_2023-05-19_final
2023-05-22 10:37:05	ga_s2am_ard_3-2-1_53HNA_2023-05-22_nrt
2023-05-29 10:27:12	ga_s2am_ard_3-2-1_53HNA_2023-05-29_final
2023-06-01 10:37:06	ga_s2am_ard_3-2-1_53HNA_2023-06-01_nrt
2023-06-08 10:27:12	ga_s2am_ard_3-2-1_53HNA_2023-06-08_final
2023-06-11 10:37:06	ga_s2am_ard_3-2-1_53HNA_2023-06-11_nrt
2023-06-18 10:27:13	ga_s2am_ard_3-2-1_53HNA_2023-06-18_final
2023-06-21 10:37:06	ga_s2am_ard_3-2-1_53HNA_2023-06-21_nrt
2023-06-28 10:27:12	ga_s2am_ard_3-2-1_53HNA_2023-06-28_final
2023-07-01 10:37:06	ga_s2am_ard_3-2-1_53HNA_2023-07-01_nrt
2023-07-08 10:27:14	ga_s2am_ard_3-2-1_53HNA_2023-07-08_final
2023-07-11 10:37:07	ga_s2am_ard_3-2-1_53HNA_2023-07-11_nrt
2023-07-18 10:27:13	ga_s2am_ard_3-2-1_53HNA_2023-07-18_final
2023-07-21 10:37:06	ga_s2am_ard_3-2-1_53HNA_2023-07-21_interim
2023-07-28 10:27:14	ga_s2am_ard_3-2-1_53HNA_2023-07-28_final
2023-07-31 10:37:07	ga_s2am_ard_3-2-1_53HNA_2023-07-31_nrt
2023-08-07 10:27:13	ga_s2am_ard_3-2-1_53HNA_2023-08-07_final
2023-08-17 10:27:14	ga_s2am_ard_3-2-1_53HNA_2023-08-17_final
2023-08-20 10:37:08	ga_s2am_ard_3-2-1_53HNA_2023-08-20_nrt
2023-08-27 10:27:14	ga_s2am_ard_3-2-1_53HNA_2023-08-27_final
2023-08-30 10:37:07	ga_s2am_ard_3-2-1_53HNA_2023-08-30_nrt
2023-09-06 10:27:14	ga_s2am_ard_3-2-1_53HNA_2023-09-06_final
2023-09-09 10:37:07	ga_s2am_ard_3-2-1_53HNA_2023-09-09_nrt
2023-09-16 10:27:12	ga_s2am_ard_3-2-1_53HNA_2023-09-16_final
2023-09-19 10:37:05	ga_s2am_ard_3-2-1_53HNA_2023-09-19_nrt
2023-09-26 10:27:11	ga_s2am_ard_3-2-1_53HNA_2023-09-26_final
2023-09-29 10:37:04	ga_s2am_ard_3-2-1_53HNA_2023-09-29_nrt
2023-10-06 10:27:09	ga_s2am_ard_3-2-1_53HNA_2023-10-06_final
2023-10-09 10:37:02	ga_s2am_ard_3-2-1_53HNA_2023-10-09_nrt
2023-10-16 10:27:07	ga_s2am_ard_3-2-1_53HNA_2023-10-16_final
2023-10-19 10:37:02	ga_s2am_ard_3-2-1_53HNA_2023-10-19_nrt
2023-10-26 10:27:09	ga_s2am_ard_3-2-1_53HNA_2023-10-26_final
2023-10-29 10:37:02	ga_s2am_ard_3-2-1_53HNA_2023-10-29_nrt
2023-11-05 10:27:08	ga_s2am_ard_3-2-1_53HNA_2023-11-05_final
2023-11-08 10:37:01	ga_s2am_ard_3-2-1_53HNA_2023-11-08_nrt
2023-11-15 10:27:07	ga_s2am_ard_3-2-1_53HNA_2023-11-15_final
2023-11-18 10:37:00	ga_s2am_ard_3-2-1_53HNA_2023-11-18_nrt
2023-11-25 10:27:03	ga_s2am_ard_3-2-1_53HNA_2023-11-25_final
2023-12-05 10:27:02	ga_s2am_ard_3-2-1_53HNA_2023-12-05_final
2023-12-15 10:27:04	ga_s2am_ard_3-2-1_53HNA_2023-12-15_final
2023-12-25 10:27:05	ga_s2am_ard_3-2-1_53HNA_2023-12-25_final
2024-01-04 10:27:05	ga_s2am_ard_3-2-1_53HNA_2024-01-04_final
2024-01-14 10:27:02	ga_s2am_ard_3-2-1_53HNA_2024-01-14_final
2024-01-24 10:27:02	ga_s2am_ard_3-2-1_53HNA_2024-01-24_final
2024-02-03 10:27:04	ga_s2am_ard_3-2-1_53HNA_2024-02-03_final
2024-02-13 10:27:06	ga_s2am_ard_3-2-1_53HNA_2024-02-13_final
2024-02-23 10:27:06	ga_s2am_ard_3-2-1_53HNA_2024-02-23_final
2024-03-04 10:27:09	ga_s2am_ard_3-2-1_53HNA_2024-03-04_final
2024-03-14 10:27:08	ga_s2am_ard_3-2-1_53HNA_2024-03-14_final
2024-03-17 10:37:02	ga_s2am_ard_3-2-1_53HNA_2024-03-17_final
2024-03-24 10:27:10	ga_s2am_ard_3-2-1_53HNA_2024-03-24_final
2024-04-03 10:27:01	ga_s2am_ard_3-2-1_53HNA_2024-04-03_final
2024-04-03 10:27:08	ga_s2am_ard_3-2-1_53HNA_2024-04-03_final
2024-04-06 10:37:00	ga_s2am_ard_3-2-1_53HNA_2024-04-06_nrt
2024-04-13 10:27:10	ga_s2am_ard_3-2-1_53HNA_2024-04-13_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

All years