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
2021-08-23 10:46:02	ga_s2am_ard_3-2-1_52JGL_2021-08-23_final.stac-item
2021-09-05 10:55:57	ga_s2am_ard_3-2-1_52JGL_2021-09-05_final.stac-item
2021-09-12 10:46:01	ga_s2am_ard_3-2-1_52JGL_2021-09-12_final.stac-item
2021-09-15 10:55:58	ga_s2am_ard_3-2-1_52JGL_2021-09-15_final.stac-item
2021-09-22 10:46:03	ga_s2am_ard_3-2-1_52JGL_2021-09-22_final.stac-item
2021-10-02 10:46:05	ga_s2am_ard_3-2-1_52JGL_2021-10-02_final.stac-item
2021-10-12 10:46:05	ga_s2am_ard_3-2-1_52JGL_2021-10-12_final.stac-item
2021-10-15 10:56:02	ga_s2am_ard_3-2-1_52JGL_2021-10-15_final.stac-item
2021-10-22 10:46:05	ga_s2am_ard_3-2-1_52JGL_2021-10-22_final.stac-item
2021-10-25 10:56:01	ga_s2am_ard_3-2-1_52JGL_2021-10-25_final.stac-item
2021-11-04 10:56:00	ga_s2am_ard_3-2-1_52JGL_2021-11-04_final.stac-item
2021-11-11 10:46:02	ga_s2am_ard_3-2-1_52JGL_2021-11-11_final.stac-item
2021-11-24 10:55:56	ga_s2am_ard_3-2-1_52JGL_2021-11-24_final.stac-item
2021-12-01 10:46:00	ga_s2am_ard_3-2-1_52JGL_2021-12-01_final.stac-item
2021-12-14 10:55:56	ga_s2am_ard_3-2-1_52JGL_2021-12-14_final.stac-item
2021-12-21 10:46:01	ga_s2am_ard_3-2-1_52JGL_2021-12-21_final.stac-item
2021-12-24 10:55:57	ga_s2am_ard_3-2-1_52JGL_2021-12-24_final.stac-item
2021-12-31 10:46:02	ga_s2am_ard_3-2-1_52JGL_2021-12-31_final.stac-item
2022-01-03 10:55:58	ga_s2am_ard_3-2-1_52JGL_2022-01-03_final.stac-item
2022-01-10 10:46:01	ga_s2am_ard_3-2-1_52JGL_2022-01-10_final.stac-item
2022-01-13 10:55:57	ga_s2am_ard_3-2-1_52JGL_2022-01-13_final.stac-item
2022-01-23 10:55:56	ga_s2am_ard_3-2-1_52JGL_2022-01-23_final.stac-item
2022-01-30 10:46:00	ga_s2am_ard_3-2-1_52JGL_2022-01-30_final.stac-item
2022-03-01 10:46:03	ga_s2am_ard_3-2-1_52JGL_2022-03-01_final.stac-item
2022-03-04 10:56:00	ga_s2am_ard_3-2-1_52JGL_2022-03-04_final.stac-item
2022-03-14 10:56:00	ga_s2am_ard_3-2-1_52JGL_2022-03-14_final.stac-item
2022-03-21 10:46:03	ga_s2am_ard_3-2-1_52JGL_2022-03-21_final.stac-item
2022-03-31 10:46:02	ga_s2am_ard_3-2-1_52JGL_2022-03-31_final.stac-item
2022-04-03 10:55:58	ga_s2am_ard_3-2-1_52JGL_2022-04-03_final.stac-item
2022-04-10 10:46:02	ga_s2am_ard_3-2-1_52JGL_2022-04-10_final.stac-item
2022-04-13 10:55:59	ga_s2am_ard_3-2-1_52JGL_2022-04-13_final.stac-item
2022-04-20 10:46:04	ga_s2am_ard_3-2-1_52JGL_2022-04-20_final.stac-item
2022-04-23 10:56:01	ga_s2am_ard_3-2-1_52JGL_2022-04-23_final.stac-item
2022-04-30 10:46:05	ga_s2am_ard_3-2-1_52JGL_2022-04-30_final.stac-item
2022-05-03 10:56:01	ga_s2am_ard_3-2-1_52JGL_2022-05-03_final.stac-item
2022-05-10 10:46:04	ga_s2am_ard_3-2-1_52JGL_2022-05-10_final.stac-item
2022-05-13 10:56:00	ga_s2am_ard_3-2-1_52JGL_2022-05-13_final.stac-item
2022-05-20 10:46:06	ga_s2am_ard_3-2-1_52JGL_2022-05-20_final.stac-item
2022-05-23 10:56:03	ga_s2am_ard_3-2-1_52JGL_2022-05-23_final.stac-item
2022-05-30 10:46:08	ga_s2am_ard_3-2-1_52JGL_2022-05-30_final.stac-item
2022-06-02 10:56:04	ga_s2am_ard_3-2-1_52JGL_2022-06-02_final.stac-item
2022-06-09 10:46:09	ga_s2am_ard_3-2-1_52JGL_2022-06-09_final.stac-item
2022-06-12 10:56:06	ga_s2am_ard_3-2-1_52JGL_2022-06-12_final.stac-item
2022-06-19 10:46:12	ga_s2am_ard_3-2-1_52JGL_2022-06-19_final.stac-item
2022-06-22 10:56:08	ga_s2am_ard_3-2-1_52JGL_2022-06-22_final.stac-item
2022-06-29 10:46:13	ga_s2am_ard_3-2-1_52JGL_2022-06-29_final.stac-item
2022-07-02 10:56:09	ga_s2am_ard_3-2-1_52JGL_2022-07-02_final.stac-item
2022-07-09 10:46:13	ga_s2am_ard_3-2-1_52JGL_2022-07-09_final.stac-item
2022-07-12 10:56:09	ga_s2am_ard_3-2-1_52JGL_2022-07-12_final.stac-item
2022-07-19 10:46:12	ga_s2am_ard_3-2-1_52JGL_2022-07-19_final.stac-item
2022-07-22 10:56:07	ga_s2am_ard_3-2-1_52JGL_2022-07-22_final.stac-item
2022-07-29 10:46:10	ga_s2am_ard_3-2-1_52JGL_2022-07-29_final.stac-item
2022-08-01 10:56:06	ga_s2am_ard_3-2-1_52JGL_2022-08-01_final.stac-item
2022-08-08 10:46:12	ga_s2am_ard_3-2-1_52JGL_2022-08-08_final.stac-item
2022-08-11 10:56:08	ga_s2am_ard_3-2-1_52JGL_2022-08-11_final.stac-item
2022-08-18 10:46:13	ga_s2am_ard_3-2-1_52JGL_2022-08-18_final.stac-item
2022-08-21 10:56:09	ga_s2am_ard_3-2-1_52JGL_2022-08-21_final.stac-item
2022-08-28 10:46:13	ga_s2am_ard_3-2-1_52JGL_2022-08-28_final.stac-item
2022-08-31 10:56:09	ga_s2am_ard_3-2-1_52JGL_2022-08-31_final.stac-item
2022-09-07 10:46:12	ga_s2am_ard_3-2-1_52JGL_2022-09-07_final.stac-item
2022-09-10 10:56:07	ga_s2am_ard_3-2-1_52JGL_2022-09-10_final.stac-item
2022-09-17 10:46:09	ga_s2am_ard_3-2-1_52JGL_2022-09-17_final.stac-item
2022-09-20 10:56:04	ga_s2am_ard_3-2-1_52JGL_2022-09-20_final.stac-item
2022-09-27 10:46:07	ga_s2am_ard_3-2-1_52JGL_2022-09-27_final.stac-item
2022-09-30 10:56:03	ga_s2am_ard_3-2-1_52JGL_2022-09-30_final.stac-item
2022-10-07 10:46:07	ga_s2am_ard_3-2-1_52JGL_2022-10-07_final.stac-item
2022-10-10 10:56:02	ga_s2am_ard_3-2-1_52JGL_2022-10-10_final.stac-item
2022-10-17 10:46:03	ga_s2am_ard_3-2-1_52JGL_2022-10-17_final.stac-item
2022-10-20 10:55:58	ga_s2am_ard_3-2-1_52JGL_2022-10-20_final.stac-item
2022-10-27 10:46:03	ga_s2am_ard_3-2-1_52JGL_2022-10-27_final.stac-item
2022-10-30 10:56:00	ga_s2am_ard_3-2-1_52JGL_2022-10-30_final.stac-item
2022-11-06 10:46:04	ga_s2am_ard_3-2-1_52JGL_2022-11-06_final.stac-item
2022-11-09 10:56:00	ga_s2am_ard_3-2-1_52JGL_2022-11-09_final.stac-item
2022-11-16 10:46:02	ga_s2am_ard_3-2-1_52JGL_2022-11-16_final.stac-item
2022-11-19 10:55:58	ga_s2am_ard_3-2-1_52JGL_2022-11-19_final.stac-item
2022-11-26 10:45:59	ga_s2am_ard_3-2-1_52JGL_2022-11-26_final.stac-item
2022-11-29 10:55:56	ga_s2am_ard_3-2-1_52JGL_2022-11-29_final.stac-item
2022-12-06 10:46:01	ga_s2am_ard_3-2-1_52JGL_2022-12-06_final.stac-item
2022-12-09 10:55:57	ga_s2am_ard_3-2-1_52JGL_2022-12-09_final.stac-item
2022-12-16 10:45:51	ga_s2am_ard_3-2-1_52JGL_2022-12-16_final.stac-item
2022-12-16 10:46:00	ga_s2am_ard_3-2-1_52JGL_2022-12-16_final.stac-item
2022-12-19 10:55:55	ga_s2am_ard_3-2-1_52JGL_2022-12-19_final.stac-item
2022-12-26 10:45:50	ga_s2am_ard_3-2-1_52JGL_2022-12-26_final.stac-item
2022-12-26 10:45:58	ga_s2am_ard_3-2-1_52JGL_2022-12-26_final.stac-item
2022-12-29 10:55:55	ga_s2am_ard_3-2-1_52JGL_2022-12-29_final.stac-item
2023-01-05 10:45:59	ga_s2am_ard_3-2-1_52JGL_2023-01-05_final.stac-item
2023-01-08 10:55:55	ga_s2am_ard_3-2-1_52JGL_2023-01-08_final.stac-item
2023-01-15 10:45:57	ga_s2am_ard_3-2-1_52JGL_2023-01-15_final.stac-item
2023-01-18 10:55:52	ga_s2am_ard_3-2-1_52JGL_2023-01-18_final.stac-item
2023-01-25 10:45:57	ga_s2am_ard_3-2-1_52JGL_2023-01-25_final.stac-item
2023-01-28 10:55:52	ga_s2am_ard_3-2-1_52JGL_2023-01-28_final.stac-item
2023-01-28 10:55:59	ga_s2am_ard_3-2-1_52JGL_2023-01-28_final.stac-item
2023-02-04 10:45:59	ga_s2am_ard_3-2-1_52JGL_2023-02-04_final.stac-item
2023-02-07 10:55:55	ga_s2am_ard_3-2-1_52JGL_2023-02-07_final
2023-02-14 10:45:58	ga_s2am_ard_3-2-1_52JGL_2023-02-14_final
2023-02-17 10:55:53	ga_s2am_ard_3-2-1_52JGL_2023-02-17_final
2023-08-03 10:46:05	ga_s2am_ard_3-2-1_52JGL_2023-08-03_final
2023-08-06 10:56:01	ga_s2am_ard_3-2-1_52JGL_2023-08-06_final
2023-08-13 10:46:05	ga_s2am_ard_3-2-1_52JGL_2023-08-13_final
2023-08-16 10:56:02	ga_s2am_ard_3-2-1_52JGL_2023-08-16_final

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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