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
2016-02-09 10:03:07	ga_s2am_ard_3-2-1_54JYQ_2016-02-09_final.stac-item
2016-02-19 11:36:40	ga_s2am_ard_3-2-1_50JNR_2016-02-19_final.stac-item
2016-02-19 11:36:40	ga_s2am_ard_3-2-1_50JPR_2016-02-19_final.stac-item
2016-02-19 11:36:40	ga_s2am_ard_3-2-1_50JQQ_2016-02-19_final.stac-item
2016-02-19 11:36:40	ga_s2am_ard_3-2-1_50JQR_2016-02-19_final.stac-item
2016-02-19 11:36:40	ga_s2am_ard_3-2-1_51JTL_2016-02-19_final.stac-item
2016-03-02 10:44:00	ga_s2am_ard_3-2-1_53JML_2016-03-02_final.stac-item
2016-03-02 10:44:00	ga_s2am_ard_3-2-1_53JNL_2016-03-02_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JLR_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JMR_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JNR_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JPR_2016-03-03_final.stac-item
2016-03-23 10:08:30	ga_s2am_ard_3-2-1_54JVR_2016-03-23_final.stac-item
2016-03-23 10:08:30	ga_s2am_ard_3-2-1_54JWR_2016-03-23_final.stac-item
2016-03-23 10:08:30	ga_s2am_ard_3-2-1_54JXR_2016-03-23_final.stac-item
2016-03-23 10:08:30	ga_s2am_ard_3-2-1_54JYR_2016-03-23_final.stac-item
2016-04-10 09:33:53	ga_s2am_ard_3-2-1_56JKR_2016-04-10_final.stac-item
2016-04-10 09:33:53	ga_s2am_ard_3-2-1_56JLR_2016-04-10_final.stac-item
2016-04-10 09:33:53	ga_s2am_ard_3-2-1_56JMR_2016-04-10_final.stac-item
2016-04-10 09:33:53	ga_s2am_ard_3-2-1_56JNR_2016-04-10_final
2016-04-14 10:51:39	ga_s2am_ard_3-2-1_53JKL_2016-04-14_final.stac-item
2016-04-14 10:51:39	ga_s2am_ard_3-2-1_53JLL_2016-04-14_final.stac-item
2016-04-14 10:51:39	ga_s2am_ard_3-2-1_52JFR_2016-04-14_final.stac-item
2016-04-14 10:51:39	ga_s2am_ard_3-2-1_52JGQ_2016-04-14_final.stac-item
2016-04-14 10:51:39	ga_s2am_ard_3-2-1_52JGR_2016-04-14_final.stac-item
2016-04-28 10:34:09	ga_s2am_ard_3-2-1_53JPL_2016-04-28_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50JNR_2016-04-29_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50JPR_2016-04-29_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50JQQ_2016-04-29_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50JQR_2016-04-29_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_51JTL_2016-04-29_final.stac-item
2016-05-10 09:32:23	ga_s2am_ard_3-2-1_56JKR_2016-05-10_final.stac-item
2016-05-10 09:32:23	ga_s2am_ard_3-2-1_56JLR_2016-05-10_final.stac-item
2016-05-10 09:32:23	ga_s2am_ard_3-2-1_56JMR_2016-05-10_final.stac-item
2016-05-10 09:32:23	ga_s2am_ard_3-2-1_56JNR_2016-05-10_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_51JYK_2016-05-10_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_51JYL_2016-05-10_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_52JBR_2016-05-10_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_52JCR_2016-05-10_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_52JDR_2016-05-10_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50JKR_2016-05-15_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50JLR_2016-05-15_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49JGK_2016-05-15_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49JGL_2016-05-15_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51JUL_2016-05-16_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51JVL_2016-05-16_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51JWL_2016-05-16_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51JTL_2016-05-16_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49JGL_2016-05-18_final.stac-item
2016-05-19 10:01:47	ga_s2am_ard_3-2-1_54JXR_2016-05-19_final.stac-item
2016-05-19 10:01:47	ga_s2am_ard_3-2-1_54JYQ_2016-05-19_final.stac-item
2016-05-19 10:01:47	ga_s2am_ard_3-2-1_54JYR_2016-05-19_final.stac-item
2016-05-19 10:01:47	ga_s2am_ard_3-2-1_55JBL_2016-05-19_final.stac-item
2017-10-12 09:32:39	ga_s2am_ard_3-2-1_56JKR_2017-10-12_final.stac-item
2017-10-12 09:32:39	ga_s2am_ard_3-2-1_56JLR_2017-10-12_final.stac-item
2017-10-12 09:32:39	ga_s2am_ard_3-2-1_56JMR_2017-10-12_final.stac-item
2017-10-22 09:32:39	ga_s2am_ard_3-2-1_56JKR_2017-10-22_final.stac-item
2017-10-22 09:32:39	ga_s2am_ard_3-2-1_56JLR_2017-10-22_final.stac-item
2017-10-22 09:32:39	ga_s2am_ard_3-2-1_56JMR_2017-10-22_final.stac-item
2017-10-26 10:53:14	ga_s2am_ard_3-2-1_53JKL_2017-10-26_final.stac-item
2017-10-26 10:53:14	ga_s2am_ard_3-2-1_53JLL_2017-10-26_final.stac-item
2017-10-26 10:53:14	ga_s2am_ard_3-2-1_52JFR_2017-10-26_final.stac-item
2017-10-26 10:53:14	ga_s2am_ard_3-2-1_52JGQ_2017-10-26_final.stac-item
2017-10-26 10:53:14	ga_s2am_ard_3-2-1_52JGR_2017-10-26_final.stac-item
2017-11-01 09:32:39	ga_s2am_ard_3-2-1_56JKR_2017-11-01_final.stac-item
2017-11-01 09:32:39	ga_s2am_ard_3-2-1_56JLR_2017-11-01_final.stac-item
2017-11-01 09:32:39	ga_s2am_ard_3-2-1_56JMR_2017-11-01_final.stac-item
2017-11-02 10:43:05	ga_s2am_ard_3-2-1_53JLL_2017-11-02_final.stac-item
2017-11-02 10:43:05	ga_s2am_ard_3-2-1_53JNL_2017-11-02_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_51JTL_2017-11-07_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_51JUL_2017-11-07_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_51JVL_2017-11-07_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_51JWL_2017-11-07_final.stac-item
2022-09-14 12:15:20	ga_s2am_ard_3-2-1_49JGL_2022-09-14_final.stac-item
2022-09-15 10:04:23	ga_s2am_ard_3-2-1_55JDL_2022-09-15_final.stac-item
2022-09-15 10:04:28	ga_s2am_ard_3-2-1_55JCL_2022-09-15_final.stac-item
2022-09-15 10:04:32	ga_s2am_ard_3-2-1_55JBL_2022-09-15_final.stac-item
2022-09-15 10:04:35	ga_s2am_ard_3-2-1_54JYR_2022-09-15_final.stac-item
2022-09-15 10:04:42	ga_s2am_ard_3-2-1_54JXR_2022-09-15_final.stac-item
2022-09-15 10:04:49	ga_s2am_ard_3-2-1_54JYQ_2022-09-15_final.stac-item
2022-10-01 12:05:15	ga_s2am_ard_3-2-1_50JLR_2022-10-01_final.stac-item
2022-10-01 12:05:19	ga_s2am_ard_3-2-1_50JKR_2022-10-01_final.stac-item
2022-10-01 12:05:22	ga_s2am_ard_3-2-1_49JGL_2022-10-01_final.stac-item
2022-10-01 12:05:26	ga_s2am_ard_3-2-1_49JFL_2022-10-01_final
2022-10-01 12:05:36	ga_s2am_ard_3-2-1_49JGK_2022-10-01_final.stac-item
2022-10-02 09:54:20	ga_s2am_ard_3-2-1_55JFL_2022-10-02_final.stac-item
2022-10-02 09:54:24	ga_s2am_ard_3-2-1_55JEL_2022-10-02_final.stac-item
2022-10-02 09:54:27	ga_s2am_ard_3-2-1_55JDL_2022-10-02_final.stac-item
2022-10-02 09:54:30	ga_s2am_ard_3-2-1_55JCL_2022-10-02_final.stac-item
2023-02-15 11:55:00	ga_s2am_ard_3-2-1_50JPR_2023-02-15_final
2023-02-15 11:55:03	ga_s2am_ard_3-2-1_50JNR_2023-02-15_nrt.stac-item
2023-02-15 11:55:03	ga_s2am_ard_3-2-1_50JNR_2023-02-15_final
2023-02-15 11:55:07	ga_s2am_ard_3-2-1_50JMR_2023-02-15_nrt.stac-item
2023-02-15 11:55:07	ga_s2am_ard_3-2-1_50JMR_2023-02-15_final
2023-02-15 11:55:10	ga_s2am_ard_3-2-1_50JLR_2023-02-15_nrt.stac-item
2023-02-15 11:55:10	ga_s2am_ard_3-2-1_50JLR_2023-02-15_final
2023-02-23 11:14:44	ga_s2am_ard_3-2-1_52JDR_2023-02-23_final
2023-02-23 11:14:47	ga_s2am_ard_3-2-1_52JCR_2023-02-23_final
2023-02-23 11:14:50	ga_s2am_ard_3-2-1_52JBR_2023-02-23_final
2023-02-23 11:14:53	ga_s2am_ard_3-2-1_51JYL_2023-02-23_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

All years