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
2019-06-26 11:55:54	ga_s2am_ard_3-2-1_50JNN_2019-06-26_final.stac-item
2019-06-26 11:55:57	ga_s2am_ard_3-2-1_50JMN_2019-06-26_final.stac-item
2019-06-26 11:56:01	ga_s2am_ard_3-2-1_50JLN_2019-06-26_final.stac-item
2019-06-26 11:56:04	ga_s2am_ard_3-2-1_50JKN_2019-06-26_final.stac-item
2019-06-26 11:56:12	ga_s2am_ard_3-2-1_50JMM_2019-06-26_final.stac-item
2019-06-26 11:56:15	ga_s2am_ard_3-2-1_50JLM_2019-06-26_final.stac-item
2019-06-26 11:56:18	ga_s2am_ard_3-2-1_50JKM_2019-06-26_final.stac-item
2019-06-29 10:25:15	ga_s2am_ard_3-2-1_54JVN_2019-06-29_final.stac-item
2019-06-29 10:25:19	ga_s2am_ard_3-2-1_54JUN_2019-06-29_final.stac-item
2019-06-29 10:25:22	ga_s2am_ard_3-2-1_54JTN_2019-06-29_final.stac-item
2019-06-29 10:25:25	ga_s2am_ard_3-2-1_53JQH_2019-06-29_final.stac-item
2019-06-29 10:25:29	ga_s2am_ard_3-2-1_54JVM_2019-06-29_final.stac-item
2019-06-29 10:25:33	ga_s2am_ard_3-2-1_54JUM_2019-06-29_final.stac-item
2019-06-29 10:25:36	ga_s2am_ard_3-2-1_54JTM_2019-06-29_final.stac-item
2019-06-29 10:25:39	ga_s2am_ard_3-2-1_53JQG_2019-06-29_final.stac-item
2019-06-29 10:25:44	ga_s2am_ard_3-2-1_53JPG_2019-06-29_final.stac-item
2019-06-30 11:35:46	ga_s2am_ard_3-2-1_51JVH_2019-06-30_final.stac-item
2019-06-30 11:35:49	ga_s2am_ard_3-2-1_51JUH_2019-06-30_final.stac-item
2019-06-30 11:35:52	ga_s2am_ard_3-2-1_51JTH_2019-06-30_final.stac-item
2019-06-30 11:35:55	ga_s2am_ard_3-2-1_50JQN_2019-06-30_final.stac-item
2019-06-30 11:36:01	ga_s2am_ard_3-2-1_51JVG_2019-06-30_final.stac-item
2019-06-30 11:36:04	ga_s2am_ard_3-2-1_51JUG_2019-06-30_final.stac-item
2019-06-30 11:36:07	ga_s2am_ard_3-2-1_51JTG_2019-06-30_final.stac-item
2019-06-30 11:36:10	ga_s2am_ard_3-2-1_50JQM_2019-06-30_final.stac-item
2019-07-03 10:05:07	ga_s2am_ard_3-2-1_55JCH_2019-07-03_final.stac-item
2019-07-03 10:05:11	ga_s2am_ard_3-2-1_55JBH_2019-07-03_final.stac-item
2019-07-03 10:05:13	ga_s2am_ard_3-2-1_54JYN_2019-07-03_final.stac-item
2019-07-03 10:05:17	ga_s2am_ard_3-2-1_54JXN_2019-07-03_final.stac-item
2019-07-03 10:05:21	ga_s2am_ard_3-2-1_55JCG_2019-07-03_final.stac-item
2019-07-03 10:05:25	ga_s2am_ard_3-2-1_55JBG_2019-07-03_final.stac-item
2019-07-03 10:05:28	ga_s2am_ard_3-2-1_54JYM_2019-07-03_final.stac-item
2019-07-03 10:05:32	ga_s2am_ard_3-2-1_54JXM_2019-07-03_final.stac-item
2019-07-06 10:15:13	ga_s2am_ard_3-2-1_54JXN_2019-07-06_final.stac-item
2019-07-06 10:15:17	ga_s2am_ard_3-2-1_54JWN_2019-07-06_final.stac-item
2019-07-06 10:15:20	ga_s2am_ard_3-2-1_54JVN_2019-07-06_final.stac-item
2019-07-06 10:15:24	ga_s2am_ard_3-2-1_54JUN_2019-07-06_final.stac-item
2019-07-06 10:15:27	ga_s2am_ard_3-2-1_54JXM_2019-07-06_final.stac-item
2019-07-06 10:15:31	ga_s2am_ard_3-2-1_54JWM_2019-07-06_final.stac-item
2019-07-06 10:15:34	ga_s2am_ard_3-2-1_54JVM_2019-07-06_final.stac-item
2019-07-06 10:15:38	ga_s2am_ard_3-2-1_54JUM_2019-07-06_final.stac-item
2019-07-16 10:15:13	ga_s2am_ard_3-2-1_54JXN_2019-07-16_final.stac-item
2019-07-16 10:15:17	ga_s2am_ard_3-2-1_54JWN_2019-07-16_final.stac-item
2019-07-16 10:15:20	ga_s2am_ard_3-2-1_54JVN_2019-07-16_final.stac-item
2019-07-16 10:15:24	ga_s2am_ard_3-2-1_54JUN_2019-07-16_final.stac-item
2019-07-16 10:15:28	ga_s2am_ard_3-2-1_54JXM_2019-07-16_final.stac-item
2019-07-16 10:15:31	ga_s2am_ard_3-2-1_54JWM_2019-07-16_final.stac-item
2019-07-17 11:25:39	ga_s2am_ard_3-2-1_51JYH_2019-07-17_final.stac-item
2019-07-17 11:25:44	ga_s2am_ard_3-2-1_51JXH_2019-07-17_final.stac-item
2019-07-17 11:25:47	ga_s2am_ard_3-2-1_51JWH_2019-07-17_final.stac-item
2019-07-17 11:25:50	ga_s2am_ard_3-2-1_51JYG_2019-07-17_final.stac-item
2019-07-17 11:25:51	ga_s2am_ard_3-2-1_51JVH_2019-07-17_final.stac-item
2019-07-17 11:25:58	ga_s2am_ard_3-2-1_51JXG_2019-07-17_final.stac-item
2019-07-17 11:26:02	ga_s2am_ard_3-2-1_51JWG_2019-07-17_final.stac-item
2024-05-05 11:05:29	ga_s2am_ard_3-2-1_52JFN_2024-05-05_final
2024-05-05 11:05:33	ga_s2am_ard_3-2-1_52JEN_2024-05-05_final
2024-05-05 11:05:37	ga_s2am_ard_3-2-1_52JDN_2024-05-05_final
2024-05-05 11:05:40	ga_s2am_ard_3-2-1_52JCN_2024-05-05_final
2024-05-05 11:05:41	ga_s2am_ard_3-2-1_52JFM_2024-05-05_final
2024-05-05 11:05:47	ga_s2am_ard_3-2-1_52JEM_2024-05-05_final
2024-05-05 11:05:51	ga_s2am_ard_3-2-1_52JDM_2024-05-05_final
2024-05-05 11:05:55	ga_s2am_ard_3-2-1_52JCM_2024-05-05_final
2024-05-21 11:25:34	ga_s2am_ard_3-2-1_51JYH_2024-05-21_final
2024-05-21 11:25:39	ga_s2am_ard_3-2-1_51JXH_2024-05-21_final
2024-05-21 11:25:42	ga_s2am_ard_3-2-1_51JWH_2024-05-21_final
2024-05-21 11:25:45	ga_s2am_ard_3-2-1_51JYG_2024-05-21_final
2024-05-21 11:25:46	ga_s2am_ard_3-2-1_51JVH_2024-05-21_final
2024-05-21 11:25:53	ga_s2am_ard_3-2-1_51JXG_2024-05-21_final
2024-05-21 11:25:57	ga_s2am_ard_3-2-1_51JWG_2024-05-21_final
2024-05-22 10:55:39	ga_s2am_ard_3-2-1_53JKG_2024-05-22_nrt
2024-05-22 10:55:45	ga_s2am_ard_3-2-1_52JFM_2024-05-22_nrt
2024-05-23 12:05:51	ga_s2am_ard_3-2-1_50JLN_2024-05-23_nrt
2024-05-23 12:05:54	ga_s2am_ard_3-2-1_50JKN_2024-05-23_nrt
2024-05-23 12:05:57	ga_s2am_ard_3-2-1_49JGH_2024-05-23_nrt
2024-05-23 12:06:03	ga_s2am_ard_3-2-1_50JLM_2024-05-23_nrt
2024-05-23 12:06:09	ga_s2am_ard_3-2-1_50JKM_2024-05-23_nrt
2024-05-23 12:06:12	ga_s2am_ard_3-2-1_49JGG_2024-05-23_nrt
2024-05-23 12:06:15	ga_s2am_ard_3-2-1_49JFG_2024-05-23_nrt
2024-06-01 10:55:31	ga_s2am_ard_3-2-1_52JGN_2024-06-01_nrt
2024-06-01 10:55:34	ga_s2am_ard_3-2-1_52JFN_2024-06-01_nrt
2024-06-01 10:55:38	ga_s2am_ard_3-2-1_52JEN_2024-06-01_nrt
2024-06-01 10:55:42	ga_s2am_ard_3-2-1_53JKG_2024-06-01_nrt
2024-06-01 10:55:45	ga_s2am_ard_3-2-1_52JGM_2024-06-01_nrt
2024-06-01 10:55:49	ga_s2am_ard_3-2-1_52JFM_2024-06-01_nrt
2024-06-01 10:55:52	ga_s2am_ard_3-2-1_52JEM_2024-06-01_nrt
2024-06-02 10:25:15	ga_s2am_ard_3-2-1_54JVN_2024-06-02_nrt
2024-06-02 10:25:18	ga_s2am_ard_3-2-1_54JUN_2024-06-02_nrt
2024-06-02 10:25:21	ga_s2am_ard_3-2-1_54JTN_2024-06-02_nrt
2024-06-02 10:25:24	ga_s2am_ard_3-2-1_53JQH_2024-06-02_nrt
2024-06-02 10:25:28	ga_s2am_ard_3-2-1_54JVM_2024-06-02_nrt
2024-06-02 10:25:32	ga_s2am_ard_3-2-1_54JUM_2024-06-02_nrt
2024-06-02 10:25:36	ga_s2am_ard_3-2-1_54JTM_2024-06-02_nrt
2024-06-02 10:25:38	ga_s2am_ard_3-2-1_53JQG_2024-06-02_nrt
2024-06-02 10:25:44	ga_s2am_ard_3-2-1_53JPG_2024-06-02_nrt
2024-06-02 12:05:55	ga_s2am_ard_3-2-1_50JLN_2024-06-02_nrt
2024-06-02 12:05:59	ga_s2am_ard_3-2-1_50JKN_2024-06-02_nrt
2024-06-02 12:06:02	ga_s2am_ard_3-2-1_49JGH_2024-06-02_nrt
2024-06-02 12:06:06	ga_s2am_ard_3-2-1_49JFH_2024-06-02_nrt
2024-06-02 12:06:08	ga_s2am_ard_3-2-1_50JLM_2024-06-02_nrt
2024-06-02 12:06:14	ga_s2am_ard_3-2-1_50JKM_2024-06-02_nrt
2024-06-02 12:06:17	ga_s2am_ard_3-2-1_49JGG_2024-06-02_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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