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
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JKH_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JKJ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JLH_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JLJ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JMJ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JNJ_2018-10-28_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JKN_2018-10-29_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JKP_2018-10-29_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JLN_2018-10-29_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JLP_2018-10-29_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JMP_2018-10-29_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JNP_2018-10-29_final.stac-item
2018-11-09 11:25:16	ga_s2am_ard_3-2-1_51JYJ_2018-11-09_final.stac-item
2018-11-09 11:25:19	ga_s2am_ard_3-2-1_51JXJ_2018-11-09_final.stac-item
2018-11-09 11:25:23	ga_s2am_ard_3-2-1_51JWJ_2018-11-09_final.stac-item
2018-11-09 11:25:26	ga_s2am_ard_3-2-1_51JVJ_2018-11-09_final.stac-item
2018-11-09 11:25:29	ga_s2am_ard_3-2-1_51JYH_2018-11-09_final.stac-item
2018-11-09 11:25:34	ga_s2am_ard_3-2-1_51JXH_2018-11-09_final.stac-item
2018-11-11 10:24:51	ga_s2am_ard_3-2-1_54JVP_2018-11-11_final.stac-item
2018-11-11 10:24:55	ga_s2am_ard_3-2-1_54JUP_2018-11-11_final.stac-item
2018-11-11 10:24:58	ga_s2am_ard_3-2-1_54JTP_2018-11-11_final.stac-item
2018-11-11 10:25:00	ga_s2am_ard_3-2-1_53JQJ_2018-11-11_final.stac-item
2018-11-11 10:25:09	ga_s2am_ard_3-2-1_54JUN_2018-11-11_final.stac-item
2018-11-11 10:25:12	ga_s2am_ard_3-2-1_54JTN_2018-11-11_final.stac-item
2018-11-11 10:25:15	ga_s2am_ard_3-2-1_53JQH_2018-11-11_final.stac-item
2018-11-15 10:04:42	ga_s2am_ard_3-2-1_55JCJ_2018-11-15_final.stac-item
2018-11-15 10:04:45	ga_s2am_ard_3-2-1_55JBJ_2018-11-15_final.stac-item
2018-11-15 10:04:48	ga_s2am_ard_3-2-1_54JYP_2018-11-15_final.stac-item
2018-11-15 10:04:52	ga_s2am_ard_3-2-1_54JXP_2018-11-15_final.stac-item
2018-11-15 10:04:57	ga_s2am_ard_3-2-1_55JCH_2018-11-15_final.stac-item
2018-11-15 10:05:00	ga_s2am_ard_3-2-1_55JBH_2018-11-15_final.stac-item
2018-11-15 10:05:03	ga_s2am_ard_3-2-1_54JYN_2018-11-15_final.stac-item
2018-11-15 10:05:07	ga_s2am_ard_3-2-1_54JXN_2018-11-15_final.stac-item
2019-01-10 10:24:51	ga_s2am_ard_3-2-1_54JVP_2019-01-10_final.stac-item
2019-01-10 10:24:55	ga_s2am_ard_3-2-1_54JUP_2019-01-10_final.stac-item
2019-01-10 10:24:58	ga_s2am_ard_3-2-1_54JTP_2019-01-10_final.stac-item
2019-01-10 10:25:01	ga_s2am_ard_3-2-1_53JQJ_2019-01-10_final.stac-item
2019-01-10 10:25:09	ga_s2am_ard_3-2-1_54JUN_2019-01-10_final.stac-item
2019-01-10 10:25:13	ga_s2am_ard_3-2-1_54JTN_2019-01-10_final.stac-item
2019-01-10 10:25:15	ga_s2am_ard_3-2-1_53JQH_2019-01-10_final.stac-item
2019-01-20 10:24:52	ga_s2am_ard_3-2-1_54JVP_2019-01-20_final.stac-item
2019-01-20 10:24:56	ga_s2am_ard_3-2-1_54JUP_2019-01-20_final.stac-item
2019-01-20 10:24:59	ga_s2am_ard_3-2-1_54JTP_2019-01-20_final.stac-item
2019-01-20 10:25:02	ga_s2am_ard_3-2-1_53JQJ_2019-01-20_final.stac-item
2019-01-20 10:25:10	ga_s2am_ard_3-2-1_54JUN_2019-01-20_final.stac-item
2019-01-20 10:25:14	ga_s2am_ard_3-2-1_54JTN_2019-01-20_final.stac-item
2019-01-20 10:25:16	ga_s2am_ard_3-2-1_53JQH_2019-01-20_final.stac-item
2019-01-30 10:25:11	ga_s2am_ard_3-2-1_54JUN_2019-01-30_final.stac-item
2019-01-30 10:25:14	ga_s2am_ard_3-2-1_54JTN_2019-01-30_final.stac-item
2019-01-30 10:25:17	ga_s2am_ard_3-2-1_53JQH_2019-01-30_final.stac-item
2019-05-18 11:25:24	ga_s2am_ard_3-2-1_51JYJ_2019-05-18_final.stac-item
2019-05-18 11:25:28	ga_s2am_ard_3-2-1_51JXJ_2019-05-18_final.stac-item
2019-05-18 11:25:31	ga_s2am_ard_3-2-1_51JWJ_2019-05-18_final.stac-item
2019-05-18 11:25:34	ga_s2am_ard_3-2-1_51JVJ_2019-05-18_final.stac-item
2019-05-18 11:25:38	ga_s2am_ard_3-2-1_51JYH_2019-05-18_final.stac-item
2019-05-18 11:25:42	ga_s2am_ard_3-2-1_51JXH_2019-05-18_final.stac-item
2019-05-24 10:04:51	ga_s2am_ard_3-2-1_55JCJ_2019-05-24_final.stac-item
2019-05-24 10:04:54	ga_s2am_ard_3-2-1_55JBJ_2019-05-24_final.stac-item
2019-05-24 10:04:57	ga_s2am_ard_3-2-1_54JYP_2019-05-24_final.stac-item
2019-05-24 10:05:01	ga_s2am_ard_3-2-1_54JXP_2019-05-24_final.stac-item
2019-05-24 10:05:06	ga_s2am_ard_3-2-1_55JCH_2019-05-24_final.stac-item
2019-05-24 10:05:09	ga_s2am_ard_3-2-1_55JBH_2019-05-24_final.stac-item
2019-05-24 10:05:12	ga_s2am_ard_3-2-1_54JYN_2019-05-24_final.stac-item
2019-05-24 10:05:15	ga_s2am_ard_3-2-1_54JXN_2019-05-24_final.stac-item
2019-05-26 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2019-05-26_final.stac-item
2019-05-26 10:45:11	ga_s2am_ard_3-2-1_53JMJ_2019-05-26_final.stac-item
2019-05-26 10:45:14	ga_s2am_ard_3-2-1_53JLJ_2019-05-26_final.stac-item
2019-05-26 10:45:17	ga_s2am_ard_3-2-1_53JKJ_2019-05-26_final.stac-item
2019-05-26 10:45:29	ga_s2am_ard_3-2-1_53JLH_2019-05-26_final.stac-item
2019-05-26 10:45:32	ga_s2am_ard_3-2-1_53JKH_2019-05-26_final.stac-item
2022-10-17 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2022-10-17_final.stac-item
2022-10-17 10:45:11	ga_s2am_ard_3-2-1_53JMJ_2022-10-17_final.stac-item
2022-10-17 10:45:14	ga_s2am_ard_3-2-1_53JLJ_2022-10-17_final.stac-item
2022-10-17 10:45:17	ga_s2am_ard_3-2-1_53JKJ_2022-10-17_final.stac-item
2022-10-17 10:45:29	ga_s2am_ard_3-2-1_53JLH_2022-10-17_final.stac-item
2022-10-17 10:45:32	ga_s2am_ard_3-2-1_53JKH_2022-10-17_final.stac-item
2022-10-24 10:35:00	ga_s2am_ard_3-2-1_54JTP_2022-10-24_final.stac-item
2022-10-24 10:35:04	ga_s2am_ard_3-2-1_53JQJ_2022-10-24_final.stac-item
2023-07-29 11:35:32	ga_s2am_ard_3-2-1_51JVJ_2023-07-29_final
2023-07-29 11:35:35	ga_s2am_ard_3-2-1_51JUJ_2023-07-29_final
2023-07-29 11:35:39	ga_s2am_ard_3-2-1_51JTJ_2023-07-29_final
2023-07-29 11:35:42	ga_s2am_ard_3-2-1_50JQP_2023-07-29_final
2023-07-29 11:35:50	ga_s2am_ard_3-2-1_51JUH_2023-07-29_final
2023-07-29 11:35:53	ga_s2am_ard_3-2-1_51JTH_2023-07-29_final
2023-07-29 11:35:56	ga_s2am_ard_3-2-1_50JQN_2023-07-29_final
2023-08-01 10:04:53	ga_s2am_ard_3-2-1_55JCJ_2023-08-01_final
2023-08-01 10:04:56	ga_s2am_ard_3-2-1_55JBJ_2023-08-01_final
2023-08-01 10:04:59	ga_s2am_ard_3-2-1_54JYP_2023-08-01_final
2023-08-01 10:05:03	ga_s2am_ard_3-2-1_54JXP_2023-08-01_final
2023-08-01 10:05:08	ga_s2am_ard_3-2-1_55JCH_2023-08-01_final
2023-08-01 10:05:11	ga_s2am_ard_3-2-1_55JBH_2023-08-01_final
2023-08-01 10:05:14	ga_s2am_ard_3-2-1_54JYN_2023-08-01_final
2023-08-01 10:05:18	ga_s2am_ard_3-2-1_54JXN_2023-08-01_final
2023-08-02 09:34:38	ga_s2am_ard_3-2-1_56JNP_2023-08-02_final
2023-08-02 09:34:42	ga_s2am_ard_3-2-1_56JMP_2023-08-02_final
2023-08-02 09:34:46	ga_s2am_ard_3-2-1_56JLP_2023-08-02_final
2023-08-02 09:34:49	ga_s2am_ard_3-2-1_56JKP_2023-08-02_final
2023-08-02 09:34:55	ga_s2am_ard_3-2-1_55JGJ_2023-08-02_final
2023-08-02 09:35:00	ga_s2am_ard_3-2-1_56JLN_2023-08-02_final
2023-08-02 09:35:04	ga_s2am_ard_3-2-1_56JKN_2023-08-02_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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