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
2015-10-08 12:03:08	ga_s2am_ard_3-2-1_50JKN_2015-10-08_final.stac-item
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KHR_2015-10-28_final.stac-item
2016-01-23 11:56:39	ga_s2am_ard_3-2-1_50HNK_2016-01-23_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JLN_2016-02-02_final.stac-item
2016-04-15 12:05:35	ga_s2am_ard_3-2-1_50JLP_2016-04-15_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HPG_2016-04-29_final
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KHR_2016-05-18_final.stac-item
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_49KGP_2016-09-15_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50HQK_2016-11-02_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50JLP_2016-12-11_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50HNG_2016-12-22_final
2016-12-24 12:14:52	ga_s2am_ard_3-2-1_49JGM_2016-12-24_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50HQK_2016-12-25_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49KHR_2016-12-31_final.stac-item
2017-01-03 12:13:15	ga_s2am_ard_3-2-1_49KGP_2017-01-03_final.stac-item
2017-04-01 11:34:45	ga_s2am_ard_3-2-1_50HPH_2017-04-01_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_50JKP_2017-04-20_final.stac-item
2017-04-30 12:03:50	ga_s2am_ard_3-2-1_49KHR_2017-04-30_final.stac-item
2017-05-13 12:13:38	ga_s2am_ard_3-2-1_49KGP_2017-05-13_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_50JLP_2017-07-29_final.stac-item
2017-10-10 12:13:43	ga_s2am_ard_3-2-1_49KGR_2017-10-10_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50JLL_2017-10-24_final.stac-item
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_49JGM_2017-10-27_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HNK_2017-10-31_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_50HPH_2017-11-07_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49KGP_2017-11-09_final.stac-item
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_50JMM_2018-04-09_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49KGP_2018-04-28_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HQJ_2018-05-29_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50JML_2018-06-28_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50JMM_2018-08-27_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KHR_2018-09-05_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HLK_2018-09-19_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-10-02_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JLQ_2018-10-12_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-10-22_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49JGN_2018-11-01_final.stac-item
2018-12-18 11:55:48	ga_s2am_ard_3-2-1_50JLN_2018-12-18_final.stac-item
2018-12-28 11:55:58	ga_s2am_ard_3-2-1_50JLM_2018-12-28_final.stac-item
2019-01-01 11:36:57	ga_s2am_ard_3-2-1_50HQH_2019-01-01_final.stac-item
2019-01-04 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2019-01-04_final.stac-item
2019-03-01 12:05:04	ga_s2am_ard_3-2-1_49JGM_2019-03-01_final.stac-item
2019-03-02 11:36:43	ga_s2am_ard_3-2-1_50HQJ_2019-03-02_final.stac-item
2019-04-30 12:05:43	ga_s2am_ard_3-2-1_50JKP_2019-04-30_final.stac-item
2019-06-09 12:04:16	ga_s2am_ard_3-2-1_49KHQ_2019-06-09_final.stac-item
2019-09-27 12:05:42	ga_s2am_ard_3-2-1_50JKP_2019-09-27_final.stac-item
2019-10-01 11:46:39	ga_s2am_ard_3-2-1_50HNK_2019-10-01_final.stac-item
2019-10-07 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-10-07_final.stac-item
2019-11-10 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2019-11-10_final.stac-item
2020-01-02 11:55:51	ga_s2am_ard_3-2-1_50JLN_2020-01-02_final.stac-item
2020-01-09 11:47:04	ga_s2am_ard_3-2-1_50HMH_2020-01-09_final.stac-item
2020-02-14 12:04:25	ga_s2am_ard_3-2-1_49KGP_2020-02-14_final.stac-item
2020-02-15 11:36:42	ga_s2am_ard_3-2-1_50HQJ_2020-02-15_final.stac-item
2020-02-17 12:13:48	ga_s2am_ard_3-2-1_49KHR_2020-02-17_final.stac-item
2020-05-21 11:56:02	ga_s2am_ard_3-2-1_50JLN_2020-05-21_final.stac-item
2020-07-06 12:15:15	ga_s2am_ard_3-2-1_49JGL_2020-07-06_final.stac-item
2020-07-24 11:37:08	ga_s2am_ard_3-2-1_50HQH_2020-07-24_final.stac-item
2020-08-29 11:56:27	ga_s2am_ard_3-2-1_50JML_2020-08-29_final.stac-item
2020-11-17 11:54:47	ga_s2am_ard_3-2-1_50JLT_2020-11-17_final.stac-item
2020-12-04 11:46:20	ga_s2am_ard_3-2-1_50JML_2020-12-04_final.stac-item
2020-12-24 11:46:36	ga_s2am_ard_3-2-1_50HNK_2020-12-24_final.stac-item
2021-03-07 11:56:12	ga_s2am_ard_3-2-1_50JMM_2021-03-07_final.stac-item
2021-04-09 12:05:18	ga_s2am_ard_3-2-1_50JLQ_2021-04-09_final.stac-item
2021-05-23 11:47:07	ga_s2am_ard_3-2-1_50HNH_2021-05-23_final.stac-item
2021-06-28 12:04:58	ga_s2am_ard_3-2-1_49JHM_2021-06-28_final.stac-item
2021-07-02 11:47:23	ga_s2am_ard_3-2-1_50HNG_2021-07-02_final
2021-07-08 12:05:03	ga_s2am_ard_3-2-1_49JGM_2021-07-08_final.stac-item
2021-07-28 12:04:02	ga_s2am_ard_3-2-1_49KHR_2021-07-28_final.stac-item
2021-09-06 12:04:00	ga_s2am_ard_3-2-1_49KHR_2021-09-06_final.stac-item
2021-09-20 11:46:40	ga_s2am_ard_3-2-1_50HNK_2021-09-20_final.stac-item
2021-09-20 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2021-09-20_final.stac-item
2021-09-29 12:14:45	ga_s2am_ard_3-2-1_49JGN_2021-09-29_final.stac-item
2021-11-16 11:36:49	ga_s2am_ard_3-2-1_50HQJ_2021-11-16_final.stac-item
2022-01-11 11:55:47	ga_s2am_ard_3-2-1_50JKP_2022-01-11_final.stac-item
2022-01-27 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-01-27_final.stac-item
2022-04-07 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2022-04-07_final.stac-item
2022-05-14 12:05:01	ga_s2am_ard_3-2-1_50JKS_2022-05-14_final.stac-item
2022-05-14 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2022-05-14_final.stac-item
2022-06-03 12:05:23	ga_s2am_ard_3-2-1_49JGL_2022-06-03_final.stac-item
2022-06-27 11:47:04	ga_s2am_ard_3-2-1_50HNJ_2022-06-27_final.stac-item
2022-06-30 11:56:38	ga_s2am_ard_3-2-1_50JLL_2022-06-30_final.stac-item
2022-08-05 12:15:21	ga_s2am_ard_3-2-1_49JGL_2022-08-05_final.stac-item
2022-12-14 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2022-12-14_final.stac-item
2023-01-13 11:46:23	ga_s2am_ard_3-2-1_50JML_2023-01-13_final.stac-item
2023-02-05 11:57:05	ga_s2am_ard_3-2-1_50HMH_2023-02-05_final
2023-03-17 11:55:54	ga_s2am_ard_3-2-1_50JLN_2023-03-17_final
2023-04-06 11:55:59	ga_s2am_ard_3-2-1_50JKN_2023-04-06_final
2023-04-29 12:05:52	ga_s2am_ard_3-2-1_50JLN_2023-04-29_final
2023-05-26 11:55:50	ga_s2am_ard_3-2-1_50JKP_2023-05-26_final
2023-06-12 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2023-06-12_final
2023-06-28 12:04:52	ga_s2am_ard_3-2-1_49JHN_2023-06-28_final
2023-07-22 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2023-07-22_final
2023-07-22 11:47:06	ga_s2am_ard_3-2-1_50HPH_2023-07-22_final
2023-10-13 11:55:47	ga_s2am_ard_3-2-1_50JLP_2023-10-13_final
2023-12-25 12:04:15	ga_s2am_ard_3-2-1_49KGQ_2023-12-25_final
2024-01-01 11:55:43	ga_s2am_ard_3-2-1_50JKP_2024-01-01_final
2024-01-25 11:36:42	ga_s2am_ard_3-2-1_50HQJ_2024-01-25_final
2024-02-06 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2024-02-06_final
2024-02-10 11:56:10	ga_s2am_ard_3-2-1_50JKM_2024-02-10_final
2024-03-31 11:56:10	ga_s2am_ard_3-2-1_50JLM_2024-03-31_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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