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
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49JGL_2016-04-15_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50HLH_2016-04-19_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_49KHP_2016-06-24_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HMJ_2016-07-08_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_50HPK_2016-07-15_final.stac-item
2016-09-05 12:13:43	ga_s2am_ard_3-2-1_49KGR_2016-09-05_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50HMK_2016-09-06_final.stac-item
2016-11-08 11:56:13	ga_s2am_ard_3-2-1_50JLM_2016-11-08_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JGN_2016-11-21_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49JGK_2017-01-20_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_50JKQ_2017-02-19_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49JGM_2017-05-10_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50JKQ_2017-06-19_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49JGL_2017-08-18_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49KHP_2017-08-18_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_50JLP_2017-12-16_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_49KHR_2018-01-28_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HPH_2018-02-18_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HPJ_2018-02-18_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49KHP_2018-02-24_final.stac-item
2018-02-27 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-02-27_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HNH_2018-03-20_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49JGL_2018-04-05_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_50HPJ_2018-04-26_final.stac-item
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_49KHR_2018-05-05_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49KGQ_2018-08-06_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49JGL_2018-09-25_final.stac-item
2019-01-01 11:36:57	ga_s2am_ard_3-2-1_50HQH_2019-01-01_final.stac-item
2019-01-07 11:56:20	ga_s2am_ard_3-2-1_50JLL_2019-01-07_final.stac-item
2019-02-23 11:46:36	ga_s2am_ard_3-2-1_50HMK_2019-02-23_final.stac-item
2019-04-07 11:55:47	ga_s2am_ard_3-2-1_50JKP_2019-04-07_final.stac-item
2019-04-20 12:05:54	ga_s2am_ard_3-2-1_50JLN_2019-04-20_final.stac-item
2019-04-24 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-04-24_final.stac-item
2019-05-13 12:14:45	ga_s2am_ard_3-2-1_49JGN_2019-05-13_final.stac-item
2019-05-30 12:04:30	ga_s2am_ard_3-2-1_49KHP_2019-05-30_final.stac-item
2019-06-03 11:46:43	ga_s2am_ard_3-2-1_50HMK_2019-06-03_final.stac-item
2019-10-28 11:36:55	ga_s2am_ard_3-2-1_50HPJ_2019-10-28_final.stac-item
2019-11-10 11:46:40	ga_s2am_ard_3-2-1_50HNK_2019-11-10_final.stac-item
2020-01-02 11:56:24	ga_s2am_ard_3-2-1_50HNK_2020-01-02_final.stac-item
2020-01-06 11:36:49	ga_s2am_ard_3-2-1_50HQJ_2020-01-06_final.stac-item
2020-01-15 12:05:32	ga_s2am_ard_3-2-1_50JLP_2020-01-15_final.stac-item
2020-03-06 11:37:02	ga_s2am_ard_3-2-1_50HPH_2020-03-06_final.stac-item
2020-03-08 12:14:37	ga_s2am_ard_3-2-1_49JGN_2020-03-08_final.stac-item
2020-03-18 12:13:54	ga_s2am_ard_3-2-1_49KGR_2020-03-18_final.stac-item
2020-03-25 12:04:53	ga_s2am_ard_3-2-1_50JKS_2020-03-25_final.stac-item
2020-04-14 12:05:28	ga_s2am_ard_3-2-1_49JGK_2020-04-14_final.stac-item
2020-04-27 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2020-04-27_final.stac-item
2020-05-18 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2020-05-18_final.stac-item
2020-06-03 12:05:03	ga_s2am_ard_3-2-1_50JKS_2020-06-03_final.stac-item
2020-06-06 12:14:48	ga_s2am_ard_3-2-1_49JGN_2020-06-06_final.stac-item
2020-06-20 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-06-20_final.stac-item
2020-10-11 12:06:10	ga_s2am_ard_3-2-1_50JLM_2020-10-11_final.stac-item
2020-10-31 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2020-10-31_final.stac-item
2020-11-13 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2020-11-13_final.stac-item
2020-11-23 12:14:43	ga_s2am_ard_3-2-1_49JGN_2020-11-23_final.stac-item
2020-12-10 12:04:15	ga_s2am_ard_3-2-1_49KGQ_2020-12-10_final.stac-item
2021-01-10 11:37:07	ga_s2am_ard_3-2-1_50HPH_2021-01-10_final.stac-item
2021-01-13 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-01-13_final.stac-item
2021-02-18 12:04:30	ga_s2am_ard_3-2-1_49KGP_2021-02-18_final.stac-item
2021-02-25 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2021-02-25_final.stac-item
2021-02-25 11:57:09	ga_s2am_ard_3-2-1_50HLH_2021-02-25_final.stac-item
2021-03-24 11:46:28	ga_s2am_ard_3-2-1_50HQK_2021-03-24_final.stac-item
2021-05-12 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2021-05-12_final.stac-item
2021-05-26 11:55:42	ga_s2am_ard_3-2-1_50JLP_2021-05-26_final.stac-item
2021-05-26 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-05-26_final
2021-06-25 11:55:48	ga_s2am_ard_3-2-1_50JKP_2021-06-25_final.stac-item
2021-08-27 12:04:30	ga_s2am_ard_3-2-1_49KHP_2021-08-27_final.stac-item
2021-09-07 11:36:38	ga_s2am_ard_3-2-1_50HPK_2021-09-07_final.stac-item
2021-09-23 11:56:29	ga_s2am_ard_3-2-1_50JLL_2021-09-23_final.stac-item
2021-10-23 11:57:11	ga_s2am_ard_3-2-1_50HMH_2021-10-23_final.stac-item
2021-11-15 12:04:29	ga_s2am_ard_3-2-1_49KHP_2021-11-15_final.stac-item
2021-11-16 11:37:04	ga_s2am_ard_3-2-1_50HQH_2021-11-16_final.stac-item
2021-12-19 11:46:36	ga_s2am_ard_3-2-1_50HPK_2021-12-19_final.stac-item
2021-12-22 11:56:27	ga_s2am_ard_3-2-1_50JLL_2021-12-22_final.stac-item
2021-12-25 12:05:39	ga_s2am_ard_3-2-1_50JLP_2021-12-25_final.stac-item
2021-12-29 11:47:26	ga_s2am_ard_3-2-1_50HMG_2021-12-29_final
2022-05-01 11:57:14	ga_s2am_ard_3-2-1_50HLH_2022-05-01_final.stac-item
2022-05-08 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2022-05-08_final.stac-item
2022-08-19 11:56:24	ga_s2am_ard_3-2-1_50JLM_2022-08-19_final.stac-item
2022-08-26 11:47:15	ga_s2am_ard_3-2-1_50HPH_2022-08-26_final
2023-01-13 11:47:07	ga_s2am_ard_3-2-1_50HMH_2023-01-13_final.stac-item
2023-02-05 11:55:45	ga_s2am_ard_3-2-1_50JKP_2023-02-05_final
2023-05-03 11:46:30	ga_s2am_ard_3-2-1_50HQK_2023-05-03_final
2023-06-08 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2023-06-08_final
2023-07-18 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2023-07-18_final
2023-08-27 12:05:57	ga_s2am_ard_3-2-1_50JLN_2023-08-27_final
2023-09-09 12:14:14	ga_s2am_ard_3-2-1_49KHQ_2023-09-09_final
2023-11-02 11:57:04	ga_s2am_ard_3-2-1_50HMH_2023-11-02_final
2023-11-09 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2023-11-09_final
2023-11-19 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2023-11-19_final
2023-11-26 11:37:15	ga_s2am_ard_3-2-1_50HPG_2023-11-26_final
2023-12-12 11:57:04	ga_s2am_ard_3-2-1_50HLH_2023-12-12_final
2023-12-19 11:46:44	ga_s2am_ard_3-2-1_50HPJ_2023-12-19_final
2024-01-11 11:57:01	ga_s2am_ard_3-2-1_50HMH_2024-01-11_final
2024-01-21 11:56:03	ga_s2am_ard_3-2-1_50JLM_2024-01-21_final
2024-02-07 11:46:39	ga_s2am_ard_3-2-1_50HQJ_2024-02-07_final
2024-02-17 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2024-02-17_final
2024-02-27 11:47:23	ga_s2am_ard_3-2-1_50HMG_2024-02-27_final
2024-04-04 11:36:46	ga_s2am_ard_3-2-1_50HQJ_2024-04-04_final
2024-04-13 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2024-04-13_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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