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
2015-11-24 11:56:24	ga_s2am_ard_3-2-1_50HMK_2015-11-24_final.stac-item
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HPK_2015-12-08_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HLK_2016-06-11_final.stac-item
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_49KGR_2016-06-27_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50HLK_2016-09-19_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50HPH_2016-10-23_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGJ_2016-11-11_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HNG_2016-11-12_final
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50HPJ_2016-12-25_final.stac-item
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_50JKR_2017-03-21_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49KHQ_2017-05-10_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49KHQ_2017-05-30_final.stac-item
2017-06-20 11:34:58	ga_s2am_ard_3-2-1_50HQH_2017-06-20_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HNJ_2017-07-03_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49JGL_2017-07-09_final.stac-item
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49KGQ_2017-08-21_final.stac-item
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_50HPH_2017-11-27_final.stac-item
2018-02-08 11:45:59	ga_s2am_ard_3-2-1_50HNH_2018-02-08_final.stac-item
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49JGN_2018-02-17_final.stac-item
2018-03-07 11:36:09	ga_s2am_ard_3-2-1_50HPK_2018-03-07_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49KGP_2018-04-05_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_50HPK_2018-04-26_final.stac-item
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_49JGN_2018-05-05_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HQJ_2018-05-19_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HNH_2018-05-29_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50HMK_2018-06-11_final.stac-item
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HPH_2018-07-08_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_50JKS_2018-11-01_final.stac-item
2018-11-14 12:15:05	ga_s2am_ard_3-2-1_49JGL_2018-11-14_final.stac-item
2018-11-15 11:47:01	ga_s2am_ard_3-2-1_50HNH_2018-11-15_final.stac-item
2018-11-25 11:46:35	ga_s2am_ard_3-2-1_50HQJ_2018-11-25_final.stac-item
2018-12-08 11:56:57	ga_s2am_ard_3-2-1_50HMH_2018-12-08_final.stac-item
2018-12-22 11:36:56	ga_s2am_ard_3-2-1_50HPH_2018-12-22_final.stac-item
2019-01-10 12:04:38	ga_s2am_ard_3-2-1_50JKT_2019-01-10_final.stac-item
2019-01-14 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2019-01-14_final.stac-item
2019-02-13 11:46:52	ga_s2am_ard_3-2-1_50HMJ_2019-02-13_final.stac-item
2019-03-28 11:56:25	ga_s2am_ard_3-2-1_50JLL_2019-03-28_final.stac-item
2019-06-02 12:14:29	ga_s2am_ard_3-2-1_49KGP_2019-06-02_final.stac-item
2019-08-02 11:47:14	ga_s2am_ard_3-2-1_50HMH_2019-08-02_final.stac-item
2019-09-08 11:36:47	ga_s2am_ard_3-2-1_50HQJ_2019-09-08_final.stac-item
2019-10-27 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2019-10-27_final.stac-item
2019-10-28 11:36:41	ga_s2am_ard_3-2-1_50HPK_2019-10-28_final.stac-item
2019-12-23 11:57:00	ga_s2am_ard_3-2-1_50HMH_2019-12-23_final.stac-item
2019-12-27 11:36:59	ga_s2am_ard_3-2-1_50HPH_2019-12-27_final.stac-item
2020-01-19 11:46:42	ga_s2am_ard_3-2-1_50HPJ_2020-01-19_final.stac-item
2020-03-02 11:55:42	ga_s2am_ard_3-2-1_50JKP_2020-03-02_final.stac-item
2020-03-09 11:46:39	ga_s2am_ard_3-2-1_50HQJ_2020-03-09_final.stac-item
2020-06-13 12:05:35	ga_s2am_ard_3-2-1_49JGK_2020-06-13_final.stac-item
2020-07-03 12:06:09	ga_s2am_ard_3-2-1_50JLM_2020-07-03_final.stac-item
2020-09-08 11:56:18	ga_s2am_ard_3-2-1_50JKM_2020-09-08_final.stac-item
2020-11-23 12:15:22	ga_s2am_ard_3-2-1_49JGK_2020-11-23_final.stac-item
2020-12-04 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2020-12-04_final.stac-item
2021-01-30 11:37:26	ga_s2am_ard_3-2-1_50HNG_2021-01-30_final
2021-03-14 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2021-03-14_final.stac-item
2021-06-05 11:55:47	ga_s2am_ard_3-2-1_50JKP_2021-06-05_final.stac-item
2021-07-18 12:05:41	ga_s2am_ard_3-2-1_50JKP_2021-07-18_final.stac-item
2021-08-17 12:04:59	ga_s2am_ard_3-2-1_50JKS_2021-08-17_final.stac-item
2021-09-07 11:37:06	ga_s2am_ard_3-2-1_50HPH_2021-09-07_final.stac-item
2021-09-19 12:13:42	ga_s2am_ard_3-2-1_49KHS_2021-09-19_final
2021-10-07 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2021-10-07_final.stac-item
2021-10-26 12:05:02	ga_s2am_ard_3-2-1_49JHM_2021-10-26_final.stac-item
2021-11-29 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2021-11-29_final.stac-item
2021-12-15 12:04:46	ga_s2am_ard_3-2-1_49JGN_2021-12-15_final.stac-item
2022-01-01 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2022-01-01_final.stac-item
2022-01-11 11:56:38	ga_s2am_ard_3-2-1_50HMK_2022-01-11_final.stac-item
2022-01-31 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2022-01-31_final.stac-item
2022-02-20 11:55:48	ga_s2am_ard_3-2-1_50JKP_2022-02-20_final.stac-item
2022-04-18 11:47:14	ga_s2am_ard_3-2-1_50HMH_2022-04-18_final.stac-item
2022-07-04 11:37:16	ga_s2am_ard_3-2-1_50HQH_2022-07-04_final.stac-item
2022-07-13 12:05:24	ga_s2am_ard_3-2-1_50JKR_2022-07-13_final.stac-item
2022-08-13 11:36:52	ga_s2am_ard_3-2-1_50HQK_2022-08-13_final.stac-item
2022-09-24 12:14:20	ga_s2am_ard_3-2-1_49KGQ_2022-09-24_final.stac-item
2022-11-21 11:37:07	ga_s2am_ard_3-2-1_50HPH_2022-11-21_final.stac-item
2023-01-23 11:46:48	ga_s2am_ard_3-2-1_50HNJ_2023-01-23_final.stac-item
2023-02-08 12:04:27	ga_s2am_ard_3-2-1_49KHP_2023-02-08_final
2023-02-12 11:47:12	ga_s2am_ard_3-2-1_50HLH_2023-02-12_nrt.stac-item
2023-02-12 11:47:12	ga_s2am_ard_3-2-1_50HLH_2023-02-12_final
2023-04-09 12:04:46	ga_s2am_ard_3-2-1_49JGN_2023-04-09_final
2023-04-23 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2023-04-23_final
2023-05-26 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2023-05-26_final
2023-08-31 11:47:29	ga_s2am_ard_3-2-1_50HMG_2023-08-31_final
2023-09-26 12:05:43	ga_s2am_ard_3-2-1_50JKP_2023-09-26_final
2023-10-13 11:56:28	ga_s2am_ard_3-2-1_50HNK_2023-10-13_final
2023-10-17 11:36:47	ga_s2am_ard_3-2-1_50HQJ_2023-10-17_final
2023-11-22 11:56:36	ga_s2am_ard_3-2-1_50HLK_2023-11-22_final
2023-12-05 12:05:19	ga_s2am_ard_3-2-1_50JKQ_2023-12-05_final
2023-12-22 11:57:02	ga_s2am_ard_3-2-1_50HMH_2023-12-22_final
2024-01-01 11:56:22	ga_s2am_ard_3-2-1_50JLL_2024-01-01_final
2024-01-08 11:47:10	ga_s2am_ard_3-2-1_50HLH_2024-01-08_final
2024-01-18 11:46:34	ga_s2am_ard_3-2-1_50HQJ_2024-01-18_final
2024-01-21 11:56:41	ga_s2am_ard_3-2-1_50HMJ_2024-01-21_final
2024-01-25 11:37:00	ga_s2am_ard_3-2-1_50HPH_2024-01-25_final
2024-02-07 11:46:34	ga_s2am_ard_3-2-1_50HPK_2024-02-07_final
2024-02-13 12:04:43	ga_s2am_ard_3-2-1_49JGN_2024-02-13_final
2024-03-01 11:56:44	ga_s2am_ard_3-2-1_50HLK_2024-03-01_final
2024-03-24 12:04:43	ga_s2am_ard_3-2-1_49JHN_2024-03-24_final
2024-04-13 12:04:47	ga_s2am_ard_3-2-1_49JGN_2024-04-13_final
2024-05-07 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2024-05-07_final
2024-05-14 11:37:20	ga_s2am_ard_3-2-1_50HQG_2024-05-14_final
2024-05-17 11:46:36	ga_s2am_ard_3-2-1_50HPK_2024-05-17_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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