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
2015-10-22 11:46:57	ga_s2am_ard_3-2-1_50HMH_2015-10-22_final.stac-item
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KHQ_2015-10-28_final.stac-item
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50HPG_2016-01-07_final
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_49KHR_2016-06-27_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50HLH_2016-07-21_final.stac-item
2016-09-25 12:13:39	ga_s2am_ard_3-2-1_49KHR_2016-09-25_final.stac-item
2016-10-19 11:56:02	ga_s2am_ard_3-2-1_50HMK_2016-10-19_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49JGN_2016-10-25_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50HPH_2016-12-22_final.stac-item
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50HMJ_2017-01-07_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HNH_2017-02-03_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49JGN_2017-07-09_final.stac-item
2017-08-11 12:14:43	ga_s2am_ard_3-2-1_49JGM_2017-08-11_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49JGN_2017-09-30_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49KHR_2017-11-09_final.stac-item
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_49JGK_2018-03-16_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HNJ_2018-03-30_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50HLK_2018-06-21_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49KHQ_2018-11-04_final.stac-item
2018-11-12 11:36:29	ga_s2am_ard_3-2-1_50HQK_2018-11-12_final.stac-item
2018-11-15 11:46:32	ga_s2am_ard_3-2-1_50HNK_2018-11-15_final.stac-item
2018-12-15 11:46:21	ga_s2am_ard_3-2-1_50HQK_2018-12-15_final.stac-item
2019-01-11 11:36:39	ga_s2am_ard_3-2-1_50HPK_2019-01-11_final.stac-item
2019-01-21 11:37:03	ga_s2am_ard_3-2-1_50HPH_2019-01-21_final.stac-item
2019-02-26 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2019-02-26_final.stac-item
2019-04-30 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-04-30_final.stac-item
2019-05-30 12:04:49	ga_s2am_ard_3-2-1_49JGN_2019-05-30_final.stac-item
2019-07-09 12:04:51	ga_s2am_ard_3-2-1_49JGN_2019-07-09_final.stac-item
2019-07-12 12:14:46	ga_s2am_ard_3-2-1_49JGN_2019-07-12_final.stac-item
2019-08-02 11:47:07	ga_s2am_ard_3-2-1_50HPH_2019-08-02_final.stac-item
2019-08-21 12:14:01	ga_s2am_ard_3-2-1_49KGR_2019-08-21_final.stac-item
2019-09-30 12:14:00	ga_s2am_ard_3-2-1_49KGR_2019-09-30_final.stac-item
2019-10-14 11:57:09	ga_s2am_ard_3-2-1_50HMH_2019-10-14_final.stac-item
2019-11-10 11:47:05	ga_s2am_ard_3-2-1_50HPH_2019-11-10_final.stac-item
2019-12-16 12:05:24	ga_s2am_ard_3-2-1_49JGK_2019-12-16_final.stac-item
2019-12-27 11:36:59	ga_s2am_ard_3-2-1_50HPH_2019-12-27_final.stac-item
2020-01-08 12:13:53	ga_s2am_ard_3-2-1_49KGR_2020-01-08_final.stac-item
2020-01-26 11:36:45	ga_s2am_ard_3-2-1_50HPJ_2020-01-26_final.stac-item
2020-02-18 11:46:42	ga_s2am_ard_3-2-1_50HPJ_2020-02-18_final.stac-item
2020-02-27 12:14:36	ga_s2am_ard_3-2-1_49JGN_2020-02-27_final.stac-item
2020-03-02 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2020-03-02_final.stac-item
2020-03-28 12:14:37	ga_s2am_ard_3-2-1_49JGN_2020-03-28_final.stac-item
2020-04-11 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2020-04-11_final.stac-item
2020-05-21 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-05-21_final.stac-item
2020-08-25 12:14:00	ga_s2am_ard_3-2-1_49KHR_2020-08-25_final.stac-item
2020-09-14 12:13:59	ga_s2am_ard_3-2-1_49KHR_2020-09-14_final.stac-item
2020-10-14 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-10-14_final.stac-item
2020-10-28 11:56:42	ga_s2am_ard_3-2-1_50HMK_2020-10-28_final.stac-item
2020-11-13 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2020-11-13_final.stac-item
2020-11-23 12:13:56	ga_s2am_ard_3-2-1_49KHR_2020-11-23_final.stac-item
2020-11-24 11:47:08	ga_s2am_ard_3-2-1_50HNH_2020-11-24_final.stac-item
2020-11-24 11:47:16	ga_s2am_ard_3-2-1_50HLH_2020-11-24_final.stac-item
2020-12-23 12:13:57	ga_s2am_ard_3-2-1_49KGR_2020-12-23_final.stac-item
2020-12-27 11:57:05	ga_s2am_ard_3-2-1_50HMH_2020-12-27_final.stac-item
2021-01-13 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-01-13_final.stac-item
2021-02-01 12:14:41	ga_s2am_ard_3-2-1_49JGN_2021-02-01_final.stac-item
2021-02-22 11:47:02	ga_s2am_ard_3-2-1_50HPH_2021-02-22_final.stac-item
2021-03-10 12:05:15	ga_s2am_ard_3-2-1_49JGL_2021-03-10_final.stac-item
2021-04-19 12:05:11	ga_s2am_ard_3-2-1_49JGL_2021-04-19_final.stac-item
2021-05-26 11:57:05	ga_s2am_ard_3-2-1_50HMH_2021-05-26_final.stac-item
2021-06-01 12:15:11	ga_s2am_ard_3-2-1_49JGL_2021-06-01_final.stac-item
2021-07-11 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2021-07-11_final.stac-item
2021-08-04 11:57:12	ga_s2am_ard_3-2-1_50HLH_2021-08-04_final.stac-item
2021-08-07 12:04:45	ga_s2am_ard_3-2-1_49JHN_2021-08-07_final.stac-item
2021-09-29 12:14:45	ga_s2am_ard_3-2-1_49JGN_2021-09-29_final.stac-item
2021-09-30 11:47:28	ga_s2am_ard_3-2-1_50HMG_2021-09-30_final
2021-10-07 11:36:43	ga_s2am_ard_3-2-1_50HPK_2021-10-07_final.stac-item
2021-10-09 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2021-10-09_final.stac-item
2021-12-18 12:13:59	ga_s2am_ard_3-2-1_49KGR_2021-12-18_final.stac-item
2022-01-27 12:14:56	ga_s2am_ard_3-2-1_49JGM_2022-01-27_final.stac-item
2022-01-31 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2022-01-31_final.stac-item
2022-07-23 12:05:08	ga_s2am_ard_3-2-1_49JHM_2022-07-23_final.stac-item
2022-08-22 12:05:09	ga_s2am_ard_3-2-1_49JHM_2022-08-22_final.stac-item
2022-09-24 12:14:02	ga_s2am_ard_3-2-1_49KHR_2022-09-24_final.stac-item
2022-10-14 12:15:15	ga_s2am_ard_3-2-1_49JGL_2022-10-14_final.stac-item
2022-11-13 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2022-11-13_final.stac-item
2022-12-01 11:37:07	ga_s2am_ard_3-2-1_50HPH_2022-12-01_final.stac-item
2022-12-13 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2022-12-13_final.stac-item
2022-12-27 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2022-12-27_final.stac-item
2023-01-22 12:15:06	ga_s2am_ard_3-2-1_49JGL_2023-01-22_final.stac-item
2023-02-12 11:47:05	ga_s2am_ard_3-2-1_50HNH_2023-02-12_nrt.stac-item
2023-03-10 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-03-10_final
2023-03-13 12:14:38	ga_s2am_ard_3-2-1_49JGN_2023-03-13_final
2023-04-23 11:47:20	ga_s2am_ard_3-2-1_50HNG_2023-04-23_final
2023-05-03 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2023-05-03_final
2023-05-20 11:36:56	ga_s2am_ard_3-2-1_50HQH_2023-05-20_final
2023-06-19 11:36:42	ga_s2am_ard_3-2-1_50HPK_2023-06-19_final
2023-07-01 12:14:03	ga_s2am_ard_3-2-1_49KGR_2023-07-01_final
2023-08-11 11:47:21	ga_s2am_ard_3-2-1_50HPG_2023-08-11_final
2023-09-19 12:13:57	ga_s2am_ard_3-2-1_49KHR_2023-09-19_final
2023-10-17 11:37:16	ga_s2am_ard_3-2-1_50HQG_2023-10-17_final
2023-11-02 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2023-11-02_final
2023-11-15 12:04:26	ga_s2am_ard_3-2-1_49KHP_2023-11-15_final
2023-11-19 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2023-11-19_final
2023-12-09 11:47:09	ga_s2am_ard_3-2-1_50HLH_2023-12-09_final
2023-12-19 11:47:10	ga_s2am_ard_3-2-1_50HLH_2023-12-19_final
2024-01-01 11:56:37	ga_s2am_ard_3-2-1_50HLK_2024-01-01_final
2024-03-11 11:56:35	ga_s2am_ard_3-2-1_50HMK_2024-03-11_final
2024-03-21 11:56:38	ga_s2am_ard_3-2-1_50HLK_2024-03-21_final
2024-03-24 12:03:46	ga_s2am_ard_3-2-1_49KHS_2024-03-24_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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