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
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HPJ_2015-12-08_final.stac-item
2016-03-07 11:32:50	ga_s2am_ard_3-2-1_50HPJ_2016-03-07_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HNK_2016-04-29_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HPJ_2016-11-12_final.stac-item
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HNH_2016-12-05_final.stac-item
2016-12-28 11:55:47	ga_s2am_ard_3-2-1_50HLJ_2016-12-28_final.stac-item
2017-04-14 11:45:07	ga_s2am_ard_3-2-1_50HPJ_2017-04-14_final.stac-item
2017-04-21 11:34:59	ga_s2am_ard_3-2-1_50HPK_2017-04-21_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HPH_2017-07-03_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50HNK_2017-07-16_final.stac-item
2017-07-26 11:56:09	ga_s2am_ard_3-2-1_50HNK_2017-07-26_final.stac-item
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49JGL_2017-08-21_final.stac-item
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_50HPJ_2018-04-09_final.stac-item
2018-05-08 12:13:24	ga_s2am_ard_3-2-1_49KHR_2018-05-08_final.stac-item
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_49JGM_2018-05-15_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50HNK_2018-06-11_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49JHM_2018-07-04_final.stac-item
2018-08-07 11:46:07	ga_s2am_ard_3-2-1_50HMK_2018-08-07_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HPH_2018-09-06_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-11-01_final.stac-item
2018-11-21 12:05:22	ga_s2am_ard_3-2-1_49JGK_2018-11-21_final.stac-item
2018-12-05 11:46:29	ga_s2am_ard_3-2-1_50HNK_2018-12-05_final.stac-item
2019-02-13 11:47:12	ga_s2am_ard_3-2-1_50HLH_2019-02-13_final.stac-item
2019-03-18 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2019-03-18_final.stac-item
2019-05-03 12:14:45	ga_s2am_ard_3-2-1_49JGN_2019-05-03_final.stac-item
2019-05-20 12:04:03	ga_s2am_ard_3-2-1_49KHR_2019-05-20_final.stac-item
2019-06-13 11:46:37	ga_s2am_ard_3-2-1_50HPK_2019-06-13_final.stac-item
2019-06-13 11:46:40	ga_s2am_ard_3-2-1_50HNK_2019-06-13_final.stac-item
2019-06-13 11:46:51	ga_s2am_ard_3-2-1_50HPJ_2019-06-13_final.stac-item
2019-06-19 12:04:03	ga_s2am_ard_3-2-1_49KHR_2019-06-19_final.stac-item
2019-08-31 12:13:59	ga_s2am_ard_3-2-1_49KGR_2019-08-31_final.stac-item
2019-09-01 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2019-09-01_final.stac-item
2019-09-14 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2019-09-14_final.stac-item
2019-09-18 11:37:06	ga_s2am_ard_3-2-1_50HPH_2019-09-18_final.stac-item
2020-01-05 12:03:54	ga_s2am_ard_3-2-1_49KHR_2020-01-05_final.stac-item
2020-02-01 11:56:48	ga_s2am_ard_3-2-1_50HLJ_2020-02-01_final.stac-item
2020-02-18 11:46:30	ga_s2am_ard_3-2-1_50HNK_2020-02-18_final.stac-item
2020-04-01 11:56:36	ga_s2am_ard_3-2-1_50HLK_2020-04-01_final.stac-item
2020-04-01 11:57:05	ga_s2am_ard_3-2-1_50HLH_2020-04-01_final.stac-item
2020-04-18 11:46:38	ga_s2am_ard_3-2-1_50HNK_2020-04-18_final.stac-item
2020-04-28 11:46:40	ga_s2am_ard_3-2-1_50HNK_2020-04-28_final.stac-item
2020-04-28 11:46:54	ga_s2am_ard_3-2-1_50HNJ_2020-04-28_final.stac-item
2020-05-11 11:56:34	ga_s2am_ard_3-2-1_50HNK_2020-05-11_final.stac-item
2020-06-03 12:05:07	ga_s2am_ard_3-2-1_49JGM_2020-06-03_final.stac-item
2020-06-27 11:47:01	ga_s2am_ard_3-2-1_50HMJ_2020-06-27_final.stac-item
2020-08-12 12:04:05	ga_s2am_ard_3-2-1_49KHR_2020-08-12_final.stac-item
2020-09-05 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2020-09-05_final.stac-item
2020-09-14 12:14:02	ga_s2am_ard_3-2-1_49KGR_2020-09-14_final.stac-item
2020-11-10 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2020-11-10_final.stac-item
2020-12-30 12:03:59	ga_s2am_ard_3-2-1_49KHR_2020-12-30_final.stac-item
2021-03-11 11:37:12	ga_s2am_ard_3-2-1_50HPH_2021-03-11_final.stac-item
2021-03-27 11:57:21	ga_s2am_ard_3-2-1_50HLG_2021-03-27_final
2021-04-13 11:46:35	ga_s2am_ard_3-2-1_50HMK_2021-04-13_final.stac-item
2021-05-23 11:46:34	ga_s2am_ard_3-2-1_50HPK_2021-05-23_final.stac-item
2021-07-11 12:14:30	ga_s2am_ard_3-2-1_49KGP_2021-07-11_final.stac-item
2021-07-12 11:47:24	ga_s2am_ard_3-2-1_50HNG_2021-07-12_final
2021-07-31 12:14:59	ga_s2am_ard_3-2-1_49JGM_2021-07-31_final.stac-item
2021-08-07 12:05:03	ga_s2am_ard_3-2-1_49JGM_2021-08-07_final.stac-item
2021-08-10 12:14:44	ga_s2am_ard_3-2-1_49JGN_2021-08-10_final.stac-item
2021-09-20 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2021-09-20_final.stac-item
2021-10-09 12:14:46	ga_s2am_ard_3-2-1_49JGN_2021-10-09_final.stac-item
2021-10-19 12:15:01	ga_s2am_ard_3-2-1_49JGM_2021-10-19_final.stac-item
2021-10-30 11:47:11	ga_s2am_ard_3-2-1_50HNH_2021-10-30_final.stac-item
2021-12-15 12:03:59	ga_s2am_ard_3-2-1_49KHR_2021-12-15_final.stac-item
2022-01-08 11:47:08	ga_s2am_ard_3-2-1_50HNH_2022-01-08_final.stac-item
2022-04-04 12:04:44	ga_s2am_ard_3-2-1_49JHN_2022-04-04_final.stac-item
2022-05-11 11:56:44	ga_s2am_ard_3-2-1_50HLK_2022-05-11_final.stac-item
2022-05-25 11:36:45	ga_s2am_ard_3-2-1_50HPK_2022-05-25_final.stac-item
2022-06-06 12:14:02	ga_s2am_ard_3-2-1_49KHR_2022-06-06_final.stac-item
2022-08-09 11:56:48	ga_s2am_ard_3-2-1_50HMK_2022-08-09_final.stac-item
2022-09-01 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-09-01_final.stac-item
2022-10-21 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2022-10-21_final.stac-item
2022-12-17 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2022-12-17_final.stac-item
2023-01-29 12:04:29	ga_s2am_ard_3-2-1_49KGP_2023-01-29_final.stac-item
2023-02-18 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2023-02-18_final
2023-05-09 12:05:29	ga_s2am_ard_3-2-1_49JGK_2023-05-09_final
2023-06-02 11:46:38	ga_s2am_ard_3-2-1_50HPK_2023-06-02_final
2023-06-12 11:46:38	ga_s2am_ard_3-2-1_50HPK_2023-06-12_final
2023-06-21 12:15:00	ga_s2am_ard_3-2-1_49JGM_2023-06-21_final
2023-07-12 11:46:43	ga_s2am_ard_3-2-1_50HNK_2023-07-12_final
2023-07-12 11:47:29	ga_s2am_ard_3-2-1_50HMG_2023-07-12_final
2023-08-08 11:36:56	ga_s2am_ard_3-2-1_50HPJ_2023-08-08_final
2023-08-17 12:05:06	ga_s2am_ard_3-2-1_49JGM_2023-08-17_final
2023-09-07 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2023-09-07_final
2023-09-26 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2023-09-26_final
2023-10-26 12:03:59	ga_s2am_ard_3-2-1_49KHR_2023-10-26_final
2023-11-16 11:36:50	ga_s2am_ard_3-2-1_50HPJ_2023-11-16_final
2023-11-26 11:37:21	ga_s2am_ard_3-2-1_50HNG_2023-11-26_final
2023-12-12 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2023-12-12_final
2023-12-15 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2023-12-15_final
2023-12-22 11:56:26	ga_s2am_ard_3-2-1_50HNK_2023-12-22_final
2024-01-04 12:04:39	ga_s2am_ard_3-2-1_49JHN_2024-01-04_final
2024-01-04 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2024-01-04_final
2024-01-09 12:50:55	ga_s2am_ard_3-2-1_48LWP_2024-01-09_final
2024-01-11 11:57:15	ga_s2am_ard_3-2-1_50HMG_2024-01-11_final
2024-02-07 11:46:30	ga_s2am_ard_3-2-1_50HNK_2024-02-07_final
2024-02-14 11:37:18	ga_s2am_ard_3-2-1_50HPG_2024-02-14_final
2024-02-17 11:47:04	ga_s2am_ard_3-2-1_50HNH_2024-02-17_final
2024-03-31 11:57:08	ga_s2am_ard_3-2-1_50HLH_2024-03-31_final
2024-04-27 11:47:26	ga_s2am_ard_3-2-1_50HMG_2024-04-27_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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