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
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50HMH_2016-04-19_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_50JKN_2016-09-12_final.stac-item
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50HLJ_2017-01-07_final.stac-item
2017-02-13 11:44:16	ga_s2am_ard_3-2-1_50HMK_2017-02-13_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50HMH_2017-02-16_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50JKN_2017-04-07_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50JKP_2017-06-19_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JKN_2017-06-26_final.stac-item
2017-09-20 12:14:37	ga_s2am_ard_3-2-1_49JFM_2017-09-20_final.stac-item
2018-02-01 11:49:16	ga_s2am_ard_3-2-1_50JKN_2018-02-01_final.stac-item
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50HLH_2018-02-28_final.stac-item
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50HMH_2018-02-28_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JKM_2018-03-13_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_50HQH_2018-03-17_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JLM_2018-05-02_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50JLM_2018-06-01_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49JHM_2018-07-04_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JKP_2018-07-04_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JKP_2018-08-10_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKP_2018-08-23_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_50HPK_2018-09-03_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50JLN_2018-09-12_final.stac-item
2018-10-03 11:32:47	ga_s2am_ard_3-2-1_50HPJ_2018-10-03_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-10-05_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50JLN_2018-10-09_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JGM_2018-10-12_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JLL_2018-10-19_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JKP_2018-10-22_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50HNK_2018-10-26_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HMH_2018-10-29_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50HPJ_2018-11-05_final.stac-item
2018-11-21 12:05:48	ga_s2am_ard_3-2-1_50JKN_2018-11-21_final.stac-item
2018-11-28 11:55:51	ga_s2am_ard_3-2-1_50JKN_2018-11-28_final.stac-item
2018-11-28 11:56:46	ga_s2am_ard_3-2-1_50HLJ_2018-11-28_final.stac-item
2018-12-18 11:55:38	ga_s2am_ard_3-2-1_50JKP_2018-12-18_final.stac-item
2018-12-25 11:46:30	ga_s2am_ard_3-2-1_50HNK_2018-12-25_final.stac-item
2019-01-03 12:13:49	ga_s2am_ard_3-2-1_49KHR_2019-01-03_final.stac-item
2019-02-13 11:47:03	ga_s2am_ard_3-2-1_50HMH_2019-02-13_final.stac-item
2019-06-19 12:06:08	ga_s2am_ard_3-2-1_50JLM_2019-06-19_final.stac-item
2019-07-09 12:05:57	ga_s2am_ard_3-2-1_50JLN_2019-07-09_final.stac-item
2019-10-24 11:57:09	ga_s2am_ard_3-2-1_50HMH_2019-10-24_final.stac-item
2019-12-03 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2019-12-03_final.stac-item
2019-12-26 12:05:50	ga_s2am_ard_3-2-1_50JKN_2019-12-26_final.stac-item
2020-02-04 12:05:33	ga_s2am_ard_3-2-1_50JKP_2020-02-04_final.stac-item
2020-02-08 11:46:47	ga_s2am_ard_3-2-1_50HMJ_2020-02-08_final.stac-item
2020-02-11 11:57:02	ga_s2am_ard_3-2-1_50HLH_2020-02-11_final.stac-item
2020-04-04 12:05:52	ga_s2am_ard_3-2-1_50JKN_2020-04-04_final.stac-item
2020-05-21 11:56:05	ga_s2am_ard_3-2-1_50JKN_2020-05-21_final.stac-item
2020-07-03 12:06:00	ga_s2am_ard_3-2-1_50JKN_2020-07-03_final.stac-item
2020-08-12 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-08-12_final.stac-item
2020-10-31 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-10-31_final.stac-item
2020-11-10 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2020-11-10_final.stac-item
2020-12-27 11:55:56	ga_s2am_ard_3-2-1_50JLN_2020-12-27_final.stac-item
2020-12-30 12:05:51	ga_s2am_ard_3-2-1_50JLN_2020-12-30_final.stac-item
2021-02-02 11:47:06	ga_s2am_ard_3-2-1_50HNH_2021-02-02_final.stac-item
2021-03-27 11:55:44	ga_s2am_ard_3-2-1_50JKP_2021-03-27_final.stac-item
2021-04-10 11:36:44	ga_s2am_ard_3-2-1_50HQJ_2021-04-10_final.stac-item
2021-04-22 12:14:55	ga_s2am_ard_3-2-1_49JFM_2021-04-22_final.stac-item
2021-05-16 11:55:46	ga_s2am_ard_3-2-1_50JKP_2021-05-16_final.stac-item
2021-06-05 11:55:57	ga_s2am_ard_3-2-1_50JLN_2021-06-05_final.stac-item
2021-06-21 12:14:57	ga_s2am_ard_3-2-1_49JGM_2021-06-21_final.stac-item
2021-07-08 12:03:47	ga_s2am_ard_3-2-1_49KHS_2021-07-08_final
2021-07-09 11:37:24	ga_s2am_ard_3-2-1_50HPG_2021-07-09_final
2021-07-22 11:47:20	ga_s2am_ard_3-2-1_50HPG_2021-07-22_final
2021-08-27 12:05:31	ga_s2am_ard_3-2-1_49JGK_2021-08-27_final.stac-item
2021-09-10 11:47:06	ga_s2am_ard_3-2-1_50HNH_2021-09-10_final.stac-item
2021-09-20 11:47:27	ga_s2am_ard_3-2-1_50HMG_2021-09-20_final
2021-11-05 12:05:33	ga_s2am_ard_3-2-1_49JGK_2021-11-05_final.stac-item
2021-12-22 11:56:52	ga_s2am_ard_3-2-1_50HMJ_2021-12-22_final.stac-item
2021-12-22 11:57:07	ga_s2am_ard_3-2-1_50HMH_2021-12-22_final.stac-item
2021-12-25 12:05:42	ga_s2am_ard_3-2-1_50JKP_2021-12-25_final.stac-item
2022-01-24 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2022-01-24_final.stac-item
2022-02-20 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-02-20_final.stac-item
2022-06-20 11:56:48	ga_s2am_ard_3-2-1_50HMK_2022-06-20_final.stac-item
2022-07-17 11:46:46	ga_s2am_ard_3-2-1_50HPK_2022-07-17_final.stac-item
2022-07-30 11:57:07	ga_s2am_ard_3-2-1_50HLJ_2022-07-30_final.stac-item
2022-08-06 11:46:49	ga_s2am_ard_3-2-1_50HNK_2022-08-06_final.stac-item
2022-08-13 11:37:15	ga_s2am_ard_3-2-1_50HQH_2022-08-13_final.stac-item
2022-11-27 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2022-11-27_final.stac-item
2022-12-07 11:57:06	ga_s2am_ard_3-2-1_50HMH_2022-12-07_final.stac-item
2022-12-14 11:47:14	ga_s2am_ard_3-2-1_50HLH_2022-12-14_final.stac-item
2022-12-17 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2022-12-17_final.stac-item
2022-12-27 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2022-12-27_final.stac-item
2023-01-03 11:47:13	ga_s2am_ard_3-2-1_50HLH_2023-01-03_final.stac-item
2023-02-01 12:14:54	ga_s2am_ard_3-2-1_49JGM_2023-02-01_final.stac-item
2023-02-18 12:05:52	ga_s2am_ard_3-2-1_50JKN_2023-02-18_final
2023-02-25 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2023-02-25_final
2023-04-13 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2023-04-13_final
2023-04-13 11:47:06	ga_s2am_ard_3-2-1_50HNH_2023-04-13_final
2023-07-12 11:47:29	ga_s2am_ard_3-2-1_50HMG_2023-07-12_final
2023-09-06 12:05:31	ga_s2am_ard_3-2-1_50JKQ_2023-09-06_final
2023-10-03 11:56:38	ga_s2am_ard_3-2-1_50HMK_2023-10-03_final
2023-10-23 11:55:46	ga_s2am_ard_3-2-1_50JKP_2023-10-23_final
2023-11-15 12:04:59	ga_s2am_ard_3-2-1_49JGM_2023-11-15_final
2023-11-22 11:57:02	ga_s2am_ard_3-2-1_50HMH_2023-11-22_final
2023-11-29 11:46:47	ga_s2am_ard_3-2-1_50HMJ_2023-11-29_final
2023-12-02 11:56:43	ga_s2am_ard_3-2-1_50HMJ_2023-12-02_final
2024-01-08 11:47:10	ga_s2am_ard_3-2-1_50HLH_2024-01-08_final
2024-01-21 11:56:58	ga_s2am_ard_3-2-1_50HMH_2024-01-21_final
2024-02-06 12:13:36	ga_s2am_ard_3-2-1_49KHS_2024-02-06_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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