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
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HQK_2015-12-21_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_50HPH_2016-02-06_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HNJ_2016-03-20_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50JKP_2016-07-14_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50HPG_2016-07-28_final
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49JHN_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KHR_2016-10-02_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49KHR_2016-11-01_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50HNG_2016-11-02_final
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JHN_2016-11-11_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HPK_2016-11-12_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49JGN_2016-12-01_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50HMJ_2017-02-16_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50HMK_2017-06-13_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_49JGN_2017-07-29_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49KHR_2017-08-01_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_50JKP_2017-08-18_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50HLH_2017-12-10_final.stac-item
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50HMH_2017-12-23_final.stac-item
2018-01-25 12:02:44	ga_s2am_ard_3-2-1_49KHQ_2018-01-25_final.stac-item
2018-02-15 11:34:02	ga_s2am_ard_3-2-1_50HPK_2018-02-15_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_50HQK_2018-03-17_final.stac-item
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_49JGL_2018-05-05_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HMH_2018-05-12_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50HMJ_2018-06-08_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGK_2018-08-13_final.stac-item
2019-01-27 11:57:06	ga_s2am_ard_3-2-1_50HLH_2019-01-27_final.stac-item
2019-02-26 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2019-02-26_final.stac-item
2019-03-31 12:04:13	ga_s2am_ard_3-2-1_49KHQ_2019-03-31_final.stac-item
2019-03-31 12:04:46	ga_s2am_ard_3-2-1_49JGN_2019-03-31_final.stac-item
2019-06-19 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-06-19_final.stac-item
2019-07-06 11:55:51	ga_s2am_ard_3-2-1_50JKP_2019-07-06_final.stac-item
2019-07-26 11:55:51	ga_s2am_ard_3-2-1_50JKP_2019-07-26_final.stac-item
2019-08-12 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2019-08-12_final.stac-item
2019-08-25 11:57:11	ga_s2am_ard_3-2-1_50HLH_2019-08-25_final.stac-item
2019-09-07 12:04:27	ga_s2am_ard_3-2-1_49KHP_2019-09-07_final.stac-item
2019-10-21 11:46:55	ga_s2am_ard_3-2-1_50HNJ_2019-10-21_final.stac-item
2019-12-10 11:46:50	ga_s2am_ard_3-2-1_50HQH_2019-12-10_final.stac-item
2019-12-16 12:04:40	ga_s2am_ard_3-2-1_49JGN_2019-12-16_final.stac-item
2019-12-17 11:36:46	ga_s2am_ard_3-2-1_50HPJ_2019-12-17_final.stac-item
2020-01-16 11:36:22	ga_s2am_ard_3-2-1_50HQK_2020-01-16_final.stac-item
2020-02-08 11:46:46	ga_s2am_ard_3-2-1_50HQH_2020-02-08_final.stac-item
2020-02-24 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2020-02-24_final.stac-item
2020-03-05 12:04:42	ga_s2am_ard_3-2-1_49JGN_2020-03-05_final.stac-item
2020-03-09 11:46:26	ga_s2am_ard_3-2-1_50HQK_2020-03-09_final.stac-item
2020-05-21 11:57:15	ga_s2am_ard_3-2-1_50HLH_2020-05-21_final.stac-item
2020-06-03 12:04:20	ga_s2am_ard_3-2-1_49KHQ_2020-06-03_final.stac-item
2020-10-01 12:04:52	ga_s2am_ard_3-2-1_49JGN_2020-10-01_final.stac-item
2020-10-05 11:47:20	ga_s2am_ard_3-2-1_50HLH_2020-10-05_final.stac-item
2020-10-25 11:47:15	ga_s2am_ard_3-2-1_50HMH_2020-10-25_final.stac-item
2020-11-21 11:36:36	ga_s2am_ard_3-2-1_50HQK_2020-11-21_final.stac-item
2020-12-07 11:57:03	ga_s2am_ard_3-2-1_50HMH_2020-12-07_final.stac-item
2021-01-09 12:04:28	ga_s2am_ard_3-2-1_49KHP_2021-01-09_final.stac-item
2021-01-30 11:36:38	ga_s2am_ard_3-2-1_50HPK_2021-01-30_final.stac-item
2021-02-12 11:47:05	ga_s2am_ard_3-2-1_50HNH_2021-02-12_final.stac-item
2021-03-14 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-03-14_final
2021-03-21 11:37:02	ga_s2am_ard_3-2-1_50HQH_2021-03-21_final.stac-item
2021-03-30 12:04:54	ga_s2am_ard_3-2-1_49JHM_2021-03-30_final.stac-item
2021-03-31 11:36:31	ga_s2am_ard_3-2-1_50HQK_2021-03-31_final.stac-item
2021-07-28 12:04:28	ga_s2am_ard_3-2-1_49KGP_2021-07-28_final.stac-item
2021-08-28 11:37:19	ga_s2am_ard_3-2-1_50HQG_2021-08-28_final
2021-11-26 11:37:03	ga_s2am_ard_3-2-1_50HQH_2021-11-26_final.stac-item
2021-12-05 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-12-05_final.stac-item
2021-12-26 11:37:08	ga_s2am_ard_3-2-1_50HPH_2021-12-26_final.stac-item
2022-02-23 12:04:16	ga_s2am_ard_3-2-1_49KHQ_2022-02-23_final.stac-item
2022-03-12 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-03-12_final.stac-item
2022-05-11 11:56:55	ga_s2am_ard_3-2-1_50HMJ_2022-05-11_final.stac-item
2022-07-27 11:47:24	ga_s2am_ard_3-2-1_50HLH_2022-07-27_final.stac-item
2022-09-28 11:56:47	ga_s2am_ard_3-2-1_50HLK_2022-09-28_final.stac-item
2022-12-24 11:46:46	ga_s2am_ard_3-2-1_50HPJ_2022-12-24_final.stac-item
2022-12-27 11:56:35	ga_s2am_ard_3-2-1_50HMK_2022-12-27_final.stac-item
2023-01-13 11:46:40	ga_s2am_ard_3-2-1_50HQJ_2023-01-13_final.stac-item
2023-02-02 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2023-02-02_final
2023-02-25 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2023-02-25_final
2023-03-10 12:03:39	ga_s2am_ard_3-2-1_49KHS_2023-03-10_final
2023-04-09 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2023-04-09_final
2023-05-09 12:04:46	ga_s2am_ard_3-2-1_49JGN_2023-05-09_final
2023-05-10 11:36:33	ga_s2am_ard_3-2-1_50HQK_2023-05-10_final
2023-05-20 11:36:36	ga_s2am_ard_3-2-1_50HQK_2023-05-20_final
2023-06-22 11:47:24	ga_s2am_ard_3-2-1_50HNG_2023-06-22_final
2023-06-28 12:04:54	ga_s2am_ard_3-2-1_49JGN_2023-06-28_final
2023-08-14 11:56:42	ga_s2am_ard_3-2-1_50HMK_2023-08-14_final
2023-09-26 12:04:48	ga_s2am_ard_3-2-1_49JGN_2023-09-26_final
2023-10-20 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2023-10-20_final
2023-10-26 12:04:28	ga_s2am_ard_3-2-1_49KHP_2023-10-26_final
2023-12-09 11:46:50	ga_s2am_ard_3-2-1_50HMJ_2023-12-09_final
2023-12-22 11:57:05	ga_s2am_ard_3-2-1_50HLH_2023-12-22_final
2023-12-25 12:03:41	ga_s2am_ard_3-2-1_49KHS_2023-12-25_final
2024-01-08 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2024-01-08_final
2024-01-08 11:47:05	ga_s2am_ard_3-2-1_50HMH_2024-01-08_final
2024-02-10 11:57:02	ga_s2am_ard_3-2-1_50HMH_2024-02-10_final
2024-02-17 11:47:22	ga_s2am_ard_3-2-1_50HMG_2024-02-17_final
2024-03-21 11:57:10	ga_s2am_ard_3-2-1_50HLH_2024-03-21_final
2024-03-21 11:57:21	ga_s2am_ard_3-2-1_50HMG_2024-03-21_final
2024-03-24 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2024-03-24_final
2024-04-07 11:46:32	ga_s2am_ard_3-2-1_50HPK_2024-04-07_final
2024-04-17 11:47:09	ga_s2am_ard_3-2-1_50HNH_2024-04-17_final
2024-04-27 11:46:32	ga_s2am_ard_3-2-1_50HQK_2024-04-27_final
2024-05-07 11:47:09	ga_s2am_ard_3-2-1_50HNH_2024-05-07_final
2024-05-13 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2024-05-13_nrt

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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