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
2015-12-27 12:05:00	ga_s2am_ard_3-2-1_49JGN_2015-12-27_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HMK_2016-06-18_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49JHM_2016-10-02_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KHQ_2016-10-22_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49KHS_2016-11-01_final
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50HPK_2016-11-02_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HMH_2016-11-05_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HPH_2016-11-15_final.stac-item
2017-04-14 11:45:07	ga_s2am_ard_3-2-1_50HNJ_2017-04-14_final.stac-item
2017-05-31 11:35:01	ga_s2am_ard_3-2-1_50HPH_2017-05-31_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50HMH_2017-06-13_final.stac-item
2017-06-20 11:34:58	ga_s2am_ard_3-2-1_50HPK_2017-06-20_final.stac-item
2017-07-16 11:56:34	ga_s2am_ard_3-2-1_50HMH_2017-07-16_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50HLJ_2017-08-25_final.stac-item
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50HLK_2017-12-23_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50HMJ_2018-01-19_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HQJ_2018-02-18_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49JGN_2018-02-24_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50HLK_2018-07-01_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49JGN_2018-07-24_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49JGL_2018-08-06_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGL_2018-08-13_final.stac-item
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_49KGR_2018-09-25_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HQJ_2018-10-16_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HMH_2018-10-29_final.stac-item
2018-12-04 12:14:33	ga_s2am_ard_3-2-1_49JGN_2018-12-04_final.stac-item
2019-02-16 11:55:43	ga_s2am_ard_3-2-1_50JKP_2019-02-16_final.stac-item
2019-02-16 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2019-02-16_final.stac-item
2019-02-20 11:36:30	ga_s2am_ard_3-2-1_50HQK_2019-02-20_final.stac-item
2019-05-21 11:37:10	ga_s2am_ard_3-2-1_50HPH_2019-05-21_final.stac-item
2019-06-09 12:04:30	ga_s2am_ard_3-2-1_49KHP_2019-06-09_final.stac-item
2019-07-09 12:04:33	ga_s2am_ard_3-2-1_49KHP_2019-07-09_final.stac-item
2019-08-15 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2019-08-15_final.stac-item
2019-08-19 11:36:51	ga_s2am_ard_3-2-1_50HQJ_2019-08-19_final.stac-item
2019-09-17 12:05:40	ga_s2am_ard_3-2-1_50JKP_2019-09-17_final.stac-item
2019-09-28 11:36:53	ga_s2am_ard_3-2-1_50HPJ_2019-09-28_final.stac-item
2019-10-07 12:04:48	ga_s2am_ard_3-2-1_49JGN_2019-10-07_final.stac-item
2019-10-17 12:04:49	ga_s2am_ard_3-2-1_49JGN_2019-10-17_final.stac-item
2019-11-13 11:56:57	ga_s2am_ard_3-2-1_50HLJ_2019-11-13_final.stac-item
2019-11-17 11:36:50	ga_s2am_ard_3-2-1_50HQJ_2019-11-17_final.stac-item
2019-11-26 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2019-11-26_final.stac-item
2019-11-27 11:37:03	ga_s2am_ard_3-2-1_50HQH_2019-11-27_final.stac-item
2019-11-30 11:46:29	ga_s2am_ard_3-2-1_50HQK_2019-11-30_final.stac-item
2020-01-08 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2020-01-08_final.stac-item
2020-01-09 11:46:57	ga_s2am_ard_3-2-1_50HPH_2020-01-09_final.stac-item
2020-01-26 11:37:00	ga_s2am_ard_3-2-1_50HPH_2020-01-26_final.stac-item
2020-02-18 11:47:00	ga_s2am_ard_3-2-1_50HNH_2020-02-18_final.stac-item
2020-02-18 11:47:08	ga_s2am_ard_3-2-1_50HLH_2020-02-18_final.stac-item
2020-03-08 12:13:54	ga_s2am_ard_3-2-1_49KGR_2020-03-08_final.stac-item
2020-03-12 11:57:05	ga_s2am_ard_3-2-1_50HLH_2020-03-12_final.stac-item
2020-05-17 12:15:25	ga_s2am_ard_3-2-1_49JGK_2020-05-17_final.stac-item
2020-07-04 11:36:39	ga_s2am_ard_3-2-1_50HQK_2020-07-04_final.stac-item
2020-07-27 11:46:35	ga_s2am_ard_3-2-1_50HQK_2020-07-27_final.stac-item
2020-09-08 11:56:44	ga_s2am_ard_3-2-1_50HLK_2020-09-08_final.stac-item
2020-09-11 12:05:00	ga_s2am_ard_3-2-1_49JHM_2020-09-11_final.stac-item
2020-10-21 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2020-10-21_final.stac-item
2020-11-10 12:04:32	ga_s2am_ard_3-2-1_49KHP_2020-11-10_final.stac-item
2021-01-13 11:47:07	ga_s2am_ard_3-2-1_50HNH_2021-01-13_final.stac-item
2021-01-23 11:47:10	ga_s2am_ard_3-2-1_50HMH_2021-01-23_final.stac-item
2021-02-11 12:13:57	ga_s2am_ard_3-2-1_49KGR_2021-02-11_final.stac-item
2021-02-25 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2021-02-25_final.stac-item
2021-02-28 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-02-28_final
2021-03-14 11:47:06	ga_s2am_ard_3-2-1_50HNH_2021-03-14_final.stac-item
2021-05-13 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2021-05-13_final.stac-item
2021-08-24 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2021-08-24_final.stac-item
2021-09-29 12:13:59	ga_s2am_ard_3-2-1_49KHR_2021-09-29_final.stac-item
2021-12-05 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2021-12-05_final.stac-item
2021-12-16 11:36:38	ga_s2am_ard_3-2-1_50HPK_2021-12-16_final.stac-item
2021-12-19 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2021-12-19_final.stac-item
2022-01-08 11:47:16	ga_s2am_ard_3-2-1_50HLH_2022-01-08_final.stac-item
2022-03-06 11:36:42	ga_s2am_ard_3-2-1_50HPK_2022-03-06_final.stac-item
2022-03-06 11:37:07	ga_s2am_ard_3-2-1_50HQH_2022-03-06_final.stac-item
2022-03-08 12:14:02	ga_s2am_ard_3-2-1_49KGR_2022-03-08_final.stac-item
2022-04-08 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2022-04-08_final.stac-item
2022-05-05 11:36:34	ga_s2am_ard_3-2-1_50HQK_2022-05-05_final.stac-item
2022-05-21 11:57:16	ga_s2am_ard_3-2-1_50HLH_2022-05-21_final.stac-item
2022-06-30 11:57:08	ga_s2am_ard_3-2-1_50HLJ_2022-06-30_final.stac-item
2022-08-22 12:04:26	ga_s2am_ard_3-2-1_49KHQ_2022-08-22_final.stac-item
2022-09-28 11:55:54	ga_s2am_ard_3-2-1_50JKP_2022-09-28_final.stac-item
2022-10-14 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2022-10-14_final.stac-item
2022-11-27 11:55:46	ga_s2am_ard_3-2-1_50JKP_2022-11-27_final.stac-item
2022-12-24 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2022-12-24_final.stac-item
2022-12-30 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2022-12-30_final.stac-item
2023-02-02 11:46:28	ga_s2am_ard_3-2-1_50HQK_2023-02-02_final
2023-02-08 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-02-08_final
2023-02-22 11:47:07	ga_s2am_ard_3-2-1_50HMH_2023-02-22_nrt.stac-item
2023-02-22 11:47:07	ga_s2am_ard_3-2-1_50HMH_2023-02-22_final
2023-03-04 11:46:45	ga_s2am_ard_3-2-1_50HPJ_2023-03-04_final
2023-05-12 12:13:39	ga_s2am_ard_3-2-1_49KHS_2023-05-12_final
2023-07-15 11:56:41	ga_s2am_ard_3-2-1_50HMK_2023-07-15_final
2023-07-15 11:57:27	ga_s2am_ard_3-2-1_50HLG_2023-07-15_final
2023-08-01 11:47:01	ga_s2am_ard_3-2-1_50HMJ_2023-08-01_final
2023-08-04 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-08-04_final
2023-08-11 11:47:25	ga_s2am_ard_3-2-1_50HNG_2023-08-11_final
2023-09-07 11:37:32	ga_s2am_ard_3-2-1_50HNG_2023-09-07_final
2023-12-05 12:04:21	ga_s2am_ard_3-2-1_49KHP_2023-12-05_final
2023-12-15 12:03:40	ga_s2am_ard_3-2-1_49KHS_2023-12-15_final
2023-12-15 12:04:09	ga_s2am_ard_3-2-1_49KHQ_2023-12-15_final
2024-02-14 11:37:15	ga_s2am_ard_3-2-1_50HQG_2024-02-14_final
2024-02-27 11:47:09	ga_s2am_ard_3-2-1_50HMH_2024-02-27_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

All years