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
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HLG_2016-03-20_final
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49JGN_2016-05-15_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50HMG_2016-10-09_final
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49JGN_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50JKR_2016-10-22_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_50HPG_2016-11-22_final
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50HMG_2016-12-08_final
2017-04-10 12:04:40	ga_s2am_ard_3-2-1_50JKT_2017-04-10_final.stac-item
2017-04-27 11:56:35	ga_s2am_ard_3-2-1_50HMH_2017-04-27_final.stac-item
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50HNK_2017-05-24_final.stac-item
2017-06-09 12:04:43	ga_s2am_ard_3-2-1_49JGL_2017-06-09_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49JGN_2017-07-09_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JKR_2017-09-17_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49JHN_2017-09-27_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_49JHN_2017-10-17_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50JKP_2017-10-24_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KHP_2017-12-19_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50HMH_2017-12-30_final.stac-item
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50HMH_2018-02-11_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-03-06_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_50JKP_2018-03-06_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_50JKS_2018-03-06_final.stac-item
2018-03-29 12:13:20	ga_s2am_ard_3-2-1_49JGL_2018-03-29_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HPK_2018-03-30_final.stac-item
2018-04-15 12:05:11	ga_s2am_ard_3-2-1_50JKN_2018-04-15_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50JKR_2018-04-25_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50JKN_2018-05-12_final.stac-item
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_50JKP_2018-05-15_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HPK_2018-05-19_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLM_2018-05-22_final
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_49JGM_2018-05-25_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JLM_2018-05-25_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JKP_2018-06-14_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JKR_2018-06-14_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JLM_2018-06-21_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JLM_2018-07-11_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGM_2018-07-14_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_50HPK_2018-07-25_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50JKP_2018-07-31_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49KHQ_2018-08-06_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_49KGP_2018-08-23_final.stac-item
2018-08-26 12:13:20	ga_s2am_ard_3-2-1_49JGL_2018-08-26_final.stac-item
2018-08-26 12:13:20	ga_s2am_ard_3-2-1_49JGM_2018-08-26_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50HNK_2018-08-27_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_50HPJ_2018-09-03_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JGL_2018-10-12_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2018-10-15_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HNJ_2018-10-16_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JKS_2018-10-22_final.stac-item
2018-11-11 12:05:21	ga_s2am_ard_3-2-1_50JKQ_2018-11-11_final.stac-item
2018-11-28 11:56:42	ga_s2am_ard_3-2-1_50HMJ_2018-11-28_final.stac-item
2018-12-08 11:56:22	ga_s2am_ard_3-2-1_50HNK_2018-12-08_final.stac-item
2018-12-21 12:04:49	ga_s2am_ard_3-2-1_50JKS_2018-12-21_final.stac-item
2019-01-04 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2019-01-04_final.stac-item
2019-04-14 11:47:09	ga_s2am_ard_3-2-1_50HNH_2019-04-14_final.stac-item
2019-05-20 12:05:44	ga_s2am_ard_3-2-1_50JKP_2019-05-20_final.stac-item
2019-05-23 12:14:59	ga_s2am_ard_3-2-1_49JGM_2019-05-23_final.stac-item
2019-05-31 11:36:54	ga_s2am_ard_3-2-1_50HPJ_2019-05-31_final.stac-item
2019-07-10 11:37:08	ga_s2am_ard_3-2-1_50HQH_2019-07-10_final.stac-item
2019-09-27 12:05:02	ga_s2am_ard_3-2-1_49JGM_2019-09-27_final.stac-item
2019-10-11 11:46:33	ga_s2am_ard_3-2-1_50HQK_2019-10-11_final.stac-item
2019-10-14 11:56:28	ga_s2am_ard_3-2-1_50JLL_2019-10-14_final.stac-item
2020-01-12 11:56:34	ga_s2am_ard_3-2-1_50HLK_2020-01-12_final.stac-item
2020-03-25 12:03:55	ga_s2am_ard_3-2-1_49KHR_2020-03-25_final.stac-item
2020-04-27 12:14:23	ga_s2am_ard_3-2-1_49KHP_2020-04-27_final.stac-item
2020-10-28 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2020-10-28_final.stac-item
2020-11-10 12:05:45	ga_s2am_ard_3-2-1_50JKP_2020-11-10_final.stac-item
2020-12-13 12:13:55	ga_s2am_ard_3-2-1_49KGR_2020-12-13_final.stac-item
2020-12-20 12:03:57	ga_s2am_ard_3-2-1_49KHR_2020-12-20_final.stac-item
2021-01-09 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-01-09_final
2021-01-09 12:05:01	ga_s2am_ard_3-2-1_49JGM_2021-01-09_final.stac-item
2021-02-05 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2021-02-05_final.stac-item
2021-03-10 12:05:11	ga_s2am_ard_3-2-1_50JKR_2021-03-10_final.stac-item
2021-03-14 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-03-14_final
2021-03-23 12:13:38	ga_s2am_ard_3-2-1_49KHS_2021-03-23_final
2021-03-24 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2021-03-24_final.stac-item
2021-03-24 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2021-03-24_final.stac-item
2021-03-30 12:05:09	ga_s2am_ard_3-2-1_50JKR_2021-03-30_final.stac-item
2021-04-03 11:46:37	ga_s2am_ard_3-2-1_50HMK_2021-04-03_final.stac-item
2021-05-03 11:46:41	ga_s2am_ard_3-2-1_50HQJ_2021-05-03_final.stac-item
2021-05-09 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-05-09_final.stac-item
2021-05-23 11:46:34	ga_s2am_ard_3-2-1_50HPK_2021-05-23_final.stac-item
2021-05-26 11:55:47	ga_s2am_ard_3-2-1_50JKP_2021-05-26_final.stac-item
2021-06-18 12:04:57	ga_s2am_ard_3-2-1_50JKS_2021-06-18_final.stac-item
2021-06-25 11:56:15	ga_s2am_ard_3-2-1_50JKM_2021-06-25_final.stac-item
2021-07-02 11:46:36	ga_s2am_ard_3-2-1_50HPK_2021-07-02_final.stac-item
2021-07-05 11:56:02	ga_s2am_ard_3-2-1_50JKN_2021-07-05_final.stac-item
2021-07-08 12:04:59	ga_s2am_ard_3-2-1_49JHM_2021-07-08_final.stac-item
2021-07-08 12:05:00	ga_s2am_ard_3-2-1_50JKS_2021-07-08_final.stac-item
2021-07-19 11:36:52	ga_s2am_ard_3-2-1_50HQJ_2021-07-19_final.stac-item
2021-08-07 12:04:49	ga_s2am_ard_3-2-1_49JGN_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
2021-08-17 12:06:07	ga_s2am_ard_3-2-1_50JLM_2021-08-17_final.stac-item
2021-09-26 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2021-09-26_final.stac-item
2022-07-30 11:57:07	ga_s2am_ard_3-2-1_50HLJ_2022-07-30_final.stac-item
2022-08-09 11:56:08	ga_s2am_ard_3-2-1_50JLN_2022-08-09_final.stac-item
2023-08-17 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-08-17_final
2023-10-03 11:55:53	ga_s2am_ard_3-2-1_50JKN_2023-10-03_final
2023-10-03 11:56:27	ga_s2am_ard_3-2-1_50JLL_2023-10-03_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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