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
2015-10-21 12:09:42	ga_s2am_ard_3-2-1_49KGQ_2015-10-21_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50JQM_2015-12-21_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JXG_2016-01-24_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_51HUD_2016-02-06_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_51KUT_2016-04-19_final.stac-item
2016-04-20 11:12:16	ga_s2am_ard_3-2-1_52JDT_2016-04-20_final.stac-item
2016-06-09 11:12:19	ga_s2am_ard_3-2-1_52KDF_2016-06-09_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_51KXQ_2016-09-13_final.stac-item
2016-12-06 11:07:09	ga_s2am_ard_3-2-1_52KDD_2016-12-06_final.stac-item
2016-12-06 11:07:09	ga_s2am_ard_3-2-1_52KDG_2016-12-06_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49KGQ_2016-12-21_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49JFM_2016-12-24_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49KGP_2016-12-24_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_50KKU_2016-12-24_final.stac-item
2017-01-05 11:12:08	ga_s2am_ard_3-2-1_52KDD_2017-01-05_final.stac-item
2017-01-24 11:35:42	ga_s2am_ard_3-2-1_51LUE_2017-01-24_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_49KHQ_2017-01-30_final.stac-item
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49KHR_2017-02-12_final.stac-item
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49KGR_2017-02-22_final.stac-item
2017-03-09 11:26:01	ga_s2am_ard_3-2-1_51JXF_2017-03-09_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_49JGJ_2017-11-06_final.stac-item
2019-01-15 11:13:15	ga_s2am_ard_3-2-1_52KDB_2019-01-15_final.stac-item
2019-01-15 11:14:03	ga_s2am_ard_3-2-1_52JET_2019-01-15_final.stac-item
2019-01-28 11:21:57	ga_s2am_ard_3-2-1_52KDG_2019-01-28_final.stac-item
2019-02-09 12:03:23	ga_s2am_ard_3-2-1_50KLC_2019-02-09_final.stac-item
2019-02-10 11:32:08	ga_s2am_ard_3-2-1_51KXB_2019-02-10_final.stac-item
2019-02-22 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-02-22_final.stac-item
2019-03-03 11:05:58	ga_s2am_ard_3-2-1_52JDL_2019-03-03_final.stac-item
2019-03-12 11:33:19	ga_s2am_ard_3-2-1_51KXS_2019-03-12_final.stac-item
2019-03-26 11:13:53	ga_s2am_ard_3-2-1_52KBV_2019-03-26_final.stac-item
2019-04-18 11:23:52	ga_s2am_ard_3-2-1_52KBV_2019-04-18_final.stac-item
2019-04-18 11:24:01	ga_s2am_ard_3-2-1_52KBU_2019-04-18_final.stac-item
2019-05-14 11:41:37	ga_s2am_ard_3-2-1_51LUE_2019-05-14_final.stac-item
2019-07-24 11:13:18	ga_s2am_ard_3-2-1_52KBC_2019-07-24_final.stac-item
2019-08-12 11:42:49	ga_s2am_ard_3-2-1_51KUV_2019-08-12_final.stac-item
2019-10-01 11:43:16	ga_s2am_ard_3-2-1_51KUT_2019-10-01_final.stac-item
2019-11-26 12:03:27	ga_s2am_ard_3-2-1_50KLC_2019-11-26_final.stac-item
2019-11-26 12:03:44	ga_s2am_ard_3-2-1_50KNA_2019-11-26_final.stac-item
2019-12-11 11:13:00	ga_s2am_ard_3-2-1_52KDC_2019-12-11_final.stac-item
2020-02-01 11:52:30	ga_s2am_ard_3-2-1_50KPF_2020-02-01_final
2020-03-19 11:43:11	ga_s2am_ard_3-2-1_51KUT_2020-03-19_final.stac-item
2020-04-18 11:43:15	ga_s2am_ard_3-2-1_51KUT_2020-04-18_final.stac-item
2020-05-02 11:23:59	ga_s2am_ard_3-2-1_51KXQ_2020-05-02_final.stac-item
2020-05-05 11:33:26	ga_s2am_ard_3-2-1_51KUT_2020-05-05_final.stac-item
2020-07-20 11:52:39	ga_s2am_ard_3-2-1_50KQF_2020-07-20_final
2020-07-31 11:24:11	ga_s2am_ard_3-2-1_52KBU_2020-07-31_final.stac-item
2020-08-24 11:03:25	ga_s2am_ard_3-2-1_52KEB_2020-08-24_final.stac-item
2020-08-26 11:43:30	ga_s2am_ard_3-2-1_51KVS_2020-08-26_final.stac-item
2020-08-29 11:52:39	ga_s2am_ard_3-2-1_50KQF_2020-08-29_final
2020-09-05 11:44:02	ga_s2am_ard_3-2-1_51KUQ_2020-09-05_final.stac-item
2020-09-06 11:12:57	ga_s2am_ard_3-2-1_52KCD_2020-09-06_final.stac-item
2020-09-06 11:13:18	ga_s2am_ard_3-2-1_52KBC_2020-09-06_final.stac-item
2020-09-06 11:13:31	ga_s2am_ard_3-2-1_52KEA_2020-09-06_final.stac-item
2020-09-09 11:24:01	ga_s2am_ard_3-2-1_51KXQ_2020-09-09_final.stac-item
2020-09-12 11:33:26	ga_s2am_ard_3-2-1_51KUT_2020-09-12_final.stac-item
2020-09-12 11:33:36	ga_s2am_ard_3-2-1_51KUS_2020-09-12_final.stac-item
2020-09-15 11:41:37	ga_s2am_ard_3-2-1_51LUE_2020-09-15_final.stac-item
2020-09-15 11:43:48	ga_s2am_ard_3-2-1_51KUR_2020-09-15_final.stac-item
2020-09-19 11:23:54	ga_s2am_ard_3-2-1_52KBV_2020-09-19_final.stac-item
2020-09-19 11:24:09	ga_s2am_ard_3-2-1_51KZP_2020-09-19_final.stac-item
2020-09-19 11:24:24	ga_s2am_ard_3-2-1_52JBT_2020-09-19_final.stac-item
2020-09-22 11:33:57	ga_s2am_ard_3-2-1_51KXQ_2020-09-22_final.stac-item
2020-09-25 11:43:02	ga_s2am_ard_3-2-1_51KVU_2020-09-25_final.stac-item
2020-09-25 11:43:05	ga_s2am_ard_3-2-1_51KUU_2020-09-25_final.stac-item
2020-09-26 11:14:00	ga_s2am_ard_3-2-1_52KBV_2020-09-26_final.stac-item
2020-09-29 11:23:48	ga_s2am_ard_3-2-1_51KXR_2020-09-29_final.stac-item
2020-10-02 11:33:18	ga_s2am_ard_3-2-1_51KWT_2020-10-02_final.stac-item
2021-01-27 11:21:26	ga_s2am_ard_3-2-1_51LZE_2021-01-27_final.stac-item
2021-01-29 12:03:44	ga_s2am_ard_3-2-1_50KNA_2021-01-29_final.stac-item
2021-08-25 11:27:00	ga_s2am_ard_3-2-1_51HVC_2021-08-25_final.stac-item
2021-09-17 11:37:08	ga_s2am_ard_3-2-1_50HPH_2021-09-17_final.stac-item
2021-09-30 11:43:19	ga_s2am_ard_3-2-1_51KUT_2021-09-30_final.stac-item
2022-01-08 11:47:04	ga_s2am_ard_3-2-1_50HPH_2022-01-08_final.stac-item
2022-03-09 11:46:52	ga_s2am_ard_3-2-1_50HPJ_2022-03-09_final.stac-item
2022-05-13 10:54:51	ga_s2am_ard_3-2-1_52JFR_2022-05-13_final.stac-item
2022-05-16 11:03:24	ga_s2am_ard_3-2-1_52KEB_2022-05-16_final.stac-item
2022-05-30 10:45:55	ga_s2am_ard_3-2-1_52JGM_2022-05-30_final.stac-item
2022-06-14 11:32:30	ga_s2am_ard_3-2-1_51KVB_2022-06-14_final.stac-item
2022-09-16 11:13:23	ga_s2am_ard_3-2-1_52KBC_2022-09-16_final.stac-item
2023-03-08 11:26:03	ga_s2am_ard_3-2-1_51JXF_2023-03-08_final
2023-04-11 11:03:35	ga_s2am_ard_3-2-1_52KEA_2023-04-11_final
2023-04-19 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2023-04-19_final
2023-04-20 11:33:22	ga_s2am_ard_3-2-1_51KXS_2023-04-20_final
2023-06-06 11:24:05	ga_s2am_ard_3-2-1_51KWQ_2023-06-06_final
2023-07-04 10:45:52	ga_s2am_ard_3-2-1_52JGM_2023-07-04_final
2023-07-15 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-07-15_final
2023-07-29 11:34:08	ga_s2am_ard_3-2-1_51KUQ_2023-07-29_final
2023-08-12 11:13:35	ga_s2am_ard_3-2-1_52KEA_2023-08-12_final
2023-08-24 11:56:20	ga_s2am_ard_3-2-1_50JKM_2023-08-24_final
2023-08-24 11:56:28	ga_s2am_ard_3-2-1_50JML_2023-08-24_final
2023-08-24 11:56:36	ga_s2am_ard_3-2-1_50HNK_2023-08-24_final
2023-09-14 11:23:32	ga_s2am_ard_3-2-1_51KXS_2023-09-14_final
2023-12-03 11:22:05	ga_s2am_ard_3-2-1_52KDF_2023-12-03_final
2023-12-08 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2023-12-08_final
2023-12-12 11:52:33	ga_s2am_ard_3-2-1_50KPF_2023-12-12_final
2023-12-15 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2023-12-15_final
2024-04-03 12:03:42	ga_s2am_ard_3-2-1_50KNA_2024-04-03_final
2024-04-04 11:33:31	ga_s2am_ard_3-2-1_51KUS_2024-04-04_final
2024-04-05 11:04:33	ga_s2am_ard_3-2-1_52JGR_2024-04-05_final
2024-04-21 11:22:55	ga_s2am_ard_3-2-1_52KBD_2024-04-21_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

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