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
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_49JGM_2015-12-07_final.stac-item
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50HNG_2016-02-19_final
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HMJ_2016-03-20_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HMK_2016-04-29_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_49JGL_2016-06-24_final.stac-item
2016-07-07 12:14:44	ga_s2am_ard_3-2-1_49JFM_2016-07-07_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGM_2016-09-12_final.stac-item
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_49JGM_2016-09-15_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KHS_2016-10-02_final
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KHP_2016-10-22_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49JGM_2016-10-25_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HMK_2016-11-05_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGL_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGM_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGN_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JHM_2016-11-11_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HNJ_2016-11-15_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HMJ_2016-11-28_final.stac-item
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_49JGL_2017-03-21_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50HLH_2017-03-25_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50HMH_2017-05-04_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_49JGL_2017-06-19_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49KGQ_2017-07-09_final.stac-item
2017-10-11 11:40:47	ga_s2am_ard_3-2-1_50HMK_2017-10-11_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50HMJ_2017-11-20_final.stac-item
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_49KHP_2017-11-29_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_49JGN_2018-01-05_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50HLK_2018-01-12_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGK_2018-03-06_final.stac-item
2018-03-19 12:13:18	ga_s2am_ard_3-2-1_49JGL_2018-03-19_final.stac-item
2018-04-15 12:05:11	ga_s2am_ard_3-2-1_49JGL_2018-04-15_final.stac-item
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_49JHN_2018-05-05_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HMH_2018-05-29_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_49JHM_2018-06-14_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50HLK_2018-07-11_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_49JGN_2018-08-03_final.stac-item
2018-08-17 11:45:55	ga_s2am_ard_3-2-1_50HMK_2018-08-17_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49JGN_2018-09-02_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-09-12_final.stac-item
2018-09-15 12:14:38	ga_s2am_ard_3-2-1_49JGL_2018-09-15_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50HMK_2018-09-26_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50HMK_2018-10-09_final.stac-item
2018-10-12 12:02:46	ga_s2am_ard_3-2-1_49KHQ_2018-10-12_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49KGQ_2018-10-12_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-10-15_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KGR_2018-10-15_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-10-22_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HMK_2018-10-29_final.stac-item
2018-11-08 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2018-11-08_final.stac-item
2018-11-21 12:05:08	ga_s2am_ard_3-2-1_49JGL_2018-11-21_final.stac-item
2018-12-01 12:04:34	ga_s2am_ard_3-2-1_49JHN_2018-12-01_final.stac-item
2018-12-05 11:46:43	ga_s2am_ard_3-2-1_50HNJ_2018-12-05_final.stac-item
2018-12-05 11:46:58	ga_s2am_ard_3-2-1_50HNH_2018-12-05_final.stac-item
2018-12-11 12:05:06	ga_s2am_ard_3-2-1_49JGL_2018-12-11_final.stac-item
2018-12-25 11:46:44	ga_s2am_ard_3-2-1_50HNJ_2018-12-25_final.stac-item
2018-12-31 12:03:53	ga_s2am_ard_3-2-1_49KHR_2018-12-31_final.stac-item
2019-05-23 12:14:45	ga_s2am_ard_3-2-1_49JGN_2019-05-23_final.stac-item
2019-07-09 12:04:47	ga_s2am_ard_3-2-1_49JHN_2019-07-09_final.stac-item
2019-07-09 12:04:51	ga_s2am_ard_3-2-1_49JGN_2019-07-09_final.stac-item
2019-08-28 12:05:16	ga_s2am_ard_3-2-1_49JGL_2019-08-28_final.stac-item
2019-10-20 12:14:02	ga_s2am_ard_3-2-1_49KHR_2019-10-20_final.stac-item
2019-11-20 11:47:11	ga_s2am_ard_3-2-1_50HMH_2019-11-20_final.stac-item
2019-11-23 11:57:02	ga_s2am_ard_3-2-1_50HMH_2019-11-23_final.stac-item
2020-01-09 11:46:35	ga_s2am_ard_3-2-1_50HMK_2020-01-09_final.stac-item
2020-01-19 11:46:49	ga_s2am_ard_3-2-1_50HMJ_2020-01-19_final.stac-item
2020-02-11 11:56:47	ga_s2am_ard_3-2-1_50HLJ_2020-02-11_final.stac-item
2020-02-18 11:47:08	ga_s2am_ard_3-2-1_50HLH_2020-02-18_final.stac-item
2020-03-05 12:05:11	ga_s2am_ard_3-2-1_49JGL_2020-03-05_final.stac-item
2020-04-01 11:57:05	ga_s2am_ard_3-2-1_50HLH_2020-04-01_final.stac-item
2020-04-21 11:56:41	ga_s2am_ard_3-2-1_50HLK_2020-04-21_final.stac-item
2020-04-28 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2020-04-28_final.stac-item
2020-04-28 11:47:12	ga_s2am_ard_3-2-1_50HMH_2020-04-28_final.stac-item
2020-06-03 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-06-03_final.stac-item
2020-06-26 12:15:01	ga_s2am_ard_3-2-1_49JGM_2020-06-26_final.stac-item
2020-10-08 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-10-08_final.stac-item
2020-10-28 11:57:11	ga_s2am_ard_3-2-1_50HMH_2020-10-28_final.stac-item
2020-10-28 11:57:14	ga_s2am_ard_3-2-1_50HLH_2020-10-28_final.stac-item
2020-11-24 11:46:39	ga_s2am_ard_3-2-1_50HNK_2020-11-24_final.stac-item
2020-12-20 12:04:59	ga_s2am_ard_3-2-1_49JGM_2020-12-20_final.stac-item
2020-12-20 12:05:13	ga_s2am_ard_3-2-1_49JGL_2020-12-20_final.stac-item
2020-12-30 12:04:42	ga_s2am_ard_3-2-1_49JHN_2020-12-30_final.stac-item
2021-01-09 12:04:43	ga_s2am_ard_3-2-1_49JHN_2021-01-09_final.stac-item
2021-01-13 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-01-13_final.stac-item
2021-01-16 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2021-01-16_final.stac-item
2021-02-02 11:47:27	ga_s2am_ard_3-2-1_50HLG_2021-02-02_final
2021-03-10 12:04:31	ga_s2am_ard_3-2-1_49KGP_2021-03-10_final.stac-item
2021-03-23 12:15:09	ga_s2am_ard_3-2-1_49JGL_2021-03-23_final.stac-item
2021-04-13 11:46:46	ga_s2am_ard_3-2-1_50HNJ_2021-04-13_final.stac-item
2021-04-19 12:04:55	ga_s2am_ard_3-2-1_49JGM_2021-04-19_final.stac-item
2021-05-22 12:14:56	ga_s2am_ard_3-2-1_49JGM_2021-05-22_final.stac-item
2021-06-18 12:04:31	ga_s2am_ard_3-2-1_49KGP_2021-06-18_final.stac-item
2021-06-18 12:04:43	ga_s2am_ard_3-2-1_49JHN_2021-06-18_final.stac-item
2021-06-21 12:14:28	ga_s2am_ard_3-2-1_49KGP_2021-06-21_final.stac-item
2021-08-27 12:04:01	ga_s2am_ard_3-2-1_49KHR_2021-08-27_final.stac-item
2021-08-27 12:05:31	ga_s2am_ard_3-2-1_49JGK_2021-08-27_final.stac-item
2021-12-02 11:57:05	ga_s2am_ard_3-2-1_50HMH_2021-12-02_final.stac-item
2022-01-11 11:56:52	ga_s2am_ard_3-2-1_50HMJ_2022-01-11_final.stac-item
2022-03-28 12:14:29	ga_s2am_ard_3-2-1_49KGP_2022-03-28_final.stac-item
2022-07-30 11:57:15	ga_s2am_ard_3-2-1_50HMH_2022-07-30_final.stac-item
2023-10-26 12:03:44	ga_s2am_ard_3-2-1_49KHS_2023-10-26_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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