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
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_49JGL_2015-12-17_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_49JGJ_2016-02-15_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_49JGL_2016-02-15_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49KGQ_2016-03-16_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50HMG_2016-04-02_final
2016-05-08 12:14:47	ga_s2am_ard_3-2-1_49JFN_2016-05-08_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49JGL_2016-10-02_final.stac-item
2016-10-12 12:04:37	ga_s2am_ard_3-2-1_49JGM_2016-10-12_final.stac-item
2016-12-21 12:04:53	ga_s2am_ard_3-2-1_49JGM_2016-12-21_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49JGL_2016-12-31_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50HLH_2017-02-16_final.stac-item
2017-04-10 12:03:46	ga_s2am_ard_3-2-1_49KHR_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
2017-06-09 12:04:43	ga_s2am_ard_3-2-1_49JGL_2017-06-09_final.stac-item
2017-07-06 11:56:07	ga_s2am_ard_3-2-1_50HLK_2017-07-06_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49KHR_2017-07-09_final.stac-item
2017-08-28 12:04:42	ga_s2am_ard_3-2-1_49JGN_2017-08-28_final.stac-item
2017-11-16 12:04:39	ga_s2am_ard_3-2-1_49JGM_2017-11-16_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49JGL_2017-12-16_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KGP_2017-12-19_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HLH_2018-03-30_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HMH_2018-03-30_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49KHP_2018-06-24_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49JGM_2018-07-17_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50HLJ_2018-08-30_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49JGN_2018-09-05_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGL_2018-09-12_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-09-12_final.stac-item
2018-09-15 12:14:38	ga_s2am_ard_3-2-1_49JGM_2018-09-15_final.stac-item
2018-12-21 12:04:37	ga_s2am_ard_3-2-1_49JGN_2018-12-21_final.stac-item
2018-12-21 12:05:35	ga_s2am_ard_3-2-1_49JGJ_2018-12-21_final.stac-item
2019-01-03 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2019-01-03_final.stac-item
2019-02-23 11:47:06	ga_s2am_ard_3-2-1_50HMH_2019-02-23_final.stac-item
2019-04-23 12:14:59	ga_s2am_ard_3-2-1_49JGM_2019-04-23_final.stac-item
2019-06-02 12:13:57	ga_s2am_ard_3-2-1_49KHR_2019-06-02_final.stac-item
2019-06-19 12:05:04	ga_s2am_ard_3-2-1_49JGM_2019-06-19_final.stac-item
2019-07-02 12:15:01	ga_s2am_ard_3-2-1_49JGM_2019-07-02_final.stac-item
2019-07-09 12:04:36	ga_s2am_ard_3-2-1_49KGP_2019-07-09_final.stac-item
2019-08-28 12:05:02	ga_s2am_ard_3-2-1_49JGM_2019-08-28_final.stac-item
2019-08-31 12:14:42	ga_s2am_ard_3-2-1_49JGN_2019-08-31_final.stac-item
2019-09-27 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2019-09-27_final.stac-item
2019-09-30 12:15:01	ga_s2am_ard_3-2-1_49JFM_2019-09-30_final.stac-item
2020-01-19 11:46:49	ga_s2am_ard_3-2-1_50HMJ_2020-01-19_final.stac-item
2020-02-08 11:46:47	ga_s2am_ard_3-2-1_50HMJ_2020-02-08_final.stac-item
2020-03-05 12:04:56	ga_s2am_ard_3-2-1_49JGM_2020-03-05_final.stac-item
2020-04-18 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2020-04-18_final.stac-item
2020-04-28 11:47:12	ga_s2am_ard_3-2-1_50HMH_2020-04-28_final.stac-item
2020-07-13 12:05:19	ga_s2am_ard_3-2-1_49JGL_2020-07-13_final.stac-item
2020-07-23 12:05:20	ga_s2am_ard_3-2-1_49JGL_2020-07-23_final.stac-item
2020-08-12 12:05:03	ga_s2am_ard_3-2-1_49JHM_2020-08-12_final.stac-item
2020-08-15 12:15:06	ga_s2am_ard_3-2-1_49JFM_2020-08-15_final.stac-item
2020-12-27 11:57:09	ga_s2am_ard_3-2-1_50HLH_2020-12-27_final.stac-item
2021-01-09 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-01-09_final
2021-02-01 12:14:27	ga_s2am_ard_3-2-1_49KGP_2021-02-01_final.stac-item
2021-02-25 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2021-02-25_final.stac-item
2021-03-10 12:04:46	ga_s2am_ard_3-2-1_49JGN_2021-03-10_final.stac-item
2021-03-10 12:05:15	ga_s2am_ard_3-2-1_49JGL_2021-03-10_final.stac-item
2021-03-24 11:47:13	ga_s2am_ard_3-2-1_50HLH_2021-03-24_final.stac-item
2021-04-16 11:57:00	ga_s2am_ard_3-2-1_50HMH_2021-04-16_final.stac-item
2021-04-19 12:03:39	ga_s2am_ard_3-2-1_49KHS_2021-04-19_final
2021-04-29 12:04:40	ga_s2am_ard_3-2-1_49JHN_2021-04-29_final.stac-item
2021-05-12 12:14:41	ga_s2am_ard_3-2-1_49JGN_2021-05-12_final.stac-item
2021-06-21 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-06-21_final.stac-item
2021-06-28 12:04:58	ga_s2am_ard_3-2-1_49JHM_2021-06-28_final.stac-item
2021-07-01 12:15:02	ga_s2am_ard_3-2-1_49JFM_2021-07-01_final.stac-item
2021-07-05 11:57:12	ga_s2am_ard_3-2-1_50HLH_2021-07-05_final.stac-item
2021-07-11 12:14:01	ga_s2am_ard_3-2-1_49KGR_2021-07-11_final.stac-item
2021-09-03 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-09-03_final.stac-item
2021-10-23 11:57:25	ga_s2am_ard_3-2-1_50HMG_2021-10-23_final
2021-12-19 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-12-19_final.stac-item
2022-01-17 12:15:11	ga_s2am_ard_3-2-1_49JGL_2022-01-17_final.stac-item
2022-01-18 11:47:10	ga_s2am_ard_3-2-1_50HMH_2022-01-18_final.stac-item
2022-01-21 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2022-01-21_final.stac-item
2022-02-07 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2022-02-07_final.stac-item
2022-02-10 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2022-02-10_final.stac-item
2022-02-16 12:15:11	ga_s2am_ard_3-2-1_49JGL_2022-02-16_final.stac-item
2022-02-20 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-02-20_final.stac-item
2022-05-17 12:14:46	ga_s2am_ard_3-2-1_49JGN_2022-05-17_final.stac-item
2022-07-16 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-07-16_final.stac-item
2022-07-30 11:57:15	ga_s2am_ard_3-2-1_50HMH_2022-07-30_final.stac-item
2022-08-02 12:04:56	ga_s2am_ard_3-2-1_49JGN_2022-08-02_final.stac-item
2022-08-26 11:47:37	ga_s2am_ard_3-2-1_50HMG_2022-08-26_final
2022-11-23 12:15:10	ga_s2am_ard_3-2-1_49JGL_2022-11-23_final.stac-item
2022-11-30 12:03:59	ga_s2am_ard_3-2-1_49KHR_2022-11-30_final.stac-item
2022-12-14 11:47:14	ga_s2am_ard_3-2-1_50HLH_2022-12-14_final.stac-item
2023-01-03 11:47:13	ga_s2am_ard_3-2-1_50HLH_2023-01-03_final.stac-item
2023-04-22 12:14:58	ga_s2am_ard_3-2-1_49JFM_2023-04-22_final
2023-05-03 11:47:24	ga_s2am_ard_3-2-1_50HMG_2023-05-03_final
2023-05-12 12:14:59	ga_s2am_ard_3-2-1_49JFM_2023-05-12_final
2023-07-08 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-07-08_final
2023-07-08 12:04:04	ga_s2am_ard_3-2-1_49KHR_2023-07-08_final
2023-08-17 12:05:06	ga_s2am_ard_3-2-1_49JGM_2023-08-17_final
2023-08-27 12:05:50	ga_s2am_ard_3-2-1_49JGJ_2023-08-27_final
2023-10-13 11:57:07	ga_s2am_ard_3-2-1_50HLH_2023-10-13_final
2023-10-16 12:03:58	ga_s2am_ard_3-2-1_49KHR_2023-10-16_final
2023-10-29 12:14:56	ga_s2am_ard_3-2-1_49JGM_2023-10-29_final
2023-11-05 12:05:14	ga_s2am_ard_3-2-1_49JGL_2023-11-05_final
2023-11-18 12:13:52	ga_s2am_ard_3-2-1_49KHR_2023-11-18_final
2023-11-28 12:13:47	ga_s2am_ard_3-2-1_49KHR_2023-11-28_final
2024-01-27 12:13:49	ga_s2am_ard_3-2-1_49KHR_2024-01-27_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

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