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
2015-10-01 12:14:44	ga_s2am_ard_3-2-1_49JGL_2015-10-01_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49KHP_2016-01-16_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JPM_2016-01-20_final.stac-item
2016-03-29 12:14:39	ga_s2am_ard_3-2-1_49JGM_2016-03-29_final.stac-item
2016-08-17 11:40:15	ga_s2am_ard_3-2-1_50HPH_2016-08-17_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49JGN_2016-08-26_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JLM_2016-10-09_final.stac-item
2016-10-19 11:56:02	ga_s2am_ard_3-2-1_50JLM_2016-10-19_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_49JGJ_2017-06-19_final.stac-item
2017-06-20 11:34:58	ga_s2am_ard_3-2-1_50HPJ_2017-06-20_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50JLM_2017-07-16_final.stac-item
2017-08-12 11:40:50	ga_s2am_ard_3-2-1_50HMH_2017-08-12_final.stac-item
2017-08-15 11:56:09	ga_s2am_ard_3-2-1_50JLM_2017-08-15_final.stac-item
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49JGM_2017-08-21_final.stac-item
2017-10-18 11:36:29	ga_s2am_ard_3-2-1_50HPJ_2017-10-18_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49JFM_2017-11-09_final.stac-item
2017-11-16 12:04:39	ga_s2am_ard_3-2-1_49JGM_2017-11-16_final.stac-item
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49JFM_2018-01-08_final.stac-item
2018-02-15 11:34:02	ga_s2am_ard_3-2-1_50HQJ_2018-02-15_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50HLJ_2018-03-03_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_50JKP_2018-03-06_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50JLL_2018-07-31_final.stac-item
2018-08-13 12:02:49	ga_s2am_ard_3-2-1_49KHR_2018-08-13_final.stac-item
2018-12-05 11:46:43	ga_s2am_ard_3-2-1_50HNJ_2018-12-05_final.stac-item
2018-12-14 12:14:18	ga_s2am_ard_3-2-1_49KGP_2018-12-14_final.stac-item
2019-01-31 11:37:00	ga_s2am_ard_3-2-1_50HQH_2019-01-31_final.stac-item
2019-02-26 11:56:21	ga_s2am_ard_3-2-1_50JLL_2019-02-26_final.stac-item
2019-04-01 11:36:20	ga_s2am_ard_3-2-1_50JQL_2019-04-01_final.stac-item
2019-04-01 11:36:34	ga_s2am_ard_3-2-1_50HQK_2019-04-01_final.stac-item
2019-04-30 12:04:46	ga_s2am_ard_3-2-1_50JKT_2019-04-30_final.stac-item
2019-07-09 12:04:36	ga_s2am_ard_3-2-1_49KGP_2019-07-09_final.stac-item
2019-09-14 11:55:52	ga_s2am_ard_3-2-1_50JMN_2019-09-14_final.stac-item
2019-09-20 12:14:41	ga_s2am_ard_3-2-1_49JGN_2019-09-20_final.stac-item
2019-10-17 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-10-17_final.stac-item
2019-11-19 12:14:28	ga_s2am_ard_3-2-1_49KGP_2019-11-19_final.stac-item
2019-12-03 11:57:08	ga_s2am_ard_3-2-1_50HLH_2019-12-03_final.stac-item
2019-12-13 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2019-12-13_final.stac-item
2019-12-26 12:04:55	ga_s2am_ard_3-2-1_49JGM_2019-12-26_final.stac-item
2020-01-08 12:14:50	ga_s2am_ard_3-2-1_49JGM_2020-01-08_final.stac-item
2020-02-24 12:05:59	ga_s2am_ard_3-2-1_50JLM_2020-02-24_final.stac-item
2020-02-27 12:14:55	ga_s2am_ard_3-2-1_49JFM_2020-02-27_final.stac-item
2020-04-01 11:56:03	ga_s2am_ard_3-2-1_50JMM_2020-04-01_final.stac-item
2020-04-27 12:15:02	ga_s2am_ard_3-2-1_49JFM_2020-04-27_final.stac-item
2020-05-27 12:14:04	ga_s2am_ard_3-2-1_49KGR_2020-05-27_final.stac-item
2020-05-31 11:55:56	ga_s2am_ard_3-2-1_50JNN_2020-05-31_final.stac-item
2020-06-17 11:46:40	ga_s2am_ard_3-2-1_50HPK_2020-06-17_final.stac-item
2020-07-07 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2020-07-07_final.stac-item
2020-07-30 11:56:02	ga_s2am_ard_3-2-1_50JLN_2020-07-30_final.stac-item
2020-08-19 11:56:35	ga_s2am_ard_3-2-1_50HNK_2020-08-19_final.stac-item
2020-09-05 11:46:52	ga_s2am_ard_3-2-1_50HPJ_2020-09-05_final.stac-item
2020-09-05 11:47:07	ga_s2am_ard_3-2-1_50HPH_2020-09-05_final.stac-item
2020-09-12 11:36:38	ga_s2am_ard_3-2-1_50HQK_2020-09-12_final.stac-item
2020-10-21 12:04:48	ga_s2am_ard_3-2-1_49JHN_2020-10-21_final.stac-item
2020-11-27 11:55:55	ga_s2am_ard_3-2-1_50JKN_2020-11-27_final.stac-item
2020-12-23 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2020-12-23_final.stac-item
2021-01-03 11:46:16	ga_s2am_ard_3-2-1_50JQL_2021-01-03_final.stac-item
2021-01-03 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2021-01-03_final.stac-item
2021-02-01 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-02-01_final.stac-item
2021-02-05 11:55:49	ga_s2am_ard_3-2-1_50JNN_2021-02-05_final.stac-item
2021-02-15 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2021-02-15_final.stac-item
2021-04-16 11:55:50	ga_s2am_ard_3-2-1_50JLN_2021-04-16_final.stac-item
2021-05-10 11:36:37	ga_s2am_ard_3-2-1_50HPK_2021-05-10_final.stac-item
2021-05-16 11:55:42	ga_s2am_ard_3-2-1_50JLP_2021-05-16_final.stac-item
2021-05-26 11:56:12	ga_s2am_ard_3-2-1_50JLM_2021-05-26_final.stac-item
2021-07-15 11:55:53	ga_s2am_ard_3-2-1_50JNN_2021-07-15_final.stac-item
2021-08-01 11:47:24	ga_s2am_ard_3-2-1_50HNG_2021-08-01_final
2021-08-17 12:05:43	ga_s2am_ard_3-2-1_50JKP_2021-08-17_final.stac-item
2022-01-18 11:46:09	ga_s2am_ard_3-2-1_50JNM_2022-01-18_final.stac-item
2022-04-08 11:47:07	ga_s2am_ard_3-2-1_50HNH_2022-04-08_final.stac-item
2022-06-13 12:05:36	ga_s2am_ard_3-2-1_50JKQ_2022-06-13_final.stac-item
2022-06-17 11:46:45	ga_s2am_ard_3-2-1_50HPK_2022-06-17_final.stac-item
2022-06-20 11:56:37	ga_s2am_ard_3-2-1_50JLL_2022-06-20_final.stac-item
2022-07-20 11:55:53	ga_s2am_ard_3-2-1_50JLP_2022-07-20_final.stac-item
2022-07-24 11:36:37	ga_s2am_ard_3-2-1_50JPL_2022-07-24_final.stac-item
2022-08-05 12:14:05	ga_s2am_ard_3-2-1_49KHR_2022-08-05_final.stac-item
2022-08-13 11:36:38	ga_s2am_ard_3-2-1_50JPL_2022-08-13_final.stac-item
2022-08-16 11:45:12	ga_s2am_ard_3-2-1_50JPS_2022-08-16_final.stac-item
2022-12-03 12:14:27	ga_s2am_ard_3-2-1_49KGP_2022-12-03_final.stac-item
2022-12-20 12:04:30	ga_s2am_ard_3-2-1_49KGP_2022-12-20_final.stac-item
2022-12-30 12:06:03	ga_s2am_ard_3-2-1_50JLM_2022-12-30_final.stac-item
2023-01-30 11:36:46	ga_s2am_ard_3-2-1_50HQJ_2023-01-30_final.stac-item
2023-04-02 12:13:53	ga_s2am_ard_3-2-1_49KHR_2023-04-02_final
2023-04-03 11:47:06	ga_s2am_ard_3-2-1_50HNH_2023-04-03_final
2023-04-12 12:14:41	ga_s2am_ard_3-2-1_49JGN_2023-04-12_final
2023-04-19 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-04-19_final
2023-04-29 12:05:41	ga_s2am_ard_3-2-1_50JKP_2023-04-29_final
2023-05-16 11:56:00	ga_s2am_ard_3-2-1_50JKN_2023-05-16_final
2023-05-16 11:57:23	ga_s2am_ard_3-2-1_50HLG_2023-05-16_final
2023-06-12 11:46:30	ga_s2am_ard_3-2-1_50JML_2023-06-12_final
2023-06-12 11:47:06	ga_s2am_ard_3-2-1_50HPH_2023-06-12_final
2023-08-10 12:15:04	ga_s2am_ard_3-2-1_49JFM_2023-08-10_final
2023-08-17 12:04:37	ga_s2am_ard_3-2-1_49KGP_2023-08-17_final
2023-09-03 11:56:01	ga_s2am_ard_3-2-1_50JLN_2023-09-03_final
2023-09-06 12:04:33	ga_s2am_ard_3-2-1_49KHP_2023-09-06_final
2023-11-06 11:36:37	ga_s2am_ard_3-2-1_50HPK_2023-11-06_final
2023-12-22 11:57:09	ga_s2am_ard_3-2-1_50HKH_2023-12-22_final
2024-01-14 12:04:21	ga_s2am_ard_3-2-1_49KHP_2024-01-14_final
2024-01-15 11:36:20	ga_s2am_ard_3-2-1_50JPL_2024-01-15_final
2024-02-03 12:04:09	ga_s2am_ard_3-2-1_49KHQ_2024-02-03_final
2024-03-21 11:56:26	ga_s2am_ard_3-2-1_50JLL_2024-03-21_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

Other products

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