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
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JMP_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JMR_2015-12-04_final.stac-item
2015-12-18 11:36:25	ga_s2am_ard_3-2-1_50JQL_2015-12-18_final.stac-item
2015-12-18 11:36:25	ga_s2am_ard_3-2-1_50JQM_2015-12-18_final.stac-item
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50JPL_2016-01-07_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49KGP_2016-01-16_final.stac-item
2016-01-17 11:36:22	ga_s2am_ard_3-2-1_50HQK_2016-01-17_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JKP_2016-02-02_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JLP_2016-02-02_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_50JRS_2016-02-06_final.stac-item
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50JNQ_2016-02-19_final.stac-item
2016-04-16 11:36:04	ga_s2am_ard_3-2-1_50HQK_2016-04-16_final.stac-item
2016-06-04 12:02:54	ga_s2am_ard_3-2-1_49JGK_2016-06-04_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_50JKS_2016-08-03_final.stac-item
2016-08-14 11:36:06	ga_s2am_ard_3-2-1_50JPL_2016-08-14_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HLH_2016-11-28_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50HPH_2017-03-25_final.stac-item
2017-04-07 11:56:31	ga_s2am_ard_3-2-1_50HLH_2017-04-07_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_49JGJ_2017-09-07_final.stac-item
2017-09-18 11:36:00	ga_s2am_ard_3-2-1_50JQM_2017-09-18_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50HMJ_2018-03-03_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_50HPH_2018-03-17_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_50HQJ_2018-03-17_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-09-12_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50HLH_2018-10-09_final.stac-item
2018-11-11 12:04:52	ga_s2am_ard_3-2-1_49JHM_2018-11-11_final.stac-item
2018-11-15 11:46:50	ga_s2am_ard_3-2-1_50HMJ_2018-11-15_final.stac-item
2019-02-20 11:36:59	ga_s2am_ard_3-2-1_50HQH_2019-02-20_final.stac-item
2019-02-26 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2019-02-26_final.stac-item
2019-04-01 11:36:49	ga_s2am_ard_3-2-1_50HQJ_2019-04-01_final.stac-item
2019-05-07 11:56:34	ga_s2am_ard_3-2-1_50HNK_2019-05-07_final.stac-item
2019-07-09 12:04:10	ga_s2am_ard_3-2-1_50KKA_2019-07-09_final.stac-item
2019-07-09 12:05:20	ga_s2am_ard_3-2-1_49JGL_2019-07-09_final.stac-item
2019-09-04 11:56:04	ga_s2am_ard_3-2-1_50JNM_2019-09-04_final.stac-item
2019-09-27 12:05:00	ga_s2am_ard_3-2-1_50JMR_2019-09-27_final.stac-item
2019-10-11 11:46:18	ga_s2am_ard_3-2-1_50JQL_2019-10-11_final.stac-item
2019-11-10 11:47:12	ga_s2am_ard_3-2-1_50HMH_2019-11-10_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 11:56:52	ga_s2am_ard_3-2-1_50HMJ_2019-11-23_final.stac-item
2020-01-29 11:46:59	ga_s2am_ard_3-2-1_50HNH_2020-01-29_final.stac-item
2020-02-08 11:46:47	ga_s2am_ard_3-2-1_50HMJ_2020-02-08_final.stac-item
2020-02-18 11:47:00	ga_s2am_ard_3-2-1_50HNH_2020-02-18_final.stac-item
2020-03-02 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2020-03-02_final.stac-item
2020-03-25 12:04:03	ga_s2am_ard_3-2-1_49KHQ_2020-03-25_final.stac-item
2020-03-25 12:04:55	ga_s2am_ard_3-2-1_50JMR_2020-03-25_final.stac-item
2020-04-04 12:05:04	ga_s2am_ard_3-2-1_50JLR_2020-04-04_final.stac-item
2020-04-08 11:45:44	ga_s2am_ard_3-2-1_50JQN_2020-04-08_final.stac-item
2020-04-08 11:46:17	ga_s2am_ard_3-2-1_50JPL_2020-04-08_final.stac-item
2020-06-06 12:14:01	ga_s2am_ard_3-2-1_49KHR_2020-06-06_final.stac-item
2020-06-13 12:04:05	ga_s2am_ard_3-2-1_50KKA_2020-06-13_final.stac-item
2020-06-14 11:36:40	ga_s2am_ard_3-2-1_50HQK_2020-06-14_final.stac-item
2020-09-05 11:46:38	ga_s2am_ard_3-2-1_50HPK_2020-09-05_final.stac-item
2020-09-28 11:56:02	ga_s2am_ard_3-2-1_50JLN_2020-09-28_final.stac-item
2020-10-04 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-10-04_final.stac-item
2020-10-04 12:15:02	ga_s2am_ard_3-2-1_49JGM_2020-10-04_final.stac-item
2020-12-17 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2020-12-17_final.stac-item
2020-12-20 12:05:42	ga_s2am_ard_3-2-1_49JGJ_2020-12-20_final.stac-item
2021-01-23 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-01-23_final.stac-item
2021-01-29 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-01-29_final.stac-item
2021-02-18 12:05:51	ga_s2am_ard_3-2-1_50JLN_2021-02-18_final.stac-item
2021-04-06 11:56:26	ga_s2am_ard_3-2-1_50HNK_2021-04-06_final.stac-item
2021-09-13 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-09-13_final.stac-item
2021-09-16 12:05:00	ga_s2am_ard_3-2-1_50JMR_2021-09-16_final.stac-item
2021-12-05 12:03:58	ga_s2am_ard_3-2-1_49KHR_2021-12-05_final.stac-item
2021-12-12 11:57:22	ga_s2am_ard_3-2-1_50HLG_2021-12-12_final
2021-12-29 11:47:11	ga_s2am_ard_3-2-1_50HMH_2021-12-29_final.stac-item
2022-01-11 11:57:10	ga_s2am_ard_3-2-1_50HLH_2022-01-11_final.stac-item
2022-01-18 11:47:07	ga_s2am_ard_3-2-1_50HNH_2022-01-18_final.stac-item
2022-03-15 12:05:19	ga_s2am_ard_3-2-1_49JGL_2022-03-15_final.stac-item
2022-04-01 11:57:11	ga_s2am_ard_3-2-1_50HLH_2022-04-01_final.stac-item
2022-04-08 11:46:31	ga_s2am_ard_3-2-1_50HQK_2022-04-08_final.stac-item
2022-04-08 11:46:44	ga_s2am_ard_3-2-1_50HQJ_2022-04-08_final.stac-item
2022-09-01 12:05:24	ga_s2am_ard_3-2-1_50JKR_2022-09-01_final.stac-item
2022-09-11 12:04:46	ga_s2am_ard_3-2-1_50JMT_2022-09-11_final.stac-item
2022-10-15 11:46:52	ga_s2am_ard_3-2-1_50HPJ_2022-10-15_final.stac-item
2022-10-15 11:46:58	ga_s2am_ard_3-2-1_50HQH_2022-10-15_final.stac-item
2022-10-28 11:57:09	ga_s2am_ard_3-2-1_50HMH_2022-10-28_final.stac-item
2022-10-28 11:57:18	ga_s2am_ard_3-2-1_49HGC_2022-10-28_nrt.stac-item
2022-11-14 11:47:17	ga_s2am_ard_3-2-1_50HLH_2022-11-14_final.stac-item
2022-12-17 11:55:52	ga_s2am_ard_3-2-1_50JMN_2022-12-17_final.stac-item
2023-01-06 11:56:39	ga_s2am_ard_3-2-1_50HLK_2023-01-06_final.stac-item
2023-02-22 11:46:17	ga_s2am_ard_3-2-1_50JPL_2023-02-22_final
2023-02-28 12:05:20	ga_s2am_ard_3-2-1_50JLQ_2023-02-28_final
2023-03-07 11:57:02	ga_s2am_ard_3-2-1_50HMH_2023-03-07_final
2023-04-06 11:55:26	ga_s2am_ard_3-2-1_50JPP_2023-04-06_final
2023-04-06 11:55:59	ga_s2am_ard_3-2-1_50JKN_2023-04-06_final
2023-04-26 11:57:09	ga_s2am_ard_3-2-1_50HLH_2023-04-26_final
2023-04-29 12:05:41	ga_s2am_ard_3-2-1_50JKP_2023-04-29_final
2023-05-09 12:03:44	ga_s2am_ard_3-2-1_49KHS_2023-05-09_final
2023-08-30 12:15:16	ga_s2am_ard_3-2-1_49JGL_2023-08-30_final
2023-09-10 11:46:06	ga_s2am_ard_3-2-1_50JQM_2023-09-10_final
2023-09-20 11:46:32	ga_s2am_ard_3-2-1_50HQK_2023-09-20_final
2023-09-20 11:46:36	ga_s2am_ard_3-2-1_50HPK_2023-09-20_final
2023-10-06 12:04:59	ga_s2am_ard_3-2-1_50JMR_2023-10-06_final
2023-10-13 11:57:18	ga_s2am_ard_3-2-1_50HMG_2023-10-13_final
2023-11-22 11:57:02	ga_s2am_ard_3-2-1_50HMH_2023-11-22_final
2023-12-09 11:47:04	ga_s2am_ard_3-2-1_50HMH_2023-12-09_final
2023-12-22 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2023-12-22_final
2024-02-03 12:05:37	ga_s2am_ard_3-2-1_50JKP_2024-02-03_final
2024-03-01 11:57:06	ga_s2am_ard_3-2-1_50HMH_2024-03-01_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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