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
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49KHQ_2016-03-16_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HNJ_2016-06-18_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50JML_2016-06-18_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HMK_2016-07-08_final.stac-item
2016-07-11 11:56:11	ga_s2am_ard_3-2-1_50JMM_2016-07-11_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50HPK_2016-09-06_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50JPL_2016-10-16_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JNM_2016-11-18_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_50JQM_2016-11-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50HNG_2016-12-22_final
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_50KKA_2017-02-12_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50JNN_2017-02-16_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_49JHN_2017-02-19_final.stac-item
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_49JGJ_2017-03-11_final.stac-item
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_50JKN_2017-03-11_final.stac-item
2017-04-10 12:04:40	ga_s2am_ard_3-2-1_49JGM_2017-04-10_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_50JKT_2017-05-10_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49JFM_2017-06-02_final.stac-item
2017-08-31 12:14:41	ga_s2am_ard_3-2-1_49JGM_2017-08-31_final.stac-item
2017-09-21 11:40:44	ga_s2am_ard_3-2-1_50JPL_2017-09-21_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50HPK_2017-12-10_final.stac-item
2018-01-18 12:13:37	ga_s2am_ard_3-2-1_50KKA_2018-01-18_final.stac-item
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_50KKA_2018-04-08_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49KGQ_2018-04-28_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50KMC_2018-07-01_final.stac-item
2018-07-05 11:35:08	ga_s2am_ard_3-2-1_50HPK_2018-07-05_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JKT_2018-10-12_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_50KKA_2018-11-01_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50JNM_2018-11-05_final.stac-item
2018-11-21 12:05:48	ga_s2am_ard_3-2-1_50JKN_2018-11-21_final.stac-item
2018-12-14 12:13:46	ga_s2am_ard_3-2-1_49KHR_2018-12-14_final.stac-item
2018-12-31 12:03:13	ga_s2am_ard_3-2-1_50KNC_2018-12-31_final.stac-item
2019-02-19 12:05:52	ga_s2am_ard_3-2-1_50JKN_2019-02-19_final.stac-item
2019-03-15 11:45:28	ga_s2am_ard_3-2-1_50JQP_2019-03-15_final.stac-item
2019-04-17 11:55:59	ga_s2am_ard_3-2-1_50JLN_2019-04-17_final.stac-item
2019-07-26 11:53:26	ga_s2am_ard_3-2-1_50KPC_2019-07-26_final.stac-item
2019-08-28 12:04:08	ga_s2am_ard_3-2-1_50KMV_2019-08-28_final.stac-item
2019-08-29 11:37:04	ga_s2am_ard_3-2-1_50HQH_2019-08-29_final.stac-item
2019-09-27 12:04:47	ga_s2am_ard_3-2-1_49JGN_2019-09-27_final.stac-item
2019-09-28 11:37:04	ga_s2am_ard_3-2-1_50HQH_2019-09-28_final.stac-item
2019-11-29 12:14:26	ga_s2am_ard_3-2-1_49KGP_2019-11-29_final.stac-item
2019-12-30 11:46:10	ga_s2am_ard_3-2-1_50JQL_2019-12-30_final.stac-item
2020-01-08 12:14:54	ga_s2am_ard_3-2-1_49JFM_2020-01-08_final.stac-item
2020-02-04 12:04:16	ga_s2am_ard_3-2-1_50KLU_2020-02-04_final.stac-item
2020-02-28 11:46:04	ga_s2am_ard_3-2-1_50JNM_2020-02-28_final.stac-item
2020-03-02 11:56:03	ga_s2am_ard_3-2-1_50JMM_2020-03-02_final.stac-item
2020-04-14 12:06:03	ga_s2am_ard_3-2-1_50JLM_2020-04-14_final.stac-item
2020-04-18 11:46:30	ga_s2am_ard_3-2-1_50HQK_2020-04-18_final.stac-item
2020-04-18 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2020-04-18_final.stac-item
2020-05-18 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-05-18_final.stac-item
2020-06-14 11:36:26	ga_s2am_ard_3-2-1_50JQL_2020-06-14_final.stac-item
2020-08-12 12:03:47	ga_s2am_ard_3-2-1_50KLB_2020-08-12_final.stac-item
2020-08-22 12:03:29	ga_s2am_ard_3-2-1_50KMC_2020-08-22_final.stac-item
2020-09-01 12:04:47	ga_s2am_ard_3-2-1_49JHN_2020-09-01_final.stac-item
2020-10-18 11:56:42	ga_s2am_ard_3-2-1_50HMK_2020-10-18_final.stac-item
2020-10-21 12:04:48	ga_s2am_ard_3-2-1_50JKT_2020-10-21_final.stac-item
2020-12-30 12:05:29	ga_s2am_ard_3-2-1_49JGK_2020-12-30_final.stac-item
2021-01-10 11:35:51	ga_s2am_ard_3-2-1_50JQN_2021-01-10_final.stac-item
2021-01-13 11:47:03	ga_s2am_ard_3-2-1_50HPH_2021-01-13_final.stac-item
2021-01-19 12:03:59	ga_s2am_ard_3-2-1_50KKA_2021-01-19_final.stac-item
2021-03-20 12:03:58	ga_s2am_ard_3-2-1_49KHR_2021-03-20_final.stac-item
2021-03-21 11:36:37	ga_s2am_ard_3-2-1_50HPK_2021-03-21_final.stac-item
2021-04-22 12:14:22	ga_s2am_ard_3-2-1_49KGP_2021-04-22_final.stac-item
2021-05-06 11:55:52	ga_s2am_ard_3-2-1_50JMN_2021-05-06_final.stac-item
2021-05-23 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-05-23_final.stac-item
2021-06-02 11:47:18	ga_s2am_ard_3-2-1_50HPG_2021-06-02_final
2021-07-05 11:56:09	ga_s2am_ard_3-2-1_50JLM_2021-07-05_final.stac-item
2021-07-18 12:04:31	ga_s2am_ard_3-2-1_49KHP_2021-07-18_final.stac-item
2021-07-25 11:56:33	ga_s2am_ard_3-2-1_50HNK_2021-07-25_final.stac-item
2021-08-21 11:46:21	ga_s2am_ard_3-2-1_50JPL_2021-08-21_final.stac-item
2021-11-15 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-11-15_final.stac-item
2021-12-15 12:03:59	ga_s2am_ard_3-2-1_50KKA_2021-12-15_final.stac-item
2021-12-25 12:05:02	ga_s2am_ard_3-2-1_49JGM_2021-12-25_final.stac-item
2022-01-18 11:46:23	ga_s2am_ard_3-2-1_50JNL_2022-01-18_final.stac-item
2022-04-18 11:44:56	ga_s2am_ard_3-2-1_50JPS_2022-04-18_final.stac-item
2022-06-23 12:04:46	ga_s2am_ard_3-2-1_50JKT_2022-06-23_final.stac-item
2022-07-27 11:47:16	ga_s2am_ard_3-2-1_50HNH_2022-07-27_final.stac-item
2022-08-26 11:47:01	ga_s2am_ard_3-2-1_50HPJ_2022-08-26_final
2022-09-05 11:45:10	ga_s2am_ard_3-2-1_50JQR_2022-09-05_final.stac-item
2022-11-11 11:36:37	ga_s2am_ard_3-2-1_50HQK_2022-11-11_final.stac-item
2022-12-03 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-12-03_final.stac-item
2022-12-07 11:56:26	ga_s2am_ard_3-2-1_50JLL_2022-12-07_final.stac-item
2023-01-06 11:56:29	ga_s2am_ard_3-2-1_50HNK_2023-01-06_final.stac-item
2023-02-05 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2023-02-05_final
2023-02-15 11:56:15	ga_s2am_ard_3-2-1_50JNL_2023-02-15_final
2023-03-10 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-03-10_final
2023-03-14 11:47:03	ga_s2am_ard_3-2-1_50HNH_2023-03-14_final
2023-04-03 11:45:24	ga_s2am_ard_3-2-1_50JNQ_2023-04-03_final
2023-04-23 11:45:06	ga_s2am_ard_3-2-1_50JPR_2023-04-23_final
2023-05-13 11:45:54	ga_s2am_ard_3-2-1_50JNN_2023-05-13_final
2023-06-28 12:05:59	ga_s2am_ard_3-2-1_50JKN_2023-06-28_final
2023-08-20 12:14:00	ga_s2am_ard_3-2-1_50KKA_2023-08-20_final
2023-09-09 12:14:03	ga_s2am_ard_3-2-1_49KGR_2023-09-09_final
2023-09-30 11:46:40	ga_s2am_ard_3-2-1_50HNK_2023-09-30_final
2023-11-08 12:14:41	ga_s2am_ard_3-2-1_49JGN_2023-11-08_final
2023-12-05 12:03:52	ga_s2am_ard_3-2-1_49KHR_2023-12-05_final
2024-01-04 12:04:36	ga_s2am_ard_3-2-1_50JLT_2024-01-04_final
2024-02-07 11:46:48	ga_s2am_ard_3-2-1_50HNJ_2024-02-07_final
2024-02-10 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2024-02-10_final
2024-03-18 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2024-03-18_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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