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_49JGL_2015-12-07_final.stac-item
2016-02-05 12:04:38	ga_s2am_ard_3-2-1_49JGM_2016-02-05_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50HPJ_2016-05-16_final.stac-item
2016-06-21 11:56:09	ga_s2am_ard_3-2-1_50JNL_2016-06-21_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50HNG_2016-11-02_final
2016-12-28 11:55:47	ga_s2am_ard_3-2-1_50HLJ_2016-12-28_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49JGL_2017-01-20_final.stac-item
2017-04-30 12:04:44	ga_s2am_ard_3-2-1_50JLS_2017-04-30_final.stac-item
2017-05-31 11:35:01	ga_s2am_ard_3-2-1_50HQJ_2017-05-31_final.stac-item
2017-06-20 11:34:58	ga_s2am_ard_3-2-1_50HQJ_2017-06-20_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HPJ_2017-07-03_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50JLN_2017-07-16_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49JFM_2017-08-01_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JQT_2017-10-31_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49JGL_2017-11-09_final.stac-item
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50HLJ_2017-11-13_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_50JLN_2017-12-16_final.stac-item
2017-12-26 12:03:42	ga_s2am_ard_3-2-1_49KHR_2017-12-26_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50JPR_2017-12-30_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_50HMJ_2018-03-10_final.stac-item
2018-04-18 12:13:22	ga_s2am_ard_3-2-1_49JGN_2018-04-18_final.stac-item
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49JGN_2018-06-17_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-10-02_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JLQ_2018-10-12_final.stac-item
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-10-25_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_50JLP_2018-11-01_final.stac-item
2018-12-31 12:04:36	ga_s2am_ard_3-2-1_50JKT_2018-12-31_final.stac-item
2019-01-14 11:46:29	ga_s2am_ard_3-2-1_50HPK_2019-01-14_final.stac-item
2019-02-26 11:55:48	ga_s2am_ard_3-2-1_50JMN_2019-02-26_final.stac-item
2019-03-11 12:04:00	ga_s2am_ard_3-2-1_49KHR_2019-03-11_final.stac-item
2019-05-10 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2019-05-10_final.stac-item
2019-06-10 11:37:05	ga_s2am_ard_3-2-1_50HQH_2019-06-10_final.stac-item
2019-07-03 11:46:42	ga_s2am_ard_3-2-1_50HNK_2019-07-03_final.stac-item
2019-07-09 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2019-07-09_final.stac-item
2019-07-20 11:36:43	ga_s2am_ard_3-2-1_50HPK_2019-07-20_final.stac-item
2019-07-23 11:46:20	ga_s2am_ard_3-2-1_50JQL_2019-07-23_final.stac-item
2019-08-15 11:56:33	ga_s2am_ard_3-2-1_50HNK_2019-08-15_final.stac-item
2019-09-10 12:14:25	ga_s2am_ard_3-2-1_49KGP_2019-09-10_final.stac-item
2019-09-17 12:03:58	ga_s2am_ard_3-2-1_49KHR_2019-09-17_final.stac-item
2019-09-21 11:46:26	ga_s2am_ard_3-2-1_50JML_2019-09-21_final.stac-item
2019-10-04 11:55:51	ga_s2am_ard_3-2-1_50JNN_2019-10-04_final.stac-item
2019-10-04 11:56:10	ga_s2am_ard_3-2-1_50JMM_2019-10-04_final.stac-item
2019-11-06 12:05:00	ga_s2am_ard_3-2-1_50JKS_2019-11-06_final.stac-item
2019-11-27 11:37:06	ga_s2am_ard_3-2-1_50HPH_2019-11-27_final.stac-item
2019-12-23 11:56:45	ga_s2am_ard_3-2-1_50HMJ_2019-12-23_final.stac-item
2020-01-05 12:04:22	ga_s2am_ard_3-2-1_49KHP_2020-01-05_final.stac-item
2020-01-15 12:05:23	ga_s2am_ard_3-2-1_49JGK_2020-01-15_final.stac-item
2020-01-29 11:46:41	ga_s2am_ard_3-2-1_50HPJ_2020-01-29_final.stac-item
2020-02-01 11:55:52	ga_s2am_ard_3-2-1_50JKN_2020-02-01_final.stac-item
2020-02-01 11:56:32	ga_s2am_ard_3-2-1_50HLK_2020-02-01_final.stac-item
2020-02-17 12:14:50	ga_s2am_ard_3-2-1_49JGM_2020-02-17_final.stac-item
2020-03-19 11:46:50	ga_s2am_ard_3-2-1_50HQH_2020-03-19_final.stac-item
2020-04-21 11:54:56	ga_s2am_ard_3-2-1_50JMS_2020-04-21_final.stac-item
2020-05-01 11:55:56	ga_s2am_ard_3-2-1_50JMN_2020-05-01_final.stac-item
2020-06-04 11:37:13	ga_s2am_ard_3-2-1_50HPH_2020-06-04_final.stac-item
2020-06-30 11:56:01	ga_s2am_ard_3-2-1_50JLN_2020-06-30_final.stac-item
2020-08-13 11:34:43	ga_s2am_ard_3-2-1_50JRT_2020-08-13_final.stac-item
2020-08-26 11:46:39	ga_s2am_ard_3-2-1_50HPK_2020-08-26_final.stac-item
2020-10-04 12:15:02	ga_s2am_ard_3-2-1_49JGM_2020-10-04_final.stac-item
2020-10-11 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-10-11_final.stac-item
2020-11-04 11:46:42	ga_s2am_ard_3-2-1_50HNK_2020-11-04_final.stac-item
2021-01-09 12:04:43	ga_s2am_ard_3-2-1_49JHN_2021-01-09_final.stac-item
2021-01-09 12:05:15	ga_s2am_ard_3-2-1_49JGL_2021-01-09_final.stac-item
2021-01-19 12:05:42	ga_s2am_ard_3-2-1_50JKP_2021-01-19_final.stac-item
2021-01-23 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-01-23_final.stac-item
2021-01-30 11:36:49	ga_s2am_ard_3-2-1_50HQJ_2021-01-30_final.stac-item
2021-03-04 11:45:50	ga_s2am_ard_3-2-1_50JPN_2021-03-04_final.stac-item
2021-05-09 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-05-09_final.stac-item
2021-05-10 11:36:33	ga_s2am_ard_3-2-1_50HQK_2021-05-10_final.stac-item
2021-07-25 11:54:44	ga_s2am_ard_3-2-1_50JMT_2021-07-25_final.stac-item
2021-08-28 11:37:23	ga_s2am_ard_3-2-1_50HPG_2021-08-28_final
2021-09-06 12:04:28	ga_s2am_ard_3-2-1_49KHP_2021-09-06_final.stac-item
2021-09-30 11:46:23	ga_s2am_ard_3-2-1_50JPL_2021-09-30_final.stac-item
2021-12-19 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-12-19_final.stac-item
2022-01-04 12:04:01	ga_s2am_ard_3-2-1_49KHR_2022-01-04_final.stac-item
2022-02-10 11:55:58	ga_s2am_ard_3-2-1_50JKN_2022-02-10_final.stac-item
2022-03-12 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-03-12_final.stac-item
2022-04-01 11:56:32	ga_s2am_ard_3-2-1_50HNK_2022-04-01_final.stac-item
2022-06-07 11:46:42	ga_s2am_ard_3-2-1_50HPK_2022-06-07_final.stac-item
2022-06-13 12:04:43	ga_s2am_ard_3-2-1_49JHN_2022-06-13_final.stac-item
2022-10-31 12:05:55	ga_s2am_ard_3-2-1_50JLN_2022-10-31_final.stac-item
2022-11-01 11:36:30	ga_s2am_ard_3-2-1_50JPL_2022-11-01_final.stac-item
2023-01-02 12:14:26	ga_s2am_ard_3-2-1_49KGP_2023-01-02_final.stac-item
2023-01-23 11:46:01	ga_s2am_ard_3-2-1_50JPM_2023-01-23_final.stac-item
2023-02-15 11:55:53	ga_s2am_ard_3-2-1_50JLN_2023-02-15_final
2023-02-18 12:05:38	ga_s2am_ard_3-2-1_50JKP_2023-02-18_nrt.stac-item
2023-04-03 11:44:30	ga_s2am_ard_3-2-1_50JRT_2023-04-03_final
2023-04-10 11:36:20	ga_s2am_ard_3-2-1_50JQL_2023-04-10_final
2023-05-09 12:04:13	ga_s2am_ard_3-2-1_49KHQ_2023-05-09_final
2023-05-12 12:14:40	ga_s2am_ard_3-2-1_49JGN_2023-05-12_final
2023-05-23 11:46:18	ga_s2am_ard_3-2-1_50JQL_2023-05-23_final
2023-05-23 11:46:33	ga_s2am_ard_3-2-1_50HQK_2023-05-23_final
2023-06-25 11:55:42	ga_s2am_ard_3-2-1_50JMP_2023-06-25_final
2023-06-28 12:05:45	ga_s2am_ard_3-2-1_50JKP_2023-06-28_final
2023-07-22 11:46:05	ga_s2am_ard_3-2-1_50JQM_2023-07-22_final
2023-10-10 11:46:33	ga_s2am_ard_3-2-1_50HPK_2023-10-10_final
2023-12-16 11:36:59	ga_s2am_ard_3-2-1_50HQH_2023-12-16_final
2024-01-14 12:04:54	ga_s2am_ard_3-2-1_49JGM_2024-01-14_final
2024-02-17 11:46:21	ga_s2am_ard_3-2-1_50JNL_2024-02-17_final
2024-05-10 11:56:32	ga_s2am_ard_3-2-1_50HNK_2024-05-10_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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