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
2015-11-27 12:03:46	ga_s2am_ard_3-2-1_49KHR_2015-11-27_final.stac-item
2015-12-28 11:36:25	ga_s2am_ard_3-2-1_50JPL_2015-12-28_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JNQ_2016-05-29_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HNH_2016-07-08_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_50JPL_2016-07-15_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50JML_2016-09-06_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49JHM_2016-10-02_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50JLN_2016-12-08_final.stac-item
2017-02-13 11:44:16	ga_s2am_ard_3-2-1_50JML_2017-02-13_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50JLM_2017-02-26_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50JPR_2017-03-25_final.stac-item
2017-04-01 11:34:45	ga_s2am_ard_3-2-1_50HPJ_2017-04-01_final.stac-item
2017-06-10 11:36:05	ga_s2am_ard_3-2-1_50JPL_2017-06-10_final.stac-item
2017-06-22 12:13:20	ga_s2am_ard_3-2-1_49JGN_2017-06-22_final.stac-item
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49KHR_2017-08-21_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JGM_2017-09-17_final.stac-item
2017-10-27 12:03:47	ga_s2am_ard_3-2-1_49KHR_2017-10-27_final.stac-item
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50JNN_2018-03-23_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_49KGP_2018-04-15_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HNK_2018-05-09_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50HPH_2018-06-08_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49KGP_2018-07-24_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50JLR_2018-08-30_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_50HQH_2018-09-03_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_50JKS_2018-10-02_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2018-10-05_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HLH_2018-10-29_final.stac-item
2018-11-11 12:05:36	ga_s2am_ard_3-2-1_50JKP_2018-11-11_final.stac-item
2018-11-28 11:55:44	ga_s2am_ard_3-2-1_50JMN_2018-11-28_final.stac-item
2019-03-01 12:04:23	ga_s2am_ard_3-2-1_49KHP_2019-03-01_final.stac-item
2019-04-01 11:36:34	ga_s2am_ard_3-2-1_50HQK_2019-04-01_final.stac-item
2019-04-04 11:47:15	ga_s2am_ard_3-2-1_50HLH_2019-04-04_final.stac-item
2019-04-20 12:05:44	ga_s2am_ard_3-2-1_50JKP_2019-04-20_final.stac-item
2019-04-24 11:47:10	ga_s2am_ard_3-2-1_50HNH_2019-04-24_final.stac-item
2019-04-30 12:04:46	ga_s2am_ard_3-2-1_50JKT_2019-04-30_final.stac-item
2019-06-29 12:04:50	ga_s2am_ard_3-2-1_49JGN_2019-06-29_final.stac-item
2019-06-29 12:06:00	ga_s2am_ard_3-2-1_50JKN_2019-06-29_final.stac-item
2019-08-05 11:55:39	ga_s2am_ard_3-2-1_50JNP_2019-08-05_final.stac-item
2019-08-22 11:46:36	ga_s2am_ard_3-2-1_50HPK_2019-08-22_final.stac-item
2019-09-21 11:46:19	ga_s2am_ard_3-2-1_50JPL_2019-09-21_final.stac-item
2019-10-30 12:15:14	ga_s2am_ard_3-2-1_49JGL_2019-10-30_final.stac-item
2019-11-30 11:46:18	ga_s2am_ard_3-2-1_50JPL_2019-11-30_final.stac-item
2019-12-06 12:05:38	ga_s2am_ard_3-2-1_50JKP_2019-12-06_final.stac-item
2020-01-15 12:04:08	ga_s2am_ard_3-2-1_49KHQ_2020-01-15_final.stac-item
2020-03-06 11:36:15	ga_s2am_ard_3-2-1_50JQL_2020-03-06_final.stac-item
2020-04-04 12:05:52	ga_s2am_ard_3-2-1_50JKN_2020-04-04_final.stac-item
2020-05-28 11:46:29	ga_s2am_ard_3-2-1_50JNL_2020-05-28_final.stac-item
2020-06-04 11:36:32	ga_s2am_ard_3-2-1_50JPL_2020-06-04_final.stac-item
2020-06-24 11:36:43	ga_s2am_ard_3-2-1_50HPK_2020-06-24_final.stac-item
2020-07-27 11:46:54	ga_s2am_ard_3-2-1_50HPJ_2020-07-27_final.stac-item
2020-10-05 11:47:16	ga_s2am_ard_3-2-1_50HMH_2020-10-05_final.stac-item
2020-12-04 11:46:52	ga_s2am_ard_3-2-1_50HQH_2020-12-04_final.stac-item
2021-01-03 11:46:13	ga_s2am_ard_3-2-1_50JMM_2021-01-03_final.stac-item
2021-01-13 11:46:34	ga_s2am_ard_3-2-1_50HPK_2021-01-13_final.stac-item
2021-02-09 11:36:47	ga_s2am_ard_3-2-1_50HQJ_2021-02-09_final.stac-item
2021-02-25 11:56:11	ga_s2am_ard_3-2-1_50JLM_2021-02-25_final.stac-item
2021-02-28 12:05:15	ga_s2am_ard_3-2-1_49JGL_2021-02-28_final.stac-item
2021-03-21 11:37:16	ga_s2am_ard_3-2-1_50HQG_2021-03-21_final
2021-08-28 11:36:28	ga_s2am_ard_3-2-1_50JPL_2021-08-28_final.stac-item
2021-12-08 12:14:55	ga_s2am_ard_3-2-1_49JGM_2021-12-08_final.stac-item
2022-01-01 11:55:11	ga_s2am_ard_3-2-1_50JMR_2022-01-01_final.stac-item
2022-02-06 12:13:54	ga_s2am_ard_3-2-1_49KHR_2022-02-06_final.stac-item
2022-02-07 11:46:25	ga_s2am_ard_3-2-1_50JML_2022-02-07_final.stac-item
2022-02-10 11:55:55	ga_s2am_ard_3-2-1_50JLN_2022-02-10_final.stac-item
2022-02-23 12:04:45	ga_s2am_ard_3-2-1_50JKT_2022-02-23_final.stac-item
2022-03-12 11:56:22	ga_s2am_ard_3-2-1_50JNL_2022-03-12_final.stac-item
2022-06-10 11:56:27	ga_s2am_ard_3-2-1_50JNL_2022-06-10_final.stac-item
2022-06-14 11:36:37	ga_s2am_ard_3-2-1_50JPL_2022-06-14_final.stac-item
2022-07-10 11:56:06	ga_s2am_ard_3-2-1_50JMN_2022-07-10_final.stac-item
2022-07-30 11:56:50	ga_s2am_ard_3-2-1_50HLK_2022-07-30_final.stac-item
2022-08-02 12:04:24	ga_s2am_ard_3-2-1_49KHQ_2022-08-02_final.stac-item
2022-08-09 11:56:23	ga_s2am_ard_3-2-1_50JLM_2022-08-09_final.stac-item
2022-08-15 12:14:25	ga_s2am_ard_3-2-1_49KGQ_2022-08-15_final.stac-item
2022-08-19 11:56:17	ga_s2am_ard_3-2-1_50JNM_2022-08-19_final.stac-item
2022-10-21 12:04:29	ga_s2am_ard_3-2-1_49KHP_2022-10-21_final.stac-item
2022-12-10 12:04:32	ga_s2am_ard_3-2-1_49KGP_2022-12-10_final.stac-item
2022-12-14 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2022-12-14_final.stac-item
2022-12-30 12:05:40	ga_s2am_ard_3-2-1_50JKP_2022-12-30_final.stac-item
2023-01-09 12:03:58	ga_s2am_ard_3-2-1_49KHR_2023-01-09_final.stac-item
2023-01-19 12:05:50	ga_s2am_ard_3-2-1_50JKN_2023-01-19_final.stac-item
2023-01-23 11:46:15	ga_s2am_ard_3-2-1_50JPL_2023-01-23_final.stac-item
2023-01-29 12:05:39	ga_s2am_ard_3-2-1_50JKP_2023-01-29_final.stac-item
2023-02-19 11:37:04	ga_s2am_ard_3-2-1_50HPH_2023-02-19_final
2023-04-10 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2023-04-10_final
2023-04-16 11:57:20	ga_s2am_ard_3-2-1_50HMG_2023-04-16_final
2023-06-05 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2023-06-05_final
2023-06-12 11:46:41	ga_s2am_ard_3-2-1_50HNK_2023-06-12_final
2023-08-11 11:45:40	ga_s2am_ard_3-2-1_50JPP_2023-08-11_final
2023-08-14 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2023-08-14_final
2023-08-17 12:05:21	ga_s2am_ard_3-2-1_49JGL_2023-08-17_final
2023-09-03 11:56:27	ga_s2am_ard_3-2-1_50JML_2023-09-03_final
2023-09-17 11:36:55	ga_s2am_ard_3-2-1_50HPJ_2023-09-17_final
2023-10-03 11:56:01	ga_s2am_ard_3-2-1_50JKN_2023-10-03_final
2023-12-19 11:46:30	ga_s2am_ard_3-2-1_50HPK_2023-12-19_final
2023-12-28 12:14:38	ga_s2am_ard_3-2-1_49JGN_2023-12-28_final
2024-01-14 12:04:21	ga_s2am_ard_3-2-1_49KHP_2024-01-14_final
2024-01-17 12:14:33	ga_s2am_ard_3-2-1_49JGN_2024-01-17_final
2024-02-27 11:47:13	ga_s2am_ard_3-2-1_50HLH_2024-02-27_final
2024-03-25 11:36:53	ga_s2am_ard_3-2-1_50HPJ_2024-03-25_final
2024-04-16 12:14:30	ga_s2am_ard_3-2-1_49KGP_2024-04-16_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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