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
2015-10-08 12:03:08	ga_s2am_ard_3-2-1_50JLS_2015-10-08_final.stac-item
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_49JGL_2015-12-07_final.stac-item
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HPH_2015-12-08_final.stac-item
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HQH_2015-12-08_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_49JGN_2015-12-17_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HPG_2016-04-29_final
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_49KHR_2016-09-12_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50JKN_2016-10-22_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JGK_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49KHP_2016-11-21_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JLR_2017-01-30_final.stac-item
2017-03-01 12:03:41	ga_s2am_ard_3-2-1_49KHR_2017-03-01_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50JNL_2017-03-05_final.stac-item
2017-03-08 11:56:00	ga_s2am_ard_3-2-1_50JLL_2017-03-08_final.stac-item
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_50JKP_2017-03-11_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50HPJ_2017-05-04_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50HNK_2017-06-13_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HPJ_2017-07-03_final.stac-item
2017-07-26 11:56:09	ga_s2am_ard_3-2-1_50JMM_2017-07-26_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49JGN_2017-09-30_final.stac-item
2017-12-17 11:32:07	ga_s2am_ard_3-2-1_50HQK_2017-12-17_final.stac-item
2018-01-15 12:04:34	ga_s2am_ard_3-2-1_50JKR_2018-01-15_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50HQJ_2018-01-19_final.stac-item
2018-01-22 11:56:02	ga_s2am_ard_3-2-1_50JLM_2018-01-22_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_49JGL_2018-01-25_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_50JNM_2018-02-08_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50JKP_2018-02-24_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JLM_2018-04-12_final
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JMM_2018-05-02_final.stac-item
2018-05-28 12:13:23	ga_s2am_ard_3-2-1_49JFM_2018-05-28_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JLN_2018-06-14_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50JMM_2018-07-31_final.stac-item
2018-11-14 12:13:53	ga_s2am_ard_3-2-1_49KGR_2018-11-14_final.stac-item
2019-02-10 11:36:45	ga_s2am_ard_3-2-1_50HQJ_2019-02-10_final.stac-item
2019-04-20 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-04-20_final.stac-item
2019-06-19 12:04:32	ga_s2am_ard_3-2-1_49KHP_2019-06-19_final.stac-item
2019-07-09 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2019-07-09_final.stac-item
2019-08-22 11:47:09	ga_s2am_ard_3-2-1_50HNH_2019-08-22_final.stac-item
2019-09-27 12:05:42	ga_s2am_ard_3-2-1_50JKP_2019-09-27_final.stac-item
2019-11-23 11:56:12	ga_s2am_ard_3-2-1_50JLM_2019-11-23_final.stac-item
2020-02-08 11:46:58	ga_s2am_ard_3-2-1_50HNH_2020-02-08_final.stac-item
2020-02-18 11:46:17	ga_s2am_ard_3-2-1_50JNL_2020-02-18_final.stac-item
2020-05-07 12:15:00	ga_s2am_ard_3-2-1_49JGM_2020-05-07_final.stac-item
2020-08-19 11:56:24	ga_s2am_ard_3-2-1_50JNL_2020-08-19_final.stac-item
2020-08-19 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-08-19_final.stac-item
2020-09-15 11:47:11	ga_s2am_ard_3-2-1_50HNH_2020-09-15_final.stac-item
2020-09-25 11:46:39	ga_s2am_ard_3-2-1_50HPK_2020-09-25_final.stac-item
2020-10-11 12:05:57	ga_s2am_ard_3-2-1_50JLN_2020-10-11_final.stac-item
2020-12-04 11:46:39	ga_s2am_ard_3-2-1_50HMK_2020-12-04_final.stac-item
2021-02-02 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2021-02-02_final.stac-item
2021-02-09 11:37:02	ga_s2am_ard_3-2-1_50HQH_2021-02-09_final.stac-item
2021-02-18 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2021-02-18_final.stac-item
2021-03-27 11:55:40	ga_s2am_ard_3-2-1_50JLP_2021-03-27_final.stac-item
2021-03-27 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2021-03-27_final.stac-item
2021-05-19 12:04:46	ga_s2am_ard_3-2-1_49JGN_2021-05-19_final.stac-item
2021-06-05 11:56:31	ga_s2am_ard_3-2-1_50HNK_2021-06-05_final.stac-item
2021-06-15 11:56:08	ga_s2am_ard_3-2-1_50JMM_2021-06-15_final.stac-item
2021-06-18 12:06:04	ga_s2am_ard_3-2-1_50JLM_2021-06-18_final.stac-item
2021-07-28 12:04:33	ga_s2am_ard_3-2-1_49KHP_2021-07-28_final.stac-item
2021-08-14 11:56:28	ga_s2am_ard_3-2-1_50JLL_2021-08-14_final.stac-item
2021-08-27 12:04:48	ga_s2am_ard_3-2-1_49JGN_2021-08-27_final.stac-item
2021-10-13 11:56:23	ga_s2am_ard_3-2-1_50JNL_2021-10-13_final.stac-item
2021-10-23 11:56:09	ga_s2am_ard_3-2-1_50JNM_2021-10-23_final.stac-item
2021-12-05 12:05:51	ga_s2am_ard_3-2-1_50JLN_2021-12-05_final.stac-item
2022-01-05 11:36:39	ga_s2am_ard_3-2-1_50HPK_2022-01-05_final.stac-item
2022-02-13 12:04:31	ga_s2am_ard_3-2-1_49KGP_2022-02-13_final.stac-item
2022-04-07 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-04-07_final.stac-item
2022-04-27 12:14:03	ga_s2am_ard_3-2-1_49KGR_2022-04-27_final.stac-item
2022-07-23 12:05:19	ga_s2am_ard_3-2-1_49JFM_2022-07-23_final.stac-item
2022-08-09 11:55:39	ga_s2am_ard_3-2-1_50JLQ_2022-08-09_final.stac-item
2022-09-02 11:37:00	ga_s2am_ard_3-2-1_50HQJ_2022-09-02_final.stac-item
2022-09-28 11:55:02	ga_s2am_ard_3-2-1_50JMS_2022-09-28_final.stac-item
2022-09-28 11:56:37	ga_s2am_ard_3-2-1_50HNK_2022-09-28_final.stac-item
2022-10-01 12:05:22	ga_s2am_ard_3-2-1_49JGL_2022-10-01_final.stac-item
2022-11-20 12:04:40	ga_s2am_ard_3-2-1_50JLT_2022-11-20_final.stac-item
2022-11-23 12:13:58	ga_s2am_ard_3-2-1_49KGR_2022-11-23_final.stac-item
2023-02-15 11:56:19	ga_s2am_ard_3-2-1_50JML_2023-02-15_nrt.stac-item
2023-02-15 11:56:19	ga_s2am_ard_3-2-1_50JML_2023-02-15_final
2023-03-10 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-03-10_final
2023-03-31 11:37:19	ga_s2am_ard_3-2-1_50HPG_2023-03-31_final
2023-04-12 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2023-04-12_final
2023-04-29 12:05:52	ga_s2am_ard_3-2-1_50JLN_2023-04-29_final
2023-05-13 11:47:14	ga_s2am_ard_3-2-1_50HLH_2023-05-13_final
2023-06-28 12:05:45	ga_s2am_ard_3-2-1_50JKP_2023-06-28_final
2023-07-05 11:55:15	ga_s2am_ard_3-2-1_50JMR_2023-07-05_final
2023-09-03 11:56:27	ga_s2am_ard_3-2-1_50JML_2023-09-03_final
2023-10-16 12:05:25	ga_s2am_ard_3-2-1_50JKQ_2023-10-16_final
2023-10-23 11:56:21	ga_s2am_ard_3-2-1_50JML_2023-10-23_final
2023-10-23 11:56:22	ga_s2am_ard_3-2-1_50JLL_2023-10-23_final
2023-12-02 11:56:22	ga_s2am_ard_3-2-1_50HNK_2023-12-02_final
2023-12-12 11:55:52	ga_s2am_ard_3-2-1_50JLN_2023-12-12_final
2024-01-18 11:46:28	ga_s2am_ard_3-2-1_50HNK_2024-01-18_final
2024-02-03 12:05:25	ga_s2am_ard_3-2-1_49JGK_2024-02-03_final
2024-02-13 12:04:28	ga_s2am_ard_3-2-1_49KGP_2024-02-13_final
2024-03-04 12:05:01	ga_s2am_ard_3-2-1_49JGM_2024-03-04_final
2024-03-07 12:13:55	ga_s2am_ard_3-2-1_49KHR_2024-03-07_final
2024-04-03 12:04:29	ga_s2am_ard_3-2-1_49KGP_2024-04-03_final
2024-04-03 12:05:49	ga_s2am_ard_3-2-1_50JLN_2024-04-03_final
2024-04-27 11:46:36	ga_s2am_ard_3-2-1_50HPK_2024-04-27_final
2024-04-27 11:46:40	ga_s2am_ard_3-2-1_50HNK_2024-04-27_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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