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
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50JML_2016-05-09_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50HMH_2016-05-29_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_49KHR_2016-08-03_final.stac-item
2016-09-26 11:40:08	ga_s2am_ard_3-2-1_50JML_2016-09-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50JPT_2016-10-26_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50HPG_2016-11-02_final
2016-11-04 12:13:19	ga_s2am_ard_3-2-1_49KGP_2016-11-04_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGN_2016-11-11_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49JGN_2016-12-21_final.stac-item
2016-12-28 11:55:47	ga_s2am_ard_3-2-1_50HNK_2016-12-28_final.stac-item
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_50HPK_2017-01-01_final.stac-item
2017-04-21 11:34:59	ga_s2am_ard_3-2-1_50HPJ_2017-04-21_final.stac-item
2017-04-23 12:13:36	ga_s2am_ard_3-2-1_49KHR_2017-04-23_final.stac-item
2017-05-13 12:13:38	ga_s2am_ard_3-2-1_49KGR_2017-05-13_final.stac-item
2017-05-17 11:49:48	ga_s2am_ard_3-2-1_50JKN_2017-05-17_final.stac-item
2017-05-20 12:04:45	ga_s2am_ard_3-2-1_50JLT_2017-05-20_final.stac-item
2017-07-23 11:45:09	ga_s2am_ard_3-2-1_50JNM_2017-07-23_final.stac-item
2017-10-14 11:56:06	ga_s2am_ard_3-2-1_50JNL_2017-10-14_final.stac-item
2017-11-26 12:05:06	ga_s2am_ard_3-2-1_50JKP_2017-11-26_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50JLN_2018-01-12_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49JGK_2018-02-14_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50JLP_2018-04-25_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HNK_2018-05-12_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JKN_2018-05-22_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JLN_2018-05-25_final.stac-item
2018-05-28 12:13:23	ga_s2am_ard_3-2-1_49JGM_2018-05-28_final.stac-item
2018-07-05 11:35:08	ga_s2am_ard_3-2-1_50HPK_2018-07-05_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKP_2018-08-13_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49KHR_2018-09-02_final.stac-item
2018-10-16 11:40:28	ga_s2am_ard_3-2-1_50JQN_2018-10-16_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_50HPJ_2018-11-02_final.stac-item
2018-12-11 12:05:32	ga_s2am_ard_3-2-1_50JKP_2018-12-11_final.stac-item
2018-12-12 11:36:25	ga_s2am_ard_3-2-1_50HQK_2018-12-12_final.stac-item
2019-02-02 12:14:38	ga_s2am_ard_3-2-1_49JGN_2019-02-02_final.stac-item
2019-02-09 12:05:37	ga_s2am_ard_3-2-1_50JKP_2019-02-09_final.stac-item
2019-02-23 11:46:44	ga_s2am_ard_3-2-1_50HPJ_2019-02-23_final.stac-item
2019-05-24 11:47:05	ga_s2am_ard_3-2-1_50HPH_2019-05-24_final.stac-item
2019-05-27 11:54:43	ga_s2am_ard_3-2-1_50JMT_2019-05-27_final.stac-item
2019-06-29 12:04:04	ga_s2am_ard_3-2-1_49KHR_2019-06-29_final.stac-item
2019-07-09 12:04:10	ga_s2am_ard_3-2-1_49KHR_2019-07-09_final.stac-item
2019-07-19 12:05:31	ga_s2am_ard_3-2-1_50JKQ_2019-07-19_final.stac-item
2019-08-12 11:46:55	ga_s2am_ard_3-2-1_50HNJ_2019-08-12_final.stac-item
2019-09-04 11:55:53	ga_s2am_ard_3-2-1_50JMN_2019-09-04_final.stac-item
2019-10-08 11:37:05	ga_s2am_ard_3-2-1_50HQH_2019-10-08_final.stac-item
2019-12-30 11:47:04	ga_s2am_ard_3-2-1_50HMH_2019-12-30_final.stac-item
2020-02-05 11:36:29	ga_s2am_ard_3-2-1_50HPK_2020-02-05_final.stac-item
2020-02-21 11:54:46	ga_s2am_ard_3-2-1_50JNS_2020-02-21_final.stac-item
2020-05-17 12:14:03	ga_s2am_ard_3-2-1_49KGR_2020-05-17_final.stac-item
2020-08-25 12:14:32	ga_s2am_ard_3-2-1_49KGP_2020-08-25_final.stac-item
2020-10-11 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-10-11_final.stac-item
2021-01-22 12:14:28	ga_s2am_ard_3-2-1_49KGP_2021-01-22_final.stac-item
2021-04-06 11:57:02	ga_s2am_ard_3-2-1_50HMH_2021-04-06_final.stac-item
2021-04-09 12:04:38	ga_s2am_ard_3-2-1_49JHN_2021-04-09_final.stac-item
2021-04-09 12:05:36	ga_s2am_ard_3-2-1_50JKP_2021-04-09_final.stac-item
2021-04-16 11:55:40	ga_s2am_ard_3-2-1_50JKP_2021-04-16_final.stac-item
2021-04-19 12:04:26	ga_s2am_ard_3-2-1_49KGP_2021-04-19_final.stac-item
2021-05-06 11:55:52	ga_s2am_ard_3-2-1_50JMN_2021-05-06_final.stac-item
2021-05-06 11:56:35	ga_s2am_ard_3-2-1_50HMK_2021-05-06_final.stac-item
2021-05-16 11:56:36	ga_s2am_ard_3-2-1_50HMK_2021-05-16_final.stac-item
2021-05-22 12:13:59	ga_s2am_ard_3-2-1_49KGR_2021-05-22_final.stac-item
2021-06-22 11:46:09	ga_s2am_ard_3-2-1_50JNM_2021-06-22_final.stac-item
2021-07-08 12:04:45	ga_s2am_ard_3-2-1_50JKT_2021-07-08_final.stac-item
2021-08-01 11:47:20	ga_s2am_ard_3-2-1_50HPG_2021-08-01_final
2021-08-10 12:15:02	ga_s2am_ard_3-2-1_49JFM_2021-08-10_final.stac-item
2021-09-03 11:56:31	ga_s2am_ard_3-2-1_50HNK_2021-09-03_final.stac-item
2021-10-13 11:56:35	ga_s2am_ard_3-2-1_50HNK_2021-10-13_final.stac-item
2021-11-18 12:13:58	ga_s2am_ard_3-2-1_49KGR_2021-11-18_final.stac-item
2021-12-08 12:14:26	ga_s2am_ard_3-2-1_49KGP_2021-12-08_final.stac-item
2021-12-15 12:05:41	ga_s2am_ard_3-2-1_50JKP_2021-12-15_final.stac-item
2022-01-04 12:05:42	ga_s2am_ard_3-2-1_50JKP_2022-01-04_final.stac-item
2022-01-14 12:05:16	ga_s2am_ard_3-2-1_49JGL_2022-01-14_final.stac-item
2022-01-31 11:55:56	ga_s2am_ard_3-2-1_50JLN_2022-01-31_final.stac-item
2022-03-09 11:46:38	ga_s2am_ard_3-2-1_50HPK_2022-03-09_final.stac-item
2022-03-09 11:47:10	ga_s2am_ard_3-2-1_50HNH_2022-03-09_final.stac-item
2022-05-11 11:55:24	ga_s2am_ard_3-2-1_50JNQ_2022-05-11_final.stac-item
2022-05-14 12:04:46	ga_s2am_ard_3-2-1_50JKT_2022-05-14_final.stac-item
2022-05-31 11:56:44	ga_s2am_ard_3-2-1_50HMK_2022-05-31_final.stac-item
2022-05-31 11:57:02	ga_s2am_ard_3-2-1_50HLJ_2022-05-31_final.stac-item
2022-06-30 11:56:38	ga_s2am_ard_3-2-1_50JLL_2022-06-30_final.stac-item
2022-08-05 12:15:21	ga_s2am_ard_3-2-1_49JGL_2022-08-05_final.stac-item
2022-08-13 11:36:54	ga_s2am_ard_3-2-1_50HPK_2022-08-13_final.stac-item
2022-09-28 11:56:03	ga_s2am_ard_3-2-1_50JLN_2022-09-28_final.stac-item
2022-10-08 11:56:20	ga_s2am_ard_3-2-1_50JKM_2022-10-08_final.stac-item
2022-10-11 12:05:32	ga_s2am_ard_3-2-1_50JKQ_2022-10-11_final.stac-item
2022-11-13 12:13:58	ga_s2am_ard_3-2-1_49KHR_2022-11-13_final.stac-item
2023-01-03 11:46:00	ga_s2am_ard_3-2-1_50JQM_2023-01-03_final.stac-item
2023-02-15 11:56:15	ga_s2am_ard_3-2-1_50JNL_2023-02-15_final
2023-02-22 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-02-22_final
2023-03-04 11:46:40	ga_s2am_ard_3-2-1_50HQJ_2023-03-04_final
2023-05-29 12:05:00	ga_s2am_ard_3-2-1_49JHM_2023-05-29_final
2023-06-09 11:37:06	ga_s2am_ard_3-2-1_50HQH_2023-06-09_final
2023-07-31 12:14:04	ga_s2am_ard_3-2-1_49KGR_2023-07-31_final
2023-09-26 12:04:41	ga_s2am_ard_3-2-1_50JLT_2023-09-26_final
2023-10-26 12:04:46	ga_s2am_ard_3-2-1_49JGN_2023-10-26_final
2023-10-30 11:46:15	ga_s2am_ard_3-2-1_50JQL_2023-10-30_final
2023-11-05 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-11-05_final
2023-11-25 12:05:59	ga_s2am_ard_3-2-1_50JLM_2023-11-25_final
2024-01-24 12:05:23	ga_s2am_ard_3-2-1_49JGK_2024-01-24_final
2024-03-31 11:55:59	ga_s2am_ard_3-2-1_50JKN_2024-03-31_final
2024-04-24 11:35:53	ga_s2am_ard_3-2-1_50JQN_2024-04-24_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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