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
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_50HMK_2015-11-21_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50JKM_2016-01-03_final.stac-item
2016-02-05 12:04:38	ga_s2am_ard_3-2-1_49JGN_2016-02-05_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_49JHN_2016-02-15_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HLJ_2016-06-11_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HLK_2016-06-11_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50JKS_2016-08-23_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_50JKT_2016-09-12_final.stac-item
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_49KHR_2016-09-15_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50HLH_2016-12-08_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50JLL_2016-12-08_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HNJ_2017-01-14_final.stac-item
2017-02-20 11:36:27	ga_s2am_ard_3-2-1_50HQK_2017-02-20_final.stac-item
2017-04-10 12:04:40	ga_s2am_ard_3-2-1_49JHN_2017-04-10_final.stac-item
2017-05-17 11:56:36	ga_s2am_ard_3-2-1_50HLH_2017-05-17_final.stac-item
2017-05-20 12:04:45	ga_s2am_ard_3-2-1_50JKS_2017-05-20_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49JGK_2017-08-18_final.stac-item
2017-08-28 12:04:42	ga_s2am_ard_3-2-1_49JGN_2017-08-28_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49KGQ_2017-11-09_final.stac-item
2017-11-16 12:04:39	ga_s2am_ard_3-2-1_49JGN_2017-11-16_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50HQJ_2017-11-20_final.stac-item
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_49JGN_2017-11-29_final.stac-item
2017-12-06 12:04:36	ga_s2am_ard_3-2-1_49JGN_2017-12-06_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50HLH_2018-01-19_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_49JGN_2018-01-25_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_49KHP_2018-01-25_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HMH_2018-02-18_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49JHN_2018-04-05_final.stac-item
2018-04-18 12:13:22	ga_s2am_ard_3-2-1_49KGR_2018-04-18_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JLL_2018-07-11_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50HLK_2018-07-31_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JKP_2018-08-10_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50HLK_2018-10-09_final.stac-item
2018-12-18 11:56:05	ga_s2am_ard_3-2-1_50JKM_2018-12-18_final.stac-item
2018-12-22 11:36:30	ga_s2am_ard_3-2-1_50HPK_2018-12-22_final.stac-item
2019-03-22 11:36:32	ga_s2am_ard_3-2-1_50HQK_2019-03-22_final.stac-item
2019-05-17 11:56:40	ga_s2am_ard_3-2-1_50HMK_2019-05-17_final.stac-item
2019-06-12 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-06-12_final.stac-item
2019-08-18 12:04:45	ga_s2am_ard_3-2-1_50JKT_2019-08-18_final.stac-item
2019-11-03 11:56:08	ga_s2am_ard_3-2-1_50JKN_2019-11-03_final.stac-item
2019-11-07 11:36:37	ga_s2am_ard_3-2-1_50HQK_2019-11-07_final.stac-item
2019-11-23 11:57:08	ga_s2am_ard_3-2-1_50HMH_2019-11-23_final.stac-item
2019-12-06 12:05:24	ga_s2am_ard_3-2-1_50JKQ_2019-12-06_final.stac-item
2019-12-19 12:13:52	ga_s2am_ard_3-2-1_49KGR_2019-12-19_final.stac-item
2020-01-29 11:46:23	ga_s2am_ard_3-2-1_50HQK_2020-01-29_final.stac-item
2020-01-29 11:46:48	ga_s2am_ard_3-2-1_50HMJ_2020-01-29_final.stac-item
2020-02-18 11:46:35	ga_s2am_ard_3-2-1_50HPJ_2020-02-18_final.stac-item
2020-04-15 11:36:33	ga_s2am_ard_3-2-1_50HQK_2020-04-15_final.stac-item
2020-04-28 11:46:56	ga_s2am_ard_3-2-1_50HQH_2020-04-28_final.stac-item
2020-05-01 11:57:09	ga_s2am_ard_3-2-1_50HMH_2020-05-01_final.stac-item
2020-06-07 11:47:13	ga_s2am_ard_3-2-1_50HNH_2020-06-07_final.stac-item
2020-06-17 11:46:47	ga_s2am_ard_3-2-1_50HMK_2020-06-17_final.stac-item
2020-07-27 11:46:46	ga_s2am_ard_3-2-1_50HMK_2020-07-27_final.stac-item
2020-09-04 12:15:15	ga_s2am_ard_3-2-1_49JGL_2020-09-04_final.stac-item
2020-10-01 12:04:24	ga_s2am_ard_3-2-1_49KGQ_2020-10-01_final.stac-item
2020-10-18 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-10-18_final.stac-item
2020-11-07 11:56:34	ga_s2am_ard_3-2-1_50HNK_2020-11-07_final.stac-item
2021-02-18 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2021-02-18_final.stac-item
2021-02-18 12:05:11	ga_s2am_ard_3-2-1_50JKR_2021-02-18_final.stac-item
2021-03-30 12:05:24	ga_s2am_ard_3-2-1_50JKQ_2021-03-30_final.stac-item
2021-05-02 12:15:04	ga_s2am_ard_3-2-1_49JGL_2021-05-02_final.stac-item
2021-05-12 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2021-05-12_final.stac-item
2021-09-26 12:04:46	ga_s2am_ard_3-2-1_49JHN_2021-09-26_final.stac-item
2021-09-29 12:13:59	ga_s2am_ard_3-2-1_49KHR_2021-09-29_final.stac-item
2021-11-22 11:55:59	ga_s2am_ard_3-2-1_50JKN_2021-11-22_final.stac-item
2021-12-02 11:56:40	ga_s2am_ard_3-2-1_50HLK_2021-12-02_final.stac-item
2022-01-14 12:04:58	ga_s2am_ard_3-2-1_49JHM_2022-01-14_final.stac-item
2022-02-20 11:56:31	ga_s2am_ard_3-2-1_50HNK_2022-02-20_final.stac-item
2022-03-06 11:36:42	ga_s2am_ard_3-2-1_50HPK_2022-03-06_final.stac-item
2022-04-14 12:04:31	ga_s2am_ard_3-2-1_49KHP_2022-04-14_final.stac-item
2022-04-18 11:46:45	ga_s2am_ard_3-2-1_50HMK_2022-04-18_final.stac-item
2022-06-27 11:47:08	ga_s2am_ard_3-2-1_50HMJ_2022-06-27_final.stac-item
2022-08-29 11:56:53	ga_s2am_ard_3-2-1_50HLK_2022-08-29_final.stac-item
2022-10-21 12:05:02	ga_s2am_ard_3-2-1_50JKS_2022-10-21_final.stac-item
2022-12-10 12:04:57	ga_s2am_ard_3-2-1_49JHM_2022-12-10_final.stac-item
2022-12-23 12:13:56	ga_s2am_ard_3-2-1_49KGR_2022-12-23_final.stac-item
2023-01-29 12:04:55	ga_s2am_ard_3-2-1_49JHM_2023-01-29_final.stac-item
2023-02-08 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-02-08_final
2023-02-11 12:14:11	ga_s2am_ard_3-2-1_49KGQ_2023-02-11_final
2023-02-18 12:04:25	ga_s2am_ard_3-2-1_49KHP_2023-02-18_final
2023-02-25 11:55:44	ga_s2am_ard_3-2-1_50JKP_2023-02-25_final
2023-02-28 12:04:43	ga_s2am_ard_3-2-1_49JGN_2023-02-28_final
2023-03-07 11:55:42	ga_s2am_ard_3-2-1_50JKP_2023-03-07_final
2023-04-23 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2023-04-23_final
2023-05-03 11:47:07	ga_s2am_ard_3-2-1_50HNH_2023-05-03_final
2023-07-21 12:15:14	ga_s2am_ard_3-2-1_49JGL_2023-07-21_final
2023-08-20 12:14:19	ga_s2am_ard_3-2-1_49KGQ_2023-08-20_final
2023-08-20 12:15:16	ga_s2am_ard_3-2-1_49JGL_2023-08-20_final
2023-09-06 12:04:19	ga_s2am_ard_3-2-1_49KHQ_2023-09-06_final
2023-09-26 12:04:48	ga_s2am_ard_3-2-1_49JGN_2023-09-26_final
2023-09-27 11:36:40	ga_s2am_ard_3-2-1_50HPK_2023-09-27_final
2023-10-26 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2023-10-26_final
2023-11-19 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-11-19_final
2024-01-21 11:56:22	ga_s2am_ard_3-2-1_50HNK_2024-01-21_final
2024-02-04 11:36:30	ga_s2am_ard_3-2-1_50HQK_2024-02-04_final
2024-02-07 11:47:10	ga_s2am_ard_3-2-1_50HLH_2024-02-07_final
2024-02-17 11:47:22	ga_s2am_ard_3-2-1_50HMG_2024-02-17_final
2024-03-28 11:47:07	ga_s2am_ard_3-2-1_50HNH_2024-03-28_final
2024-04-04 11:37:18	ga_s2am_ard_3-2-1_50HPG_2024-04-04_final
2024-05-03 12:05:32	ga_s2am_ard_3-2-1_49JGK_2024-05-03_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

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