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
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49KHQ_2016-01-16_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50HLG_2016-04-02_final
2016-04-29 11:47:17	ga_s2am_ard_3-2-1_50HPG_2016-04-29_final
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HMJ_2016-06-18_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_49KHS_2016-08-03_final
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_50JKS_2016-09-12_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49KHQ_2016-12-31_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_50JKT_2017-02-19_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50HNH_2017-03-05_final.stac-item
2017-09-08 11:36:17	ga_s2am_ard_3-2-1_50HQH_2017-09-08_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50HMK_2018-02-21_final.stac-item
2018-02-27 12:13:18	ga_s2am_ard_3-2-1_49KGR_2018-02-27_final.stac-item
2018-03-07 11:36:09	ga_s2am_ard_3-2-1_50HPH_2018-03-07_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JKP_2018-03-13_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_49JHN_2018-03-26_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HMK_2018-03-30_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50JKP_2018-05-12_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_49KGQ_2018-08-03_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JLN_2018-08-13_final.stac-item
2018-11-08 11:57:01	ga_s2am_ard_3-2-1_50HMH_2018-11-08_final.stac-item
2018-11-15 11:46:46	ga_s2am_ard_3-2-1_50HNJ_2018-11-15_final.stac-item
2018-11-28 11:56:28	ga_s2am_ard_3-2-1_50HMK_2018-11-28_final.stac-item
2018-12-31 12:04:07	ga_s2am_ard_3-2-1_49KHQ_2018-12-31_final.stac-item
2019-03-05 11:47:04	ga_s2am_ard_3-2-1_50HMH_2019-03-05_final.stac-item
2019-03-21 12:04:44	ga_s2am_ard_3-2-1_49JGN_2019-03-21_final.stac-item
2019-05-10 12:04:32	ga_s2am_ard_3-2-1_49KHP_2019-05-10_final.stac-item
2019-05-11 11:37:10	ga_s2am_ard_3-2-1_50HPH_2019-05-11_final.stac-item
2019-05-24 11:47:13	ga_s2am_ard_3-2-1_50HMH_2019-05-24_final.stac-item
2019-06-13 11:47:17	ga_s2am_ard_3-2-1_50HLH_2019-06-13_final.stac-item
2019-07-03 11:46:35	ga_s2am_ard_3-2-1_50HQK_2019-07-03_final.stac-item
2019-07-29 12:05:34	ga_s2am_ard_3-2-1_49JGK_2019-07-29_final.stac-item
2019-08-02 11:47:19	ga_s2am_ard_3-2-1_50HLH_2019-08-02_final.stac-item
2019-08-08 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2019-08-08_final.stac-item
2019-09-28 11:36:50	ga_s2am_ard_3-2-1_50HQJ_2019-09-28_final.stac-item
2019-11-13 11:57:11	ga_s2am_ard_3-2-1_50HLH_2019-11-13_final.stac-item
2019-11-16 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2019-11-16_final.stac-item
2019-11-30 11:47:13	ga_s2am_ard_3-2-1_50HLH_2019-11-30_final.stac-item
2019-12-10 11:46:26	ga_s2am_ard_3-2-1_50HQK_2019-12-10_final.stac-item
2020-01-19 11:47:04	ga_s2am_ard_3-2-1_50HMH_2020-01-19_final.stac-item
2020-01-26 11:36:45	ga_s2am_ard_3-2-1_50HPJ_2020-01-26_final.stac-item
2020-02-14 12:04:18	ga_s2am_ard_3-2-1_49KHP_2020-02-14_final.stac-item
2020-03-09 11:47:08	ga_s2am_ard_3-2-1_50HNH_2020-03-09_final.stac-item
2020-05-11 11:56:45	ga_s2am_ard_3-2-1_50HLK_2020-05-11_final.stac-item
2020-08-22 12:05:03	ga_s2am_ard_3-2-1_50JKS_2020-08-22_final.stac-item
2020-10-21 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-10-21_final.stac-item
2020-12-30 12:04:57	ga_s2am_ard_3-2-1_49JHM_2020-12-30_final.stac-item
2021-01-09 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-01-09_final
2021-01-19 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-01-19_final
2021-02-18 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-02-18_final
2021-02-28 12:04:42	ga_s2am_ard_3-2-1_49JHN_2021-02-28_final.stac-item
2021-03-20 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-03-20_final.stac-item
2021-03-24 11:47:08	ga_s2am_ard_3-2-1_50HMH_2021-03-24_final.stac-item
2021-07-08 12:06:07	ga_s2am_ard_3-2-1_50JLM_2021-07-08_final.stac-item
2021-08-04 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2021-08-04_final.stac-item
2021-08-24 11:56:42	ga_s2am_ard_3-2-1_50HLK_2021-08-24_final.stac-item
2021-10-17 11:37:23	ga_s2am_ard_3-2-1_50HQG_2021-10-17_final
2021-10-23 11:57:25	ga_s2am_ard_3-2-1_50HMG_2021-10-23_final
2021-10-30 11:47:21	ga_s2am_ard_3-2-1_50HPG_2021-10-30_final
2021-11-25 12:04:42	ga_s2am_ard_3-2-1_49JHN_2021-11-25_final.stac-item
2021-12-05 12:05:11	ga_s2am_ard_3-2-1_50JKR_2021-12-05_final.stac-item
2021-12-22 11:55:43	ga_s2am_ard_3-2-1_50JLP_2021-12-22_final.stac-item
2021-12-29 11:46:31	ga_s2am_ard_3-2-1_50HQK_2021-12-29_final.stac-item
2022-01-21 11:56:36	ga_s2am_ard_3-2-1_50HMK_2022-01-21_final.stac-item
2022-02-10 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2022-02-10_final.stac-item
2022-02-23 12:04:30	ga_s2am_ard_3-2-1_49KHP_2022-02-23_final.stac-item
2022-04-11 11:57:16	ga_s2am_ard_3-2-1_50HMH_2022-04-11_final.stac-item
2022-05-08 11:46:45	ga_s2am_ard_3-2-1_50HMK_2022-05-08_final.stac-item
2022-10-08 11:55:48	ga_s2am_ard_3-2-1_50JLP_2022-10-08_final.stac-item
2022-10-21 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2022-10-21_final.stac-item
2022-10-31 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2022-10-31_final.stac-item
2022-11-30 12:04:28	ga_s2am_ard_3-2-1_49KHP_2022-11-30_final.stac-item
2022-12-11 11:36:34	ga_s2am_ard_3-2-1_50HQK_2022-12-11_final.stac-item
2022-12-14 11:46:30	ga_s2am_ard_3-2-1_50HQK_2022-12-14_final.stac-item
2023-01-29 12:04:40	ga_s2am_ard_3-2-1_50JKT_2023-01-29_final.stac-item
2023-01-29 12:04:44	ga_s2am_ard_3-2-1_49JGN_2023-01-29_final.stac-item
2023-02-02 11:47:12	ga_s2am_ard_3-2-1_50HNH_2023-02-02_final
2023-02-05 11:55:49	ga_s2am_ard_3-2-1_50JLP_2023-02-05_final
2023-03-14 11:46:48	ga_s2am_ard_3-2-1_50HNJ_2023-03-14_final
2023-03-14 11:47:06	ga_s2am_ard_3-2-1_50HMH_2023-03-14_final
2023-05-09 12:05:11	ga_s2am_ard_3-2-1_50JKR_2023-05-09_final
2023-05-22 12:14:01	ga_s2am_ard_3-2-1_49KGR_2023-05-22_final
2023-06-28 12:05:30	ga_s2am_ard_3-2-1_50JKQ_2023-06-28_final
2023-10-20 11:46:30	ga_s2am_ard_3-2-1_50HQK_2023-10-20_final
2023-11-05 12:03:44	ga_s2am_ard_3-2-1_49KHS_2023-11-05_final
2023-11-09 11:46:53	ga_s2am_ard_3-2-1_50HQH_2023-11-09_final
2023-12-06 11:37:00	ga_s2am_ard_3-2-1_50HPH_2023-12-06_final
2024-01-04 12:05:23	ga_s2am_ard_3-2-1_50JKQ_2024-01-04_final
2024-01-08 11:47:16	ga_s2am_ard_3-2-1_50HNG_2024-01-08_final
2024-01-11 11:56:31	ga_s2am_ard_3-2-1_50HMK_2024-01-11_final
2024-01-18 11:46:46	ga_s2am_ard_3-2-1_50HMJ_2024-01-18_final
2024-02-04 11:36:30	ga_s2am_ard_3-2-1_50HQK_2024-02-04_final
2024-02-13 12:05:09	ga_s2am_ard_3-2-1_50JKR_2024-02-13_final
2024-02-17 11:47:12	ga_s2am_ard_3-2-1_50HLH_2024-02-17_final
2024-02-23 12:04:38	ga_s2am_ard_3-2-1_50JKT_2024-02-23_final
2024-04-06 12:13:38	ga_s2am_ard_3-2-1_49KHS_2024-04-06_final
2024-04-10 11:56:29	ga_s2am_ard_3-2-1_50HMK_2024-04-10_final
2024-04-10 11:56:31	ga_s2am_ard_3-2-1_50HNK_2024-04-10_final
2024-04-13 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2024-04-13_final
2024-05-17 11:46:32	ga_s2am_ard_3-2-1_50HQK_2024-05-17_final
2024-05-23 12:04:42	ga_s2am_ard_3-2-1_50JKT_2024-05-23_nrt

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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