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
2015-10-22 11:38:10	ga_s2am_ard_3-2-1_50HMJ_2015-10-22_final.stac-item
2015-10-22 11:38:10	ga_s2am_ard_3-2-1_50HNJ_2015-10-22_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50HLH_2015-11-14_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49JGN_2016-05-15_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HMG_2016-11-15_final
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HPG_2016-11-15_final
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HLH_2017-02-03_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_49JGM_2017-02-19_final.stac-item
2017-05-11 11:35:01	ga_s2am_ard_3-2-1_50HQK_2017-05-11_final.stac-item
2017-07-30 11:34:57	ga_s2am_ard_3-2-1_50HPK_2017-07-30_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JGM_2017-09-17_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49KHR_2017-10-07_final.stac-item
2017-10-18 11:30:06	ga_s2am_ard_3-2-1_50HPK_2017-10-18_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_49JGL_2017-11-26_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50HPK_2017-12-10_final.stac-item
2018-02-08 11:45:59	ga_s2am_ard_3-2-1_50HMH_2018-02-08_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HMH_2018-02-18_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JKN_2018-02-21_final.stac-item
2018-02-25 11:27:26	ga_s2am_ard_3-2-1_50HPH_2018-02-25_final.stac-item
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50HMH_2018-02-28_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50HMH_2018-03-13_final.stac-item
2018-03-29 12:13:20	ga_s2am_ard_3-2-1_49JGM_2018-03-29_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HNH_2018-05-09_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HNK_2018-05-12_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49KGP_2018-06-24_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50HNJ_2018-08-27_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-09-12_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HMH_2018-10-16_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HMJ_2018-10-16_final.stac-item
2018-11-28 11:55:51	ga_s2am_ard_3-2-1_50JKN_2018-11-28_final.stac-item
2019-01-27 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2019-01-27_final.stac-item
2019-01-27 11:57:02	ga_s2am_ard_3-2-1_50HMH_2019-01-27_final.stac-item
2019-02-03 11:47:11	ga_s2am_ard_3-2-1_50HLH_2019-02-03_final.stac-item
2019-02-06 11:56:48	ga_s2am_ard_3-2-1_50HMJ_2019-02-06_final.stac-item
2019-02-06 11:57:03	ga_s2am_ard_3-2-1_50HMH_2019-02-06_final.stac-item
2019-10-11 11:46:33	ga_s2am_ard_3-2-1_50HQK_2019-10-11_final.stac-item
2019-11-20 11:47:15	ga_s2am_ard_3-2-1_50HLH_2019-11-20_final.stac-item
2020-01-09 11:46:37	ga_s2am_ard_3-2-1_50HQJ_2020-01-09_final.stac-item
2020-01-12 11:56:45	ga_s2am_ard_3-2-1_50HMJ_2020-01-12_final.stac-item
2020-02-18 11:47:08	ga_s2am_ard_3-2-1_50HLH_2020-02-18_final.stac-item
2020-03-05 12:04:00	ga_s2am_ard_3-2-1_49KHR_2020-03-05_final.stac-item
2020-04-04 12:04:27	ga_s2am_ard_3-2-1_49KGP_2020-04-04_final.stac-item
2020-06-10 11:57:01	ga_s2am_ard_3-2-1_50HLJ_2020-06-10_final.stac-item
2020-06-17 11:47:16	ga_s2am_ard_3-2-1_50HMH_2020-06-17_final.stac-item
2020-08-02 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-08-02_final.stac-item
2020-10-25 11:46:39	ga_s2am_ard_3-2-1_50HPK_2020-10-25_final.stac-item
2020-12-17 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2020-12-17_final.stac-item
2020-12-20 12:05:54	ga_s2am_ard_3-2-1_50JKN_2020-12-20_final.stac-item
2021-01-10 11:37:22	ga_s2am_ard_3-2-1_50HPG_2021-01-10_final
2021-01-12 12:14:42	ga_s2am_ard_3-2-1_49JGN_2021-01-12_final.stac-item
2021-02-02 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-02-02_final
2021-03-10 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-03-10_final
2021-03-13 12:14:56	ga_s2am_ard_3-2-1_49JGM_2021-03-13_final.stac-item
2021-03-17 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2021-03-17_final.stac-item
2021-03-20 12:03:58	ga_s2am_ard_3-2-1_49KHR_2021-03-20_final.stac-item
2021-04-26 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-04-26_final.stac-item
2021-04-29 12:03:42	ga_s2am_ard_3-2-1_49KHS_2021-04-29_final
2021-07-11 12:13:57	ga_s2am_ard_3-2-1_49KHR_2021-07-11_final.stac-item
2021-08-01 11:47:13	ga_s2am_ard_3-2-1_50HMH_2021-08-01_final.stac-item
2021-08-10 12:15:02	ga_s2am_ard_3-2-1_49JFM_2021-08-10_final.stac-item
2021-08-17 12:04:45	ga_s2am_ard_3-2-1_49JHN_2021-08-17_final.stac-item
2021-09-07 11:37:13	ga_s2am_ard_3-2-1_50HPH_2021-09-07_final.stac-item
2021-10-10 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2021-10-10_final.stac-item
2021-12-25 12:04:00	ga_s2am_ard_3-2-1_49KHR_2021-12-25_final.stac-item
2022-02-27 11:46:40	ga_s2am_ard_3-2-1_50HNK_2022-02-27_final.stac-item
2022-03-28 12:15:13	ga_s2am_ard_3-2-1_49JGL_2022-03-28_final.stac-item
2022-04-04 12:04:44	ga_s2am_ard_3-2-1_49JHN_2022-04-04_final.stac-item
2022-04-24 12:06:00	ga_s2am_ard_3-2-1_50JKN_2022-04-24_final.stac-item
2022-05-07 12:15:00	ga_s2am_ard_3-2-1_49JGM_2022-05-07_final.stac-item
2022-06-17 11:46:45	ga_s2am_ard_3-2-1_50HPK_2022-06-17_final.stac-item
2022-06-17 11:46:59	ga_s2am_ard_3-2-1_50HPJ_2022-06-17_final.stac-item
2022-07-23 12:05:26	ga_s2am_ard_3-2-1_49JGL_2022-07-23_final.stac-item
2022-07-27 11:46:53	ga_s2am_ard_3-2-1_50HQJ_2022-07-27_final.stac-item
2022-09-01 12:05:13	ga_s2am_ard_3-2-1_49JGM_2022-09-01_final.stac-item
2022-10-14 12:15:01	ga_s2am_ard_3-2-1_49JGM_2022-10-14_final.stac-item
2022-10-31 12:04:50	ga_s2am_ard_3-2-1_49JGN_2022-10-31_final.stac-item
2022-11-20 12:05:30	ga_s2am_ard_3-2-1_49JGK_2022-11-20_final.stac-item
2022-12-03 12:14:56	ga_s2am_ard_3-2-1_49JGM_2022-12-03_final.stac-item
2022-12-30 12:03:58	ga_s2am_ard_3-2-1_49KHR_2022-12-30_final.stac-item
2023-01-06 11:56:39	ga_s2am_ard_3-2-1_50HLK_2023-01-06_final.stac-item
2023-01-06 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2023-01-06_final.stac-item
2023-01-22 12:15:06	ga_s2am_ard_3-2-1_49JGL_2023-01-22_final.stac-item
2023-04-06 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2023-04-06_final
2023-05-06 11:57:09	ga_s2am_ard_3-2-1_50HLH_2023-05-06_final
2023-05-23 11:47:09	ga_s2am_ard_3-2-1_50HNH_2023-05-23_final
2023-06-09 11:37:06	ga_s2am_ard_3-2-1_50HQH_2023-06-09_final
2023-06-15 11:56:44	ga_s2am_ard_3-2-1_50HLK_2023-06-15_final
2023-07-01 12:14:46	ga_s2am_ard_3-2-1_49JGN_2023-07-01_final
2023-07-12 11:46:39	ga_s2am_ard_3-2-1_50HPK_2023-07-12_final
2023-07-28 12:04:04	ga_s2am_ard_3-2-1_49KHR_2023-07-28_final
2023-08-14 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-08-14_final
2023-08-18 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2023-08-18_final
2023-09-29 12:14:58	ga_s2am_ard_3-2-1_49JGM_2023-09-29_final
2023-09-30 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2023-09-30_final
2023-10-13 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2023-10-13_final
2023-11-02 11:56:35	ga_s2am_ard_3-2-1_50HMK_2023-11-02_final
2023-12-19 11:46:39	ga_s2am_ard_3-2-1_50HQJ_2023-12-19_final
2024-01-24 12:04:54	ga_s2am_ard_3-2-1_49JGM_2024-01-24_final
2024-02-03 12:03:40	ga_s2am_ard_3-2-1_49KHS_2024-02-03_final
2024-02-07 11:46:30	ga_s2am_ard_3-2-1_50HNK_2024-02-07_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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