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_49JGM_2015-10-08_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49KGP_2016-05-15_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_49JGM_2016-08-23_final.stac-item
2017-04-07 11:56:31	ga_s2am_ard_3-2-1_50HLJ_2017-04-07_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JGM_2017-06-29_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49JGN_2017-07-09_final.stac-item
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49JGM_2017-08-21_final.stac-item
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49JGN_2017-08-21_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_49JHN_2017-10-17_final.stac-item
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50HMJ_2017-12-23_final.stac-item
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50HLJ_2018-02-11_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGN_2018-03-06_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49KGR_2018-03-09_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50HMH_2018-03-13_final.stac-item
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_49JGL_2018-03-16_final.stac-item
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50HLJ_2018-04-02_final.stac-item
2018-04-18 12:13:22	ga_s2am_ard_3-2-1_49JGM_2018-04-18_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_49JHM_2018-04-25_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50HMH_2018-04-29_final.stac-item
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_49JGJ_2018-05-05_final.stac-item
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_49JGL_2018-05-15_final.stac-item
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_49JFM_2018-05-18_final.stac-item
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_49JGM_2018-05-18_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HLK_2018-05-22_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_49JGK_2018-06-14_final.stac-item
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49JGM_2018-06-17_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49KHQ_2018-06-24_final.stac-item
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49JGL_2018-07-07_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49KGR_2018-08-06_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-09-12_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49JGM_2018-09-25_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50HLJ_2018-10-09_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KHP_2018-10-15_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HMK_2018-10-16_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49JGN_2018-10-22_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50HMK_2018-11-05_final.stac-item
2018-11-08 11:57:05	ga_s2am_ard_3-2-1_50HLH_2018-11-08_final.stac-item
2018-12-01 12:04:23	ga_s2am_ard_3-2-1_49KGP_2018-12-01_final.stac-item
2019-03-05 11:46:35	ga_s2am_ard_3-2-1_50HMK_2019-03-05_final.stac-item
2019-05-20 12:04:35	ga_s2am_ard_3-2-1_49KGP_2019-05-20_final.stac-item
2019-06-09 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-06-09_final.stac-item
2019-06-19 12:04:35	ga_s2am_ard_3-2-1_49KGP_2019-06-19_final.stac-item
2019-06-29 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-06-29_final.stac-item
2019-07-09 12:05:20	ga_s2am_ard_3-2-1_49JGL_2019-07-09_final.stac-item
2019-09-04 11:56:36	ga_s2am_ard_3-2-1_50HMK_2019-09-04_final.stac-item
2019-09-10 12:14:54	ga_s2am_ard_3-2-1_49JGM_2019-09-10_final.stac-item
2019-10-10 12:14:59	ga_s2am_ard_3-2-1_49JGM_2019-10-10_final.stac-item
2019-11-20 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2019-11-20_final.stac-item
2019-12-26 12:03:54	ga_s2am_ard_3-2-1_49KHR_2019-12-26_final.stac-item
2020-01-08 12:14:50	ga_s2am_ard_3-2-1_49JGM_2020-01-08_final.stac-item
2020-01-12 11:56:34	ga_s2am_ard_3-2-1_50HLK_2020-01-12_final.stac-item
2020-04-18 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2020-04-18_final.stac-item
2020-04-28 11:47:12	ga_s2am_ard_3-2-1_50HMH_2020-04-28_final.stac-item
2020-05-31 11:57:12	ga_s2am_ard_3-2-1_50HMH_2020-05-31_final.stac-item
2020-07-03 12:05:05	ga_s2am_ard_3-2-1_49JGM_2020-07-03_final.stac-item
2020-07-16 12:14:03	ga_s2am_ard_3-2-1_49KGR_2020-07-16_final.stac-item
2020-08-02 12:05:50	ga_s2am_ard_3-2-1_49JGJ_2020-08-02_final.stac-item
2020-08-12 12:05:35	ga_s2am_ard_3-2-1_49JGK_2020-08-12_final.stac-item
2020-09-24 12:15:01	ga_s2am_ard_3-2-1_49JGM_2020-09-24_final.stac-item
2020-10-14 12:14:00	ga_s2am_ard_3-2-1_49KHR_2020-10-14_final.stac-item
2020-12-07 11:57:03	ga_s2am_ard_3-2-1_50HMH_2020-12-07_final.stac-item
2020-12-10 12:05:11	ga_s2am_ard_3-2-1_49JGL_2020-12-10_final.stac-item
2020-12-20 12:05:13	ga_s2am_ard_3-2-1_49JGL_2020-12-20_final.stac-item
2020-12-24 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2020-12-24_final.stac-item
2020-12-27 11:57:05	ga_s2am_ard_3-2-1_50HMH_2020-12-27_final.stac-item
2021-01-16 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-01-16_final.stac-item
2021-02-05 11:57:05	ga_s2am_ard_3-2-1_50HMH_2021-02-05_final.stac-item
2021-02-18 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-02-18_final.stac-item
2021-02-22 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-02-22_final
2021-03-13 12:14:56	ga_s2am_ard_3-2-1_49JGM_2021-03-13_final.stac-item
2021-04-03 11:46:37	ga_s2am_ard_3-2-1_50HMK_2021-04-03_final.stac-item
2021-04-16 11:56:49	ga_s2am_ard_3-2-1_50HLJ_2021-04-16_final.stac-item
2021-04-16 11:57:00	ga_s2am_ard_3-2-1_50HMH_2021-04-16_final.stac-item
2021-04-16 11:57:17	ga_s2am_ard_3-2-1_50HLG_2021-04-16_final
2021-04-29 12:04:25	ga_s2am_ard_3-2-1_49KHP_2021-04-29_final.stac-item
2021-05-06 11:56:39	ga_s2am_ard_3-2-1_50HLK_2021-05-06_final.stac-item
2021-07-28 12:04:33	ga_s2am_ard_3-2-1_49KHP_2021-07-28_final.stac-item
2021-08-11 11:47:29	ga_s2am_ard_3-2-1_50HLG_2021-08-11_final
2021-09-06 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-09-06_final
2021-09-10 11:46:41	ga_s2am_ard_3-2-1_50HMK_2021-09-10_final.stac-item
2021-11-15 12:05:30	ga_s2am_ard_3-2-1_49JGK_2021-11-15_final.stac-item
2021-12-19 11:47:25	ga_s2am_ard_3-2-1_50HMG_2021-12-19_final
2022-01-24 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2022-01-24_final.stac-item
2022-02-13 12:04:42	ga_s2am_ard_3-2-1_49JHN_2022-02-13_final.stac-item
2022-03-02 11:57:09	ga_s2am_ard_3-2-1_50HMH_2022-03-02_final.stac-item
2022-05-11 11:56:44	ga_s2am_ard_3-2-1_50HLK_2022-05-11_final.stac-item
2022-05-14 12:05:19	ga_s2am_ard_3-2-1_49JGL_2022-05-14_final.stac-item
2022-05-27 12:15:18	ga_s2am_ard_3-2-1_49JGL_2022-05-27_final.stac-item
2022-11-10 12:04:46	ga_s2am_ard_3-2-1_49JHN_2022-11-10_final.stac-item
2023-02-08 12:05:28	ga_s2am_ard_3-2-1_49JGK_2023-02-08_final
2023-02-18 12:03:56	ga_s2am_ard_3-2-1_49KHR_2023-02-18_final
2023-03-10 12:03:39	ga_s2am_ard_3-2-1_49KHS_2023-03-10_final
2023-04-09 12:03:45	ga_s2am_ard_3-2-1_49KHS_2023-04-09_final
2023-05-16 11:57:23	ga_s2am_ard_3-2-1_50HLG_2023-05-16_final
2023-09-06 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-09-06_final
2023-09-16 12:04:35	ga_s2am_ard_3-2-1_49KGP_2023-09-16_final
2023-10-16 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-10-16_final
2024-02-26 12:14:55	ga_s2am_ard_3-2-1_49JGM_2024-02-26_final
2024-03-14 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2024-03-14_final
2024-04-03 12:03:42	ga_s2am_ard_3-2-1_49KHS_2024-04-03_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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