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
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_49JGL_2015-12-17_final.stac-item
2015-12-27 12:05:25	ga_s2am_ard_3-2-1_49JGM_2015-12-27_final.stac-item
2016-01-19 12:13:57	ga_s2am_ard_3-2-1_49KHR_2016-01-19_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JGK_2016-01-26_final.stac-item
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49KGQ_2016-03-09_final.stac-item
2016-09-25 12:14:37	ga_s2am_ard_3-2-1_49JGL_2016-09-25_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHR_2016-11-11_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HNG_2016-11-12_final
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49JGM_2016-11-14_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49JGM_2016-12-24_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49JGK_2016-12-31_final.stac-item
2017-02-02 12:13:15	ga_s2am_ard_3-2-1_49KHQ_2017-02-02_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_49JGM_2017-09-07_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_49JGJ_2017-11-06_final.stac-item
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_49JGM_2017-11-29_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50HMJ_2017-12-03_final.stac-item
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50HMJ_2017-12-23_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-02-14_final.stac-item
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_49JGJ_2018-05-05_final.stac-item
2018-12-11 12:03:51	ga_s2am_ard_3-2-1_49KHR_2018-12-11_final.stac-item
2019-02-13 11:47:12	ga_s2am_ard_3-2-1_50HLH_2019-02-13_final.stac-item
2019-03-01 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2019-03-01_final.stac-item
2019-03-08 11:56:31	ga_s2am_ard_3-2-1_50HMK_2019-03-08_final.stac-item
2019-09-01 11:46:38	ga_s2am_ard_3-2-1_50HNK_2019-09-01_final.stac-item
2019-11-10 11:47:12	ga_s2am_ard_3-2-1_50HMH_2019-11-10_final.stac-item
2019-12-23 11:56:45	ga_s2am_ard_3-2-1_50HMJ_2019-12-23_final.stac-item
2020-01-18 12:13:48	ga_s2am_ard_3-2-1_49KHR_2020-01-18_final.stac-item
2020-02-04 12:05:36	ga_s2am_ard_3-2-1_49JGJ_2020-02-04_final.stac-item
2020-02-11 11:56:44	ga_s2am_ard_3-2-1_50HMJ_2020-02-11_final.stac-item
2020-02-17 12:14:06	ga_s2am_ard_3-2-1_49KGQ_2020-02-17_final.stac-item
2020-03-05 12:05:25	ga_s2am_ard_3-2-1_49JGK_2020-03-05_final.stac-item
2020-04-01 11:57:05	ga_s2am_ard_3-2-1_50HLH_2020-04-01_final.stac-item
2020-04-28 11:46:54	ga_s2am_ard_3-2-1_50HNJ_2020-04-28_final.stac-item
2020-05-04 12:05:04	ga_s2am_ard_3-2-1_49JGM_2020-05-04_final.stac-item
2020-07-07 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2020-07-07_final.stac-item
2020-07-16 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2020-07-16_final.stac-item
2020-08-12 12:04:05	ga_s2am_ard_3-2-1_49KHR_2020-08-12_final.stac-item
2020-08-15 12:15:06	ga_s2am_ard_3-2-1_49JFM_2020-08-15_final.stac-item
2020-08-19 11:56:35	ga_s2am_ard_3-2-1_50HNK_2020-08-19_final.stac-item
2020-11-13 12:15:03	ga_s2am_ard_3-2-1_49JFM_2020-11-13_final.stac-item
2020-11-30 12:03:59	ga_s2am_ard_3-2-1_49KHR_2020-11-30_final.stac-item
2020-12-17 11:56:38	ga_s2am_ard_3-2-1_50HLK_2020-12-17_final.stac-item
2020-12-23 12:14:55	ga_s2am_ard_3-2-1_49JGM_2020-12-23_final.stac-item
2020-12-27 11:57:05	ga_s2am_ard_3-2-1_50HMH_2020-12-27_final.stac-item
2021-01-12 12:14:28	ga_s2am_ard_3-2-1_49KGP_2021-01-12_final.stac-item
2021-01-29 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2021-01-29_final.stac-item
2021-02-05 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2021-02-05_final.stac-item
2021-02-11 12:14:40	ga_s2am_ard_3-2-1_49JGN_2021-02-11_final.stac-item
2021-02-28 12:05:15	ga_s2am_ard_3-2-1_49JGL_2021-02-28_final.stac-item
2021-04-19 12:03:54	ga_s2am_ard_3-2-1_49KHR_2021-04-19_final.stac-item
2021-05-09 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-05-09_final.stac-item
2021-05-13 11:46:37	ga_s2am_ard_3-2-1_50HNK_2021-05-13_final.stac-item
2021-05-22 12:14:42	ga_s2am_ard_3-2-1_49JGN_2021-05-22_final.stac-item
2021-06-05 11:56:31	ga_s2am_ard_3-2-1_50HNK_2021-06-05_final.stac-item
2021-07-28 12:04:35	ga_s2am_ard_3-2-1_49KGP_2021-07-28_final.stac-item
2021-10-09 12:14:03	ga_s2am_ard_3-2-1_49KGR_2021-10-09_final.stac-item
2021-10-26 12:05:13	ga_s2am_ard_3-2-1_49JFM_2021-10-26_final.stac-item
2021-10-29 12:13:59	ga_s2am_ard_3-2-1_49KHR_2021-10-29_final.stac-item
2021-10-29 12:15:15	ga_s2am_ard_3-2-1_49JGL_2021-10-29_final.stac-item
2021-11-05 12:05:04	ga_s2am_ard_3-2-1_49JGM_2021-11-05_final.stac-item
2021-11-15 12:04:00	ga_s2am_ard_3-2-1_49KHR_2021-11-15_final.stac-item
2021-11-19 11:47:21	ga_s2am_ard_3-2-1_50HNG_2021-11-19_final
2021-11-28 12:13:54	ga_s2am_ard_3-2-1_49KHR_2021-11-28_final.stac-item
2021-12-19 11:47:25	ga_s2am_ard_3-2-1_50HMG_2021-12-19_final
2021-12-25 12:04:00	ga_s2am_ard_3-2-1_49KHR_2021-12-25_final.stac-item
2022-01-01 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2022-01-01_final.stac-item
2022-01-07 12:13:56	ga_s2am_ard_3-2-1_49KHR_2022-01-07_final.stac-item
2022-01-11 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-01-11_final.stac-item
2022-01-17 12:13:59	ga_s2am_ard_3-2-1_49KGR_2022-01-17_final.stac-item
2022-01-24 12:05:01	ga_s2am_ard_3-2-1_49JGM_2022-01-24_final.stac-item
2022-01-27 12:15:10	ga_s2am_ard_3-2-1_49JGL_2022-01-27_final.stac-item
2022-02-06 12:13:54	ga_s2am_ard_3-2-1_49KHR_2022-02-06_final.stac-item
2022-04-21 11:56:45	ga_s2am_ard_3-2-1_50HLK_2022-04-21_final.stac-item
2022-04-27 12:15:13	ga_s2am_ard_3-2-1_49JGL_2022-04-27_final.stac-item
2022-05-24 12:05:08	ga_s2am_ard_3-2-1_49JGM_2022-05-24_final.stac-item
2022-06-23 12:04:30	ga_s2am_ard_3-2-1_49KGQ_2022-06-23_final.stac-item
2022-08-26 11:47:19	ga_s2am_ard_3-2-1_50HNH_2022-08-26_final
2022-10-24 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2022-10-24_final.stac-item
2022-11-30 12:05:01	ga_s2am_ard_3-2-1_49JGM_2022-11-30_final.stac-item
2023-01-02 12:13:54	ga_s2am_ard_3-2-1_49KHR_2023-01-02_final.stac-item
2023-01-02 12:13:57	ga_s2am_ard_3-2-1_49KGR_2023-01-02_final.stac-item
2023-01-09 12:05:13	ga_s2am_ard_3-2-1_49JGL_2023-01-09_final.stac-item
2023-01-12 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-01-12_final.stac-item
2023-03-04 11:47:21	ga_s2am_ard_3-2-1_50HMG_2023-03-04_final
2023-05-13 11:46:40	ga_s2am_ard_3-2-1_50HMK_2023-05-13_final
2023-05-19 12:03:46	ga_s2am_ard_3-2-1_49KHS_2023-05-19_final
2023-06-22 11:47:28	ga_s2am_ard_3-2-1_50HMG_2023-06-22_final
2023-08-11 11:47:11	ga_s2am_ard_3-2-1_50HNH_2023-08-11_final
2023-09-26 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2023-09-26_final
2023-10-26 12:05:29	ga_s2am_ard_3-2-1_49JGK_2023-10-26_final
2023-11-15 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-11-15_final
2023-11-22 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2023-11-22_final
2023-11-28 12:13:47	ga_s2am_ard_3-2-1_49KHR_2023-11-28_final
2024-01-11 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2024-01-11_final
2024-01-27 12:14:50	ga_s2am_ard_3-2-1_49JGM_2024-01-27_final
2024-02-03 12:05:11	ga_s2am_ard_3-2-1_49JGL_2024-02-03_final
2024-02-06 12:15:06	ga_s2am_ard_3-2-1_49JGL_2024-02-06_final
2024-02-13 12:03:56	ga_s2am_ard_3-2-1_49KHR_2024-02-13_final
2024-02-17 11:47:04	ga_s2am_ard_3-2-1_50HNH_2024-02-17_final
2024-04-30 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2024-04-30_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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