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
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49KHR_2016-04-15_final.stac-item
2016-05-05 12:04:47	ga_s2am_ard_3-2-1_49JGL_2016-05-05_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50HNG_2016-05-16_final
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_50HNG_2016-06-05_final
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_49JGL_2016-07-24_final.stac-item
2016-07-27 12:14:46	ga_s2am_ard_3-2-1_49JGM_2016-07-27_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50HNK_2016-09-06_final.stac-item
2016-09-26 11:40:08	ga_s2am_ard_3-2-1_50HPJ_2016-09-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HNK_2016-10-26_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50HLH_2016-10-29_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HMJ_2016-11-05_final.stac-item
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HMJ_2017-01-24_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_49KHR_2017-02-19_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_49JGJ_2017-06-19_final.stac-item
2017-07-23 11:45:09	ga_s2am_ard_3-2-1_50HMK_2017-07-23_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49KHR_2017-10-07_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_50JKT_2017-10-07_final.stac-item
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50HLJ_2017-11-13_final.stac-item
2018-02-08 11:45:59	ga_s2am_ard_3-2-1_50HNH_2018-02-08_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-02-24_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_50HNH_2018-03-10_final.stac-item
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50HLJ_2018-04-02_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JLN_2018-06-14_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49KHR_2018-06-24_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_50HPK_2018-07-25_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKN_2018-08-13_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_50HQH_2018-08-14_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JLM_2018-10-19_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-11-01_final.stac-item
2018-12-15 11:46:25	ga_s2am_ard_3-2-1_50HPK_2018-12-15_final.stac-item
2019-01-20 12:03:55	ga_s2am_ard_3-2-1_49KHR_2019-01-20_final.stac-item
2019-03-31 12:05:41	ga_s2am_ard_3-2-1_50JKP_2019-03-31_final.stac-item
2019-04-14 11:47:12	ga_s2am_ard_3-2-1_50HMH_2019-04-14_final.stac-item
2019-04-24 11:47:05	ga_s2am_ard_3-2-1_50HPH_2019-04-24_final.stac-item
2019-04-30 12:05:50	ga_s2am_ard_3-2-1_50JKP_2019-04-30_final.stac-item
2019-05-27 11:55:59	ga_s2am_ard_3-2-1_50JLN_2019-05-27_final.stac-item
2019-09-01 11:46:34	ga_s2am_ard_3-2-1_50HPK_2019-09-01_final.stac-item
2019-10-14 11:57:09	ga_s2am_ard_3-2-1_50HMH_2019-10-14_final.stac-item
2019-10-27 12:05:12	ga_s2am_ard_3-2-1_49JGL_2019-10-27_final.stac-item
2020-02-08 11:46:26	ga_s2am_ard_3-2-1_50HPK_2020-02-08_final.stac-item
2020-02-11 11:55:52	ga_s2am_ard_3-2-1_50JKN_2020-02-11_final.stac-item
2020-03-05 12:03:54	ga_s2am_ard_3-2-1_49KHR_2020-03-05_final.stac-item
2020-03-12 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2020-03-12_final.stac-item
2020-04-18 11:46:38	ga_s2am_ard_3-2-1_50HNK_2020-04-18_final.stac-item
2020-05-21 11:55:52	ga_s2am_ard_3-2-1_50JKP_2020-05-21_final.stac-item
2020-06-23 12:05:35	ga_s2am_ard_3-2-1_49JGK_2020-06-23_final.stac-item
2020-06-30 11:56:01	ga_s2am_ard_3-2-1_50JLN_2020-06-30_final.stac-item
2020-07-13 12:05:05	ga_s2am_ard_3-2-1_49JGM_2020-07-13_final.stac-item
2020-10-11 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-10-11_final.stac-item
2020-11-21 11:37:05	ga_s2am_ard_3-2-1_50HQH_2020-11-21_final.stac-item
2020-12-24 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2020-12-24_final.stac-item
2021-01-02 12:15:11	ga_s2am_ard_3-2-1_49JGL_2021-01-02_final.stac-item
2021-01-06 11:55:42	ga_s2am_ard_3-2-1_50JLP_2021-01-06_final.stac-item
2021-03-04 11:47:10	ga_s2am_ard_3-2-1_50HMH_2021-03-04_final.stac-item
2021-03-11 11:36:37	ga_s2am_ard_3-2-1_50HPK_2021-03-11_final.stac-item
2021-03-24 11:46:36	ga_s2am_ard_3-2-1_50HNK_2021-03-24_final.stac-item
2021-03-24 11:47:05	ga_s2am_ard_3-2-1_50HNH_2021-03-24_final.stac-item
2021-03-27 11:57:11	ga_s2am_ard_3-2-1_50HLH_2021-03-27_final.stac-item
2021-03-30 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2021-03-30_final.stac-item
2021-05-03 11:47:22	ga_s2am_ard_3-2-1_50HMG_2021-05-03_final
2021-05-09 12:03:43	ga_s2am_ard_3-2-1_49KHS_2021-05-09_final
2021-05-23 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2021-05-23_final.stac-item
2021-05-26 11:55:47	ga_s2am_ard_3-2-1_50JKP_2021-05-26_final.stac-item
2021-05-26 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-05-26_final
2021-07-02 11:47:23	ga_s2am_ard_3-2-1_50HNG_2021-07-02_final
2021-07-18 12:05:55	ga_s2am_ard_3-2-1_50JLN_2021-07-18_final.stac-item
2021-07-21 12:14:45	ga_s2am_ard_3-2-1_49JGN_2021-07-21_final.stac-item
2021-08-11 11:46:54	ga_s2am_ard_3-2-1_50HNJ_2021-08-11_final.stac-item
2021-08-17 12:04:48	ga_s2am_ard_3-2-1_49JGN_2021-08-17_final.stac-item
2021-09-29 12:15:00	ga_s2am_ard_3-2-1_49JGM_2021-09-29_final.stac-item
2021-09-30 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2021-09-30_final.stac-item
2021-11-12 11:55:48	ga_s2am_ard_3-2-1_50JKP_2021-11-12_final.stac-item
2021-11-12 11:56:38	ga_s2am_ard_3-2-1_50HMK_2021-11-12_final.stac-item
2021-12-09 11:47:08	ga_s2am_ard_3-2-1_50HMH_2021-12-09_final.stac-item
2021-12-29 11:47:11	ga_s2am_ard_3-2-1_50HMH_2021-12-29_final.stac-item
2022-01-01 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2022-01-01_final.stac-item
2022-01-08 11:47:11	ga_s2am_ard_3-2-1_50HMH_2022-01-08_final.stac-item
2022-02-07 11:46:37	ga_s2am_ard_3-2-1_50HNK_2022-02-07_final.stac-item
2022-03-28 12:14:59	ga_s2am_ard_3-2-1_49JGM_2022-03-28_final.stac-item
2022-05-15 11:37:11	ga_s2am_ard_3-2-1_50HPH_2022-05-15_final.stac-item
2022-12-14 11:47:10	ga_s2am_ard_3-2-1_50HMH_2022-12-14_final.stac-item
2022-12-24 11:47:08	ga_s2am_ard_3-2-1_50HMH_2022-12-24_final.stac-item
2023-02-15 11:55:56	ga_s2am_ard_3-2-1_50JKN_2023-02-15_nrt.stac-item
2023-02-15 11:55:56	ga_s2am_ard_3-2-1_50JKN_2023-02-15_final
2023-02-28 12:03:57	ga_s2am_ard_3-2-1_49KHR_2023-02-28_final
2023-05-19 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2023-05-19_final
2023-06-08 12:03:48	ga_s2am_ard_3-2-1_49KHS_2023-06-08_final
2023-06-15 11:56:30	ga_s2am_ard_3-2-1_50JLL_2023-06-15_final
2023-07-05 11:56:16	ga_s2am_ard_3-2-1_50JLM_2023-07-05_final
2023-07-08 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2023-07-08_final
2023-10-06 12:05:42	ga_s2am_ard_3-2-1_50JKP_2023-10-06_final
2023-11-02 11:55:50	ga_s2am_ard_3-2-1_50JKP_2023-11-02_final
2023-11-16 11:37:05	ga_s2am_ard_3-2-1_50HPH_2023-11-16_final
2023-12-08 12:14:50	ga_s2am_ard_3-2-1_49JGM_2023-12-08_final
2023-12-09 11:47:04	ga_s2am_ard_3-2-1_50HMH_2023-12-09_final
2023-12-19 11:47:06	ga_s2am_ard_3-2-1_50HMH_2023-12-19_final
2024-01-01 11:56:48	ga_s2am_ard_3-2-1_50HMJ_2024-01-01_final
2024-01-04 12:03:41	ga_s2am_ard_3-2-1_49KHS_2024-01-04_final
2024-02-23 12:05:27	ga_s2am_ard_3-2-1_49JGK_2024-02-23_final
2024-03-24 12:03:46	ga_s2am_ard_3-2-1_49KHS_2024-03-24_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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