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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KGP_2015-10-28_final.stac-item
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_50JKP_2015-10-28_final.stac-item
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50HPJ_2016-01-07_final.stac-item
2016-01-09 12:16:04	ga_s2am_ard_3-2-1_49KGR_2016-01-09_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50JLN_2016-01-16_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_50HNG_2016-02-06_final
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_49JGJ_2016-02-15_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49KHP_2016-04-15_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50JLN_2016-06-11_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HMK_2016-10-26_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50JKN_2016-11-01_final.stac-item
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HNH_2017-01-24_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HNK_2017-02-03_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50HPK_2017-03-05_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_50JKP_2017-04-20_final.stac-item
2017-04-27 11:49:47	ga_s2am_ard_3-2-1_50JLM_2017-04-27_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49KGP_2017-05-10_final.stac-item
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50HMH_2017-05-24_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49JGL_2017-05-30_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_50JKP_2017-05-30_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JLL_2017-06-26_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50HNH_2017-11-20_final.stac-item
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50HNK_2017-12-23_final.stac-item
2018-01-02 11:56:01	ga_s2am_ard_3-2-1_50JLM_2018-01-02_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_50HNJ_2018-03-10_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49JFM_2018-04-28_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JKP_2018-06-14_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKP_2018-06-24_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JGL_2018-10-12_final.stac-item
2018-11-21 12:05:45	ga_s2am_ard_3-2-1_50JLN_2018-11-21_final.stac-item
2018-11-21 12:06:03	ga_s2am_ard_3-2-1_50JKM_2018-11-21_final.stac-item
2019-03-02 11:36:58	ga_s2am_ard_3-2-1_50HQH_2019-03-02_final.stac-item
2019-04-07 11:56:41	ga_s2am_ard_3-2-1_50HLK_2019-04-07_final.stac-item
2019-04-10 12:04:33	ga_s2am_ard_3-2-1_49KGP_2019-04-10_final.stac-item
2019-04-30 12:05:43	ga_s2am_ard_3-2-1_50JKP_2019-04-30_final.stac-item
2019-06-29 12:04:50	ga_s2am_ard_3-2-1_49JGN_2019-06-29_final.stac-item
2019-09-07 12:04:30	ga_s2am_ard_3-2-1_49KGP_2019-09-07_final.stac-item
2019-10-07 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2019-10-07_final.stac-item
2019-11-16 12:05:43	ga_s2am_ard_3-2-1_50JKP_2019-11-16_final.stac-item
2019-12-10 11:46:30	ga_s2am_ard_3-2-1_50HPK_2019-12-10_final.stac-item
2019-12-29 12:14:36	ga_s2am_ard_3-2-1_49JGN_2019-12-29_final.stac-item
2020-02-08 11:46:35	ga_s2am_ard_3-2-1_50HQJ_2020-02-08_final.stac-item
2020-02-27 12:14:22	ga_s2am_ard_3-2-1_49KGP_2020-02-27_final.stac-item
2020-03-05 12:05:47	ga_s2am_ard_3-2-1_50JLN_2020-03-05_final.stac-item
2020-03-25 12:04:42	ga_s2am_ard_3-2-1_49JGN_2020-03-25_final.stac-item
2020-05-14 12:04:47	ga_s2am_ard_3-2-1_50JKT_2020-05-14_final.stac-item
2020-06-20 11:55:52	ga_s2am_ard_3-2-1_50JKP_2020-06-20_final.stac-item
2020-07-04 11:37:07	ga_s2am_ard_3-2-1_50HQH_2020-07-04_final.stac-item
2020-07-06 12:15:15	ga_s2am_ard_3-2-1_49JGL_2020-07-06_final.stac-item
2020-07-27 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-07-27_final.stac-item
2020-08-19 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-08-19_final.stac-item
2020-08-26 11:47:08	ga_s2am_ard_3-2-1_50HPH_2020-08-26_final.stac-item
2020-12-24 11:47:09	ga_s2am_ard_3-2-1_50HMH_2020-12-24_final.stac-item
2021-01-06 11:57:06	ga_s2am_ard_3-2-1_50HMH_2021-01-06_final.stac-item
2021-02-01 12:15:10	ga_s2am_ard_3-2-1_49JGL_2021-02-01_final.stac-item
2021-02-08 12:04:56	ga_s2am_ard_3-2-1_49JHM_2021-02-08_final.stac-item
2021-02-12 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2021-02-12_final.stac-item
2021-03-24 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2021-03-24_final.stac-item
2021-04-23 11:46:49	ga_s2am_ard_3-2-1_50HQH_2021-04-23_final.stac-item
2021-04-23 11:47:02	ga_s2am_ard_3-2-1_50HNH_2021-04-23_final.stac-item
2021-04-26 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2021-04-26_final.stac-item
2021-06-02 11:47:22	ga_s2am_ard_3-2-1_50HNG_2021-06-02_final
2021-06-05 11:56:15	ga_s2am_ard_3-2-1_50JKM_2021-06-05_final.stac-item
2021-06-05 11:56:41	ga_s2am_ard_3-2-1_50HLK_2021-06-05_final.stac-item
2021-06-19 11:36:38	ga_s2am_ard_3-2-1_50HPK_2021-06-19_final.stac-item
2021-07-09 11:37:29	ga_s2am_ard_3-2-1_50HNG_2021-07-09_final
2021-07-11 12:15:13	ga_s2am_ard_3-2-1_49JGL_2021-07-11_final.stac-item
2021-10-10 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2021-10-10_final.stac-item
2021-10-10 11:47:26	ga_s2am_ard_3-2-1_50HNG_2021-10-10_final
2021-10-16 12:04:04	ga_s2am_ard_3-2-1_49KHR_2021-10-16_final.stac-item
2021-10-30 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2021-10-30_final.stac-item
2021-10-30 11:47:07	ga_s2am_ard_3-2-1_50HPH_2021-10-30_final.stac-item
2022-01-01 11:56:13	ga_s2am_ard_3-2-1_50JLM_2022-01-01_final.stac-item
2022-02-03 12:04:57	ga_s2am_ard_3-2-1_49JHM_2022-02-03_final.stac-item
2022-02-10 11:55:45	ga_s2am_ard_3-2-1_50JKP_2022-02-10_final.stac-item
2022-03-05 12:05:19	ga_s2am_ard_3-2-1_49JGL_2022-03-05_final.stac-item
2022-03-22 11:55:49	ga_s2am_ard_3-2-1_50JKP_2022-03-22_final.stac-item
2022-05-07 12:14:31	ga_s2am_ard_3-2-1_49KGP_2022-05-07_final.stac-item
2022-05-21 11:56:07	ga_s2am_ard_3-2-1_50JLN_2022-05-21_final.stac-item
2022-06-07 11:46:45	ga_s2am_ard_3-2-1_50HNK_2022-06-07_final.stac-item
2022-06-27 11:47:04	ga_s2am_ard_3-2-1_50HNJ_2022-06-27_final.stac-item
2022-06-30 11:56:24	ga_s2am_ard_3-2-1_50JLM_2022-06-30_final.stac-item
2022-08-22 12:04:12	ga_s2am_ard_3-2-1_49KHR_2022-08-22_final.stac-item
2022-09-11 12:04:53	ga_s2am_ard_3-2-1_49JHN_2022-09-11_final.stac-item
2022-12-24 11:46:41	ga_s2am_ard_3-2-1_50HQJ_2022-12-24_final.stac-item
2022-12-30 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2022-12-30_final.stac-item
2023-02-18 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-02-18_nrt.stac-item
2023-02-25 11:57:07	ga_s2am_ard_3-2-1_50HLH_2023-02-25_final
2023-04-10 11:36:38	ga_s2am_ard_3-2-1_50HPK_2023-04-10_final
2023-05-12 12:14:26	ga_s2am_ard_3-2-1_49KGP_2023-05-12_final
2023-05-19 12:05:31	ga_s2am_ard_3-2-1_49JGK_2023-05-19_final
2023-06-19 11:37:25	ga_s2am_ard_3-2-1_50HPG_2023-06-19_final
2023-06-29 11:36:56	ga_s2am_ard_3-2-1_50HPJ_2023-06-29_final
2023-07-15 11:56:19	ga_s2am_ard_3-2-1_50JKM_2023-07-15_final
2023-07-22 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2023-07-22_final
2023-09-16 12:04:32	ga_s2am_ard_3-2-1_49KHP_2023-09-16_final
2024-01-11 11:57:04	ga_s2am_ard_3-2-1_50HLH_2024-01-11_final
2024-02-06 12:13:54	ga_s2am_ard_3-2-1_49KGR_2024-02-06_final
2024-02-20 11:55:44	ga_s2am_ard_3-2-1_50JKP_2024-02-20_final
2024-05-06 12:14:59	ga_s2am_ard_3-2-1_49JGM_2024-05-06_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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