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_50HPH_2015-10-22_final.stac-item
2015-10-22 11:46:57	ga_s2am_ard_3-2-1_50HMG_2015-10-22_final
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49JGM_2015-10-28_final.stac-item
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_49JGM_2015-12-07_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_50HPJ_2016-02-06_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49KHS_2016-05-15_final
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JLR_2016-05-22_final.stac-item
2016-09-26 11:40:08	ga_s2am_ard_3-2-1_50HPG_2016-09-26_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_50HPK_2016-10-03_final.stac-item
2016-12-28 11:55:47	ga_s2am_ard_3-2-1_50HNK_2016-12-28_final.stac-item
2017-01-13 12:14:33	ga_s2am_ard_3-2-1_49JGM_2017-01-13_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HLH_2017-01-14_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HMH_2017-02-03_final.stac-item
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49KHR_2017-02-12_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50HNH_2017-03-25_final.stac-item
2017-05-23 12:13:46	ga_s2am_ard_3-2-1_49KGR_2017-05-23_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_50JLM_2017-07-09_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_50JKP_2017-07-29_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_49JGJ_2017-09-07_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49JGM_2017-09-30_final.stac-item
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_50HPK_2017-11-27_final.stac-item
2017-12-26 12:04:47	ga_s2am_ard_3-2-1_49JGL_2017-12-26_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50HLH_2018-01-19_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_49JGK_2018-01-25_final.stac-item
2018-02-08 11:45:59	ga_s2am_ard_3-2-1_50HNJ_2018-02-08_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HLH_2018-02-18_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50HLH_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JLL_2018-10-19_final.stac-item
2018-11-21 12:05:48	ga_s2am_ard_3-2-1_50JKN_2018-11-21_final.stac-item
2018-11-25 11:46:59	ga_s2am_ard_3-2-1_50HNH_2018-11-25_final.stac-item
2019-02-20 11:36:59	ga_s2am_ard_3-2-1_50HQH_2019-02-20_final.stac-item
2019-03-22 11:36:50	ga_s2am_ard_3-2-1_50HPJ_2019-03-22_final.stac-item
2019-03-31 12:05:41	ga_s2am_ard_3-2-1_50JKP_2019-03-31_final.stac-item
2019-04-03 12:15:10	ga_s2am_ard_3-2-1_49JGL_2019-04-03_final.stac-item
2019-04-04 11:46:53	ga_s2am_ard_3-2-1_50HNJ_2019-04-04_final.stac-item
2019-04-14 11:46:32	ga_s2am_ard_3-2-1_50HQK_2019-04-14_final.stac-item
2019-06-13 11:46:40	ga_s2am_ard_3-2-1_50HNK_2019-06-13_final.stac-item
2019-07-06 11:56:04	ga_s2am_ard_3-2-1_50JKN_2019-07-06_final.stac-item
2019-07-20 11:36:39	ga_s2am_ard_3-2-1_50HQK_2019-07-20_final.stac-item
2019-09-27 12:05:02	ga_s2am_ard_3-2-1_49JGM_2019-09-27_final.stac-item
2019-10-24 11:57:12	ga_s2am_ard_3-2-1_50HLH_2019-10-24_final.stac-item
2019-11-06 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-11-06_final.stac-item
2019-11-23 11:56:00	ga_s2am_ard_3-2-1_50JKN_2019-11-23_final.stac-item
2019-12-03 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2019-12-03_final.stac-item
2019-12-13 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2019-12-13_final.stac-item
2020-01-08 12:13:49	ga_s2am_ard_3-2-1_49KHR_2020-01-08_final.stac-item
2020-02-01 11:56:41	ga_s2am_ard_3-2-1_50HLJ_2020-02-01_final.stac-item
2020-02-08 11:47:06	ga_s2am_ard_3-2-1_50HLH_2020-02-08_final.stac-item
2020-02-15 11:36:31	ga_s2am_ard_3-2-1_50HPK_2020-02-15_final.stac-item
2020-02-18 11:46:30	ga_s2am_ard_3-2-1_50HNK_2020-02-18_final.stac-item
2020-02-25 11:36:33	ga_s2am_ard_3-2-1_50HPK_2020-02-25_final.stac-item
2020-05-11 11:56:30	ga_s2am_ard_3-2-1_50JLL_2020-05-11_final.stac-item
2020-05-25 11:37:12	ga_s2am_ard_3-2-1_50HPH_2020-05-25_final.stac-item
2020-05-28 11:46:40	ga_s2am_ard_3-2-1_50HPK_2020-05-28_final.stac-item
2020-06-06 12:15:06	ga_s2am_ard_3-2-1_49JFM_2020-06-06_final.stac-item
2020-06-10 11:56:32	ga_s2am_ard_3-2-1_50JLL_2020-06-10_final.stac-item
2020-06-30 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-06-30_final.stac-item
2020-07-06 12:14:46	ga_s2am_ard_3-2-1_49JGN_2020-07-06_final.stac-item
2020-07-14 11:37:11	ga_s2am_ard_3-2-1_50HPH_2020-07-14_final.stac-item
2020-07-26 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-07-26_final.stac-item
2020-08-23 11:37:08	ga_s2am_ard_3-2-1_50HQH_2020-08-23_final.stac-item
2020-10-31 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-10-31_final.stac-item
2020-12-10 12:05:11	ga_s2am_ard_3-2-1_49JGL_2020-12-10_final.stac-item
2020-12-24 11:47:09	ga_s2am_ard_3-2-1_50HMH_2020-12-24_final.stac-item
2021-01-03 11:47:14	ga_s2am_ard_3-2-1_50HLH_2021-01-03_final.stac-item
2021-01-23 11:47:10	ga_s2am_ard_3-2-1_50HMH_2021-01-23_final.stac-item
2021-01-29 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2021-01-29_final.stac-item
2021-01-30 11:37:21	ga_s2am_ard_3-2-1_50HPG_2021-01-30_final
2021-04-23 11:46:58	ga_s2am_ard_3-2-1_50HPH_2021-04-23_final.stac-item
2021-06-22 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-06-22_final.stac-item
2021-08-10 12:14:59	ga_s2am_ard_3-2-1_49JGM_2021-08-10_final.stac-item
2021-10-07 11:37:26	ga_s2am_ard_3-2-1_50HPG_2021-10-07_final
2021-10-30 11:47:11	ga_s2am_ard_3-2-1_50HNH_2021-10-30_final.stac-item
2021-11-22 11:57:09	ga_s2am_ard_3-2-1_50HLH_2021-11-22_final.stac-item
2021-11-25 12:05:41	ga_s2am_ard_3-2-1_50JKP_2021-11-25_final.stac-item
2021-12-08 12:14:55	ga_s2am_ard_3-2-1_49JGM_2021-12-08_final.stac-item
2021-12-22 11:57:07	ga_s2am_ard_3-2-1_50HMH_2021-12-22_final.stac-item
2022-05-07 12:15:00	ga_s2am_ard_3-2-1_49JGM_2022-05-07_final.stac-item
2022-05-17 12:15:16	ga_s2am_ard_3-2-1_49JGL_2022-05-17_final.stac-item
2022-05-31 11:57:17	ga_s2am_ard_3-2-1_50HLH_2022-05-31_final.stac-item
2022-06-03 12:05:49	ga_s2am_ard_3-2-1_50JKP_2022-06-03_final.stac-item
2022-06-13 12:05:18	ga_s2am_ard_3-2-1_49JFM_2022-06-13_final.stac-item
2022-07-27 11:47:12	ga_s2am_ard_3-2-1_50HPH_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 12:15:15	ga_s2am_ard_3-2-1_49JGL_2022-10-14_final.stac-item
2022-11-01 11:36:38	ga_s2am_ard_3-2-1_50HQK_2022-11-01_final.stac-item
2022-11-20 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2022-11-20_final.stac-item
2023-02-28 12:05:20	ga_s2am_ard_3-2-1_50JLQ_2023-02-28_final
2023-02-28 12:05:49	ga_s2am_ard_3-2-1_50JLN_2023-02-28_final
2023-04-06 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2023-04-06_final
2023-04-09 12:05:29	ga_s2am_ard_3-2-1_49JGK_2023-04-09_final
2023-04-20 11:37:15	ga_s2am_ard_3-2-1_50HQG_2023-04-20_final
2023-06-01 12:14:31	ga_s2am_ard_3-2-1_49KGP_2023-06-01_final
2023-06-02 11:46:38	ga_s2am_ard_3-2-1_50HPK_2023-06-02_final
2023-10-13 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2023-10-13_final
2023-12-02 11:56:58	ga_s2am_ard_3-2-1_50HMH_2023-12-02_final
2024-01-08 11:47:10	ga_s2am_ard_3-2-1_50HLH_2024-01-08_final
2024-01-27 12:15:05	ga_s2am_ard_3-2-1_49JGL_2024-01-27_final
2024-02-10 11:55:56	ga_s2am_ard_3-2-1_50JKN_2024-02-10_final
2024-03-04 12:05:41	ga_s2am_ard_3-2-1_50JKP_2024-03-04_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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