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_49JGM_2015-10-28_final.stac-item
2015-11-30 12:14:12	ga_s2am_ard_3-2-1_49KHP_2015-11-30_final.stac-item
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_49JHM_2015-12-07_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_49JGL_2015-12-17_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JHN_2016-01-26_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49KHP_2016-05-15_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50HQJ_2016-05-16_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_49JHM_2016-09-12_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HNK_2016-11-15_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49KHS_2016-12-21_final
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50HLJ_2017-01-07_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49JGM_2017-01-20_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49KHR_2017-01-20_final.stac-item
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49JHN_2017-03-14_final.stac-item
2017-03-24 12:13:37	ga_s2am_ard_3-2-1_49KHR_2017-03-24_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_49JGK_2017-03-31_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_49JGL_2017-03-31_final.stac-item
2017-04-03 12:14:19	ga_s2am_ard_3-2-1_49JGM_2017-04-03_final.stac-item
2017-05-23 12:14:44	ga_s2am_ard_3-2-1_49JGM_2017-05-23_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49JFM_2017-06-02_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JGK_2017-06-29_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49KGQ_2017-09-30_final.stac-item
2018-01-15 12:04:34	ga_s2am_ard_3-2-1_49JHN_2018-01-15_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HNH_2018-02-18_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49KHQ_2018-04-28_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50HLJ_2018-05-02_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HLH_2018-09-19_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HLK_2018-09-19_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49JGL_2018-10-02_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HMH_2018-10-16_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HNJ_2018-10-16_final.stac-item
2018-10-26 11:46:33	ga_s2am_ard_3-2-1_50HLH_2018-10-26_final.stac-item
2018-11-15 11:46:46	ga_s2am_ard_3-2-1_50HNJ_2018-11-15_final.stac-item
2019-01-14 11:46:33	ga_s2am_ard_3-2-1_50HNK_2019-01-14_final.stac-item
2019-01-23 12:14:18	ga_s2am_ard_3-2-1_49KHP_2019-01-23_final.stac-item
2019-02-13 11:47:02	ga_s2am_ard_3-2-1_50HNH_2019-02-13_final.stac-item
2019-05-03 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2019-05-03_final.stac-item
2019-09-08 11:36:37	ga_s2am_ard_3-2-1_50HPK_2019-09-08_final.stac-item
2019-09-27 12:04:58	ga_s2am_ard_3-2-1_49JHM_2019-09-27_final.stac-item
2019-09-27 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2019-09-27_final.stac-item
2019-10-01 11:46:53	ga_s2am_ard_3-2-1_50HNJ_2019-10-01_final.stac-item
2019-10-14 11:56:43	ga_s2am_ard_3-2-1_50HLK_2019-10-14_final.stac-item
2019-10-31 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-10-31_final.stac-item
2019-11-30 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2019-11-30_final.stac-item
2019-12-03 11:56:35	ga_s2am_ard_3-2-1_50HMK_2019-12-03_final.stac-item
2020-01-29 11:46:33	ga_s2am_ard_3-2-1_50HMK_2020-01-29_final.stac-item
2020-02-01 11:56:32	ga_s2am_ard_3-2-1_50HLK_2020-02-01_final.stac-item
2020-02-18 11:46:37	ga_s2am_ard_3-2-1_50HNJ_2020-02-18_final.stac-item
2020-04-04 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2020-04-04_final.stac-item
2020-04-11 11:57:08	ga_s2am_ard_3-2-1_50HLH_2020-04-11_final.stac-item
2020-05-27 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-05-27_final.stac-item
2020-09-18 11:57:14	ga_s2am_ard_3-2-1_50HLH_2020-09-18_final.stac-item
2020-10-08 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-10-08_final.stac-item
2020-10-11 12:05:02	ga_s2am_ard_3-2-1_49JHM_2020-10-11_final.stac-item
2020-10-11 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-10-11_final.stac-item
2020-10-25 11:47:01	ga_s2am_ard_3-2-1_50HMJ_2020-10-25_final.stac-item
2020-12-17 11:56:34	ga_s2am_ard_3-2-1_50HMK_2020-12-17_final.stac-item
2020-12-27 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2020-12-27_final.stac-item
2021-01-03 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2021-01-03_final.stac-item
2021-01-06 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2021-01-06_final.stac-item
2021-02-02 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2021-02-02_final.stac-item
2021-02-22 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2021-02-22_final.stac-item
2021-04-12 12:14:22	ga_s2am_ard_3-2-1_49KGP_2021-04-12_final.stac-item
2021-06-18 12:05:29	ga_s2am_ard_3-2-1_49JGK_2021-06-18_final.stac-item
2021-08-11 11:46:56	ga_s2am_ard_3-2-1_50HQH_2021-08-11_final.stac-item
2021-09-03 11:56:37	ga_s2am_ard_3-2-1_50HMK_2021-09-03_final.stac-item
2021-09-26 12:05:00	ga_s2am_ard_3-2-1_49JHM_2021-09-26_final.stac-item
2021-11-16 11:36:39	ga_s2am_ard_3-2-1_50HPK_2021-11-16_final.stac-item
2021-12-19 11:47:07	ga_s2am_ard_3-2-1_50HNH_2021-12-19_final.stac-item
2022-01-18 11:46:38	ga_s2am_ard_3-2-1_50HNK_2022-01-18_final.stac-item
2022-01-18 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2022-01-18_final.stac-item
2022-02-07 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2022-02-07_final.stac-item
2022-02-17 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2022-02-17_final.stac-item
2022-04-11 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2022-04-11_final.stac-item
2022-09-01 12:05:09	ga_s2am_ard_3-2-1_49JHM_2022-09-01_final.stac-item
2022-09-01 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-09-01_final.stac-item
2022-09-11 12:05:07	ga_s2am_ard_3-2-1_49JHM_2022-09-11_final.stac-item
2022-11-14 11:46:55	ga_s2am_ard_3-2-1_50HNJ_2022-11-14_final.stac-item
2022-11-17 11:56:57	ga_s2am_ard_3-2-1_50HLJ_2022-11-17_final.stac-item
2022-11-27 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2022-11-27_final.stac-item
2022-12-24 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2022-12-24_final.stac-item
2022-12-27 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2022-12-27_final.stac-item
2023-02-22 11:46:35	ga_s2am_ard_3-2-1_50HNK_2023-02-22_nrt.stac-item
2023-02-22 11:46:35	ga_s2am_ard_3-2-1_50HNK_2023-02-22_final
2023-03-14 11:47:11	ga_s2am_ard_3-2-1_50HLH_2023-03-14_final
2023-04-09 12:05:29	ga_s2am_ard_3-2-1_49JGK_2023-04-09_final
2023-04-19 12:03:43	ga_s2am_ard_3-2-1_49KHS_2023-04-19_final
2023-04-26 11:57:09	ga_s2am_ard_3-2-1_50HLH_2023-04-26_final
2023-05-03 11:46:53	ga_s2am_ard_3-2-1_50HQH_2023-05-03_final
2023-05-23 11:46:37	ga_s2am_ard_3-2-1_50HPK_2023-05-23_final
2023-06-22 11:46:37	ga_s2am_ard_3-2-1_50HPK_2023-06-22_final
2023-07-05 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2023-07-05_final
2023-08-31 11:46:39	ga_s2am_ard_3-2-1_50HPK_2023-08-31_final
2023-09-03 11:57:27	ga_s2am_ard_3-2-1_50HLG_2023-09-03_final
2023-09-19 12:14:24	ga_s2am_ard_3-2-1_49KHP_2023-09-19_final
2023-09-20 11:46:40	ga_s2am_ard_3-2-1_50HNK_2023-09-20_final
2023-09-29 12:14:44	ga_s2am_ard_3-2-1_49JGN_2023-09-29_final
2023-11-19 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2023-11-19_final
2023-12-22 11:57:05	ga_s2am_ard_3-2-1_50HLH_2023-12-22_final
2024-01-08 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2024-01-08_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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