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
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KHP_2015-11-30_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JLQ_2015-12-04_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50JLR_2016-01-16_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50JKR_2016-04-15_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_49JHN_2016-07-24_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_50HQG_2016-09-13_final
2016-11-04 12:13:19	ga_s2am_ard_3-2-1_49KHQ_2016-11-04_final.stac-item
2016-11-08 11:56:13	ga_s2am_ard_3-2-1_50HMJ_2016-11-08_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_50JKQ_2016-12-01_final.stac-item
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49KHQ_2016-12-04_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49KHQ_2016-12-24_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_50JKR_2017-01-20_final.stac-item
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49KHQ_2017-02-22_final.stac-item
2017-03-01 12:04:35	ga_s2am_ard_3-2-1_50JLQ_2017-03-01_final.stac-item
2017-03-18 11:51:11	ga_s2am_ard_3-2-1_50JLR_2017-03-18_final.stac-item
2017-03-28 11:56:02	ga_s2am_ard_3-2-1_50HMJ_2017-03-28_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_50JLQ_2017-03-31_final.stac-item
2017-06-09 12:03:49	ga_s2am_ard_3-2-1_49KHQ_2017-06-09_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JHM_2017-06-29_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_50JKS_2017-06-29_final.stac-item
2017-08-28 12:03:48	ga_s2am_ard_3-2-1_49KHQ_2017-08-28_final.stac-item
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50JLR_2017-10-04_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_50JLQ_2017-11-06_final.stac-item
2017-12-26 12:04:36	ga_s2am_ard_3-2-1_50JLS_2017-12-26_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_50JKR_2018-01-25_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50JLS_2018-02-24_final.stac-item
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50JLS_2018-04-02_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JKR_2018-04-05_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JLQ_2018-04-12_final.stac-item
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_50JLQ_2018-05-05_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JLR_2018-07-21_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50JLR_2018-08-20_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_50JLS_2018-10-02_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JLQ_2018-10-29_final.stac-item
2018-11-24 12:14:01	ga_s2am_ard_3-2-1_49KHQ_2018-11-24_final.stac-item
2018-12-18 11:54:49	ga_s2am_ard_3-2-1_50JLS_2018-12-18_final.stac-item
2019-05-30 12:05:25	ga_s2am_ard_3-2-1_50JLQ_2019-05-30_final.stac-item
2019-07-16 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2019-07-16_final.stac-item
2019-07-26 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2019-07-26_final.stac-item
2019-07-29 12:04:58	ga_s2am_ard_3-2-1_50JLS_2019-07-29_final.stac-item
2019-09-07 12:04:53	ga_s2am_ard_3-2-1_50JLS_2019-09-07_final.stac-item
2019-09-27 12:05:09	ga_s2am_ard_3-2-1_50JLR_2019-09-27_final.stac-item
2020-02-27 12:14:16	ga_s2am_ard_3-2-1_49KHP_2020-02-27_final.stac-item
2020-03-25 12:04:50	ga_s2am_ard_3-2-1_50JLS_2020-03-25_final.stac-item
2020-04-11 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2020-04-11_final.stac-item
2020-04-21 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2020-04-21_final.stac-item
2020-05-01 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2020-05-01_final.stac-item
2020-05-31 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2020-05-31_final.stac-item
2020-06-06 12:14:15	ga_s2am_ard_3-2-1_49KHQ_2020-06-06_final.stac-item
2020-06-13 12:05:29	ga_s2am_ard_3-2-1_50JLQ_2020-06-13_final.stac-item
2020-07-20 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2020-07-20_final.stac-item
2020-10-01 12:05:14	ga_s2am_ard_3-2-1_49JFM_2020-10-01_final.stac-item
2020-10-04 12:14:24	ga_s2am_ard_3-2-1_49KGP_2020-10-04_final.stac-item
2020-11-20 12:04:56	ga_s2am_ard_3-2-1_50JLS_2020-11-20_final.stac-item
2020-11-27 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2020-11-27_final.stac-item
2021-01-06 11:54:58	ga_s2am_ard_3-2-1_50JLS_2021-01-06_final.stac-item
2021-01-23 11:46:54	ga_s2am_ard_3-2-1_50HQH_2021-01-23_final.stac-item
2021-01-23 11:47:28	ga_s2am_ard_3-2-1_50HLG_2021-01-23_final
2021-02-12 11:46:52	ga_s2am_ard_3-2-1_50HQH_2021-02-12_final.stac-item
2021-02-15 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2021-02-15_final.stac-item
2021-03-23 12:13:38	ga_s2am_ard_3-2-1_49KHS_2021-03-23_final
2021-04-22 12:13:35	ga_s2am_ard_3-2-1_49KHS_2021-04-22_final
2021-05-03 11:47:25	ga_s2am_ard_3-2-1_50HLG_2021-05-03_final
2021-05-09 12:05:07	ga_s2am_ard_3-2-1_50JLR_2021-05-09_final.stac-item
2021-07-18 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-07-18_final
2021-07-31 12:13:43	ga_s2am_ard_3-2-1_49KHS_2021-07-31_final
2021-08-27 12:03:46	ga_s2am_ard_3-2-1_49KHS_2021-08-27_final
2021-08-30 12:14:10	ga_s2am_ard_3-2-1_49KHQ_2021-08-30_final.stac-item
2021-10-30 11:46:58	ga_s2am_ard_3-2-1_50HQH_2021-10-30_final.stac-item
2021-11-15 12:05:13	ga_s2am_ard_3-2-1_50JKR_2021-11-15_final.stac-item
2021-12-02 11:55:12	ga_s2am_ard_3-2-1_50JLR_2021-12-02_final.stac-item
2021-12-09 11:47:25	ga_s2am_ard_3-2-1_50HLG_2021-12-09_final
2021-12-15 12:05:23	ga_s2am_ard_3-2-1_50JLQ_2021-12-15_final.stac-item
2021-12-29 11:46:55	ga_s2am_ard_3-2-1_50HQH_2021-12-29_final.stac-item
2022-02-13 12:05:08	ga_s2am_ard_3-2-1_50JLR_2022-02-13_final.stac-item
2022-02-17 11:46:54	ga_s2am_ard_3-2-1_50HQH_2022-02-17_final.stac-item
2022-06-26 12:14:33	ga_s2am_ard_3-2-1_49KHP_2022-06-26_final.stac-item
2022-07-20 11:55:09	ga_s2am_ard_3-2-1_50JLS_2022-07-20_final.stac-item
2022-08-22 12:05:21	ga_s2am_ard_3-2-1_50JLR_2022-08-22_final.stac-item
2022-09-24 12:14:16	ga_s2am_ard_3-2-1_49KHQ_2022-09-24_final.stac-item
2022-10-21 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2022-10-21_final.stac-item
2022-10-31 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2022-10-31_final.stac-item
2022-12-17 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2022-12-17_final.stac-item
2023-01-03 11:47:26	ga_s2am_ard_3-2-1_50HLG_2023-01-03_final
2023-02-08 12:05:07	ga_s2am_ard_3-2-1_49JFM_2023-02-08_final
2023-04-16 11:55:12	ga_s2am_ard_3-2-1_50JLR_2023-04-16_final
2023-04-29 12:05:23	ga_s2am_ard_3-2-1_50JLQ_2023-04-29_final
2023-05-19 12:05:25	ga_s2am_ard_3-2-1_50JLQ_2023-05-19_final
2023-05-20 11:37:29	ga_s2am_ard_3-2-1_50HNG_2023-05-20_final
2023-06-15 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2023-06-15_final
2023-08-04 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2023-08-04_final
2023-09-06 12:05:14	ga_s2am_ard_3-2-1_49JFM_2023-09-06_final
2023-10-03 11:55:14	ga_s2am_ard_3-2-1_50JLR_2023-10-03_final
2023-10-09 12:13:39	ga_s2am_ard_3-2-1_49KHS_2023-10-09_final
2023-10-26 12:05:12	ga_s2am_ard_3-2-1_50JKR_2023-10-26_final
2023-11-12 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2023-11-12_final
2023-12-15 12:05:08	ga_s2am_ard_3-2-1_50JKR_2023-12-15_final
2024-01-04 12:05:05	ga_s2am_ard_3-2-1_50JLR_2024-01-04_final
2024-01-28 11:46:48	ga_s2am_ard_3-2-1_50HQH_2024-01-28_final
2024-02-26 12:13:39	ga_s2am_ard_3-2-1_49KHS_2024-02-26_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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