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
2015-12-30 12:16:05	ga_s2am_ard_3-2-1_49KHP_2015-12-30_final.stac-item
2016-01-09 12:16:04	ga_s2am_ard_3-2-1_49KHP_2016-01-09_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50JLM_2016-01-16_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50JLQ_2016-02-15_final.stac-item
2016-03-06 12:04:37	ga_s2am_ard_3-2-1_50JLQ_2016-03-06_final.stac-item
2016-05-05 12:04:47	ga_s2am_ard_3-2-1_50JLR_2016-05-05_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50HNG_2016-05-16_final
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50JLR_2016-08-10_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JLR_2016-08-30_final.stac-item
2016-09-22 12:04:37	ga_s2am_ard_3-2-1_50JLQ_2016-09-22_final.stac-item
2016-10-12 12:04:37	ga_s2am_ard_3-2-1_50JLQ_2016-10-12_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49KHP_2016-10-25_final.stac-item
2016-11-08 11:56:13	ga_s2am_ard_3-2-1_50HMJ_2016-11-08_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50JKR_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50JLQ_2016-11-21_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50JLQ_2016-11-28_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50HLG_2016-12-08_final
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49KHQ_2016-12-24_final.stac-item
2017-04-03 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2017-04-03_final.stac-item
2017-04-27 11:56:35	ga_s2am_ard_3-2-1_50HMK_2017-04-27_final.stac-item
2017-06-09 12:04:43	ga_s2am_ard_3-2-1_49JHN_2017-06-09_final.stac-item
2017-06-09 12:04:43	ga_s2am_ard_3-2-1_50JKQ_2017-06-09_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50JKR_2017-06-19_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JLR_2017-09-17_final.stac-item
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_50JKR_2017-10-27_final.stac-item
2017-10-30 12:13:43	ga_s2am_ard_3-2-1_49KHQ_2017-10-30_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_50JKR_2017-11-06_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_50JLQ_2018-02-14_final.stac-item
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_50JLR_2018-03-16_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JLR_2018-04-05_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLR_2018-05-22_final.stac-item
2018-06-27 12:13:22	ga_s2am_ard_3-2-1_49KHP_2018-06-27_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49KHP_2018-07-17_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JLR_2018-08-23_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JLR_2018-09-02_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KHP_2018-10-15_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49KHP_2018-11-04_final.stac-item
2018-11-24 12:14:01	ga_s2am_ard_3-2-1_49KHQ_2018-11-24_final.stac-item
2019-01-10 12:05:07	ga_s2am_ard_3-2-1_50JKR_2019-01-10_final.stac-item
2019-02-06 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2019-02-06_final.stac-item
2019-02-09 12:05:05	ga_s2am_ard_3-2-1_50JLR_2019-02-09_final.stac-item
2019-06-19 12:05:15	ga_s2am_ard_3-2-1_50JKR_2019-06-19_final.stac-item
2019-08-01 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2019-08-01_final.stac-item
2019-08-18 12:05:11	ga_s2am_ard_3-2-1_50JLR_2019-08-18_final.stac-item
2019-08-28 12:05:09	ga_s2am_ard_3-2-1_50JLR_2019-08-28_final.stac-item
2019-09-17 12:05:07	ga_s2am_ard_3-2-1_50JLR_2019-09-17_final.stac-item
2019-10-14 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2019-10-14_final.stac-item
2020-02-01 11:55:20	ga_s2am_ard_3-2-1_50JLQ_2020-02-01_final.stac-item
2020-02-17 12:14:15	ga_s2am_ard_3-2-1_49KHP_2020-02-17_final.stac-item
2020-04-08 11:46:51	ga_s2am_ard_3-2-1_50HQH_2020-04-08_final.stac-item
2020-06-10 11:55:34	ga_s2am_ard_3-2-1_50JLQ_2020-06-10_final.stac-item
2020-06-20 11:55:19	ga_s2am_ard_3-2-1_50JLR_2020-06-20_final.stac-item
2020-07-20 11:55:18	ga_s2am_ard_3-2-1_50JLR_2020-07-20_final.stac-item
2020-07-30 11:55:18	ga_s2am_ard_3-2-1_50JLR_2020-07-30_final.stac-item
2020-08-25 12:14:26	ga_s2am_ard_3-2-1_49KHP_2020-08-25_final.stac-item
2020-09-18 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2020-09-18_final.stac-item
2020-10-01 12:05:17	ga_s2am_ard_3-2-1_50JKR_2020-10-01_final.stac-item
2020-10-11 12:05:18	ga_s2am_ard_3-2-1_50JKR_2020-10-11_final.stac-item
2020-10-21 12:05:14	ga_s2am_ard_3-2-1_50JLR_2020-10-21_final.stac-item
2020-11-07 11:55:17	ga_s2am_ard_3-2-1_50JLR_2020-11-07_final.stac-item
2020-12-20 12:05:06	ga_s2am_ard_3-2-1_50JLR_2020-12-20_final.stac-item
2020-12-30 12:05:08	ga_s2am_ard_3-2-1_50JLR_2020-12-30_final.stac-item
2021-01-06 11:55:13	ga_s2am_ard_3-2-1_50JLR_2021-01-06_final.stac-item
2021-01-30 11:37:26	ga_s2am_ard_3-2-1_50HNG_2021-01-30_final
2021-02-02 11:46:53	ga_s2am_ard_3-2-1_50HQH_2021-02-02_final.stac-item
2021-03-17 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2021-03-17_final.stac-item
2021-03-23 12:13:38	ga_s2am_ard_3-2-1_49KHS_2021-03-23_final
2021-04-23 11:47:23	ga_s2am_ard_3-2-1_50HLG_2021-04-23_final
2021-10-16 12:05:14	ga_s2am_ard_3-2-1_49JFM_2021-10-16_final.stac-item
2021-11-25 12:05:08	ga_s2am_ard_3-2-1_50JLR_2021-11-25_final.stac-item
2021-12-25 12:05:09	ga_s2am_ard_3-2-1_50JLR_2021-12-25_final.stac-item
2022-01-31 11:55:13	ga_s2am_ard_3-2-1_50JLR_2022-01-31_final.stac-item
2022-02-20 11:55:14	ga_s2am_ard_3-2-1_50JLR_2022-02-20_final.stac-item
2022-04-14 12:05:12	ga_s2am_ard_3-2-1_50JLR_2022-04-14_final.stac-item
2022-04-24 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2022-04-24_final.stac-item
2022-06-06 12:14:16	ga_s2am_ard_3-2-1_49KHQ_2022-06-06_final.stac-item
2022-06-30 11:55:40	ga_s2am_ard_3-2-1_50JLQ_2022-06-30_final.stac-item
2022-07-16 12:14:33	ga_s2am_ard_3-2-1_49KHP_2022-07-16_final.stac-item
2022-08-25 12:14:21	ga_s2am_ard_3-2-1_49KHQ_2022-08-25_final.stac-item
2022-09-01 12:06:16	ga_s2am_ard_3-2-1_50JLM_2022-09-01_final.stac-item
2022-09-11 12:05:22	ga_s2am_ard_3-2-1_50JKR_2022-09-11_final.stac-item
2022-09-14 12:14:31	ga_s2am_ard_3-2-1_49KHP_2022-09-14_final.stac-item
2022-10-14 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2022-10-14_final.stac-item
2022-10-18 11:55:15	ga_s2am_ard_3-2-1_50JLR_2022-10-18_final.stac-item
2023-01-13 11:46:51	ga_s2am_ard_3-2-1_50HQH_2023-01-13_final.stac-item
2023-02-05 11:55:11	ga_s2am_ard_3-2-1_50JLR_2023-02-05_final
2023-02-15 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2023-02-15_nrt.stac-item
2023-02-15 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2023-02-15_final
2023-04-29 12:05:08	ga_s2am_ard_3-2-1_50JLR_2023-04-29_final
2023-05-03 11:46:53	ga_s2am_ard_3-2-1_50HQH_2023-05-03_final
2023-05-23 11:47:17	ga_s2am_ard_3-2-1_50HLH_2023-05-23_final
2023-06-28 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2023-06-28_final
2023-07-28 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-07-28_final
2023-08-14 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2023-08-14_final
2023-08-31 11:46:58	ga_s2am_ard_3-2-1_50HQH_2023-08-31_final
2023-09-16 12:05:15	ga_s2am_ard_3-2-1_50JKR_2023-09-16_final
2023-10-23 11:55:13	ga_s2am_ard_3-2-1_50JLR_2023-10-23_final
2023-11-19 11:46:51	ga_s2am_ard_3-2-1_50HQH_2023-11-19_final
2024-01-04 12:05:05	ga_s2am_ard_3-2-1_50JLR_2024-01-04_final
2024-02-17 11:46:51	ga_s2am_ard_3-2-1_50HQH_2024-02-17_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

All years