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
2015-12-27 12:05:25	ga_s2am_ard_3-2-1_50JLQ_2015-12-27_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JLR_2016-02-02_final.stac-item
2016-02-05 12:04:38	ga_s2am_ard_3-2-1_50JKQ_2016-02-05_final.stac-item
2016-05-05 12:04:47	ga_s2am_ard_3-2-1_50JLQ_2016-05-05_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KHS_2016-08-26_final
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50HMG_2016-11-18_final
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50JLQ_2017-04-07_final.stac-item
2017-04-07 11:56:31	ga_s2am_ard_3-2-1_50HNK_2017-04-07_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_50JLQ_2017-05-30_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49KGQ_2017-07-09_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49KHP_2017-08-01_final.stac-item
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50JLR_2017-08-05_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49KHQ_2017-09-30_final.stac-item
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_50JLR_2017-10-27_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_50JKQ_2017-11-26_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50JLR_2018-01-12_final.stac-item
2018-03-29 12:13:20	ga_s2am_ard_3-2-1_49KHP_2018-03-29_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_50JLR_2018-04-15_final.stac-item
2018-04-15 12:05:11	ga_s2am_ard_3-2-1_50JKR_2018-04-15_final.stac-item
2018-05-08 12:13:24	ga_s2am_ard_3-2-1_49KHP_2018-05-08_final.stac-item
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_49KHP_2018-05-18_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLQ_2018-05-22_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLR_2018-05-22_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KHP_2018-07-27_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50HQH_2018-08-27_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JLR_2018-10-29_final.stac-item
2018-11-15 11:46:48	ga_s2am_ard_3-2-1_50HQH_2018-11-15_final.stac-item
2018-11-24 12:14:24	ga_s2am_ard_3-2-1_49JHN_2018-11-24_final.stac-item
2019-01-13 12:14:17	ga_s2am_ard_3-2-1_49KHP_2019-01-13_final.stac-item
2019-01-17 11:55:23	ga_s2am_ard_3-2-1_50JLQ_2019-01-17_final.stac-item
2019-01-23 12:14:18	ga_s2am_ard_3-2-1_49KHP_2019-01-23_final.stac-item
2019-02-09 12:05:20	ga_s2am_ard_3-2-1_50JLQ_2019-02-09_final.stac-item
2019-03-18 11:54:55	ga_s2am_ard_3-2-1_50JLS_2019-03-18_final.stac-item
2019-06-19 12:05:12	ga_s2am_ard_3-2-1_50JLR_2019-06-19_final.stac-item
2019-06-19 12:05:15	ga_s2am_ard_3-2-1_50JKR_2019-06-19_final.stac-item
2019-07-13 11:47:19	ga_s2am_ard_3-2-1_50HLH_2019-07-13_final.stac-item
2019-08-28 12:04:55	ga_s2am_ard_3-2-1_50JLS_2019-08-28_final.stac-item
2019-10-14 11:55:16	ga_s2am_ard_3-2-1_50JLR_2019-10-14_final.stac-item
2019-11-13 11:55:15	ga_s2am_ard_3-2-1_50JLR_2019-11-13_final.stac-item
2019-12-03 11:55:11	ga_s2am_ard_3-2-1_50JLR_2019-12-03_final.stac-item
2020-02-04 12:04:45	ga_s2am_ard_3-2-1_50JLS_2020-02-04_final.stac-item
2020-03-02 11:55:08	ga_s2am_ard_3-2-1_50JLR_2020-03-02_final.stac-item
2020-04-01 11:54:54	ga_s2am_ard_3-2-1_50JLS_2020-04-01_final.stac-item
2020-06-23 12:04:59	ga_s2am_ard_3-2-1_50JLS_2020-06-23_final.stac-item
2020-09-14 12:14:25	ga_s2am_ard_3-2-1_49KHP_2020-09-14_final.stac-item
2020-10-04 12:14:27	ga_s2am_ard_3-2-1_49KHP_2020-10-04_final.stac-item
2020-10-21 12:05:14	ga_s2am_ard_3-2-1_49JFM_2020-10-21_final.stac-item
2020-10-24 12:14:26	ga_s2am_ard_3-2-1_49KHP_2020-10-24_final.stac-item
2020-11-07 11:55:17	ga_s2am_ard_3-2-1_50JLR_2020-11-07_final.stac-item
2020-11-20 12:05:11	ga_s2am_ard_3-2-1_50JLR_2020-11-20_final.stac-item
2020-11-23 12:14:23	ga_s2am_ard_3-2-1_49KHP_2020-11-23_final.stac-item
2020-12-27 11:55:12	ga_s2am_ard_3-2-1_50JLR_2020-12-27_final.stac-item
2021-03-14 11:47:27	ga_s2am_ard_3-2-1_50HLG_2021-03-14_final
2021-03-17 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2021-03-17_final.stac-item
2021-10-23 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2021-10-23_final.stac-item
2021-11-12 11:55:00	ga_s2am_ard_3-2-1_50JLS_2021-11-12_final.stac-item
2021-11-18 12:14:21	ga_s2am_ard_3-2-1_49KHP_2021-11-18_final.stac-item
2021-12-02 11:54:57	ga_s2am_ard_3-2-1_50JLS_2021-12-02_final.stac-item
2021-12-08 12:14:20	ga_s2am_ard_3-2-1_49KHP_2021-12-08_final.stac-item
2021-12-12 11:54:57	ga_s2am_ard_3-2-1_50JLS_2021-12-12_final.stac-item
2021-12-22 11:54:59	ga_s2am_ard_3-2-1_50JLS_2021-12-22_final.stac-item
2022-01-01 11:54:59	ga_s2am_ard_3-2-1_50JLS_2022-01-01_final.stac-item
2022-01-11 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2022-01-11_final.stac-item
2022-01-14 12:04:55	ga_s2am_ard_3-2-1_50JLS_2022-01-14_final.stac-item
2022-01-17 12:14:22	ga_s2am_ard_3-2-1_49KHP_2022-01-17_final.stac-item
2022-01-24 12:04:54	ga_s2am_ard_3-2-1_50JLS_2022-01-24_final.stac-item
2022-01-27 12:14:21	ga_s2am_ard_3-2-1_49KHP_2022-01-27_final.stac-item
2022-02-23 12:05:10	ga_s2am_ard_3-2-1_50JLR_2022-02-23_final.stac-item
2022-03-05 12:05:07	ga_s2am_ard_3-2-1_50JLR_2022-03-05_final.stac-item
2022-03-22 11:55:01	ga_s2am_ard_3-2-1_50JLS_2022-03-22_final.stac-item
2022-03-22 11:55:16	ga_s2am_ard_3-2-1_50JLR_2022-03-22_final.stac-item
2022-04-14 12:05:06	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
2022-08-12 12:05:20	ga_s2am_ard_3-2-1_50JLR_2022-08-12_final.stac-item
2022-10-21 12:04:54	ga_s2am_ard_3-2-1_50JLS_2022-10-21_final.stac-item
2022-11-03 12:14:25	ga_s2am_ard_3-2-1_49KHP_2022-11-03_final.stac-item
2022-11-13 12:14:24	ga_s2am_ard_3-2-1_49KHP_2022-11-13_final.stac-item
2022-11-27 11:54:57	ga_s2am_ard_3-2-1_50JLS_2022-11-27_final.stac-item
2022-11-30 12:05:08	ga_s2am_ard_3-2-1_50JLR_2022-11-30_final.stac-item
2022-12-13 12:14:21	ga_s2am_ard_3-2-1_49KHP_2022-12-13_final.stac-item
2022-12-17 11:55:12	ga_s2am_ard_3-2-1_50JLR_2022-12-17_final.stac-item
2022-12-27 11:54:56	ga_s2am_ard_3-2-1_50JLS_2022-12-27_final.stac-item
2022-12-30 12:05:07	ga_s2am_ard_3-2-1_50JLR_2022-12-30_final.stac-item
2023-01-06 11:54:57	ga_s2am_ard_3-2-1_50JLS_2023-01-06_final.stac-item
2023-01-06 11:55:11	ga_s2am_ard_3-2-1_50JLR_2023-01-06_final.stac-item
2023-02-05 11:54:57	ga_s2am_ard_3-2-1_50JLS_2023-02-05_final
2023-02-15 11:54:57	ga_s2am_ard_3-2-1_50JLS_2023-02-15_nrt.stac-item
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
2023-02-21 12:14:18	ga_s2am_ard_3-2-1_49KHP_2023-02-21_nrt.stac-item
2023-02-21 12:14:18	ga_s2am_ard_3-2-1_49KHP_2023-02-21_final
2023-03-13 12:14:17	ga_s2am_ard_3-2-1_49KHP_2023-03-13_final
2023-04-19 12:05:07	ga_s2am_ard_3-2-1_50JLR_2023-04-19_final
2023-07-15 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2023-07-15_final
2023-07-28 12:05:13	ga_s2am_ard_3-2-1_50JLR_2023-07-28_final
2023-08-01 11:47:32	ga_s2am_ard_3-2-1_50HLG_2023-08-01_final
2023-09-23 11:55:14	ga_s2am_ard_3-2-1_50JLR_2023-09-23_final
2023-09-27 11:37:28	ga_s2am_ard_3-2-1_50HNG_2023-09-27_final
2023-12-05 12:05:01	ga_s2am_ard_3-2-1_50JLR_2023-12-05_final
2023-12-19 11:46:49	ga_s2am_ard_3-2-1_50HQH_2023-12-19_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