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
2015-10-03 11:13:11	ga_s2am_ard_3-2-1_51KZP_2015-10-03_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JMR_2015-12-17_final.stac-item
2015-12-22 11:14:14	ga_s2am_ard_3-2-1_51JZN_2015-12-22_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_50JLQ_2016-01-26_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_51HUD_2016-02-06_final.stac-item
2016-02-20 11:12:10	ga_s2am_ard_3-2-1_51JZN_2016-02-20_final.stac-item
2016-05-13 11:26:15	ga_s2am_ard_3-2-1_51HWE_2016-05-13_final.stac-item
2016-07-27 12:13:48	ga_s2am_ard_3-2-1_49KGR_2016-07-27_final.stac-item
2016-12-09 11:21:01	ga_s2am_ard_3-2-1_51HXE_2016-12-09_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_51JUM_2016-12-12_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51JTG_2016-12-15_final.stac-item
2016-12-16 11:08:59	ga_s2am_ard_3-2-1_51JXF_2016-12-16_final.stac-item
2017-02-17 11:23:12	ga_s2am_ard_3-2-1_51JXG_2017-02-17_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50KNA_2017-06-19_final.stac-item
2017-07-07 11:26:09	ga_s2am_ard_3-2-1_51JXF_2017-07-07_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_50KMA_2017-09-17_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KHP_2017-11-19_final.stac-item
2019-01-25 11:15:36	ga_s2am_ard_3-2-1_51JYH_2019-01-25_final.stac-item
2019-01-28 11:25:28	ga_s2am_ard_3-2-1_51JVJ_2019-01-28_final.stac-item
2019-01-28 11:26:02	ga_s2am_ard_3-2-1_51JUG_2019-01-28_final.stac-item
2019-01-30 12:04:45	ga_s2am_ard_3-2-1_50JMS_2019-01-30_final.stac-item
2019-02-22 12:14:15	ga_s2am_ard_3-2-1_50KKU_2019-02-22_final.stac-item
2019-02-26 11:55:11	ga_s2am_ard_3-2-1_50JPQ_2019-02-26_final.stac-item
2019-02-27 11:26:33	ga_s2am_ard_3-2-1_51HVE_2019-02-27_final.stac-item
2019-03-22 11:36:32	ga_s2am_ard_3-2-1_51HVD_2019-03-22_final.stac-item
2019-05-14 11:46:57	ga_s2am_ard_3-2-1_50HQH_2019-05-14_final.stac-item
2019-08-01 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2019-08-01_final.stac-item
2019-11-26 12:03:44	ga_s2am_ard_3-2-1_50KNA_2019-11-26_final.stac-item
2019-12-04 11:25:51	ga_s2am_ard_3-2-1_51JXG_2019-12-04_final.stac-item
2020-01-25 12:03:38	ga_s2am_ard_3-2-1_50KNA_2020-01-25_final.stac-item
2020-02-29 11:15:38	ga_s2am_ard_3-2-1_51JXH_2020-02-29_final.stac-item
2020-07-21 11:22:21	ga_s2am_ard_3-2-1_51KZB_2020-07-21_final.stac-item
2020-07-30 11:53:56	ga_s2am_ard_3-2-1_50KPA_2020-07-30_final.stac-item
2020-07-30 11:54:08	ga_s2am_ard_3-2-1_50KNA_2020-07-30_final.stac-item
2020-08-02 12:03:32	ga_s2am_ard_3-2-1_50KLC_2020-08-02_final.stac-item
2020-08-02 12:03:47	ga_s2am_ard_3-2-1_50KNA_2020-08-02_final.stac-item
2020-08-29 11:53:41	ga_s2am_ard_3-2-1_50KPB_2020-08-29_final.stac-item
2020-09-01 12:03:57	ga_s2am_ard_3-2-1_50KMA_2020-09-01_final.stac-item
2020-09-08 11:52:38	ga_s2am_ard_3-2-1_50KQF_2020-09-08_final
2020-09-18 11:53:55	ga_s2am_ard_3-2-1_50KPA_2020-09-18_final.stac-item
2020-09-18 11:55:20	ga_s2am_ard_3-2-1_50JPQ_2020-09-18_final.stac-item
2020-09-19 11:24:49	ga_s2am_ard_3-2-1_51JWM_2020-09-19_final.stac-item
2020-09-26 11:16:02	ga_s2am_ard_3-2-1_51JXG_2020-09-26_final.stac-item
2021-08-24 11:57:08	ga_s2am_ard_3-2-1_50HMH_2021-08-24_final.stac-item
2021-08-25 11:26:07	ga_s2am_ard_3-2-1_51JUG_2021-08-25_final.stac-item
2021-11-30 11:15:53	ga_s2am_ard_3-2-1_51JYG_2021-11-30_final.stac-item
2021-11-30 11:15:57	ga_s2am_ard_3-2-1_51JXG_2021-11-30_final.stac-item
2021-12-10 11:15:56	ga_s2am_ard_3-2-1_51JXG_2021-12-10_final.stac-item
2021-12-19 11:46:54	ga_s2am_ard_3-2-1_50HQH_2021-12-19_final.stac-item
2022-01-05 11:36:35	ga_s2am_ard_3-2-1_51HVD_2022-01-05_final.stac-item
2022-01-09 11:15:58	ga_s2am_ard_3-2-1_51JXG_2022-01-09_final.stac-item
2022-02-11 11:25:52	ga_s2am_ard_3-2-1_51JXG_2022-02-11_final.stac-item
2022-02-18 11:15:55	ga_s2am_ard_3-2-1_51JYG_2022-02-18_final.stac-item
2022-03-05 12:05:02	ga_s2am_ard_3-2-1_50JMR_2022-03-05_final.stac-item
2022-03-13 11:25:57	ga_s2am_ard_3-2-1_51JXG_2022-03-13_final.stac-item
2022-03-20 11:15:57	ga_s2am_ard_3-2-1_51JYG_2022-03-20_final.stac-item
2022-04-19 11:15:58	ga_s2am_ard_3-2-1_51JYG_2022-04-19_final.stac-item
2022-07-31 11:23:02	ga_s2am_ard_3-2-1_51KXU_2022-07-31_final.stac-item
2022-08-07 11:16:55	ga_s2am_ard_3-2-1_51HWD_2022-08-07_final.stac-item
2022-08-20 11:26:18	ga_s2am_ard_3-2-1_51JUG_2022-08-20_final.stac-item
2022-08-20 11:26:20	ga_s2am_ard_3-2-1_51JXF_2022-08-20_final.stac-item
2022-08-30 11:26:17	ga_s2am_ard_3-2-1_51JUG_2022-08-30_final.stac-item
2022-10-19 11:26:08	ga_s2am_ard_3-2-1_51JUG_2022-10-19_final.stac-item
2022-10-21 12:04:59	ga_s2am_ard_3-2-1_50JMR_2022-10-21_final.stac-item
2022-12-14 11:44:51	ga_s2am_ard_3-2-1_51JUL_2022-12-14_final.stac-item
2022-12-17 11:55:15	ga_s2am_ard_3-2-1_50JPQ_2022-12-17_final.stac-item
2022-12-17 11:55:25	ga_s2am_ard_3-2-1_50JPP_2022-12-17_final.stac-item
2022-12-25 11:15:52	ga_s2am_ard_3-2-1_51JYG_2022-12-25_final.stac-item
2023-01-07 11:26:21	ga_s2am_ard_3-2-1_51HXE_2023-01-07_final.stac-item
2023-01-13 11:46:51	ga_s2am_ard_3-2-1_50HQH_2023-01-13_final.stac-item
2023-02-13 11:15:55	ga_s2am_ard_3-2-1_51JXG_2023-02-13_nrt.stac-item
2023-02-13 11:15:55	ga_s2am_ard_3-2-1_51JXG_2023-02-13_final
2023-03-05 11:15:54	ga_s2am_ard_3-2-1_51JXG_2023-03-05_final
2023-05-16 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2023-05-16_final
2023-05-16 11:57:07	ga_s2am_ard_3-2-1_50HMH_2023-05-16_final
2023-05-17 11:26:41	ga_s2am_ard_3-2-1_51HWD_2023-05-17_final
2023-05-27 11:26:10	ga_s2am_ard_3-2-1_51JUG_2023-05-27_final
2023-07-06 11:26:10	ga_s2am_ard_3-2-1_51JUG_2023-07-06_final
2023-07-16 11:26:10	ga_s2am_ard_3-2-1_51JUG_2023-07-16_final
2023-07-23 11:15:52	ga_s2am_ard_3-2-1_51JXH_2023-07-23_final
2023-08-04 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2023-08-04_final
2023-08-22 11:16:03	ga_s2am_ard_3-2-1_51JXG_2023-08-22_final
2023-08-25 11:26:28	ga_s2am_ard_3-2-1_51HXE_2023-08-25_final
2023-10-21 11:15:57	ga_s2am_ard_3-2-1_51JXG_2023-10-21_final
2023-11-28 12:14:14	ga_s2am_ard_3-2-1_49KHP_2023-11-28_final
2023-12-05 12:04:42	ga_s2am_ard_3-2-1_50JMS_2023-12-05_final
2023-12-05 12:04:52	ga_s2am_ard_3-2-1_50JMR_2023-12-05_final
2024-01-19 11:15:45	ga_s2am_ard_3-2-1_51JYG_2024-01-19_final
2024-01-29 11:15:49	ga_s2am_ard_3-2-1_51JYG_2024-01-29_final
2024-01-31 11:52:15	ga_s2am_ard_3-2-1_50KQG_2024-01-31_final
2024-02-18 11:15:51	ga_s2am_ard_3-2-1_51JYG_2024-02-18_final
2024-02-18 11:15:55	ga_s2am_ard_3-2-1_51JXG_2024-02-18_final
2024-02-21 11:25:51	ga_s2am_ard_3-2-1_51JXG_2024-02-21_final
2024-03-01 11:56:37	ga_s2am_ard_3-2-1_50HLK_2024-03-01_final
2024-04-03 12:03:42	ga_s2am_ard_3-2-1_50KNA_2024-04-03_final
2024-04-04 11:36:31	ga_s2am_ard_3-2-1_51HVD_2024-04-04_final
2024-04-07 11:45:42	ga_s2am_ard_3-2-1_51JTH_2024-04-07_final
2024-05-04 11:35:48	ga_s2am_ard_3-2-1_51JUH_2024-05-04_final
2024-05-08 11:16:00	ga_s2am_ard_3-2-1_51JXG_2024-05-08_final
2024-05-17 11:46:55	ga_s2am_ard_3-2-1_50HQH_2024-05-17_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