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
2015-11-14 11:47:22	ga_s2am_ard_3-2-1_50KPB_2015-11-14_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HQK_2015-12-21_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_51JTJ_2015-12-21_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51JXF_2015-12-25_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51JTJ_2016-01-20_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_50JLT_2016-01-26_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50JLR_2016-02-15_final.stac-item
2016-08-14 11:36:06	ga_s2am_ard_3-2-1_50JQM_2016-08-14_final.stac-item
2016-08-14 11:36:06	ga_s2am_ard_3-2-1_51JTG_2016-08-14_final.stac-item
2016-08-21 11:26:11	ga_s2am_ard_3-2-1_51JXF_2016-08-21_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50JPQ_2016-11-28_final.stac-item
2016-12-09 11:21:01	ga_s2am_ard_3-2-1_51JXF_2016-12-09_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50JMS_2016-12-11_final.stac-item
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49KHQ_2016-12-14_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50JRS_2016-12-15_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51JTL_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
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_50KKU_2016-12-24_final.stac-item
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_51JXH_2017-01-25_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JMS_2017-01-30_final.stac-item
2017-05-18 11:21:00	ga_s2am_ard_3-2-1_51JXG_2017-05-18_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49KHP_2017-08-01_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_50KKU_2017-08-01_final.stac-item
2017-08-06 11:22:11	ga_s2am_ard_3-2-1_51JXF_2017-08-06_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_50KMV_2017-09-17_final.stac-item
2019-01-28 11:25:35	ga_s2am_ard_3-2-1_51JXH_2019-01-28_final.stac-item
2019-01-31 11:34:43	ga_s2am_ard_3-2-1_51JUM_2019-01-31_final.stac-item
2019-01-31 11:34:58	ga_s2am_ard_3-2-1_51JUL_2019-01-31_final.stac-item
2019-02-20 11:34:42	ga_s2am_ard_3-2-1_51JUM_2019-02-20_final.stac-item
2019-02-23 11:45:17	ga_s2am_ard_3-2-1_50JPQ_2019-02-23_final.stac-item
2019-02-26 11:55:22	ga_s2am_ard_3-2-1_50JPP_2019-02-26_final.stac-item
2019-02-26 11:55:23	ga_s2am_ard_3-2-1_50JLQ_2019-02-26_final.stac-item
2019-02-26 11:55:30	ga_s2am_ard_3-2-1_50JNP_2019-02-26_final.stac-item
2019-02-27 11:25:26	ga_s2am_ard_3-2-1_51JVJ_2019-02-27_final.stac-item
2019-03-02 11:35:54	ga_s2am_ard_3-2-1_51JUG_2019-03-02_final.stac-item
2019-03-02 11:35:57	ga_s2am_ard_3-2-1_51JTG_2019-03-02_final.stac-item
2019-03-12 11:36:29	ga_s2am_ard_3-2-1_51HVD_2019-03-12_final.stac-item
2019-04-18 11:25:55	ga_s2am_ard_3-2-1_51JXG_2019-04-18_final.stac-item
2019-08-06 11:26:11	ga_s2am_ard_3-2-1_51JXF_2019-08-06_final.stac-item
2019-11-29 12:14:20	ga_s2am_ard_3-2-1_49KHP_2019-11-29_final.stac-item
2019-12-04 11:25:51	ga_s2am_ard_3-2-1_51JXG_2019-12-04_final.stac-item
2019-12-10 11:44:46	ga_s2am_ard_3-2-1_51JTL_2019-12-10_final.stac-item
2019-12-16 12:05:03	ga_s2am_ard_3-2-1_50JLR_2019-12-16_final.stac-item
2020-01-28 12:14:24	ga_s2am_ard_3-2-1_49JHN_2020-01-28_final.stac-item
2020-01-30 11:15:50	ga_s2am_ard_3-2-1_51JXG_2020-01-30_final.stac-item
2020-07-30 11:54:09	ga_s2am_ard_3-2-1_50KMV_2020-07-30_final.stac-item
2020-08-17 11:16:03	ga_s2am_ard_3-2-1_51JXG_2020-08-17_final.stac-item
2020-09-18 11:54:38	ga_s2am_ard_3-2-1_50JPT_2020-09-18_final.stac-item
2020-09-25 11:44:56	ga_s2am_ard_3-2-1_51JUL_2020-09-25_final.stac-item
2020-10-05 11:45:27	ga_s2am_ard_3-2-1_50JPQ_2020-10-05_final.stac-item
2021-04-10 11:37:13	ga_s2am_ard_3-2-1_50HQG_2021-04-10_final
2021-08-28 11:36:04	ga_s2am_ard_3-2-1_51JTG_2021-08-28_final.stac-item
2021-11-13 11:25:54	ga_s2am_ard_3-2-1_51JXG_2021-11-13_final.stac-item
2021-12-12 11:55:25	ga_s2am_ard_3-2-1_50JPP_2021-12-12_final.stac-item
2021-12-23 11:25:54	ga_s2am_ard_3-2-1_51JXG_2021-12-23_final.stac-item
2022-02-08 11:15:56	ga_s2am_ard_3-2-1_51JXG_2022-02-08_final.stac-item
2022-02-11 11:25:52	ga_s2am_ard_3-2-1_51JXG_2022-02-11_final.stac-item
2022-03-09 11:46:01	ga_s2am_ard_3-2-1_51JTG_2022-03-09_final.stac-item
2022-03-09 11:46:05	ga_s2am_ard_3-2-1_50JQM_2022-03-09_final.stac-item
2022-03-13 11:25:57	ga_s2am_ard_3-2-1_51JXG_2022-03-13_final.stac-item
2022-05-19 11:16:36	ga_s2am_ard_3-2-1_51HWE_2022-05-19_final.stac-item
2022-05-29 11:16:05	ga_s2am_ard_3-2-1_51JXG_2022-05-29_final.stac-item
2022-06-28 11:16:32	ga_s2am_ard_3-2-1_51JWF_2022-06-28_final.stac-item
2022-07-08 11:16:10	ga_s2am_ard_3-2-1_51JXG_2022-07-08_final.stac-item
2022-07-08 11:16:32	ga_s2am_ard_3-2-1_51JWF_2022-07-08_final.stac-item
2022-08-07 11:16:31	ga_s2am_ard_3-2-1_51JWF_2022-08-07_final.stac-item
2022-08-10 11:26:19	ga_s2am_ard_3-2-1_51JXF_2022-08-10_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
2022-08-26 11:46:09	ga_s2am_ard_3-2-1_51JTG_2022-08-26_final
2022-08-27 11:16:32	ga_s2am_ard_3-2-1_51JWF_2022-08-27_final.stac-item
2022-12-25 11:15:55	ga_s2am_ard_3-2-1_51JXG_2022-12-25_final.stac-item
2022-12-28 11:25:51	ga_s2am_ard_3-2-1_51JXG_2022-12-28_final.stac-item
2023-01-07 11:25:44	ga_s2am_ard_3-2-1_51JYG_2023-01-07_final.stac-item
2023-01-07 11:26:21	ga_s2am_ard_3-2-1_51HXE_2023-01-07_final.stac-item
2023-01-24 11:15:54	ga_s2am_ard_3-2-1_51JXG_2023-01-24_final.stac-item
2023-02-03 11:15:56	ga_s2am_ard_3-2-1_51JXG_2023-02-03_final.stac-item
2023-03-05 11:15:44	ga_s2am_ard_3-2-1_51JXH_2023-03-05_final
2023-04-14 11:16:30	ga_s2am_ard_3-2-1_51HWE_2023-04-14_final
2023-04-27 11:26:22	ga_s2am_ard_3-2-1_51HXE_2023-04-27_final
2023-05-17 11:26:06	ga_s2am_ard_3-2-1_51JUG_2023-05-17_final
2023-06-13 11:16:01	ga_s2am_ard_3-2-1_51JXG_2023-06-13_final
2023-07-03 11:16:02	ga_s2am_ard_3-2-1_51JXG_2023-07-03_final
2023-07-06 11:26:10	ga_s2am_ard_3-2-1_51JUG_2023-07-06_final
2023-07-23 11:16:02	ga_s2am_ard_3-2-1_51JXG_2023-07-23_final
2023-07-23 11:16:35	ga_s2am_ard_3-2-1_51HWE_2023-07-23_final
2023-08-25 11:26:11	ga_s2am_ard_3-2-1_51JUG_2023-08-25_final
2023-11-20 11:15:54	ga_s2am_ard_3-2-1_51JXG_2023-11-20_final
2023-12-02 11:55:18	ga_s2am_ard_3-2-1_50JPP_2023-12-02_final
2023-12-20 11:15:53	ga_s2am_ard_3-2-1_51JXG_2023-12-20_final
2024-01-18 11:45:48	ga_s2am_ard_3-2-1_51JTG_2024-01-18_final
2024-01-19 11:15:48	ga_s2am_ard_3-2-1_51JXG_2024-01-19_final
2024-01-22 11:26:15	ga_s2am_ard_3-2-1_51HXE_2024-01-22_final
2024-02-07 11:44:47	ga_s2am_ard_3-2-1_51JUL_2024-02-07_final
2024-02-14 11:35:57	ga_s2am_ard_3-2-1_51JUG_2024-02-14_final
2024-02-17 11:45:55	ga_s2am_ard_3-2-1_51JTG_2024-02-17_final
2024-04-03 12:04:04	ga_s2am_ard_3-2-1_50KMV_2024-04-03_final
2024-04-07 11:45:59	ga_s2am_ard_3-2-1_50JQM_2024-04-07_final
2024-04-10 11:55:26	ga_s2am_ard_3-2-1_50JPP_2024-04-10_final
2024-04-11 11:25:53	ga_s2am_ard_3-2-1_51JXG_2024-04-11_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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