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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_50KNA_2015-10-28_final.stac-item
2015-11-14 11:47:22	ga_s2am_ard_3-2-1_50KQB_2015-11-14_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JPQ_2015-11-14_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HPJ_2015-12-21_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51HXD_2015-12-25_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51HXE_2015-12-25_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_50JLR_2016-01-26_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JNN_2016-02-02_final.stac-item
2016-03-06 12:04:37	ga_s2am_ard_3-2-1_50JLR_2016-03-06_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50KQB_2016-04-02_final.stac-item
2016-04-25 12:04:45	ga_s2am_ard_3-2-1_50JLS_2016-04-25_final.stac-item
2016-05-12 11:56:32	ga_s2am_ard_3-2-1_50HLK_2016-05-12_final.stac-item
2016-08-14 11:36:06	ga_s2am_ard_3-2-1_50JQM_2016-08-14_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50KNA_2016-11-21_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50JPQ_2016-11-28_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49JGN_2016-12-11_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49KGP_2016-12-11_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49KHP_2016-12-11_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50JMT_2016-12-11_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50KLA_2016-12-11_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50KMA_2016-12-11_final.stac-item
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49KGP_2016-12-14_final.stac-item
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_50KKV_2016-12-14_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HQH_2016-12-15_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50JPR_2016-12-15_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JLT_2017-01-30_final.stac-item
2017-01-31 11:26:14	ga_s2am_ard_3-2-1_50JRS_2017-01-31_final.stac-item
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49KHP_2017-02-22_final.stac-item
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_50KKV_2017-02-22_final.stac-item
2017-03-09 11:26:01	ga_s2am_ard_3-2-1_51HXE_2017-03-09_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_50KMV_2017-09-17_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_50KKU_2017-11-19_final.stac-item
2018-12-14 12:13:59	ga_s2am_ard_3-2-1_50KKV_2018-12-14_final.stac-item
2018-12-14 12:14:13	ga_s2am_ard_3-2-1_49KHP_2018-12-14_final.stac-item
2019-01-21 11:34:45	ga_s2am_ard_3-2-1_50JRS_2019-01-21_final.stac-item
2019-01-28 11:26:40	ga_s2am_ard_3-2-1_51HVD_2019-01-28_final.stac-item
2019-01-30 12:03:41	ga_s2am_ard_3-2-1_50KNA_2019-01-30_final.stac-item
2019-02-13 11:46:50	ga_s2am_ard_3-2-1_50HQH_2019-02-13_final.stac-item
2019-02-19 12:03:40	ga_s2am_ard_3-2-1_50KNA_2019-02-19_final.stac-item
2019-02-19 12:04:45	ga_s2am_ard_3-2-1_50JMS_2019-02-19_final.stac-item
2019-02-22 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2019-02-22_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
2019-02-27 11:26:17	ga_s2am_ard_3-2-1_51HXE_2019-02-27_final.stac-item
2019-02-27 11:26:33	ga_s2am_ard_3-2-1_51HVD_2019-02-27_final.stac-item
2019-03-18 11:53:53	ga_s2am_ard_3-2-1_50KMA_2019-03-18_final.stac-item
2019-05-07 11:53:54	ga_s2am_ard_3-2-1_50KPA_2019-05-07_final.stac-item
2019-05-18 11:26:26	ga_s2am_ard_3-2-1_51HXE_2019-05-18_final.stac-item
2019-08-01 12:14:31	ga_s2am_ard_3-2-1_49KGP_2019-08-01_final.stac-item
2019-12-13 11:55:11	ga_s2am_ard_3-2-1_50JPQ_2019-12-13_final.stac-item
2019-12-16 12:05:03	ga_s2am_ard_3-2-1_50JLR_2019-12-16_final.stac-item
2019-12-16 12:05:17	ga_s2am_ard_3-2-1_50JLQ_2019-12-16_final.stac-item
2020-01-29 11:46:46	ga_s2am_ard_3-2-1_50HQH_2020-01-29_final.stac-item
2020-06-20 11:52:43	ga_s2am_ard_3-2-1_50KPF_2020-06-20_final
2020-07-20 11:53:58	ga_s2am_ard_3-2-1_50KPA_2020-07-20_final.stac-item
2020-07-21 11:26:27	ga_s2am_ard_3-2-1_51HXE_2020-07-21_final.stac-item
2020-07-23 12:03:49	ga_s2am_ard_3-2-1_50KNA_2020-07-23_final.stac-item
2020-08-02 12:03:47	ga_s2am_ard_3-2-1_50KNB_2020-08-02_final.stac-item
2020-09-01 12:03:38	ga_s2am_ard_3-2-1_50KNB_2020-09-01_final.stac-item
2020-09-18 11:54:38	ga_s2am_ard_3-2-1_50JPT_2020-09-18_final.stac-item
2021-03-17 11:52:37	ga_s2am_ard_3-2-1_50KPF_2021-03-17_final
2021-08-24 11:56:42	ga_s2am_ard_3-2-1_50HLK_2021-08-24_final.stac-item
2021-08-24 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2021-08-24_final.stac-item
2021-08-25 11:26:46	ga_s2am_ard_3-2-1_51HVD_2021-08-25_final.stac-item
2021-08-28 11:36:07	ga_s2am_ard_3-2-1_50JQM_2021-08-28_final.stac-item
2021-12-23 11:26:23	ga_s2am_ard_3-2-1_51HXE_2021-12-23_final.stac-item
2021-12-25 12:06:05	ga_s2am_ard_3-2-1_50JLM_2021-12-25_final.stac-item
2022-03-05 12:05:09	ga_s2am_ard_3-2-1_49JGL_2022-03-05_final.stac-item
2022-05-18 11:46:06	ga_s2am_ard_3-2-1_50JQM_2022-05-18_final.stac-item
2022-05-19 11:16:36	ga_s2am_ard_3-2-1_51HWE_2022-05-19_final.stac-item
2022-06-30 11:57:08	ga_s2am_ard_3-2-1_50HLJ_2022-06-30_final.stac-item
2022-08-27 11:16:56	ga_s2am_ard_3-2-1_51HWD_2022-08-27_final
2022-12-21 11:36:03	ga_s2am_ard_3-2-1_50JQM_2022-12-21_final.stac-item
2022-12-27 11:55:25	ga_s2am_ard_3-2-1_50JPP_2022-12-27_final.stac-item
2023-04-14 11:16:26	ga_s2am_ard_3-2-1_51HXE_2023-04-14_final
2023-04-27 11:26:22	ga_s2am_ard_3-2-1_51HXE_2023-04-27_final
2023-07-15 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2023-07-15_final
2023-07-15 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2023-07-15_final
2023-07-15 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-07-15_final
2023-07-16 11:26:41	ga_s2am_ard_3-2-1_51HXD_2023-07-16_final
2023-07-23 11:16:30	ga_s2am_ard_3-2-1_51HXE_2023-07-23_final
2023-07-23 11:16:35	ga_s2am_ard_3-2-1_51HWE_2023-07-23_final
2023-07-23 11:16:48	ga_s2am_ard_3-2-1_51HWD_2023-07-23_final
2023-08-01 11:47:19	ga_s2am_ard_3-2-1_50HLH_2023-08-01_final
2023-08-15 11:26:28	ga_s2am_ard_3-2-1_51HXE_2023-08-15_final
2023-08-25 11:26:46	ga_s2am_ard_3-2-1_51HWD_2023-08-25_final
2023-08-31 11:47:19	ga_s2am_ard_3-2-1_50HLH_2023-08-31_final
2023-11-19 11:46:51	ga_s2am_ard_3-2-1_50HQH_2023-11-19_final
2023-11-23 11:26:36	ga_s2am_ard_3-2-1_51HWD_2023-11-23_final
2023-12-02 11:56:32	ga_s2am_ard_3-2-1_50HLK_2023-12-02_final
2023-12-05 12:04:00	ga_s2am_ard_3-2-1_50KMV_2023-12-05_final
2023-12-08 12:14:03	ga_s2am_ard_3-2-1_49KHQ_2023-12-08_final
2023-12-08 12:14:15	ga_s2am_ard_3-2-1_49KHP_2023-12-08_final
2023-12-23 11:26:18	ga_s2am_ard_3-2-1_51HXE_2023-12-23_final
2023-12-23 11:26:37	ga_s2am_ard_3-2-1_51HWD_2023-12-23_final
2024-01-18 11:45:52	ga_s2am_ard_3-2-1_50JQM_2024-01-18_final
2024-02-21 11:26:20	ga_s2am_ard_3-2-1_51HXE_2024-02-21_final
2024-03-04 12:04:59	ga_s2am_ard_3-2-1_50JMR_2024-03-04_final
2024-04-03 12:04:04	ga_s2am_ard_3-2-1_50KMV_2024-04-03_final
2024-04-26 12:14:07	ga_s2am_ard_3-2-1_50KKV_2024-04-26_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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