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
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JPM_2016-01-20_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JGK_2016-01-26_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50HMH_2016-05-29_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_50KKU_2016-06-24_final.stac-item
2016-07-07 12:13:46	ga_s2am_ard_3-2-1_49KHR_2016-07-07_final.stac-item
2016-07-17 12:13:25	ga_s2am_ard_3-2-1_49KGR_2016-07-17_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_50KKU_2016-08-03_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KGP_2016-11-11_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JPL_2016-12-05_final.stac-item
2016-12-28 11:55:47	ga_s2am_ard_3-2-1_50HMJ_2016-12-28_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JLQ_2017-01-30_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_49KGP_2017-03-31_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_50JLT_2017-07-09_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50JML_2017-07-16_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_50JKT_2017-07-29_final.stac-item
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50KRC_2017-08-05_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50HMJ_2017-10-24_final.stac-item
2017-11-26 12:05:06	ga_s2am_ard_3-2-1_50JKM_2017-11-26_final.stac-item
2017-12-29 12:13:37	ga_s2am_ard_3-2-1_50KKA_2017-12-29_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50JLP_2018-02-24_final.stac-item
2018-02-25 11:27:26	ga_s2am_ard_3-2-1_51HTE_2018-02-25_final.stac-item
2018-04-22 11:48:31	ga_s2am_ard_3-2-1_50KRC_2018-04-22_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50JPP_2018-06-28_final.stac-item
2018-07-05 11:35:08	ga_s2am_ard_3-2-1_50JQL_2018-07-05_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGN_2018-07-14_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_50KLC_2018-08-03_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_50KLU_2018-08-03_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKT_2018-08-23_final.stac-item
2018-09-20 11:24:00	ga_s2am_ard_3-2-1_51HUC_2018-09-20_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_50KLA_2018-10-02_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JKQ_2018-10-12_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_50HQJ_2018-11-02_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50JMM_2018-11-05_final.stac-item
2018-11-21 12:03:37	ga_s2am_ard_3-2-1_50KKB_2018-11-21_final.stac-item
2018-12-05 11:46:54	ga_s2am_ard_3-2-1_50HPH_2018-12-05_final.stac-item
2019-03-31 12:03:59	ga_s2am_ard_3-2-1_49KHR_2019-03-31_final.stac-item
2019-04-01 11:36:20	ga_s2am_ard_3-2-1_50JQL_2019-04-01_final.stac-item
2019-05-20 12:04:35	ga_s2am_ard_3-2-1_49KGP_2019-05-20_final.stac-item
2019-05-20 12:04:49	ga_s2am_ard_3-2-1_49JGN_2019-05-20_final.stac-item
2019-05-23 12:13:58	ga_s2am_ard_3-2-1_49KHR_2019-05-23_final.stac-item
2019-06-20 11:36:50	ga_s2am_ard_3-2-1_51HTD_2019-06-20_final.stac-item
2019-07-06 11:56:41	ga_s2am_ard_3-2-1_50HMK_2019-07-06_final.stac-item
2019-08-15 11:54:16	ga_s2am_ard_3-2-1_50KQU_2019-08-15_final.stac-item
2019-09-11 11:47:01	ga_s2am_ard_3-2-1_50HPH_2019-09-11_final.stac-item
2019-10-01 11:46:17	ga_s2am_ard_3-2-1_50JQL_2019-10-01_final.stac-item
2019-12-03 11:55:48	ga_s2am_ard_3-2-1_50JNN_2019-12-03_final.stac-item
2019-12-24 11:26:48	ga_s2am_ard_3-2-1_51HUD_2019-12-24_final.stac-item
2020-01-25 12:04:32	ga_s2am_ard_3-2-1_50JLT_2020-01-25_final.stac-item
2020-03-05 12:03:53	ga_s2am_ard_3-2-1_50KKA_2020-03-05_final.stac-item
2020-05-31 11:52:44	ga_s2am_ard_3-2-1_50KPF_2020-05-31_final
2020-07-30 11:52:25	ga_s2am_ard_3-2-1_50KQG_2020-07-30_final
2020-08-15 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-08-15_final.stac-item
2020-08-16 11:45:49	ga_s2am_ard_3-2-1_50JQN_2020-08-16_final.stac-item
2020-08-29 11:56:31	ga_s2am_ard_3-2-1_50JLL_2020-08-29_final.stac-item
2020-09-28 11:53:30	ga_s2am_ard_3-2-1_50KNC_2020-09-28_final.stac-item
2020-09-28 11:53:44	ga_s2am_ard_3-2-1_50KNB_2020-09-28_final.stac-item
2020-10-28 11:56:05	ga_s2am_ard_3-2-1_50JKN_2020-10-28_final.stac-item
2020-11-20 12:03:22	ga_s2am_ard_3-2-1_50KNC_2020-11-20_final.stac-item
2020-12-23 12:13:53	ga_s2am_ard_3-2-1_49KHR_2020-12-23_final.stac-item
2021-01-06 11:53:50	ga_s2am_ard_3-2-1_50KPA_2021-01-06_final.stac-item
2021-02-05 11:57:09	ga_s2am_ard_3-2-1_50HLH_2021-02-05_final.stac-item
2021-02-15 11:53:20	ga_s2am_ard_3-2-1_50KPC_2021-02-15_final.stac-item
2021-03-04 11:46:08	ga_s2am_ard_3-2-1_50JNM_2021-03-04_final.stac-item
2021-03-31 11:36:29	ga_s2am_ard_3-2-1_51HTE_2021-03-31_final.stac-item
2021-05-19 12:04:13	ga_s2am_ard_3-2-1_50KKV_2021-05-19_final.stac-item
2021-05-23 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2021-05-23_final.stac-item
2021-06-19 11:37:03	ga_s2am_ard_3-2-1_50HQH_2021-06-19_final.stac-item
2021-08-14 11:52:37	ga_s2am_ard_3-2-1_50KQF_2021-08-14_final
2021-08-20 12:15:13	ga_s2am_ard_3-2-1_49JGL_2021-08-20_final.stac-item
2021-09-14 11:26:33	ga_s2am_ard_3-2-1_51HUE_2021-09-14_final.stac-item
2021-10-20 11:43:27	ga_s2am_ard_3-2-1_50KQC_2021-10-20_final.stac-item
2021-10-30 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2021-10-30_final.stac-item
2021-11-02 11:57:13	ga_s2am_ard_3-2-1_50HLH_2021-11-02_final.stac-item
2022-01-21 11:56:25	ga_s2am_ard_3-2-1_50JLL_2022-01-21_final.stac-item
2022-02-07 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2022-02-07_final.stac-item
2022-03-02 11:57:09	ga_s2am_ard_3-2-1_50HMH_2022-03-02_final.stac-item
2022-06-10 11:55:55	ga_s2am_ard_3-2-1_50JKP_2022-06-10_final.stac-item
2022-07-10 11:57:22	ga_s2am_ard_3-2-1_50HLH_2022-07-10_final.stac-item
2022-08-02 12:04:42	ga_s2am_ard_3-2-1_50KKU_2022-08-02_final.stac-item
2022-08-05 12:14:05	ga_s2am_ard_3-2-1_50KKA_2022-08-05_final.stac-item
2022-10-12 11:36:39	ga_s2am_ard_3-2-1_50HQK_2022-10-12_final.stac-item
2022-10-14 12:13:59	ga_s2am_ard_3-2-1_50KKA_2022-10-14_final.stac-item
2022-11-10 12:05:30	ga_s2am_ard_3-2-1_50JKQ_2022-11-10_final.stac-item
2023-01-16 11:54:04	ga_s2am_ard_3-2-1_50KNV_2023-01-16_final.stac-item
2023-02-28 12:04:24	ga_s2am_ard_3-2-1_50KKU_2023-02-28_final
2023-04-03 11:47:01	ga_s2am_ard_3-2-1_50HPH_2023-04-03_final
2023-04-19 12:04:27	ga_s2am_ard_3-2-1_49KHP_2023-04-19_final
2023-04-23 11:43:21	ga_s2am_ard_3-2-1_50KQC_2023-04-23_final
2023-06-02 11:46:38	ga_s2am_ard_3-2-1_50HPK_2023-06-02_final
2023-06-12 11:47:06	ga_s2am_ard_3-2-1_50HPH_2023-06-12_final
2023-08-17 12:04:05	ga_s2am_ard_3-2-1_49KHR_2023-08-17_final
2023-10-07 11:37:07	ga_s2am_ard_3-2-1_50HPH_2023-10-07_final
2023-10-30 11:43:21	ga_s2am_ard_3-2-1_50KQC_2023-10-30_final
2023-12-09 11:46:14	ga_s2am_ard_3-2-1_50JPL_2023-12-09_final
2023-12-15 12:05:11	ga_s2am_ard_3-2-1_49JGL_2023-12-15_final
2024-01-15 11:36:41	ga_s2am_ard_3-2-1_50HQJ_2024-01-15_final
2024-02-27 11:46:18	ga_s2am_ard_3-2-1_50JPL_2024-02-27_final
2024-03-27 12:13:59	ga_s2am_ard_3-2-1_49KGR_2024-03-27_final
2024-04-10 11:56:40	ga_s2am_ard_3-2-1_50HLK_2024-04-10_final
2024-04-16 12:14:01	ga_s2am_ard_3-2-1_49KGR_2024-04-16_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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