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
2015-10-22 11:46:57	ga_s2am_ard_3-2-1_50HNH_2015-10-22_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51HUC_2015-12-25_final.stac-item
2016-02-12 11:56:22	ga_s2am_ard_3-2-1_50HNK_2016-02-12_final.stac-item
2016-04-10 11:16:26	ga_s2am_ard_3-2-1_51HWC_2016-04-10_final
2016-08-17 11:40:15	ga_s2am_ard_3-2-1_50HPJ_2016-08-17_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50JKN_2016-09-19_final.stac-item
2016-09-25 12:13:39	ga_s2am_ard_3-2-1_49KHQ_2016-09-25_final.stac-item
2016-10-30 11:18:19	ga_s2am_ard_3-2-1_51HUD_2016-10-30_final.stac-item
2016-11-09 11:26:07	ga_s2am_ard_3-2-1_51HUE_2016-11-09_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKP_2016-11-11_final.stac-item
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_49JGL_2017-03-21_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50KQG_2017-04-07_final
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_50KNC_2017-05-10_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49JGM_2017-06-02_final.stac-item
2017-07-10 11:34:59	ga_s2am_ard_3-2-1_50HPH_2017-07-10_final.stac-item
2017-07-22 12:13:45	ga_s2am_ard_3-2-1_49KHQ_2017-07-22_final.stac-item
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50JMM_2017-08-05_final.stac-item
2017-08-09 11:36:05	ga_s2am_ard_3-2-1_51JUG_2017-08-09_final.stac-item
2017-08-15 11:56:09	ga_s2am_ard_3-2-1_50JNL_2017-08-15_final.stac-item
2017-10-11 11:40:47	ga_s2am_ard_3-2-1_50KRD_2017-10-11_final.stac-item
2017-10-28 11:36:03	ga_s2am_ard_3-2-1_50JPL_2017-10-28_final.stac-item
2017-12-06 12:03:42	ga_s2am_ard_3-2-1_49KHR_2017-12-06_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51HTC_2018-01-06_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50HMH_2018-01-12_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50KMC_2018-03-03_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50HMJ_2018-04-12_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JKN_2018-05-02_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JLM_2018-05-25_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50JNM_2018-06-08_final.stac-item
2018-06-22 11:26:00	ga_s2am_ard_3-2-1_51HUD_2018-06-22_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JKS_2018-07-04_final.stac-item
2018-07-05 11:35:08	ga_s2am_ard_3-2-1_51HTE_2018-07-05_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50HLJ_2018-07-31_final.stac-item
2018-08-26 12:13:20	ga_s2am_ard_3-2-1_49JGN_2018-08-26_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50JLQ_2018-08-30_final.stac-item
2018-10-06 11:46:03	ga_s2am_ard_3-2-1_50JQL_2018-10-06_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50HLJ_2018-10-19_final.stac-item
2019-03-14 12:14:23	ga_s2am_ard_3-2-1_49KGP_2019-03-14_final.stac-item
2019-03-28 11:53:10	ga_s2am_ard_3-2-1_50KRC_2019-03-28_final.stac-item
2019-03-28 11:55:59	ga_s2am_ard_3-2-1_50JKN_2019-03-28_final.stac-item
2019-06-30 11:37:11	ga_s2am_ard_3-2-1_50HPH_2019-06-30_final.stac-item
2019-07-26 11:53:15	ga_s2am_ard_3-2-1_50KRC_2019-07-26_final.stac-item
2019-09-05 11:26:32	ga_s2am_ard_3-2-1_51HUE_2019-09-05_final.stac-item
2019-11-07 11:36:29	ga_s2am_ard_3-2-1_50JPL_2019-11-07_final.stac-item
2020-01-16 11:34:43	ga_s2am_ard_3-2-1_51JTM_2020-01-16_final.stac-item
2020-03-25 12:05:37	ga_s2am_ard_3-2-1_50JKP_2020-03-25_final.stac-item
2020-04-05 11:36:25	ga_s2am_ard_3-2-1_51HUE_2020-04-05_final.stac-item
2020-04-18 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2020-04-18_final.stac-item
2020-05-07 12:13:58	ga_s2am_ard_3-2-1_50KKA_2020-05-07_final.stac-item
2020-08-23 11:37:03	ga_s2am_ard_3-2-1_51HUC_2020-08-23_final.stac-item
2020-11-27 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2020-11-27_final.stac-item
2021-03-21 11:37:20	ga_s2am_ard_3-2-1_50HPG_2021-03-21_final
2021-04-06 11:57:05	ga_s2am_ard_3-2-1_50HLH_2021-04-06_final.stac-item
2021-04-10 11:36:27	ga_s2am_ard_3-2-1_51HTE_2021-04-10_final.stac-item
2021-04-13 11:46:24	ga_s2am_ard_3-2-1_50HQK_2021-04-13_final.stac-item
2021-05-19 12:06:04	ga_s2am_ard_3-2-1_50JLM_2021-05-19_final.stac-item
2021-05-30 11:36:32	ga_s2am_ard_3-2-1_51HTE_2021-05-30_final.stac-item
2021-06-02 11:44:31	ga_s2am_ard_3-2-1_50JRT_2021-06-02_final.stac-item
2021-06-28 12:05:28	ga_s2am_ard_3-2-1_50JKQ_2021-06-28_final.stac-item
2021-06-28 12:05:42	ga_s2am_ard_3-2-1_50JKP_2021-06-28_final.stac-item
2021-07-09 11:36:46	ga_s2am_ard_3-2-1_51HUD_2021-07-09_final.stac-item
2021-07-15 11:56:33	ga_s2am_ard_3-2-1_50HNK_2021-07-15_final.stac-item
2021-07-19 11:37:06	ga_s2am_ard_3-2-1_50HQH_2021-07-19_final.stac-item
2021-07-22 11:45:25	ga_s2am_ard_3-2-1_50JPQ_2021-07-22_final.stac-item
2021-08-08 11:34:39	ga_s2am_ard_3-2-1_51JTN_2021-08-08_final.stac-item
2021-08-31 11:43:05	ga_s2am_ard_3-2-1_50KRD_2021-08-31_final.stac-item
2021-09-10 11:47:06	ga_s2am_ard_3-2-1_50HNH_2021-09-10_final.stac-item
2021-09-16 12:05:42	ga_s2am_ard_3-2-1_50JKP_2021-09-16_final.stac-item
2021-09-26 12:05:18	ga_s2am_ard_3-2-1_49JGL_2021-09-26_final.stac-item
2021-10-26 12:05:06	ga_s2am_ard_3-2-1_49JGM_2021-10-26_final.stac-item
2022-02-13 12:03:23	ga_s2am_ard_3-2-1_50KMC_2022-02-13_final.stac-item
2022-05-01 11:52:25	ga_s2am_ard_3-2-1_50KQG_2022-05-01_final
2022-05-04 12:03:25	ga_s2am_ard_3-2-1_50KNC_2022-05-04_final.stac-item
2022-05-11 11:54:55	ga_s2am_ard_3-2-1_50JNS_2022-05-11_final.stac-item
2022-05-24 12:03:30	ga_s2am_ard_3-2-1_50KMC_2022-05-24_final.stac-item
2022-07-07 11:46:43	ga_s2am_ard_3-2-1_50HQK_2022-07-07_final.stac-item
2022-07-11 11:27:11	ga_s2am_ard_3-2-1_51HVC_2022-07-11_final.stac-item
2022-07-13 12:06:04	ga_s2am_ard_3-2-1_50JLN_2022-07-13_final.stac-item
2022-09-04 12:14:25	ga_s2am_ard_3-2-1_49KGQ_2022-09-04_final.stac-item
2022-09-09 11:27:09	ga_s2am_ard_3-2-1_51HVC_2022-09-09_final.stac-item
2022-09-19 11:26:52	ga_s2am_ard_3-2-1_51HWD_2022-09-19_final.stac-item
2022-12-14 11:47:02	ga_s2am_ard_3-2-1_50HPH_2022-12-14_final.stac-item
2023-02-18 12:04:57	ga_s2am_ard_3-2-1_49JGM_2023-02-18_nrt.stac-item
2023-02-19 11:36:54	ga_s2am_ard_3-2-1_51HUC_2023-02-19_nrt.stac-item
2023-02-19 11:36:54	ga_s2am_ard_3-2-1_51HUC_2023-02-19_final
2023-04-09 12:03:44	ga_s2am_ard_3-2-1_50KKB_2023-04-09_final
2023-04-16 11:57:20	ga_s2am_ard_3-2-1_50HMG_2023-04-16_final
2023-04-26 11:56:18	ga_s2am_ard_3-2-1_50JNL_2023-04-26_final
2023-05-27 11:27:02	ga_s2am_ard_3-2-1_51HVC_2023-05-27_final
2023-06-15 11:57:17	ga_s2am_ard_3-2-1_50HLH_2023-06-15_final
2023-06-22 11:43:08	ga_s2am_ard_3-2-1_50KRD_2023-06-22_final
2023-09-26 12:03:22	ga_s2am_ard_3-2-1_50KNC_2023-09-26_final
2023-10-03 11:57:11	ga_s2am_ard_3-2-1_50HLH_2023-10-03_final
2023-10-06 12:04:00	ga_s2am_ard_3-2-1_49KHR_2023-10-06_final
2023-10-11 11:16:39	ga_s2am_ard_3-2-1_51HXD_2023-10-11_final
2023-10-23 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2023-10-23_final
2023-11-15 12:04:59	ga_s2am_ard_3-2-1_49JGM_2023-11-15_final
2024-01-01 11:53:18	ga_s2am_ard_3-2-1_50KPC_2024-01-01_final
2024-03-08 11:46:16	ga_s2am_ard_3-2-1_50JQL_2024-03-08_final
2024-04-16 12:14:59	ga_s2am_ard_3-2-1_49JGM_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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