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
2015-09-19 11:36:06	ga_s2am_ard_3-2-1_51HUE_2015-09-19_final.stac-item
2016-03-24 11:21:55	ga_s2am_ard_3-2-1_51JVG_2016-03-24_final
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51HTC_2016-04-23_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50JKQ_2016-05-15_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50KLU_2016-05-22_final.stac-item
2016-05-23 11:22:44	ga_s2am_ard_3-2-1_51HUE_2016-05-23_final.stac-item
2016-05-30 11:11:45	ga_s2am_ard_3-2-1_51JYK_2016-05-30_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_51HVE_2016-06-05_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49JGL_2016-10-25_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50HLJ_2016-10-29_final.stac-item
2016-12-26 11:14:08	ga_s2am_ard_3-2-1_51HWC_2016-12-26_final
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50KPC_2017-01-07_final.stac-item
2017-02-07 11:26:03	ga_s2am_ard_3-2-1_51JVF_2017-02-07_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50JPL_2017-07-03_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49JGK_2017-12-16_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51HUC_2018-01-06_final.stac-item
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50JMM_2018-03-23_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JLP_2018-05-02_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_51JXN_2018-05-06_final.stac-item
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_50KKB_2018-06-04_final.stac-item
2018-06-11 11:48:18	ga_s2am_ard_3-2-1_50KQC_2018-06-11_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KMC_2018-07-14_final.stac-item
2018-07-28 11:45:46	ga_s2am_ard_3-2-1_50JQM_2018-07-28_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_50KKB_2018-08-06_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKN_2018-08-23_final.stac-item
2018-08-24 11:33:07	ga_s2am_ard_3-2-1_51JXN_2018-08-24_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_50KKA_2018-10-05_final.stac-item
2018-11-21 12:04:56	ga_s2am_ard_3-2-1_49JGM_2018-11-21_final.stac-item
2018-12-29 11:26:29	ga_s2am_ard_3-2-1_51HXD_2018-12-29_final.stac-item
2019-01-03 12:13:48	ga_s2am_ard_3-2-1_50KKA_2019-01-03_final.stac-item
2019-01-24 11:46:05	ga_s2am_ard_3-2-1_50JNM_2019-01-24_final.stac-item
2019-03-05 11:45:16	ga_s2am_ard_3-2-1_50JPQ_2019-03-05_final.stac-item
2019-03-08 11:56:20	ga_s2am_ard_3-2-1_50JLL_2019-03-08_final.stac-item
2019-06-30 11:34:20	ga_s2am_ard_3-2-1_51JXN_2019-06-30_final.stac-item
2019-08-28 12:04:32	ga_s2am_ard_3-2-1_49KGP_2019-08-28_final.stac-item
2019-09-05 11:26:58	ga_s2am_ard_3-2-1_51HVC_2019-09-05_final.stac-item
2020-02-08 11:45:13	ga_s2am_ard_3-2-1_50JPQ_2020-02-08_final.stac-item
2020-02-15 11:36:54	ga_s2am_ard_3-2-1_51HTC_2020-02-15_final.stac-item
2020-03-12 11:53:51	ga_s2am_ard_3-2-1_50KNA_2020-03-12_final.stac-item
2020-03-16 11:36:23	ga_s2am_ard_3-2-1_50JPL_2020-03-16_final.stac-item
2020-04-14 12:03:58	ga_s2am_ard_3-2-1_49KHR_2020-04-14_final.stac-item
2020-04-25 11:37:08	ga_s2am_ard_3-2-1_50HPH_2020-04-25_final.stac-item
2020-04-28 11:46:40	ga_s2am_ard_3-2-1_50HNK_2020-04-28_final.stac-item
2020-05-28 11:46:32	ga_s2am_ard_3-2-1_50JML_2020-05-28_final.stac-item
2020-06-01 11:26:35	ga_s2am_ard_3-2-1_51HVE_2020-06-01_final.stac-item
2020-06-17 11:43:10	ga_s2am_ard_3-2-1_50KRD_2020-06-17_final.stac-item
2020-06-30 11:53:16	ga_s2am_ard_3-2-1_50KRC_2020-06-30_final.stac-item
2020-07-23 12:05:57	ga_s2am_ard_3-2-1_50JLN_2020-07-23_final.stac-item
2020-08-15 12:14:02	ga_s2am_ard_3-2-1_50KKA_2020-08-15_final.stac-item
2020-11-15 11:16:44	ga_s2am_ard_3-2-1_51HXD_2020-11-15_final.stac-item
2020-12-21 11:37:01	ga_s2am_ard_3-2-1_50HQH_2020-12-21_final.stac-item
2021-02-02 11:43:47	ga_s2am_ard_3-2-1_50KRA_2021-02-02_final.stac-item
2021-02-08 12:04:30	ga_s2am_ard_3-2-1_49KGP_2021-02-08_final.stac-item
2021-02-16 11:26:28	ga_s2am_ard_3-2-1_51HVE_2021-02-16_final.stac-item
2021-02-19 11:36:42	ga_s2am_ard_3-2-1_51HUD_2021-02-19_final.stac-item
2021-03-27 11:52:18	ga_s2am_ard_3-2-1_50KQG_2021-03-27_final
2021-04-10 11:36:44	ga_s2am_ard_3-2-1_50HQJ_2021-04-10_final.stac-item
2021-04-20 11:37:02	ga_s2am_ard_3-2-1_50HPH_2021-04-20_final.stac-item
2021-04-22 12:14:55	ga_s2am_ard_3-2-1_49JFM_2021-04-22_final.stac-item
2021-04-23 11:46:58	ga_s2am_ard_3-2-1_50HPH_2021-04-23_final.stac-item
2021-06-01 12:14:42	ga_s2am_ard_3-2-1_49JGN_2021-06-01_final.stac-item
2021-06-02 11:44:17	ga_s2am_ard_3-2-1_50KRU_2021-06-02_final.stac-item
2021-06-09 11:36:29	ga_s2am_ard_3-2-1_51HUE_2021-06-09_final.stac-item
2021-06-15 11:56:00	ga_s2am_ard_3-2-1_50JKN_2021-06-15_final.stac-item
2021-06-28 12:04:33	ga_s2am_ard_3-2-1_49KGP_2021-06-28_final.stac-item
2021-07-05 11:56:13	ga_s2am_ard_3-2-1_50JNM_2021-07-05_final.stac-item
2021-07-05 11:56:57	ga_s2am_ard_3-2-1_50HLJ_2021-07-05_final.stac-item
2021-08-08 11:37:09	ga_s2am_ard_3-2-1_50HPH_2021-08-08_final.stac-item
2021-08-31 11:43:23	ga_s2am_ard_3-2-1_50KQC_2021-08-31_final.stac-item
2021-09-06 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-09-06_final.stac-item
2021-09-17 11:36:50	ga_s2am_ard_3-2-1_50HQJ_2021-09-17_final.stac-item
2021-09-27 11:36:27	ga_s2am_ard_3-2-1_51HVE_2021-09-27_final.stac-item
2021-10-16 12:03:50	ga_s2am_ard_3-2-1_50KKB_2021-10-16_final.stac-item
2021-11-02 11:57:13	ga_s2am_ard_3-2-1_50HLH_2021-11-02_final.stac-item
2021-11-15 12:03:24	ga_s2am_ard_3-2-1_50KMC_2021-11-15_final.stac-item
2022-02-27 11:43:21	ga_s2am_ard_3-2-1_50KRC_2022-02-27_final.stac-item
2022-04-01 11:52:22	ga_s2am_ard_3-2-1_50KQG_2022-04-01_final
2022-05-11 11:52:38	ga_s2am_ard_3-2-1_50KQF_2022-05-11_final
2022-05-31 11:56:15	ga_s2am_ard_3-2-1_50JMM_2022-05-31_final.stac-item
2022-09-05 11:44:31	ga_s2am_ard_3-2-1_50KQU_2022-09-05_final.stac-item
2022-09-12 11:35:51	ga_s2am_ard_3-2-1_51JVH_2022-09-12_final.stac-item
2022-09-12 11:36:21	ga_s2am_ard_3-2-1_51JVF_2022-09-12_final.stac-item
2022-10-11 12:04:42	ga_s2am_ard_3-2-1_50JMT_2022-10-11_final.stac-item
2022-11-04 11:47:10	ga_s2am_ard_3-2-1_50HNH_2022-11-04_final.stac-item
2023-02-22 11:43:45	ga_s2am_ard_3-2-1_50KRA_2023-02-22_nrt.stac-item
2023-02-22 11:43:45	ga_s2am_ard_3-2-1_50KRA_2023-02-22_final
2023-04-10 11:37:17	ga_s2am_ard_3-2-1_50HQG_2023-04-10_final
2023-04-16 11:53:17	ga_s2am_ard_3-2-1_50KQC_2023-04-16_final
2023-05-07 11:26:54	ga_s2am_ard_3-2-1_51HWC_2023-05-07_final
2023-05-26 11:53:14	ga_s2am_ard_3-2-1_50KRC_2023-05-26_final
2023-06-05 11:56:00	ga_s2am_ard_3-2-1_50JLN_2023-06-05_final
2023-06-11 12:15:14	ga_s2am_ard_3-2-1_49JGL_2023-06-11_final
2023-06-12 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2023-06-12_final
2023-07-05 11:56:16	ga_s2am_ard_3-2-1_50JLM_2023-07-05_final
2023-08-04 11:56:19	ga_s2am_ard_3-2-1_50JKM_2023-08-04_final
2023-09-03 11:55:47	ga_s2am_ard_3-2-1_50JLP_2023-09-03_final
2023-11-25 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-11-25_final
2024-01-31 11:53:20	ga_s2am_ard_3-2-1_50KNC_2024-01-31_final
2024-02-10 11:53:21	ga_s2am_ard_3-2-1_50KNC_2024-02-10_final
2024-02-23 12:05:39	ga_s2am_ard_3-2-1_50JKP_2024-02-23_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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