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
2015-10-01 12:14:44	ga_s2am_ard_3-2-1_49JGM_2015-10-01_final.stac-item
2015-10-04 10:45:32	ga_s2am_ard_3-2-1_53HME_2015-10-04_final.stac-item
2015-10-23 11:14:04	ga_s2am_ard_3-2-1_52JBQ_2015-10-23_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49JGM_2016-01-16_final.stac-item
2016-06-07 12:13:25	ga_s2am_ard_3-2-1_49JGN_2016-06-07_final.stac-item
2016-06-25 11:32:00	ga_s2am_ard_3-2-1_50HQH_2016-06-25_final.stac-item
2016-08-24 11:31:54	ga_s2am_ard_3-2-1_51JUH_2016-08-24_final.stac-item
2016-10-12 12:03:43	ga_s2am_ard_3-2-1_50KKB_2016-10-12_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_51KUP_2016-12-05_final.stac-item
2016-12-30 10:53:16	ga_s2am_ard_3-2-1_52JGM_2016-12-30_final.stac-item
2017-02-11 11:01:12	ga_s2am_ard_3-2-1_52LGK_2017-02-11_final.stac-item
2017-02-24 11:12:09	ga_s2am_ard_3-2-1_52KDE_2017-02-24_final.stac-item
2017-03-25 11:38:25	ga_s2am_ard_3-2-1_50JRS_2017-03-25_final.stac-item
2017-04-16 10:43:06	ga_s2am_ard_3-2-1_53HLE_2017-04-16_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49JGN_2017-05-10_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_51KUT_2017-11-20_final.stac-item
2017-12-17 11:32:07	ga_s2am_ard_3-2-1_51JVN_2017-12-17_final.stac-item
2018-02-23 10:53:12	ga_s2am_ard_3-2-1_52JFN_2018-02-23_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49KHP_2018-03-06_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JKN_2018-04-12_final.stac-item
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_50JLT_2018-06-04_final.stac-item
2018-06-12 11:22:26	ga_s2am_ard_3-2-1_51KYS_2018-06-12_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50HQK_2018-06-28_final.stac-item
2018-08-08 11:13:24	ga_s2am_ard_3-2-1_51HWD_2018-08-08_final.stac-item
2018-09-15 12:14:38	ga_s2am_ard_3-2-1_49JGN_2018-09-15_final.stac-item
2018-11-19 11:26:11	ga_s2am_ard_3-2-1_51JUF_2018-11-19_final.stac-item
2018-11-22 11:31:13	ga_s2am_ard_3-2-1_51LZE_2018-11-22_final.stac-item
2019-01-25 11:11:45	ga_s2am_ard_3-2-1_52LEH_2019-01-25_final.stac-item
2019-01-25 11:14:38	ga_s2am_ard_3-2-1_51JYM_2019-01-25_final.stac-item
2019-01-25 11:15:01	ga_s2am_ard_3-2-1_52JCQ_2019-01-25_final.stac-item
2019-01-31 11:31:15	ga_s2am_ard_3-2-1_52LBK_2019-01-31_final.stac-item
2019-02-03 11:42:46	ga_s2am_ard_3-2-1_51KUV_2019-02-03_final.stac-item
2019-05-05 11:13:58	ga_s2am_ard_3-2-1_52KBV_2019-05-05_final.stac-item
2019-07-31 11:06:11	ga_s2am_ard_3-2-1_52JCL_2019-07-31_final.stac-item
2019-08-16 11:23:42	ga_s2am_ard_3-2-1_51KYR_2019-08-16_final.stac-item
2019-09-01 11:46:34	ga_s2am_ard_3-2-1_50HPK_2019-09-01_final.stac-item
2019-10-09 11:04:50	ga_s2am_ard_3-2-1_52JER_2019-10-09_final.stac-item
2019-10-18 11:33:12	ga_s2am_ard_3-2-1_51KXT_2019-10-18_final.stac-item
2019-11-29 12:14:55	ga_s2am_ard_3-2-1_49JGM_2019-11-29_final.stac-item
2019-12-14 11:23:20	ga_s2am_ard_3-2-1_51KYS_2019-12-14_final.stac-item
2020-02-12 11:21:57	ga_s2am_ard_3-2-1_52KCG_2020-02-12_final.stac-item
2020-03-27 11:04:39	ga_s2am_ard_3-2-1_52JFR_2020-03-27_final.stac-item
2020-04-03 10:54:45	ga_s2am_ard_3-2-1_52JFR_2020-04-03_final.stac-item
2020-05-09 11:13:44	ga_s2am_ard_3-2-1_51KZR_2020-05-09_final.stac-item
2020-08-17 11:13:13	ga_s2am_ard_3-2-1_52KCC_2020-08-17_final.stac-item
2020-08-23 11:33:58	ga_s2am_ard_3-2-1_51KXQ_2020-08-23_final.stac-item
2020-09-01 10:26:55	ga_s2am_ard_3-2-1_53HPB_2020-09-01_final.stac-item
2020-09-04 10:36:55	ga_s2am_ard_3-2-1_53HNB_2020-09-04_final.stac-item
2020-10-12 11:33:33	ga_s2am_ard_3-2-1_51KWS_2020-10-12_final.stac-item
2020-10-14 12:15:02	ga_s2am_ard_3-2-1_49JGM_2020-10-14_final.stac-item
2020-12-14 11:42:10	ga_s2am_ard_3-2-1_51KVB_2020-12-14_final.stac-item
2021-01-20 11:32:55	ga_s2am_ard_3-2-1_51KXU_2021-01-20_final.stac-item
2021-02-13 11:12:34	ga_s2am_ard_3-2-1_52KDE_2021-02-13_final.stac-item
2021-02-22 11:46:29	ga_s2am_ard_3-2-1_50HQK_2021-02-22_final.stac-item
2021-02-26 11:21:32	ga_s2am_ard_3-2-1_52LDJ_2021-02-26_final.stac-item
2021-03-13 10:36:10	ga_s2am_ard_3-2-1_53HME_2021-03-13_final.stac-item
2021-04-14 11:14:32	ga_s2am_ard_3-2-1_51JZM_2021-04-14_final.stac-item
2021-04-30 11:34:00	ga_s2am_ard_3-2-1_51KUQ_2021-04-30_final.stac-item
2021-06-22 11:41:19	ga_s2am_ard_3-2-1_51LUF_2021-06-22_final.stac-item
2021-07-01 10:36:23	ga_s2am_ard_3-2-1_53HND_2021-07-01_final.stac-item
2021-07-12 11:43:28	ga_s2am_ard_3-2-1_51KVS_2021-07-12_final.stac-item
2021-07-25 11:56:03	ga_s2am_ard_3-2-1_50JKN_2021-07-25_final.stac-item
2021-08-21 11:43:17	ga_s2am_ard_3-2-1_51KUT_2021-08-21_final.stac-item
2021-09-14 11:23:14	ga_s2am_ard_3-2-1_51KXT_2021-09-14_final.stac-item
2021-09-14 11:24:05	ga_s2am_ard_3-2-1_52KBU_2021-09-14_final.stac-item
2021-12-26 11:33:14	ga_s2am_ard_3-2-1_51KWT_2021-12-26_final.stac-item
2022-02-14 11:33:23	ga_s2am_ard_3-2-1_51KXS_2022-02-14_final.stac-item
2022-02-21 11:23:59	ga_s2am_ard_3-2-1_51KXQ_2022-02-21_final.stac-item
2022-03-23 11:23:38	ga_s2am_ard_3-2-1_51KZR_2022-03-23_final.stac-item
2022-04-01 11:54:50	ga_s2am_ard_3-2-1_50JPS_2022-04-01_final.stac-item
2022-04-05 11:33:10	ga_s2am_ard_3-2-1_51KXT_2022-04-05_final.stac-item
2022-05-03 10:54:20	ga_s2am_ard_3-2-1_52JGT_2022-05-03_final.stac-item
2022-06-15 11:05:01	ga_s2am_ard_3-2-1_52JDR_2022-06-15_final.stac-item
2022-06-28 11:13:35	ga_s2am_ard_3-2-1_52KCB_2022-06-28_final.stac-item
2022-08-03 11:33:13	ga_s2am_ard_3-2-1_51KYT_2022-08-03_final.stac-item
2022-08-20 11:24:35	ga_s2am_ard_3-2-1_51JXN_2022-08-20_final.stac-item
2022-10-13 11:05:01	ga_s2am_ard_3-2-1_52JCR_2022-10-13_final.stac-item
2022-10-25 11:43:06	ga_s2am_ard_3-2-1_51KTU_2022-10-25_final.stac-item
2022-11-09 10:52:48	ga_s2am_ard_3-2-1_52KHD_2022-11-09_final.stac-item
2022-12-08 11:22:09	ga_s2am_ard_3-2-1_51KZB_2022-12-08_final.stac-item
2023-01-23 11:44:12	ga_s2am_ard_3-2-1_50KRU_2023-01-23_final.stac-item
2023-04-11 11:00:45	ga_s2am_ard_3-2-1_52LHM_2023-04-11_final
2023-04-13 11:46:26	ga_s2am_ard_3-2-1_50JML_2023-04-13_final
2023-05-14 11:16:25	ga_s2am_ard_3-2-1_51HXE_2023-05-14_final
2023-05-17 11:22:38	ga_s2am_ard_3-2-1_52KBE_2023-05-17_final
2023-05-19 10:26:38	ga_s2am_ard_3-2-1_53HPC_2023-05-19_final
2023-06-12 11:42:13	ga_s2am_ard_3-2-1_51KWB_2023-06-12_final
2023-06-21 12:15:00	ga_s2am_ard_3-2-1_49JGM_2023-06-21_final
2023-07-29 11:33:58	ga_s2am_ard_3-2-1_51KXQ_2023-07-29_final
2023-08-02 11:13:59	ga_s2am_ard_3-2-1_51KZQ_2023-08-02_final
2023-08-14 11:53:44	ga_s2am_ard_3-2-1_50KNB_2023-08-14_final
2023-09-16 12:04:02	ga_s2am_ard_3-2-1_50KKA_2023-09-16_final
2023-10-15 10:54:20	ga_s2am_ard_3-2-1_52JFT_2023-10-15_final
2023-10-27 11:33:42	ga_s2am_ard_3-2-1_51KWR_2023-10-27_final
2023-10-30 11:42:56	ga_s2am_ard_3-2-1_51KVU_2023-10-30_final
2023-11-03 11:24:03	ga_s2am_ard_3-2-1_52KBU_2023-11-03_final
2024-01-16 11:03:26	ga_s2am_ard_3-2-1_52KHV_2024-01-16_final
2024-02-28 11:12:38	ga_s2am_ard_3-2-1_52KCE_2024-02-28_final
2024-03-12 11:24:30	ga_s2am_ard_3-2-1_51JWN_2024-03-12_final
2024-03-27 12:13:59	ga_s2am_ard_3-2-1_49KGR_2024-03-27_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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