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
2016-07-30 10:45:24	ga_s2am_ard_3-2-1_53HLE_2016-07-30_final.stac-item
2016-12-06 11:07:09	ga_s2am_ard_3-2-1_52KDU_2016-12-06_final.stac-item
2016-12-26 11:07:06	ga_s2am_ard_3-2-1_52LGJ_2016-12-26_final.stac-item
2016-12-27 10:43:36	ga_s2am_ard_3-2-1_53HLD_2016-12-27_final.stac-item
2017-12-21 11:12:09	ga_s2am_ard_3-2-1_52KCA_2017-12-21_final.stac-item
2018-02-13 10:52:02	ga_s2am_ard_3-2-1_52JGP_2018-02-13_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51HUD_2018-02-22_final.stac-item
2018-03-04 11:22:24	ga_s2am_ard_3-2-1_51HXE_2018-03-04_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50KKA_2018-05-25_final.stac-item
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_50JKP_2018-06-04_final.stac-item
2018-06-06 10:57:16	ga_s2am_ard_3-2-1_52HBK_2018-06-06_final.stac-item
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_51KXT_2018-06-15_final.stac-item
2018-10-27 11:13:53	ga_s2am_ard_3-2-1_51HWE_2018-10-27_final.stac-item
2018-11-12 11:36:58	ga_s2am_ard_3-2-1_50HQH_2018-11-12_final.stac-item
2019-01-05 11:13:35	ga_s2am_ard_3-2-1_51KZR_2019-01-05_final.stac-item
2019-01-18 11:24:11	ga_s2am_ard_3-2-1_51KWP_2019-01-18_final.stac-item
2019-03-14 12:14:17	ga_s2am_ard_3-2-1_49KHP_2019-03-14_final.stac-item
2019-03-23 11:05:29	ga_s2am_ard_3-2-1_52JEN_2019-03-23_final.stac-item
2019-05-19 10:52:48	ga_s2am_ard_3-2-1_52KHD_2019-05-19_final.stac-item
2019-08-11 12:13:43	ga_s2am_ard_3-2-1_50KKB_2019-08-11_final.stac-item
2019-09-27 12:05:56	ga_s2am_ard_3-2-1_50JKN_2019-09-27_final.stac-item
2019-11-24 11:25:21	ga_s2am_ard_3-2-1_51JYJ_2019-11-24_final.stac-item
2019-12-08 11:05:20	ga_s2am_ard_3-2-1_52JCP_2019-12-08_final.stac-item
2020-01-09 11:43:52	ga_s2am_ard_3-2-1_51KUQ_2020-01-09_final.stac-item
2020-01-10 11:10:38	ga_s2am_ard_3-2-1_52LGM_2020-01-10_final.stac-item
2020-02-08 11:45:31	ga_s2am_ard_3-2-1_50JNP_2020-02-08_final.stac-item
2020-02-12 11:26:29	ga_s2am_ard_3-2-1_51HXD_2020-02-12_final.stac-item
2020-02-22 11:25:33	ga_s2am_ard_3-2-1_51JXH_2020-02-22_final.stac-item
2020-02-22 11:25:40	ga_s2am_ard_3-2-1_51JVH_2020-02-22_final.stac-item
2020-02-26 11:04:38	ga_s2am_ard_3-2-1_52JFR_2020-02-26_final.stac-item
2020-05-09 11:16:45	ga_s2am_ard_3-2-1_51HXD_2020-05-09_final.stac-item
2020-06-01 11:25:45	ga_s2am_ard_3-2-1_51JXH_2020-06-01_final.stac-item
2020-07-17 11:46:02	ga_s2am_ard_3-2-1_50JQM_2020-07-17_final.stac-item
2020-08-07 11:10:35	ga_s2am_ard_3-2-1_52LGN_2020-08-07_final.stac-item
2020-12-11 11:33:05	ga_s2am_ard_3-2-1_51KXT_2020-12-11_final.stac-item
2021-01-04 11:14:21	ga_s2am_ard_3-2-1_52JCT_2021-01-04_final.stac-item
2021-01-27 11:26:41	ga_s2am_ard_3-2-1_51HWD_2021-01-27_final.stac-item
2021-01-31 11:05:02	ga_s2am_ard_3-2-1_52JEQ_2021-01-31_final.stac-item
2021-05-23 11:45:36	ga_s2am_ard_3-2-1_50JPP_2021-05-23_final.stac-item
2021-05-31 11:05:35	ga_s2am_ard_3-2-1_52JDN_2021-05-31_final.stac-item
2021-06-10 11:03:50	ga_s2am_ard_3-2-1_52KEV_2021-06-10_final.stac-item
2021-06-16 11:23:39	ga_s2am_ard_3-2-1_51KYR_2021-06-16_final.stac-item
2021-06-23 11:15:49	ga_s2am_ard_3-2-1_52JCM_2021-06-23_final.stac-item
2021-08-01 11:43:21	ga_s2am_ard_3-2-1_51KTT_2021-08-01_final.stac-item
2021-09-27 11:36:38	ga_s2am_ard_3-2-1_50HQK_2021-09-27_final.stac-item
2021-10-31 11:12:40	ga_s2am_ard_3-2-1_52KDE_2021-10-31_final.stac-item
2021-11-01 10:46:28	ga_s2am_ard_3-2-1_53HLD_2021-11-01_final.stac-item
2021-12-07 11:00:47	ga_s2am_ard_3-2-1_52LGM_2021-12-07_final.stac-item
2022-01-06 11:00:32	ga_s2am_ard_3-2-1_52LHN_2022-01-06_final.stac-item
2022-01-15 11:31:40	ga_s2am_ard_3-2-1_51LYD_2022-01-15_final.stac-item
2022-01-16 11:05:38	ga_s2am_ard_3-2-1_52JCN_2022-01-16_final.stac-item
2022-01-28 11:42:13	ga_s2am_ard_3-2-1_51KVB_2022-01-28_final.stac-item
2022-01-29 11:11:16	ga_s2am_ard_3-2-1_52LFK_2022-01-29_final.stac-item
2022-01-29 11:11:45	ga_s2am_ard_3-2-1_52LFH_2022-01-29_final.stac-item
2022-02-01 11:22:37	ga_s2am_ard_3-2-1_52KBE_2022-02-01_final.stac-item
2022-03-27 11:06:09	ga_s2am_ard_3-2-1_52JCL_2022-03-27_final.stac-item
2022-04-14 12:03:26	ga_s2am_ard_3-2-1_50KMC_2022-04-14_final.stac-item
2022-04-20 10:46:14	ga_s2am_ard_3-2-1_53HLE_2022-04-20_final.stac-item
2022-05-02 11:24:37	ga_s2am_ard_3-2-1_52JBS_2022-05-02_final.stac-item
2022-05-06 11:05:53	ga_s2am_ard_3-2-1_52JDM_2022-05-06_final.stac-item
2022-07-12 10:55:55	ga_s2am_ard_3-2-1_52JGM_2022-07-12_final.stac-item
2022-08-02 12:05:40	ga_s2am_ard_3-2-1_49JGK_2022-08-02_final.stac-item
2022-08-31 10:54:38	ga_s2am_ard_3-2-1_52JHS_2022-08-31_final.stac-item
2022-09-10 10:54:26	ga_s2am_ard_3-2-1_52JGT_2022-09-10_final.stac-item
2022-09-25 13:21:45	ga_s2am_ard_3-2-1_47LKH_2022-09-25_interim
2022-10-13 11:05:01	ga_s2am_ard_3-2-1_52JCR_2022-10-13_final.stac-item
2022-10-22 11:36:12	ga_s2am_ard_3-2-1_51JVF_2022-10-22_final.stac-item
2022-10-26 11:15:42	ga_s2am_ard_3-2-1_51JYH_2022-10-26_final.stac-item
2022-11-14 13:21:41	ga_s2am_ard_3-2-1_47LKH_2022-11-14_interim
2022-12-08 11:26:26	ga_s2am_ard_3-2-1_51HWE_2022-12-08_final.stac-item
2022-12-25 11:11:57	ga_s2am_ard_3-2-1_52KFG_2022-12-25_final.stac-item
2022-12-28 11:24:03	ga_s2am_ard_3-2-1_51KZP_2022-12-28_final.stac-item
2023-01-08 10:54:28	ga_s2am_ard_3-2-1_52JGS_2023-01-08_final.stac-item
2023-01-20 11:32:14	ga_s2am_ard_3-2-1_51KVB_2023-01-20_final.stac-item
2023-02-03 11:16:21	ga_s2am_ard_3-2-1_51HYE_2023-02-03_final.stac-item
2023-03-05 11:12:50	ga_s2am_ard_3-2-1_52KFC_2023-03-05_final
2023-04-14 11:12:10	ga_s2am_ard_3-2-1_52KCG_2023-04-14_final
2023-04-14 11:13:30	ga_s2am_ard_3-2-1_52KEA_2023-04-14_final
2023-04-27 11:27:02	ga_s2am_ard_3-2-1_51HUC_2023-04-27_final
2023-06-19 11:35:20	ga_s2am_ard_3-2-1_51JUK_2023-06-19_final
2023-06-25 11:56:17	ga_s2am_ard_3-2-1_50JKM_2023-06-25_final
2023-06-26 11:24:04	ga_s2am_ard_3-2-1_51KZP_2023-06-26_final
2023-06-27 10:54:33	ga_s2am_ard_3-2-1_52JGS_2023-06-27_final
2023-06-27 10:55:31	ga_s2am_ard_3-2-1_52JGN_2023-06-27_final
2023-06-30 11:03:32	ga_s2am_ard_3-2-1_52KGA_2023-06-30_final
2023-09-14 11:24:06	ga_s2am_ard_3-2-1_51KWQ_2023-09-14_final
2023-09-24 11:22:29	ga_s2am_ard_3-2-1_51KYA_2023-09-24_final
2023-10-27 11:32:40	ga_s2am_ard_3-2-1_51KXV_2023-10-27_final
2023-11-26 11:33:10	ga_s2am_ard_3-2-1_51KVT_2023-11-26_final
2023-12-10 11:15:16	ga_s2am_ard_3-2-1_52JBP_2023-12-10_final
2024-01-05 11:36:16	ga_s2am_ard_3-2-1_50JQL_2024-01-05_final
2024-01-09 11:13:03	ga_s2am_ard_3-2-1_52KEC_2024-01-09_final
2024-01-26 11:04:37	ga_s2am_ard_3-2-1_52JFR_2024-01-26_final
2024-02-11 11:21:47	ga_s2am_ard_3-2-1_52LDH_2024-02-11_final
2024-03-06 11:02:32	ga_s2am_ard_3-2-1_52KFE_2024-03-06_final
2024-03-09 11:12:21	ga_s2am_ard_3-2-1_52KDF_2024-03-09_final
2024-03-23 10:53:58	ga_s2am_ard_3-2-1_52KHU_2024-03-23_final
2024-03-25 11:34:12	ga_s2am_ard_3-2-1_51KWP_2024-03-25_final
2024-03-26 11:04:48	ga_s2am_ard_3-2-1_52JER_2024-03-26_final
2024-05-08 11:14:11	ga_s2am_ard_3-2-1_51KZP_2024-05-08_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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