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
2017-10-18 11:30:06	ga_s2am_ard_3-2-1_51LWE_2017-10-18_final.stac-item
2017-10-18 11:30:06	ga_s2am_ard_3-2-1_51LYE_2017-10-18_final.stac-item
2017-10-18 11:30:06	ga_s2am_ard_3-2-1_51LZE_2017-10-18_final.stac-item
2017-10-18 11:30:06	ga_s2am_ard_3-2-1_52LBK_2017-10-18_final.stac-item
2017-11-13 11:49:19	ga_s2am_ard_3-2-1_51LUE_2017-11-13_final.stac-item
2017-11-13 11:49:19	ga_s2am_ard_3-2-1_51LUF_2017-11-13_final.stac-item
2017-11-19 10:28:06	ga_s2am_ard_3-2-1_54LWL_2017-11-19_final.stac-item
2017-12-03 11:49:15	ga_s2am_ard_3-2-1_51LUE_2017-12-03_final.stac-item
2017-12-03 11:49:15	ga_s2am_ard_3-2-1_51LUF_2017-12-03_final.stac-item
2018-07-27 10:27:09	ga_s2am_ard_3-2-1_54LWL_2018-07-27_final.stac-item
2018-07-29 11:07:13	ga_s2am_ard_3-2-1_52LFK_2018-07-29_final.stac-item
2018-07-29 11:07:13	ga_s2am_ard_3-2-1_52LFL_2018-07-29_final.stac-item
2018-07-29 11:07:13	ga_s2am_ard_3-2-1_52LGK_2018-07-29_final.stac-item
2018-07-29 11:07:13	ga_s2am_ard_3-2-1_52LGL_2018-07-29_final.stac-item
2018-08-21 11:16:58	ga_s2am_ard_3-2-1_51LZE_2018-08-21_final.stac-item
2018-08-21 11:16:58	ga_s2am_ard_3-2-1_52LBK_2018-08-21_final.stac-item
2018-08-25 10:57:15	ga_s2am_ard_3-2-1_52LGK_2018-08-25_final.stac-item
2018-08-25 10:57:15	ga_s2am_ard_3-2-1_53LKE_2018-08-25_final.stac-item
2018-08-25 10:57:15	ga_s2am_ard_3-2-1_53LKF_2018-08-25_final.stac-item
2018-08-25 10:57:15	ga_s2am_ard_3-2-1_52LGL_2018-08-25_final.stac-item
2018-08-25 10:57:15	ga_s2am_ard_3-2-1_52LHK_2018-08-25_final.stac-item
2018-08-25 10:57:15	ga_s2am_ard_3-2-1_52LHL_2018-08-25_final.stac-item
2018-08-25 10:57:15	ga_s2am_ard_3-2-1_53LLE_2018-08-25_final.stac-item
2018-08-25 10:57:15	ga_s2am_ard_3-2-1_53LLF_2018-08-25_final.stac-item
2018-08-25 10:57:15	ga_s2am_ard_3-2-1_53LMF_2018-08-25_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_51LUE_2018-08-27_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_51LUF_2018-08-27_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_51LVF_2018-08-27_final.stac-item
2018-08-28 11:07:11	ga_s2am_ard_3-2-1_52LFK_2018-08-28_final.stac-item
2018-08-28 11:07:11	ga_s2am_ard_3-2-1_52LFL_2018-08-28_final.stac-item
2018-08-28 11:07:11	ga_s2am_ard_3-2-1_52LGK_2018-08-28_final.stac-item
2018-08-28 11:07:11	ga_s2am_ard_3-2-1_52LGL_2018-08-28_final.stac-item
2018-08-28 11:10:58	ga_s2am_ard_3-2-1_52LFK_2018-08-28_final.stac-item
2018-08-28 11:10:58	ga_s2am_ard_3-2-1_52LFL_2018-08-28_final.stac-item
2018-08-28 11:10:58	ga_s2am_ard_3-2-1_52LGK_2018-08-28_final.stac-item
2018-08-28 11:10:58	ga_s2am_ard_3-2-1_52LGL_2018-08-28_final.stac-item
2019-05-11 11:31:22	ga_s2am_ard_3-2-1_52LBK_2019-05-11_final.stac-item
2019-05-11 11:31:24	ga_s2am_ard_3-2-1_51LZE_2019-05-11_final.stac-item
2019-05-11 11:31:28	ga_s2am_ard_3-2-1_51LYE_2019-05-11_final.stac-item
2019-05-11 11:31:34	ga_s2am_ard_3-2-1_51LWE_2019-05-11_final.stac-item
2019-05-15 11:11:01	ga_s2am_ard_3-2-1_52LGL_2019-05-15_final.stac-item
2019-05-15 11:11:05	ga_s2am_ard_3-2-1_52LFL_2019-05-15_final.stac-item
2019-05-15 11:11:16	ga_s2am_ard_3-2-1_52LGK_2019-05-15_final.stac-item
2019-05-15 11:11:20	ga_s2am_ard_3-2-1_52LFK_2019-05-15_final.stac-item
2019-05-19 10:50:53	ga_s2am_ard_3-2-1_53LPF_2019-05-19_final.stac-item
2019-05-19 10:50:56	ga_s2am_ard_3-2-1_53LNF_2019-05-19_final.stac-item
2019-05-19 10:51:00	ga_s2am_ard_3-2-1_53LMF_2019-05-19_final.stac-item
2019-05-19 10:51:03	ga_s2am_ard_3-2-1_53LLF_2019-05-19_final.stac-item
2019-05-19 10:51:07	ga_s2am_ard_3-2-1_53LPE_2019-05-19_final.stac-item
2019-05-19 10:51:11	ga_s2am_ard_3-2-1_53LNE_2019-05-19_final.stac-item
2019-05-19 10:51:17	ga_s2am_ard_3-2-1_53LLE_2019-05-19_final.stac-item
2019-05-27 10:10:43	ga_s2am_ard_3-2-1_54LZL_2019-05-27_final.stac-item
2019-05-27 10:10:53	ga_s2am_ard_3-2-1_55LCE_2019-05-27_final.stac-item
2019-05-27 10:10:56	ga_s2am_ard_3-2-1_55LBE_2019-05-27_final.stac-item
2019-05-27 10:10:58	ga_s2am_ard_3-2-1_54LZK_2019-05-27_final.stac-item
2019-06-02 10:30:43	ga_s2am_ard_3-2-1_54LWL_2019-06-02_final.stac-item
2019-06-04 11:11:00	ga_s2am_ard_3-2-1_52LGL_2019-06-04_final.stac-item
2019-06-04 11:11:04	ga_s2am_ard_3-2-1_52LFL_2019-06-04_final.stac-item
2019-06-04 11:11:14	ga_s2am_ard_3-2-1_52LGK_2019-06-04_final.stac-item
2019-06-04 11:11:18	ga_s2am_ard_3-2-1_52LFK_2019-06-04_final.stac-item
2019-06-05 10:40:56	ga_s2am_ard_3-2-1_53LPF_2019-06-05_final.stac-item
2019-06-05 10:41:11	ga_s2am_ard_3-2-1_53LPE_2019-06-05_final.stac-item
2019-06-06 10:10:42	ga_s2am_ard_3-2-1_54LZL_2019-06-06_final.stac-item
2019-06-06 10:10:52	ga_s2am_ard_3-2-1_55LCE_2019-06-06_final.stac-item
2019-06-06 10:10:55	ga_s2am_ard_3-2-1_55LBE_2019-06-06_final.stac-item
2019-06-06 10:10:57	ga_s2am_ard_3-2-1_54LZK_2019-06-06_final.stac-item
2019-06-15 10:40:57	ga_s2am_ard_3-2-1_53LPF_2019-06-15_final.stac-item
2019-06-15 10:41:12	ga_s2am_ard_3-2-1_53LPE_2019-06-15_final.stac-item
2019-06-16 10:10:44	ga_s2am_ard_3-2-1_54LZL_2019-06-16_final.stac-item
2019-06-16 10:10:54	ga_s2am_ard_3-2-1_55LCE_2019-06-16_final.stac-item
2019-06-16 10:10:57	ga_s2am_ard_3-2-1_55LBE_2019-06-16_final.stac-item
2019-06-16 10:10:58	ga_s2am_ard_3-2-1_54LZK_2019-06-16_final.stac-item
2019-06-18 10:50:53	ga_s2am_ard_3-2-1_53LPF_2019-06-18_final.stac-item
2019-06-18 10:50:56	ga_s2am_ard_3-2-1_53LNF_2019-06-18_final.stac-item
2019-06-18 10:51:00	ga_s2am_ard_3-2-1_53LMF_2019-06-18_final.stac-item
2019-06-18 10:51:03	ga_s2am_ard_3-2-1_53LLF_2019-06-18_final.stac-item
2019-06-18 10:51:07	ga_s2am_ard_3-2-1_53LPE_2019-06-18_final.stac-item
2019-06-18 10:51:11	ga_s2am_ard_3-2-1_53LNE_2019-06-18_final.stac-item
2019-06-18 10:51:17	ga_s2am_ard_3-2-1_53LLE_2019-06-18_final.stac-item
2019-06-21 11:00:52	ga_s2am_ard_3-2-1_53LMF_2019-06-21_final.stac-item
2019-06-21 11:00:58	ga_s2am_ard_3-2-1_53LLF_2019-06-21_final.stac-item
2019-06-21 11:01:02	ga_s2am_ard_3-2-1_53LKF_2019-06-21_final.stac-item
2019-06-21 11:01:03	ga_s2am_ard_3-2-1_52LHL_2019-06-21_final.stac-item
2019-06-21 11:01:06	ga_s2am_ard_3-2-1_52LGL_2019-06-21_final.stac-item
2019-06-21 11:01:13	ga_s2am_ard_3-2-1_53LLE_2019-06-21_final.stac-item
2019-06-21 11:01:16	ga_s2am_ard_3-2-1_53LKE_2019-06-21_final.stac-item
2019-06-21 11:01:18	ga_s2am_ard_3-2-1_52LHK_2019-06-21_final.stac-item
2019-06-21 11:01:21	ga_s2am_ard_3-2-1_52LGK_2019-06-21_final.stac-item
2019-08-17 10:50:52	ga_s2am_ard_3-2-1_53LPF_2019-08-17_final.stac-item
2019-08-17 10:50:56	ga_s2am_ard_3-2-1_53LNF_2019-08-17_final.stac-item
2019-08-17 10:50:59	ga_s2am_ard_3-2-1_53LMF_2019-08-17_final.stac-item
2019-08-17 10:51:03	ga_s2am_ard_3-2-1_53LLF_2019-08-17_final.stac-item
2019-08-17 10:51:07	ga_s2am_ard_3-2-1_53LPE_2019-08-17_final.stac-item
2019-08-17 10:51:10	ga_s2am_ard_3-2-1_53LNE_2019-08-17_final.stac-item
2019-08-17 10:51:16	ga_s2am_ard_3-2-1_53LLE_2019-08-17_final.stac-item
2019-08-25 10:10:42	ga_s2am_ard_3-2-1_54LZL_2019-08-25_final.stac-item
2019-08-25 10:10:52	ga_s2am_ard_3-2-1_55LCE_2019-08-25_final.stac-item
2019-08-25 10:10:55	ga_s2am_ard_3-2-1_55LBE_2019-08-25_final.stac-item
2019-08-25 10:10:57	ga_s2am_ard_3-2-1_54LZK_2019-08-25_final.stac-item
2019-09-02 11:11:02	ga_s2am_ard_3-2-1_52LFL_2019-09-02_final.stac-item

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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