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
2018-03-05 10:47:21	ga_s2am_ard_3-2-1_53KKA_2018-03-05_final.stac-item
2018-03-05 10:47:21	ga_s2am_ard_3-2-1_53KKB_2018-03-05_final.stac-item
2018-03-05 10:47:21	ga_s2am_ard_3-2-1_53KLA_2018-03-05_final.stac-item
2018-03-05 10:47:21	ga_s2am_ard_3-2-1_53KLB_2018-03-05_final.stac-item
2018-03-05 10:47:21	ga_s2am_ard_3-2-1_53KMB_2018-03-05_final.stac-item
2018-03-05 10:47:21	ga_s2am_ard_3-2-1_53KNB_2018-03-05_final.stac-item
2018-03-07 09:50:50	ga_s2am_ard_3-2-1_56KKF_2018-03-07_final.stac-item
2018-03-07 09:50:50	ga_s2am_ard_3-2-1_55KFA_2018-03-07_final.stac-item
2018-03-07 09:50:50	ga_s2am_ard_3-2-1_55KFB_2018-03-07_final.stac-item
2018-03-07 09:50:50	ga_s2am_ard_3-2-1_55KGB_2018-03-07_final.stac-item
2018-03-08 10:57:12	ga_s2am_ard_3-2-1_53KKA_2018-03-08_final.stac-item
2018-03-08 10:57:12	ga_s2am_ard_3-2-1_53KKB_2018-03-08_final.stac-item
2018-03-08 10:57:12	ga_s2am_ard_3-2-1_53KLA_2018-03-08_final.stac-item
2018-03-08 10:57:12	ga_s2am_ard_3-2-1_53KLB_2018-03-08_final.stac-item
2018-03-08 10:57:12	ga_s2am_ard_3-2-1_52KFF_2018-03-08_final.stac-item
2018-03-08 10:57:12	ga_s2am_ard_3-2-1_52KFG_2018-03-08_final.stac-item
2018-03-08 10:57:12	ga_s2am_ard_3-2-1_52KGF_2018-03-08_final.stac-item
2018-03-08 10:57:12	ga_s2am_ard_3-2-1_52KGG_2018-03-08_final.stac-item
2018-03-08 10:57:12	ga_s2am_ard_3-2-1_52KHF_2018-03-08_final.stac-item
2018-03-08 10:57:12	ga_s2am_ard_3-2-1_52KHG_2018-03-08_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KKA_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KKB_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KLA_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KLB_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KMB_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KNB_2018-03-15_final.stac-item
2018-03-17 09:50:50	ga_s2am_ard_3-2-1_56KKF_2018-03-17_final.stac-item
2018-03-20 09:57:04	ga_s2am_ard_3-2-1_55KCA_2018-03-20_final.stac-item
2018-03-20 09:57:04	ga_s2am_ard_3-2-1_55KCB_2018-03-20_final.stac-item
2018-03-20 09:57:04	ga_s2am_ard_3-2-1_55KDB_2018-03-20_final.stac-item
2018-03-20 09:57:04	ga_s2am_ard_3-2-1_55KEB_2018-03-20_final.stac-item
2018-03-20 09:57:04	ga_s2am_ard_3-2-1_55KFB_2018-03-20_final.stac-item
2019-03-23 11:01:50	ga_s2am_ard_3-2-1_53KLB_2019-03-23_final.stac-item
2019-03-23 11:01:54	ga_s2am_ard_3-2-1_53KKB_2019-03-23_final.stac-item
2019-03-23 11:01:55	ga_s2am_ard_3-2-1_52KHG_2019-03-23_final.stac-item
2019-03-23 11:01:59	ga_s2am_ard_3-2-1_52KGG_2019-03-23_final.stac-item
2019-03-23 11:02:02	ga_s2am_ard_3-2-1_53KLA_2019-03-23_final.stac-item
2019-03-23 11:02:02	ga_s2am_ard_3-2-1_52KFG_2019-03-23_final.stac-item
2019-03-23 11:02:09	ga_s2am_ard_3-2-1_53KKA_2019-03-23_final.stac-item
2019-03-23 11:02:10	ga_s2am_ard_3-2-1_52KHF_2019-03-23_final.stac-item
2019-03-23 11:02:13	ga_s2am_ard_3-2-1_52KGF_2019-03-23_final.stac-item
2019-03-23 11:02:17	ga_s2am_ard_3-2-1_52KFF_2019-03-23_final.stac-item
2019-04-08 09:41:43	ga_s2am_ard_3-2-1_56KLF_2019-04-08_final.stac-item
2019-04-08 09:41:46	ga_s2am_ard_3-2-1_56KKF_2019-04-08_final.stac-item
2019-04-09 10:51:52	ga_s2am_ard_3-2-1_53KNB_2019-04-09_final.stac-item
2019-04-09 10:51:56	ga_s2am_ard_3-2-1_53KMB_2019-04-09_final.stac-item
2019-04-09 10:51:59	ga_s2am_ard_3-2-1_53KLB_2019-04-09_final.stac-item
2019-04-09 10:52:03	ga_s2am_ard_3-2-1_53KKB_2019-04-09_final.stac-item
2019-04-09 10:52:13	ga_s2am_ard_3-2-1_53KLA_2019-04-09_final.stac-item
2019-04-09 10:52:16	ga_s2am_ard_3-2-1_53KKA_2019-04-09_final.stac-item
2019-04-11 09:51:32	ga_s2am_ard_3-2-1_55KGB_2019-04-11_final.stac-item
2019-04-11 09:51:35	ga_s2am_ard_3-2-1_55KFB_2019-04-11_final.stac-item
2019-04-11 09:51:42	ga_s2am_ard_3-2-1_56KKF_2019-04-11_final.stac-item
2019-04-11 09:51:50	ga_s2am_ard_3-2-1_55KFA_2019-04-11_final.stac-item
2019-07-07 11:22:05	ga_s2am_ard_3-2-1_52KDG_2019-07-07_final.stac-item
2019-07-07 11:22:10	ga_s2am_ard_3-2-1_52KCG_2019-07-07_final.stac-item
2019-07-07 11:22:13	ga_s2am_ard_3-2-1_52KBG_2019-07-07_final.stac-item
2019-07-07 11:22:14	ga_s2am_ard_3-2-1_51KZB_2019-07-07_final.stac-item
2019-07-07 11:22:17	ga_s2am_ard_3-2-1_51KYB_2019-07-07_final.stac-item
2019-07-07 11:22:24	ga_s2am_ard_3-2-1_52KCF_2019-07-07_final.stac-item
2019-07-07 11:22:27	ga_s2am_ard_3-2-1_52KBF_2019-07-07_final.stac-item
2019-07-07 11:22:28	ga_s2am_ard_3-2-1_51KZA_2019-07-07_final.stac-item
2019-07-07 11:22:32	ga_s2am_ard_3-2-1_51KYA_2019-07-07_final.stac-item
2019-07-17 11:22:06	ga_s2am_ard_3-2-1_52KDG_2019-07-17_final.stac-item
2019-07-17 11:22:10	ga_s2am_ard_3-2-1_52KCG_2019-07-17_final.stac-item
2019-07-17 11:22:13	ga_s2am_ard_3-2-1_52KBG_2019-07-17_final.stac-item
2019-07-17 11:22:14	ga_s2am_ard_3-2-1_51KZB_2019-07-17_final.stac-item
2019-07-17 11:22:17	ga_s2am_ard_3-2-1_51KYB_2019-07-17_final.stac-item
2019-07-17 11:22:24	ga_s2am_ard_3-2-1_52KCF_2019-07-17_final.stac-item
2019-07-17 11:22:28	ga_s2am_ard_3-2-1_52KBF_2019-07-17_final.stac-item
2019-07-17 11:22:29	ga_s2am_ard_3-2-1_51KZA_2019-07-17_final.stac-item
2019-07-17 11:22:32	ga_s2am_ard_3-2-1_51KYA_2019-07-17_final.stac-item
2019-07-19 10:21:56	ga_s2am_ard_3-2-1_54KYF_2019-07-19_final.stac-item
2019-07-19 10:22:00	ga_s2am_ard_3-2-1_54KXF_2019-07-19_final.stac-item
2019-08-02 11:42:14	ga_s2am_ard_3-2-1_51KWB_2019-08-02_final.stac-item
2019-08-02 11:42:18	ga_s2am_ard_3-2-1_51KVB_2019-08-02_final.stac-item
2019-08-02 11:42:36	ga_s2am_ard_3-2-1_51KUA_2019-08-02_final.stac-item
2019-10-09 11:01:54	ga_s2am_ard_3-2-1_53KLB_2019-10-09_final.stac-item
2019-10-09 11:01:58	ga_s2am_ard_3-2-1_53KKB_2019-10-09_final.stac-item
2019-10-09 11:01:59	ga_s2am_ard_3-2-1_52KHG_2019-10-09_final.stac-item
2019-10-09 11:02:04	ga_s2am_ard_3-2-1_53KLA_2019-10-09_final.stac-item
2019-10-09 11:02:06	ga_s2am_ard_3-2-1_53KKB_2019-10-09_final.stac-item
2019-10-09 11:02:06	ga_s2am_ard_3-2-1_53KKA_2019-10-09_final.stac-item
2019-10-09 11:02:06	ga_s2am_ard_3-2-1_52KHF_2019-10-09_final.stac-item
2019-10-09 11:02:06	ga_s2am_ard_3-2-1_52KHG_2019-10-09_final.stac-item
2019-10-09 11:02:08	ga_s2am_ard_3-2-1_52KGG_2019-10-09_final.stac-item
2019-10-09 11:02:09	ga_s2am_ard_3-2-1_52KFG_2019-10-09_final.stac-item
2019-10-09 11:02:13	ga_s2am_ard_3-2-1_53KKA_2019-10-09_final.stac-item
2019-10-09 11:02:14	ga_s2am_ard_3-2-1_52KHF_2019-10-09_final.stac-item
2019-10-09 11:02:18	ga_s2am_ard_3-2-1_52KGF_2019-10-09_final.stac-item
2019-10-09 11:02:21	ga_s2am_ard_3-2-1_52KFF_2019-10-09_final.stac-item
2019-10-10 10:31:45	ga_s2am_ard_3-2-1_54KVG_2019-10-10_final.stac-item
2019-10-10 10:31:48	ga_s2am_ard_3-2-1_54KUG_2019-10-10_final.stac-item
2019-10-10 10:31:51	ga_s2am_ard_3-2-1_54KTG_2019-10-10_final.stac-item
2019-10-10 10:31:53	ga_s2am_ard_3-2-1_53KRB_2019-10-10_final
2019-10-16 10:51:54	ga_s2am_ard_3-2-1_53KNB_2019-10-16_final.stac-item
2019-10-16 10:51:57	ga_s2am_ard_3-2-1_53KMB_2019-10-16_final.stac-item
2019-10-16 10:52:00	ga_s2am_ard_3-2-1_53KLB_2019-10-16_final.stac-item
2019-10-16 10:52:05	ga_s2am_ard_3-2-1_53KKB_2019-10-16_final.stac-item
2019-10-16 10:52:15	ga_s2am_ard_3-2-1_53KLA_2019-10-16_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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