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
2018-11-18 10:12:58	ga_s2am_ard_3-2-1_55KBR_2018-11-18_final.stac-item
2018-11-18 10:12:58	ga_s2am_ard_3-2-1_54KZA_2018-11-18_final.stac-item
2018-11-18 10:13:02	ga_s2am_ard_3-2-1_54KYA_2018-11-18_final.stac-item
2018-11-18 10:13:06	ga_s2am_ard_3-2-1_54KXA_2018-11-18_final.stac-item
2018-11-18 10:13:09	ga_s2am_ard_3-2-1_54KWA_2018-11-18_final.stac-item
2018-11-18 10:13:13	ga_s2am_ard_3-2-1_54KZV_2018-11-18_final.stac-item
2018-11-18 11:53:40	ga_s2am_ard_3-2-1_50KQA_2018-11-18_final.stac-item
2018-11-18 11:53:44	ga_s2am_ard_3-2-1_50KPA_2018-11-18_final.stac-item
2018-11-19 09:42:43	ga_s2am_ard_3-2-1_56KMA_2018-11-19_final.stac-item
2018-11-19 09:42:48	ga_s2am_ard_3-2-1_56KLA_2018-11-19_final.stac-item
2018-11-19 09:42:51	ga_s2am_ard_3-2-1_56KKA_2018-11-19_final.stac-item
2018-11-19 09:42:51	ga_s2am_ard_3-2-1_55KHR_2018-11-19_final.stac-item
2018-11-19 09:42:55	ga_s2am_ard_3-2-1_55KGR_2018-11-19_final.stac-item
2018-11-19 09:43:06	ga_s2am_ard_3-2-1_55KHQ_2018-11-19_final.stac-item
2018-11-27 10:43:06	ga_s2am_ard_3-2-1_53KQR_2018-11-27_final.stac-item
2018-11-27 10:43:11	ga_s2am_ard_3-2-1_53KPR_2018-11-27_final.stac-item
2018-11-27 10:43:14	ga_s2am_ard_3-2-1_53KNR_2018-11-27_final.stac-item
2018-11-27 10:43:18	ga_s2am_ard_3-2-1_53KMR_2018-11-27_final.stac-item
2018-11-28 10:12:56	ga_s2am_ard_3-2-1_55KBR_2018-11-28_final.stac-item
2018-11-28 10:12:56	ga_s2am_ard_3-2-1_54KZA_2018-11-28_final.stac-item
2018-11-28 10:13:00	ga_s2am_ard_3-2-1_54KYA_2018-11-28_final.stac-item
2018-11-28 10:13:03	ga_s2am_ard_3-2-1_54KXA_2018-11-28_final.stac-item
2018-11-28 10:13:07	ga_s2am_ard_3-2-1_54KWA_2018-11-28_final.stac-item
2018-11-28 10:13:11	ga_s2am_ard_3-2-1_54KZV_2018-11-28_final.stac-item
2018-11-28 11:53:38	ga_s2am_ard_3-2-1_50KQA_2018-11-28_final.stac-item
2018-11-28 11:53:41	ga_s2am_ard_3-2-1_50KPA_2018-11-28_final.stac-item
2018-11-28 11:53:45	ga_s2am_ard_3-2-1_50KNA_2018-11-28_final.stac-item
2018-11-28 11:53:48	ga_s2am_ard_3-2-1_50KMA_2018-11-28_final.stac-item
2018-12-08 11:53:38	ga_s2am_ard_3-2-1_50KQA_2018-12-08_final.stac-item
2018-12-08 11:53:42	ga_s2am_ard_3-2-1_50KPA_2018-12-08_final.stac-item
2018-12-08 11:53:45	ga_s2am_ard_3-2-1_50KNA_2018-12-08_final.stac-item
2018-12-08 11:53:48	ga_s2am_ard_3-2-1_50KMA_2018-12-08_final.stac-item
2018-12-09 09:42:41	ga_s2am_ard_3-2-1_56KMA_2018-12-09_final.stac-item
2018-12-09 09:42:46	ga_s2am_ard_3-2-1_56KLA_2018-12-09_final.stac-item
2018-12-09 09:42:49	ga_s2am_ard_3-2-1_56KKA_2018-12-09_final.stac-item
2018-12-09 09:42:53	ga_s2am_ard_3-2-1_55KGR_2018-12-09_final.stac-item
2018-12-09 09:43:04	ga_s2am_ard_3-2-1_55KHQ_2018-12-09_final.stac-item
2018-12-09 11:23:26	ga_s2am_ard_3-2-1_52KBA_2018-12-09_final.stac-item
2018-12-09 11:23:27	ga_s2am_ard_3-2-1_51KZR_2018-12-09_final.stac-item
2018-12-09 11:23:31	ga_s2am_ard_3-2-1_51KYR_2018-12-09_final.stac-item
2018-12-09 11:23:34	ga_s2am_ard_3-2-1_51KXR_2018-12-09_final.stac-item
2018-12-09 11:23:41	ga_s2am_ard_3-2-1_51KZQ_2018-12-09_final.stac-item
2019-02-04 11:13:27	ga_s2am_ard_3-2-1_52KEA_2019-02-04_final.stac-item
2019-02-04 11:13:30	ga_s2am_ard_3-2-1_52KDA_2019-02-04_final.stac-item
2019-02-04 11:13:33	ga_s2am_ard_3-2-1_52KCA_2019-02-04_final.stac-item
2019-02-04 11:13:36	ga_s2am_ard_3-2-1_52KBA_2019-02-04_final.stac-item
2019-02-04 11:13:37	ga_s2am_ard_3-2-1_51KZR_2019-02-04_final.stac-item
2019-02-04 11:13:51	ga_s2am_ard_3-2-1_51KZQ_2019-02-04_final.stac-item
2019-02-08 10:53:18	ga_s2am_ard_3-2-1_53KMR_2019-02-08_final.stac-item
2019-02-08 10:53:22	ga_s2am_ard_3-2-1_53KLR_2019-02-08_final.stac-item
2019-02-08 10:53:25	ga_s2am_ard_3-2-1_53KKR_2019-02-08_final.stac-item
2019-02-08 10:53:25	ga_s2am_ard_3-2-1_52KHA_2019-02-08_final.stac-item
2019-02-08 10:53:29	ga_s2am_ard_3-2-1_52KGA_2019-02-08_final.stac-item
2019-02-08 10:53:40	ga_s2am_ard_3-2-1_52KHV_2019-02-08_final.stac-item
2019-02-18 10:53:18	ga_s2am_ard_3-2-1_53KMR_2019-02-18_final.stac-item
2019-02-18 10:53:21	ga_s2am_ard_3-2-1_53KLR_2019-02-18_final.stac-item
2019-02-18 10:53:24	ga_s2am_ard_3-2-1_53KKR_2019-02-18_final.stac-item
2019-02-18 10:53:25	ga_s2am_ard_3-2-1_52KHA_2019-02-18_final.stac-item
2019-02-18 10:53:28	ga_s2am_ard_3-2-1_52KGA_2019-02-18_final.stac-item
2019-02-18 10:53:39	ga_s2am_ard_3-2-1_52KHV_2019-02-18_final.stac-item
2019-02-22 12:13:50	ga_s2am_ard_3-2-1_50KKA_2019-02-22_final.stac-item
2019-02-22 12:13:50	ga_s2am_ard_3-2-1_49KHR_2019-02-22_final.stac-item
2019-02-22 12:13:54	ga_s2am_ard_3-2-1_49KGR_2019-02-22_final.stac-item
2019-02-22 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2019-02-22_final.stac-item
2019-02-23 10:02:54	ga_s2am_ard_3-2-1_55KER_2019-02-23_final.stac-item
2019-02-23 10:02:58	ga_s2am_ard_3-2-1_55KDR_2019-02-23_final.stac-item
2019-02-23 10:03:02	ga_s2am_ard_3-2-1_55KCR_2019-02-23_final.stac-item
2019-02-23 10:03:05	ga_s2am_ard_3-2-1_55KBR_2019-02-23_final.stac-item
2019-02-23 10:03:05	ga_s2am_ard_3-2-1_54KZA_2019-02-23_final.stac-item
2019-02-23 10:03:20	ga_s2am_ard_3-2-1_54KZV_2019-02-23_final.stac-item
2019-05-13 10:33:17	ga_s2am_ard_3-2-1_54KUA_2019-05-13_final.stac-item
2019-05-13 10:33:20	ga_s2am_ard_3-2-1_54KTA_2019-05-13_final.stac-item
2019-05-13 10:33:20	ga_s2am_ard_3-2-1_53KRR_2019-05-13_final.stac-item
2019-05-13 10:33:24	ga_s2am_ard_3-2-1_53KQR_2019-05-13_final.stac-item
2019-05-13 10:33:28	ga_s2am_ard_3-2-1_53KPR_2019-05-13_final.stac-item
2019-05-13 10:33:35	ga_s2am_ard_3-2-1_53KRQ_2019-05-13_final.stac-item
2019-05-13 12:13:58	ga_s2am_ard_3-2-1_50KKA_2019-05-13_final.stac-item
2019-05-13 12:13:58	ga_s2am_ard_3-2-1_49KHR_2019-05-13_final.stac-item
2019-05-13 12:14:02	ga_s2am_ard_3-2-1_49KGR_2019-05-13_final.stac-item
2019-05-13 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2019-05-13_final.stac-item
2019-05-14 10:03:02	ga_s2am_ard_3-2-1_55KER_2019-05-14_final.stac-item
2019-05-14 10:03:06	ga_s2am_ard_3-2-1_55KDR_2019-05-14_final.stac-item
2019-05-14 10:03:10	ga_s2am_ard_3-2-1_55KCR_2019-05-14_final.stac-item
2019-05-14 10:03:13	ga_s2am_ard_3-2-1_55KBR_2019-05-14_final.stac-item
2019-05-14 10:03:13	ga_s2am_ard_3-2-1_54KZA_2019-05-14_final.stac-item
2019-05-14 10:03:28	ga_s2am_ard_3-2-1_54KZV_2019-05-14_final.stac-item
2019-05-22 11:03:26	ga_s2am_ard_3-2-1_52KHA_2019-05-22_final.stac-item
2019-05-22 11:03:31	ga_s2am_ard_3-2-1_52KGA_2019-05-22_final.stac-item
2019-05-22 11:03:34	ga_s2am_ard_3-2-1_52KFA_2019-05-22_final.stac-item
2019-05-22 11:03:38	ga_s2am_ard_3-2-1_52KEA_2019-05-22_final.stac-item
2019-05-24 10:03:01	ga_s2am_ard_3-2-1_55KER_2019-05-24_final.stac-item
2019-05-24 10:03:06	ga_s2am_ard_3-2-1_55KDR_2019-05-24_final.stac-item
2019-05-24 10:03:09	ga_s2am_ard_3-2-1_55KCR_2019-05-24_final.stac-item
2019-05-24 10:03:12	ga_s2am_ard_3-2-1_55KBR_2019-05-24_final.stac-item
2019-05-24 10:03:12	ga_s2am_ard_3-2-1_54KZA_2019-05-24_final.stac-item
2019-05-24 10:03:27	ga_s2am_ard_3-2-1_54KZV_2019-05-24_final.stac-item
2019-05-25 11:13:33	ga_s2am_ard_3-2-1_52KEA_2019-05-25_final.stac-item
2019-05-26 10:43:18	ga_s2am_ard_3-2-1_53KQR_2019-05-26_final.stac-item
2019-05-26 10:43:22	ga_s2am_ard_3-2-1_53KPR_2019-05-26_final.stac-item
2019-05-26 10:43:26	ga_s2am_ard_3-2-1_53KNR_2019-05-26_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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