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
2019-01-01 11:31:14	ga_s2am_ard_3-2-1_51LZE_2019-01-01_final.stac-item
2019-01-01 11:32:05	ga_s2am_ard_3-2-1_51KXB_2019-01-01_final.stac-item
2019-01-01 11:32:13	ga_s2am_ard_3-2-1_51KVB_2019-01-01_final.stac-item
2019-01-01 11:32:20	ga_s2am_ard_3-2-1_51KXA_2019-01-01_final.stac-item
2019-01-01 11:32:37	ga_s2am_ard_3-2-1_51KWV_2019-01-01_final.stac-item
2019-01-01 11:32:40	ga_s2am_ard_3-2-1_51KVV_2019-01-01_final.stac-item
2019-01-01 11:32:48	ga_s2am_ard_3-2-1_51KXU_2019-01-01_final.stac-item
2019-01-02 11:03:43	ga_s2am_ard_3-2-1_52KEV_2019-01-02_final.stac-item
2019-01-04 11:42:25	ga_s2am_ard_3-2-1_51KUA_2019-01-04_final.stac-item
2019-01-04 11:42:36	ga_s2am_ard_3-2-1_51KVV_2019-01-04_final.stac-item
2019-01-05 11:14:11	ga_s2am_ard_3-2-1_52JDT_2019-01-05_final.stac-item
2019-01-08 11:21:27	ga_s2am_ard_3-2-1_52LDJ_2019-01-08_final.stac-item
2019-01-08 11:22:55	ga_s2am_ard_3-2-1_51KXU_2019-01-08_final.stac-item
2019-01-11 11:31:16	ga_s2am_ard_3-2-1_51LZE_2019-01-11_final.stac-item
2019-01-11 11:32:07	ga_s2am_ard_3-2-1_51KXB_2019-01-11_final.stac-item
2019-01-11 11:32:15	ga_s2am_ard_3-2-1_51KVB_2019-01-11_final.stac-item
2019-01-11 11:32:21	ga_s2am_ard_3-2-1_51KXA_2019-01-11_final.stac-item
2019-01-11 11:32:39	ga_s2am_ard_3-2-1_51KWV_2019-01-11_final.stac-item
2019-01-11 11:32:42	ga_s2am_ard_3-2-1_51KVV_2019-01-11_final.stac-item
2019-01-11 11:32:50	ga_s2am_ard_3-2-1_51KXU_2019-01-11_final.stac-item
2019-01-14 11:42:09	ga_s2am_ard_3-2-1_51KVB_2019-01-14_final.stac-item
2019-01-14 11:42:38	ga_s2am_ard_3-2-1_51KVV_2019-01-14_final.stac-item
2019-01-18 11:22:56	ga_s2am_ard_3-2-1_51KXU_2019-01-18_final.stac-item
2019-01-21 11:32:08	ga_s2am_ard_3-2-1_51KXB_2019-01-21_final.stac-item
2019-01-21 11:32:16	ga_s2am_ard_3-2-1_51KVB_2019-01-21_final.stac-item
2019-01-21 11:32:22	ga_s2am_ard_3-2-1_51KXA_2019-01-21_final.stac-item
2019-01-21 11:32:37	ga_s2am_ard_3-2-1_51KXV_2019-01-21_final.stac-item
2019-01-21 11:32:40	ga_s2am_ard_3-2-1_51KWV_2019-01-21_final.stac-item
2019-01-21 11:32:43	ga_s2am_ard_3-2-1_51KVV_2019-01-21_final.stac-item
2019-01-22 11:04:14	ga_s2am_ard_3-2-1_52JET_2019-01-22_final.stac-item
2019-01-24 11:42:10	ga_s2am_ard_3-2-1_51KVB_2019-01-24_final.stac-item
2019-01-24 11:42:28	ga_s2am_ard_3-2-1_51KUA_2019-01-24_final.stac-item
2019-01-24 11:42:39	ga_s2am_ard_3-2-1_51KVV_2019-01-24_final.stac-item
2019-01-25 11:11:33	ga_s2am_ard_3-2-1_52LDJ_2019-01-25_final.stac-item
2019-01-31 11:32:08	ga_s2am_ard_3-2-1_51KXB_2019-01-31_final.stac-item
2019-01-31 11:32:22	ga_s2am_ard_3-2-1_51KXA_2019-01-31_final.stac-item
2019-01-31 11:32:40	ga_s2am_ard_3-2-1_51KWV_2019-01-31_final.stac-item
2019-01-31 11:32:43	ga_s2am_ard_3-2-1_51KVV_2019-01-31_final.stac-item
2019-01-31 11:32:51	ga_s2am_ard_3-2-1_51KXU_2019-01-31_final.stac-item
2019-02-02 12:14:04	ga_s2am_ard_3-2-1_50KKV_2019-02-02_final.stac-item
2019-02-02 12:14:06	ga_s2am_ard_3-2-1_49KHQ_2019-02-02_final.stac-item
2019-02-02 12:14:28	ga_s2am_ard_3-2-1_49JHN_2019-02-02_final.stac-item
2019-02-05 10:45:26	ga_s2am_ard_3-2-1_53JKH_2019-02-05_final.stac-item
2019-02-08 10:55:21	ga_s2am_ard_3-2-1_53JKH_2019-02-08_final.stac-item
2019-02-09 12:03:56	ga_s2am_ard_3-2-1_50KKA_2019-02-09_final.stac-item
2019-02-09 12:04:10	ga_s2am_ard_3-2-1_50KKV_2019-02-09_final.stac-item
2019-02-09 12:04:39	ga_s2am_ard_3-2-1_50JKT_2019-02-09_final.stac-item
2019-02-12 12:13:51	ga_s2am_ard_3-2-1_50KKA_2019-02-12_final.stac-item
2019-02-12 12:14:04	ga_s2am_ard_3-2-1_50KKV_2019-02-12_final.stac-item
2019-02-12 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2019-02-12_final.stac-item
2019-02-18 10:54:59	ga_s2am_ard_3-2-1_52JFQ_2019-02-18_final.stac-item
2019-02-19 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2019-02-19_final.stac-item
2019-02-19 12:04:39	ga_s2am_ard_3-2-1_49JHN_2019-02-19_final.stac-item
2019-02-19 12:04:39	ga_s2am_ard_3-2-1_50JKT_2019-02-19_final.stac-item
2019-02-21 11:01:35	ga_s2am_ard_3-2-1_52LFJ_2019-02-21_final.stac-item
2019-02-22 12:14:03	ga_s2am_ard_3-2-1_50KKV_2019-02-22_final.stac-item
2019-02-25 10:45:18	ga_s2am_ard_3-2-1_53JMH_2019-02-25_final.stac-item
2019-03-03 11:00:25	ga_s2am_ard_3-2-1_52LHN_2019-03-03_final.stac-item
2019-03-03 11:00:32	ga_s2am_ard_3-2-1_52LGN_2019-03-03_final.stac-item
2019-03-04 12:15:14	ga_s2am_ard_3-2-1_49JGK_2019-03-04_final.stac-item
2019-03-05 11:46:38	ga_s2am_ard_3-2-1_50HQJ_2019-03-05_final.stac-item
2019-03-05 11:46:50	ga_s2am_ard_3-2-1_50HMJ_2019-03-05_final.stac-item
2019-03-06 11:10:23	ga_s2am_ard_3-2-1_52LGN_2019-03-06_final.stac-item
2019-03-06 11:10:38	ga_s2am_ard_3-2-1_52LGM_2019-03-06_final.stac-item
2019-03-08 11:56:12	ga_s2am_ard_3-2-1_50JNL_2019-03-08_final.stac-item
2019-03-08 11:57:00	ga_s2am_ard_3-2-1_50HMH_2019-03-08_final.stac-item
2019-03-11 12:05:50	ga_s2am_ard_3-2-1_50JKN_2019-03-11_final.stac-item
2019-03-13 11:00:26	ga_s2am_ard_3-2-1_52LHN_2019-03-13_final.stac-item
2019-03-15 11:46:09	ga_s2am_ard_3-2-1_50JMM_2019-03-15_final.stac-item
2019-03-16 11:10:21	ga_s2am_ard_3-2-1_52LHN_2019-03-16_final.stac-item
2019-03-16 11:11:12	ga_s2am_ard_3-2-1_52LFK_2019-03-16_final.stac-item
2019-03-16 11:11:27	ga_s2am_ard_3-2-1_52LFJ_2019-03-16_final.stac-item
2019-03-21 12:03:57	ga_s2am_ard_3-2-1_50KKA_2019-03-21_final.stac-item
2019-03-21 12:05:53	ga_s2am_ard_3-2-1_50JKN_2019-03-21_final.stac-item
2019-03-23 11:00:29	ga_s2am_ard_3-2-1_52LHN_2019-03-23_final.stac-item
2019-03-23 11:00:35	ga_s2am_ard_3-2-1_52LGN_2019-03-23_final.stac-item
2019-03-25 11:46:07	ga_s2am_ard_3-2-1_50JMM_2019-03-25_final.stac-item
2019-03-25 11:46:18	ga_s2am_ard_3-2-1_50JPL_2019-03-25_final.stac-item
2019-03-25 11:46:21	ga_s2am_ard_3-2-1_50JNL_2019-03-25_final.stac-item
2019-03-26 11:10:24	ga_s2am_ard_3-2-1_52LHN_2019-03-26_final.stac-item
2019-03-26 11:10:28	ga_s2am_ard_3-2-1_52LGN_2019-03-26_final.stac-item
2019-03-26 11:10:42	ga_s2am_ard_3-2-1_52LGM_2019-03-26_final.stac-item
2019-03-28 11:56:25	ga_s2am_ard_3-2-1_50JLL_2019-03-28_final.stac-item
2019-03-31 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2019-03-31_final.stac-item
2019-03-31 12:05:55	ga_s2am_ard_3-2-1_50JKN_2019-03-31_final.stac-item
2019-04-04 11:45:44	ga_s2am_ard_3-2-1_51JTH_2019-04-04_final.stac-item
2019-04-07 11:55:06	ga_s2am_ard_3-2-1_50JLS_2019-04-07_final.stac-item
2019-04-07 11:55:36	ga_s2am_ard_3-2-1_50JNP_2019-04-07_final.stac-item
2019-04-10 12:05:39	ga_s2am_ard_3-2-1_50JLP_2019-04-10_final.stac-item
2019-04-17 11:55:44	ga_s2am_ard_3-2-1_50JLP_2019-04-17_final.stac-item
2019-04-18 11:24:58	ga_s2am_ard_3-2-1_51JXL_2019-04-18_final.stac-item
2019-04-18 11:25:34	ga_s2am_ard_3-2-1_51JVJ_2019-04-18_final.stac-item
2019-04-20 10:26:10	ga_s2am_ard_3-2-1_53HPE_2019-04-20_final.stac-item
2019-04-20 12:04:57	ga_s2am_ard_3-2-1_50JLS_2019-04-20_final.stac-item
2019-04-21 11:35:07	ga_s2am_ard_3-2-1_51JTL_2019-04-21_final.stac-item
2019-04-23 10:35:52	ga_s2am_ard_3-2-1_53JPF_2019-04-23_final.stac-item
2019-04-23 10:36:06	ga_s2am_ard_3-2-1_53HPE_2019-04-23_final.stac-item
2019-04-24 11:44:54	ga_s2am_ard_3-2-1_51JUL_2019-04-24_final.stac-item
2019-04-24 11:45:35	ga_s2am_ard_3-2-1_50JQP_2019-04-24_final.stac-item
2019-04-27 11:55:19	ga_s2am_ard_3-2-1_50JPQ_2019-04-27_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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