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
2018-12-14 12:14:47	ga_s2am_ard_3-2-1_49JGM_2018-12-14_final.stac-item
2018-12-14 12:14:51	ga_s2am_ard_3-2-1_49JFM_2018-12-14_final.stac-item
2018-12-15 10:03:52	ga_s2am_ard_3-2-1_55JDM_2018-12-15_final.stac-item
2018-12-15 10:03:56	ga_s2am_ard_3-2-1_55JCM_2018-12-15_final.stac-item
2018-12-15 10:03:59	ga_s2am_ard_3-2-1_54JZS_2018-12-15_final.stac-item
2018-12-15 10:03:59	ga_s2am_ard_3-2-1_55JBM_2018-12-15_final.stac-item
2018-12-15 10:04:02	ga_s2am_ard_3-2-1_54JYS_2018-12-15_final.stac-item
2018-12-16 11:14:23	ga_s2am_ard_3-2-1_52JDS_2018-12-16_final.stac-item
2018-12-16 11:14:26	ga_s2am_ard_3-2-1_52JCS_2018-12-16_final.stac-item
2018-12-16 11:14:29	ga_s2am_ard_3-2-1_51JZM_2018-12-16_final.stac-item
2018-12-16 11:14:29	ga_s2am_ard_3-2-1_52JBS_2018-12-16_final.stac-item
2018-12-16 11:14:33	ga_s2am_ard_3-2-1_51JYM_2018-12-16_final.stac-item
2018-12-17 10:44:08	ga_s2am_ard_3-2-1_53JPM_2018-12-17_final.stac-item
2018-12-17 10:44:12	ga_s2am_ard_3-2-1_53JNM_2018-12-17_final.stac-item
2018-12-17 10:44:16	ga_s2am_ard_3-2-1_53JMM_2018-12-17_final.stac-item
2018-12-17 10:44:19	ga_s2am_ard_3-2-1_53JLM_2018-12-17_final.stac-item
2018-12-23 09:23:46	ga_s2am_ard_3-2-1_56JNS_2018-12-22_final.stac-item
2018-12-23 11:04:16	ga_s2am_ard_3-2-1_52JGS_2018-12-23_final.stac-item
2018-12-23 11:04:21	ga_s2am_ard_3-2-1_52JFS_2018-12-23_final.stac-item
2018-12-23 11:04:24	ga_s2am_ard_3-2-1_52JES_2018-12-23_final.stac-item
2018-12-23 11:04:28	ga_s2am_ard_3-2-1_52JDS_2018-12-23_final.stac-item
2018-12-26 11:14:24	ga_s2am_ard_3-2-1_52JDS_2018-12-26_final.stac-item
2018-12-26 11:14:27	ga_s2am_ard_3-2-1_52JCS_2018-12-26_final.stac-item
2018-12-26 11:14:30	ga_s2am_ard_3-2-1_51JZM_2018-12-26_final.stac-item
2018-12-26 11:14:31	ga_s2am_ard_3-2-1_52JBS_2018-12-26_final.stac-item
2018-12-26 11:14:34	ga_s2am_ard_3-2-1_51JYM_2018-12-26_final.stac-item
2019-01-03 10:34:08	ga_s2am_ard_3-2-1_53JRM_2019-01-03_final.stac-item
2019-01-03 10:34:09	ga_s2am_ard_3-2-1_54JTS_2019-01-03_final.stac-item
2019-01-03 10:34:12	ga_s2am_ard_3-2-1_53JQM_2019-01-03_final.stac-item
2019-01-03 10:34:16	ga_s2am_ard_3-2-1_53JPM_2019-01-03_final.stac-item
2019-01-03 10:34:19	ga_s2am_ard_3-2-1_53JNM_2019-01-03_final.stac-item
2019-01-03 12:14:50	ga_s2am_ard_3-2-1_49JGM_2019-01-03_final.stac-item
2019-01-03 12:14:54	ga_s2am_ard_3-2-1_49JFM_2019-01-03_final.stac-item
2019-01-05 11:14:26	ga_s2am_ard_3-2-1_52JDS_2019-01-05_final.stac-item
2019-01-05 11:14:29	ga_s2am_ard_3-2-1_52JCS_2019-01-05_final.stac-item
2019-01-05 11:14:32	ga_s2am_ard_3-2-1_51JZM_2019-01-05_final.stac-item
2019-01-05 11:14:32	ga_s2am_ard_3-2-1_52JBS_2019-01-05_final.stac-item
2019-01-05 11:14:36	ga_s2am_ard_3-2-1_51JYM_2019-01-05_final.stac-item
2019-04-08 11:24:33	ga_s2am_ard_3-2-1_51JZM_2019-04-08_final.stac-item
2019-04-08 11:24:34	ga_s2am_ard_3-2-1_52JBS_2019-04-08_final.stac-item
2019-04-08 11:24:38	ga_s2am_ard_3-2-1_51JYM_2019-04-08_final.stac-item
2019-04-08 11:24:42	ga_s2am_ard_3-2-1_51JXM_2019-04-08_final.stac-item
2019-04-08 11:24:45	ga_s2am_ard_3-2-1_51JWM_2019-04-08_final.stac-item
2022-09-12 11:34:50	ga_s2am_ard_3-2-1_51JWM_2022-09-12_final.stac-item
2022-09-12 11:34:54	ga_s2am_ard_3-2-1_51JVM_2022-09-12_final.stac-item
2022-09-12 11:34:57	ga_s2am_ard_3-2-1_51JUM_2022-09-12_final.stac-item
2022-09-12 11:34:59	ga_s2am_ard_3-2-1_50JRS_2022-09-12_final.stac-item
2022-09-12 11:35:00	ga_s2am_ard_3-2-1_51JTM_2022-09-12_final.stac-item
2022-09-15 11:44:50	ga_s2am_ard_3-2-1_51JUM_2022-09-15_final.stac-item
2022-09-15 11:44:54	ga_s2am_ard_3-2-1_50JRS_2022-09-15_final.stac-item
2022-09-15 11:44:55	ga_s2am_ard_3-2-1_51JTM_2022-09-15_final.stac-item
2022-09-15 11:44:58	ga_s2am_ard_3-2-1_50JQS_2022-09-15_final.stac-item
2022-09-15 11:45:02	ga_s2am_ard_3-2-1_50JPS_2022-09-15_final.stac-item
2022-09-17 10:44:30	ga_s2am_ard_3-2-1_53JNM_2022-09-17_final.stac-item
2022-09-17 10:44:33	ga_s2am_ard_3-2-1_53JMM_2022-09-17_final.stac-item
2022-09-17 10:44:36	ga_s2am_ard_3-2-1_53JLM_2022-09-17_final.stac-item
2022-09-20 10:54:31	ga_s2am_ard_3-2-1_53JLM_2022-09-20_final.stac-item
2022-09-20 10:54:34	ga_s2am_ard_3-2-1_52JHS_2022-09-20_final.stac-item
2022-09-20 10:54:34	ga_s2am_ard_3-2-1_53JKM_2022-09-20_final.stac-item
2022-09-20 10:54:37	ga_s2am_ard_3-2-1_52JGS_2022-09-20_final.stac-item
2022-09-20 10:54:41	ga_s2am_ard_3-2-1_52JFS_2022-09-20_final.stac-item
2022-09-25 10:04:18	ga_s2am_ard_3-2-1_54JYS_2022-09-25_final.stac-item
2022-09-29 09:43:59	ga_s2am_ard_3-2-1_56JLS_2022-09-29_final.stac-item
2022-09-29 09:44:03	ga_s2am_ard_3-2-1_55JHM_2022-09-29_final.stac-item
2022-09-29 09:44:03	ga_s2am_ard_3-2-1_56JKS_2022-09-29_final.stac-item
2022-09-29 09:44:06	ga_s2am_ard_3-2-1_55JGM_2022-09-29_final.stac-item
2022-09-29 09:44:10	ga_s2am_ard_3-2-1_55JFM_2022-09-29_final.stac-item
2022-09-30 10:54:31	ga_s2am_ard_3-2-1_53JLM_2022-09-30_final.stac-item
2022-09-30 10:54:33	ga_s2am_ard_3-2-1_52JHS_2022-09-30_final.stac-item
2022-09-30 10:54:34	ga_s2am_ard_3-2-1_53JKM_2022-09-30_final.stac-item
2022-09-30 10:54:37	ga_s2am_ard_3-2-1_52JGS_2022-09-30_final.stac-item
2022-09-30 10:54:40	ga_s2am_ard_3-2-1_52JFS_2022-09-30_final.stac-item
2022-10-05 10:04:18	ga_s2am_ard_3-2-1_54JYS_2022-10-05_final.stac-item
2022-11-18 11:24:42	ga_s2am_ard_3-2-1_51JXM_2022-11-18_final.stac-item
2022-11-18 11:24:46	ga_s2am_ard_3-2-1_51JWM_2022-11-18_final.stac-item
2022-11-21 09:53:59	ga_s2am_ard_3-2-1_55JFM_2022-11-21_final.stac-item
2022-11-21 09:54:03	ga_s2am_ard_3-2-1_55JEM_2022-11-21_final.stac-item
2022-11-21 09:54:06	ga_s2am_ard_3-2-1_55JDM_2022-11-21_final.stac-item
2022-11-21 09:54:10	ga_s2am_ard_3-2-1_55JCM_2022-11-21_final.stac-item
2022-11-26 10:44:16	ga_s2am_ard_3-2-1_53JPM_2022-11-26_final.stac-item
2022-11-26 10:44:20	ga_s2am_ard_3-2-1_53JNM_2022-11-26_final.stac-item
2022-11-26 10:44:24	ga_s2am_ard_3-2-1_53JMM_2022-11-26_final.stac-item
2022-11-26 10:44:27	ga_s2am_ard_3-2-1_53JLM_2022-11-26_final.stac-item
2022-12-02 11:04:25	ga_s2am_ard_3-2-1_52JGS_2022-12-02_final.stac-item
2022-12-02 11:04:29	ga_s2am_ard_3-2-1_52JFS_2022-12-02_final.stac-item
2022-12-02 11:04:33	ga_s2am_ard_3-2-1_52JES_2022-12-02_final.stac-item
2022-12-02 11:04:36	ga_s2am_ard_3-2-1_52JDS_2022-12-02_final.stac-item
2022-12-04 10:04:01	ga_s2am_ard_3-2-1_55JDM_2022-12-04_final.stac-item
2022-12-04 10:04:05	ga_s2am_ard_3-2-1_55JCM_2022-12-04_final.stac-item
2022-12-04 10:04:08	ga_s2am_ard_3-2-1_54JZS_2022-12-04_final.stac-item
2022-12-04 10:04:08	ga_s2am_ard_3-2-1_55JBM_2022-12-04_final.stac-item
2022-12-04 10:04:11	ga_s2am_ard_3-2-1_54JYS_2022-12-04_final.stac-item
2022-12-05 09:33:50	ga_s2am_ard_3-2-1_56JNS_2022-12-05_final.stac-item
2022-12-05 09:33:54	ga_s2am_ard_3-2-1_56JMS_2022-12-05_final.stac-item
2022-12-05 09:33:57	ga_s2am_ard_3-2-1_56JLS_2022-12-05_final.stac-item
2022-12-05 09:34:01	ga_s2am_ard_3-2-1_55JHM_2022-12-05_final.stac-item
2022-12-05 09:34:01	ga_s2am_ard_3-2-1_56JKS_2022-12-05_final.stac-item
2022-12-06 10:44:17	ga_s2am_ard_3-2-1_53JPM_2022-12-06_final.stac-item
2022-12-06 10:44:21	ga_s2am_ard_3-2-1_53JNM_2022-12-06_final.stac-item
2022-12-06 10:44:25	ga_s2am_ard_3-2-1_53JMM_2022-12-06_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

All years