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
2018-10-23 09:50:51	ga_s2am_ard_3-2-1_55JCM_2018-10-23_final.stac-item
2018-10-23 09:50:51	ga_s2am_ard_3-2-1_55JDM_2018-10-23_final.stac-item
2018-10-23 09:50:51	ga_s2am_ard_3-2-1_55JEM_2018-10-23_final.stac-item
2018-10-23 09:50:51	ga_s2am_ard_3-2-1_55JFM_2018-10-23_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54JVS_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54JWS_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54JXS_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54JYS_2018-10-29_final.stac-item
2018-11-18 11:54:42	ga_s2am_ard_3-2-1_50JPS_2018-11-18_final.stac-item
2018-11-18 11:54:45	ga_s2am_ard_3-2-1_50JNS_2018-11-18_final.stac-item
2018-11-18 11:54:49	ga_s2am_ard_3-2-1_50JMS_2018-11-18_final.stac-item
2018-11-18 11:54:52	ga_s2am_ard_3-2-1_50JLS_2018-11-18_final.stac-item
2018-11-20 10:54:16	ga_s2am_ard_3-2-1_53JLM_2018-11-20_final.stac-item
2018-11-20 10:54:19	ga_s2am_ard_3-2-1_52JHS_2018-11-20_final.stac-item
2018-11-20 10:54:20	ga_s2am_ard_3-2-1_53JKM_2018-11-20_final.stac-item
2018-11-20 10:54:23	ga_s2am_ard_3-2-1_52JGS_2018-11-20_final.stac-item
2018-11-20 10:54:27	ga_s2am_ard_3-2-1_52JFS_2018-11-20_final.stac-item
2018-11-20 10:54:34	ga_s2am_ard_3-2-1_53JKL_2018-11-20_final.stac-item
2018-11-20 10:54:37	ga_s2am_ard_3-2-1_52JGR_2018-11-20_final.stac-item
2018-11-22 11:34:32	ga_s2am_ard_3-2-1_51JWM_2018-11-22_final.stac-item
2018-11-22 11:34:36	ga_s2am_ard_3-2-1_51JVM_2018-11-22_final.stac-item
2018-11-22 11:34:39	ga_s2am_ard_3-2-1_51JUM_2018-11-22_final.stac-item
2018-11-22 11:34:42	ga_s2am_ard_3-2-1_50JRS_2018-11-22_final.stac-item
2018-11-22 11:34:42	ga_s2am_ard_3-2-1_51JTM_2018-11-22_final.stac-item
2018-11-25 10:03:53	ga_s2am_ard_3-2-1_55JDM_2018-11-25_final.stac-item
2018-11-25 10:03:56	ga_s2am_ard_3-2-1_55JCM_2018-11-25_final.stac-item
2018-11-25 10:03:59	ga_s2am_ard_3-2-1_54JZS_2018-11-25_final.stac-item
2018-11-25 10:04:00	ga_s2am_ard_3-2-1_55JBM_2018-11-25_final.stac-item
2018-11-25 10:04:03	ga_s2am_ard_3-2-1_54JYS_2018-11-25_final.stac-item
2018-11-25 10:04:14	ga_s2am_ard_3-2-1_55JBL_2018-11-25_final.stac-item
2018-11-25 10:04:18	ga_s2am_ard_3-2-1_54JYR_2018-11-25_final.stac-item
2018-11-25 11:44:33	ga_s2am_ard_3-2-1_51JUM_2018-11-25_final.stac-item
2018-11-25 11:44:37	ga_s2am_ard_3-2-1_50JRS_2018-11-25_final.stac-item
2018-11-25 11:44:37	ga_s2am_ard_3-2-1_51JTM_2018-11-25_final.stac-item
2018-11-25 11:44:41	ga_s2am_ard_3-2-1_50JQS_2018-11-25_final.stac-item
2018-11-25 11:44:45	ga_s2am_ard_3-2-1_50JPS_2018-11-25_final.stac-item
2018-11-25 11:44:52	ga_s2am_ard_3-2-1_51JTL_2018-11-25_final.stac-item
2018-11-25 11:44:56	ga_s2am_ard_3-2-1_50JQR_2018-11-25_final.stac-item
2018-11-27 10:44:08	ga_s2am_ard_3-2-1_53JPM_2018-11-27_final.stac-item
2018-11-27 10:44:12	ga_s2am_ard_3-2-1_53JNM_2018-11-27_final.stac-item
2018-11-27 10:44:16	ga_s2am_ard_3-2-1_53JMM_2018-11-27_final.stac-item
2018-11-27 10:44:19	ga_s2am_ard_3-2-1_53JLM_2018-11-27_final.stac-item
2018-11-29 09:43:44	ga_s2am_ard_3-2-1_56JLS_2018-11-29_final.stac-item
2018-11-29 09:43:47	ga_s2am_ard_3-2-1_55JHM_2018-11-29_final.stac-item
2018-11-29 09:43:47	ga_s2am_ard_3-2-1_56JKS_2018-11-29_final.stac-item
2018-11-29 09:43:50	ga_s2am_ard_3-2-1_55JGM_2018-11-29_final.stac-item
2018-11-29 09:43:54	ga_s2am_ard_3-2-1_55JFM_2018-11-29_final.stac-item
2018-11-29 09:44:01	ga_s2am_ard_3-2-1_56JKR_2018-11-29_final.stac-item
2018-11-29 09:44:05	ga_s2am_ard_3-2-1_55JGL_2018-11-29_final.stac-item
2018-12-02 09:53:49	ga_s2am_ard_3-2-1_55JFM_2018-12-02_final.stac-item
2018-12-02 09:53:53	ga_s2am_ard_3-2-1_55JEM_2018-12-02_final.stac-item
2018-12-02 09:53:57	ga_s2am_ard_3-2-1_55JDM_2018-12-02_final.stac-item
2018-12-02 09:54:01	ga_s2am_ard_3-2-1_55JCM_2018-12-02_final.stac-item
2018-12-07 10:44:08	ga_s2am_ard_3-2-1_53JPM_2018-12-07_final.stac-item
2018-12-07 10:44:12	ga_s2am_ard_3-2-1_53JNM_2018-12-07_final.stac-item
2018-12-07 10:44:16	ga_s2am_ard_3-2-1_53JMM_2018-12-07_final.stac-item
2018-12-07 10:44:19	ga_s2am_ard_3-2-1_53JLM_2018-12-07_final.stac-item
2018-12-18 10:13:57	ga_s2am_ard_3-2-1_54JYS_2018-12-18_final.stac-item
2018-12-18 10:14:01	ga_s2am_ard_3-2-1_54JXS_2018-12-18_final.stac-item
2018-12-18 10:14:05	ga_s2am_ard_3-2-1_54JWS_2018-12-18_final.stac-item
2018-12-18 10:14:08	ga_s2am_ard_3-2-1_54JVS_2018-12-18_final.stac-item
2018-12-21 12:04:40	ga_s2am_ard_3-2-1_50JMS_2018-12-21_final.stac-item
2018-12-21 12:04:45	ga_s2am_ard_3-2-1_50JLS_2018-12-21_final.stac-item
2018-12-21 12:04:48	ga_s2am_ard_3-2-1_49JHM_2018-12-21_final.stac-item
2018-12-21 12:04:49	ga_s2am_ard_3-2-1_50JKS_2018-12-21_final.stac-item
2018-12-21 12:04:52	ga_s2am_ard_3-2-1_49JGM_2018-12-21_final.stac-item
2018-12-21 12:05:03	ga_s2am_ard_3-2-1_50JKR_2018-12-21_final.stac-item
2018-12-21 12:05:06	ga_s2am_ard_3-2-1_49JGL_2018-12-21_final.stac-item
2018-12-26 09:33:43	ga_s2am_ard_3-2-1_56JNS_2018-12-26_final.stac-item
2018-12-26 09:33:46	ga_s2am_ard_3-2-1_56JMS_2018-12-26_final.stac-item
2018-12-26 09:33:50	ga_s2am_ard_3-2-1_56JLS_2018-12-26_final.stac-item
2018-12-26 09:33:53	ga_s2am_ard_3-2-1_55JHM_2018-12-26_final.stac-item
2018-12-26 09:33:53	ga_s2am_ard_3-2-1_56JKS_2018-12-26_final.stac-item
2018-12-28 10:13:59	ga_s2am_ard_3-2-1_54JYS_2018-12-28_final.stac-item
2018-12-28 10:14:03	ga_s2am_ard_3-2-1_54JXS_2018-12-28_final.stac-item
2018-12-28 10:14:07	ga_s2am_ard_3-2-1_54JWS_2018-12-28_final.stac-item
2018-12-28 10:14:10	ga_s2am_ard_3-2-1_54JVS_2018-12-28_final.stac-item
2018-12-29 11:24:25	ga_s2am_ard_3-2-1_51JZM_2018-12-29_final.stac-item
2018-12-29 11:24:26	ga_s2am_ard_3-2-1_52JBS_2018-12-29_final.stac-item
2018-12-29 11:24:30	ga_s2am_ard_3-2-1_51JYM_2018-12-29_final.stac-item
2018-12-29 11:24:34	ga_s2am_ard_3-2-1_51JXM_2018-12-29_final.stac-item
2018-12-29 11:24:37	ga_s2am_ard_3-2-1_52JBR_2018-12-29_final.stac-item
2018-12-29 11:24:37	ga_s2am_ard_3-2-1_51JWM_2018-12-29_final.stac-item
2018-12-29 11:24:44	ga_s2am_ard_3-2-1_51JYL_2018-12-29_final.stac-item
2018-12-31 10:24:02	ga_s2am_ard_3-2-1_54JWS_2018-12-31_final.stac-item
2018-12-31 10:24:06	ga_s2am_ard_3-2-1_54JVS_2018-12-31_final.stac-item
2018-12-31 10:24:10	ga_s2am_ard_3-2-1_54JUS_2018-12-31_final.stac-item
2018-12-31 10:24:12	ga_s2am_ard_3-2-1_53JRM_2018-12-31_final.stac-item
2018-12-31 10:24:13	ga_s2am_ard_3-2-1_54JTS_2018-12-31_final.stac-item
2019-01-02 11:04:30	ga_s2am_ard_3-2-1_52JDS_2019-01-02_final.stac-item
2019-01-07 10:14:01	ga_s2am_ard_3-2-1_54JYS_2019-01-07_final.stac-item
2019-01-07 10:14:05	ga_s2am_ard_3-2-1_54JXS_2019-01-07_final.stac-item
2019-01-07 10:14:08	ga_s2am_ard_3-2-1_54JWS_2019-01-07_final.stac-item
2019-01-07 10:14:12	ga_s2am_ard_3-2-1_54JVS_2019-01-07_final.stac-item
2019-05-12 11:04:33	ga_s2am_ard_3-2-1_52JFS_2019-05-12_final.stac-item
2019-05-12 11:04:36	ga_s2am_ard_3-2-1_52JES_2019-05-12_final.stac-item
2019-05-12 11:04:40	ga_s2am_ard_3-2-1_52JDS_2019-05-12_final.stac-item
2019-05-16 10:44:20	ga_s2am_ard_3-2-1_53JPM_2019-05-16_final.stac-item
2019-05-16 10:44:24	ga_s2am_ard_3-2-1_53JNM_2019-05-16_final.stac-item
2019-05-16 10:44:28	ga_s2am_ard_3-2-1_53JMM_2019-05-16_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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