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
2019-07-02 12:15:01	ga_s2am_ard_3-2-1_49JGM_2019-07-02_final.stac-item
2019-07-02 12:15:04	ga_s2am_ard_3-2-1_49JFM_2019-07-02_final.stac-item
2019-07-03 11:43:56	ga_s2am_ard_3-2-1_50KQA_2019-07-03_final.stac-item
2019-07-06 11:56:04	ga_s2am_ard_3-2-1_50JKN_2019-07-06_final.stac-item
2019-07-09 12:06:00	ga_s2am_ard_3-2-1_50JKN_2019-07-09_final.stac-item
2019-07-12 12:15:01	ga_s2am_ard_3-2-1_49JGM_2019-07-12_final.stac-item
2019-07-12 12:15:15	ga_s2am_ard_3-2-1_49JGL_2019-07-12_final.stac-item
2019-07-19 12:05:06	ga_s2am_ard_3-2-1_49JGM_2019-07-19_final.stac-item
2019-07-19 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2019-07-19_final.stac-item
2019-07-22 12:15:05	ga_s2am_ard_3-2-1_49JFM_2019-07-22_final.stac-item
2019-07-22 12:15:15	ga_s2am_ard_3-2-1_49JGL_2019-07-22_final.stac-item
2019-07-26 11:56:04	ga_s2am_ard_3-2-1_50JKN_2019-07-26_final.stac-item
2019-07-29 12:05:20	ga_s2am_ard_3-2-1_49JGL_2019-07-29_final.stac-item
2019-07-29 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2019-07-29_final.stac-item
2019-07-29 12:06:00	ga_s2am_ard_3-2-1_50JKN_2019-07-29_final.stac-item
2019-07-30 11:34:20	ga_s2am_ard_3-2-1_51JXN_2019-07-30_final.stac-item
2019-08-02 11:43:41	ga_s2am_ard_3-2-1_50KQB_2019-08-02_final.stac-item
2019-08-02 11:43:52	ga_s2am_ard_3-2-1_50KRA_2019-08-02_final.stac-item
2019-08-02 11:43:55	ga_s2am_ard_3-2-1_50KQA_2019-08-02_final.stac-item
2019-08-02 11:44:06	ga_s2am_ard_3-2-1_50KRV_2019-08-02_final.stac-item
2019-08-02 11:44:10	ga_s2am_ard_3-2-1_50KQV_2019-08-02_final.stac-item
2019-08-02 11:44:32	ga_s2am_ard_3-2-1_51JUN_2019-08-02_final.stac-item
2019-08-02 11:44:35	ga_s2am_ard_3-2-1_51JTN_2019-08-02_final.stac-item
2019-08-02 11:44:39	ga_s2am_ard_3-2-1_50JQT_2019-08-02_final.stac-item
2019-08-05 11:53:29	ga_s2am_ard_3-2-1_50KNC_2019-08-05_final.stac-item
2019-08-05 11:53:36	ga_s2am_ard_3-2-1_50KQB_2019-08-05_final.stac-item
2019-08-05 11:53:51	ga_s2am_ard_3-2-1_50KQA_2019-08-05_final.stac-item
2019-08-05 11:54:05	ga_s2am_ard_3-2-1_50KQV_2019-08-05_final.stac-item
2019-08-05 11:54:26	ga_s2am_ard_3-2-1_50KNU_2019-08-05_final.stac-item
2019-08-05 11:54:27	ga_s2am_ard_3-2-1_50JQT_2019-08-05_final.stac-item
2019-08-05 11:54:28	ga_s2am_ard_3-2-1_50KMU_2019-08-05_final.stac-item
2019-08-05 11:54:33	ga_s2am_ard_3-2-1_50KNU_2019-08-05_final.stac-item
2019-08-05 11:54:35	ga_s2am_ard_3-2-1_50KMU_2019-08-05_final.stac-item
2019-08-05 11:54:38	ga_s2am_ard_3-2-1_50KLU_2019-08-05_final.stac-item
2019-08-05 11:54:45	ga_s2am_ard_3-2-1_50JMT_2019-08-05_final.stac-item
2019-08-06 11:24:30	ga_s2am_ard_3-2-1_51JXN_2019-08-06_final.stac-item
2019-08-08 12:03:24	ga_s2am_ard_3-2-1_50KNC_2019-08-08_final.stac-item
2019-08-08 12:04:09	ga_s2am_ard_3-2-1_50KLV_2019-08-08_final.stac-item
2019-08-08 12:04:14	ga_s2am_ard_3-2-1_50KLV_2019-08-08_final.stac-item
2019-08-08 12:04:25	ga_s2am_ard_3-2-1_50KMU_2019-08-08_final.stac-item
2019-08-08 12:04:29	ga_s2am_ard_3-2-1_50KLU_2019-08-08_final.stac-item
2019-08-08 12:04:40	ga_s2am_ard_3-2-1_50JMT_2019-08-08_final.stac-item
2019-08-08 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2019-08-08_final.stac-item
2019-08-08 12:05:59	ga_s2am_ard_3-2-1_50JKN_2019-08-08_final.stac-item
2019-08-09 11:34:19	ga_s2am_ard_3-2-1_51JXN_2019-08-09_final.stac-item
2019-08-09 11:34:36	ga_s2am_ard_3-2-1_51JUN_2019-08-09_final.stac-item
2019-08-09 11:34:40	ga_s2am_ard_3-2-1_51JTN_2019-08-09_final.stac-item
2019-08-12 11:43:40	ga_s2am_ard_3-2-1_50KQB_2019-08-12_final.stac-item
2019-08-12 11:43:51	ga_s2am_ard_3-2-1_50KRA_2019-08-12_final.stac-item
2019-08-12 11:43:55	ga_s2am_ard_3-2-1_50KQA_2019-08-12_final.stac-item
2019-08-12 11:44:05	ga_s2am_ard_3-2-1_50KRV_2019-08-12_final.stac-item
2019-08-12 11:44:09	ga_s2am_ard_3-2-1_50KQV_2019-08-12_final.stac-item
2019-08-12 11:44:31	ga_s2am_ard_3-2-1_51JUN_2019-08-12_final.stac-item
2019-08-12 11:44:34	ga_s2am_ard_3-2-1_51JTN_2019-08-12_final.stac-item
2019-08-12 11:44:38	ga_s2am_ard_3-2-1_50JQT_2019-08-12_final.stac-item
2019-08-15 11:53:28	ga_s2am_ard_3-2-1_50KNC_2019-08-15_final.stac-item
2019-08-15 11:53:35	ga_s2am_ard_3-2-1_50KQB_2019-08-15_final.stac-item
2019-08-15 11:53:50	ga_s2am_ard_3-2-1_50KQA_2019-08-15_final.stac-item
2019-08-15 11:54:04	ga_s2am_ard_3-2-1_50KQV_2019-08-15_final.stac-item
2019-08-15 11:54:26	ga_s2am_ard_3-2-1_50KNU_2019-08-15_final.stac-item
2019-08-15 11:54:26	ga_s2am_ard_3-2-1_50JQT_2019-08-15_final.stac-item
2019-08-15 11:54:29	ga_s2am_ard_3-2-1_50KMU_2019-08-15_final.stac-item
2019-08-15 11:54:36	ga_s2am_ard_3-2-1_50KLU_2019-08-15_final.stac-item
2019-08-15 11:54:44	ga_s2am_ard_3-2-1_50JMT_2019-08-15_final.stac-item
2019-08-16 11:24:29	ga_s2am_ard_3-2-1_51JXN_2019-08-16_final.stac-item
2019-08-18 12:03:23	ga_s2am_ard_3-2-1_50KNC_2019-08-18_final.stac-item
2019-08-18 12:04:13	ga_s2am_ard_3-2-1_50KLV_2019-08-18_final.stac-item
2019-08-18 12:04:24	ga_s2am_ard_3-2-1_50KMU_2019-08-18_final.stac-item
2019-08-18 12:04:28	ga_s2am_ard_3-2-1_50KLU_2019-08-18_final.stac-item
2019-08-18 12:04:38	ga_s2am_ard_3-2-1_50JMT_2019-08-18_final.stac-item
2019-08-18 12:05:58	ga_s2am_ard_3-2-1_50JKN_2019-08-18_final.stac-item
2019-08-19 11:34:18	ga_s2am_ard_3-2-1_51JXN_2019-08-19_final.stac-item
2019-08-19 11:34:35	ga_s2am_ard_3-2-1_51JUN_2019-08-19_final.stac-item
2019-08-19 11:34:39	ga_s2am_ard_3-2-1_51JTN_2019-08-19_final.stac-item
2019-08-22 11:43:38	ga_s2am_ard_3-2-1_50KQB_2019-08-22_final.stac-item
2019-08-22 11:43:50	ga_s2am_ard_3-2-1_50KRA_2019-08-22_final.stac-item
2019-08-22 11:43:53	ga_s2am_ard_3-2-1_50KQA_2019-08-22_final.stac-item
2019-08-22 11:44:04	ga_s2am_ard_3-2-1_50KRV_2019-08-22_final.stac-item
2019-08-22 11:44:08	ga_s2am_ard_3-2-1_50KQV_2019-08-22_final.stac-item
2019-08-22 11:44:30	ga_s2am_ard_3-2-1_51JUN_2019-08-22_final.stac-item
2019-08-22 11:44:33	ga_s2am_ard_3-2-1_51JTN_2019-08-22_final.stac-item
2019-08-25 11:53:26	ga_s2am_ard_3-2-1_50KNC_2019-08-25_final.stac-item
2019-08-25 11:53:33	ga_s2am_ard_3-2-1_50KQB_2019-08-25_final.stac-item
2019-08-25 11:53:48	ga_s2am_ard_3-2-1_50KQA_2019-08-25_final.stac-item
2019-08-25 11:54:02	ga_s2am_ard_3-2-1_50KQV_2019-08-25_final.stac-item
2019-08-25 11:54:24	ga_s2am_ard_3-2-1_50KNU_2019-08-25_final.stac-item
2019-08-25 11:54:25	ga_s2am_ard_3-2-1_50JQT_2019-08-25_final.stac-item
2019-08-25 11:54:28	ga_s2am_ard_3-2-1_50KMU_2019-08-25_final.stac-item
2019-08-25 11:54:35	ga_s2am_ard_3-2-1_50KLU_2019-08-25_final.stac-item
2019-08-25 11:54:42	ga_s2am_ard_3-2-1_50JMT_2019-08-25_final.stac-item
2019-08-26 11:24:28	ga_s2am_ard_3-2-1_51JXN_2019-08-26_final.stac-item
2019-08-28 12:03:21	ga_s2am_ard_3-2-1_50KNC_2019-08-28_final.stac-item
2019-08-28 12:04:11	ga_s2am_ard_3-2-1_50KLV_2019-08-28_final.stac-item
2019-08-28 12:04:23	ga_s2am_ard_3-2-1_50KMU_2019-08-28_final.stac-item
2019-08-28 12:04:26	ga_s2am_ard_3-2-1_50KLU_2019-08-28_final.stac-item
2019-08-28 12:04:37	ga_s2am_ard_3-2-1_50JMT_2019-08-28_final.stac-item
2019-08-29 11:34:16	ga_s2am_ard_3-2-1_51JXN_2019-08-29_final.stac-item
2019-08-29 11:34:33	ga_s2am_ard_3-2-1_51JUN_2019-08-29_final.stac-item
2019-08-29 11:34:37	ga_s2am_ard_3-2-1_51JTN_2019-08-29_final.stac-item
2019-08-31 12:15:00	ga_s2am_ard_3-2-1_49JFM_2019-08-31_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