Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2019-03-01 12:05:33	ga_s2am_ard_3-2-1_50JLP_2019-03-01_final
2019-03-01 12:05:36	ga_s2am_ard_3-2-1_50JKP_2019-03-01_final
2019-03-01 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2019-03-01_final
2019-03-01 12:05:50	ga_s2am_ard_3-2-1_50JKN_2019-03-01_final
2019-03-01 12:05:53	ga_s2am_ard_3-2-1_49JGH_2019-03-01_final.stac-item
2019-03-01 12:06:05	ga_s2am_ard_3-2-1_50JKM_2019-03-01_final
2019-03-02 09:51:07	ga_s2am_ard_3-2-1_55LHC_2019-03-02_final.stac-item
2019-03-02 09:51:10	ga_s2am_ard_3-2-1_55LGC_2019-03-02_final
2019-03-02 09:51:14	ga_s2am_ard_3-2-1_55LFC_2019-03-02_final
2019-03-02 09:51:20	ga_s2am_ard_3-2-1_56KKG_2019-03-02_final.stac-item
2019-03-02 09:51:21	ga_s2am_ard_3-2-1_55KHB_2019-03-02_final.stac-item
2019-03-02 09:51:25	ga_s2am_ard_3-2-1_55KGB_2019-03-02_final
2019-03-02 09:52:01	ga_s2am_ard_3-2-1_55KEV_2019-03-02_final
2019-03-02 09:52:15	ga_s2am_ard_3-2-1_55KEU_2019-03-02_final
2019-03-02 09:52:30	ga_s2am_ard_3-2-1_55KHS_2019-03-02_final
2019-03-02 09:52:59	ga_s2am_ard_3-2-1_55KER_2019-03-02_final
2019-03-02 09:53:02	ga_s2am_ard_3-2-1_55KDR_2019-03-02_final
2019-03-02 09:53:10	ga_s2am_ard_3-2-1_55KFQ_2019-03-02_final
2019-03-02 09:53:20	ga_s2am_ard_3-2-1_55KGP_2019-03-02_final
2019-03-02 09:53:28	ga_s2am_ard_3-2-1_55KEP_2019-03-02_final
2019-03-02 09:53:39	ga_s2am_ard_3-2-1_55JFN_2019-03-02_final
2019-03-02 09:53:42	ga_s2am_ard_3-2-1_55JEN_2019-03-02_final
2019-03-02 09:53:46	ga_s2am_ard_3-2-1_55JDN_2019-03-02_final
2019-03-02 09:53:53	ga_s2am_ard_3-2-1_55JFM_2019-03-02_final
2019-03-02 09:54:04	ga_s2am_ard_3-2-1_55JCM_2019-03-02_final
2019-03-02 09:54:08	ga_s2am_ard_3-2-1_55JFL_2019-03-02_final
2019-03-02 09:54:11	ga_s2am_ard_3-2-1_55JEL_2019-03-02_final
2019-03-02 09:54:15	ga_s2am_ard_3-2-1_55JDL_2019-03-02_final
2019-03-02 09:54:18	ga_s2am_ard_3-2-1_55JCL_2019-03-02_final
2019-03-02 09:54:26	ga_s2am_ard_3-2-1_55JEK_2019-03-02_final
2019-03-02 09:54:29	ga_s2am_ard_3-2-1_55JDK_2019-03-02_final
2019-03-02 09:54:35	ga_s2am_ard_3-2-1_55JFJ_2019-03-02_final
2019-03-02 09:54:40	ga_s2am_ard_3-2-1_55JEJ_2019-03-02_final
2019-03-02 09:54:44	ga_s2am_ard_3-2-1_55JDJ_2019-03-02_final
2019-03-02 09:54:47	ga_s2am_ard_3-2-1_55JCJ_2019-03-02_final
2019-03-02 09:54:55	ga_s2am_ard_3-2-1_55JEH_2019-03-02_final
2019-03-02 09:54:58	ga_s2am_ard_3-2-1_55JDH_2019-03-02_final
2019-03-02 09:55:06	ga_s2am_ard_3-2-1_55JBH_2019-03-02_final
2019-03-02 09:55:09	ga_s2am_ard_3-2-1_55JEG_2019-03-02_final
2019-03-02 09:55:13	ga_s2am_ard_3-2-1_55JDG_2019-03-02_final
2019-03-02 09:55:19	ga_s2am_ard_3-2-1_55JBG_2019-03-02_final
2019-03-02 09:55:24	ga_s2am_ard_3-2-1_55JEF_2019-03-02_final
2019-03-02 09:55:27	ga_s2am_ard_3-2-1_55JDF_2019-03-02_final
2019-03-02 09:56:18	ga_s2am_ard_3-2-1_55HBC_2019-03-02_final
2019-03-02 09:56:20	ga_s2am_ard_3-2-1_54HYH_2019-03-02_final
2019-03-02 09:56:40	ga_s2am_ard_3-2-1_55HDA_2019-03-02_final
2019-03-02 09:56:53	ga_s2am_ard_3-2-1_55HDV_2019-03-02_final
2019-03-02 09:56:58	ga_s2am_ard_3-2-1_55HCV_2019-03-02_final
2019-03-02 09:57:01	ga_s2am_ard_3-2-1_55HBV_2019-03-02_final
2019-03-02 09:57:03	ga_s2am_ard_3-2-1_54HYE_2019-03-02_final
2019-03-02 09:57:06	ga_s2am_ard_3-2-1_54HXE_2019-03-02_final
2019-03-02 09:57:42	ga_s2am_ard_3-2-1_55HCS_2019-03-02_final
2019-03-02 09:57:45	ga_s2am_ard_3-2-1_55HBS_2019-03-02_final
2019-03-02 09:57:46	ga_s2am_ard_3-2-1_54HYB_2019-03-02_final
2019-03-02 09:58:09	ga_s2am_ard_3-2-1_55GCQ_2019-03-02_final
2019-03-02 09:58:14	ga_s2am_ard_3-2-1_55GBQ_2019-03-02_final.stac-item
2019-03-02 09:58:14	ga_s2am_ard_3-2-1_54GYV_2019-03-02_final.stac-item
2019-03-02 09:58:19	ga_s2am_ard_3-2-1_55GCP_2019-03-02_final
2019-03-02 11:31:13	ga_s2am_ard_3-2-1_52LBK_2019-03-02_final
2019-03-02 11:31:16	ga_s2am_ard_3-2-1_51LZE_2019-03-02_final
2019-03-02 11:31:19	ga_s2am_ard_3-2-1_51LYE_2019-03-02_final
2019-03-02 11:31:26	ga_s2am_ard_3-2-1_51LWE_2019-03-02_final
2019-03-02 11:31:37	ga_s2am_ard_3-2-1_51LXD_2019-03-02_final
2019-03-02 11:31:43	ga_s2am_ard_3-2-1_51LZC_2019-03-02_final
2019-03-02 11:31:52	ga_s2am_ard_3-2-1_51LXC_2019-03-02_final
2019-03-02 11:31:54	ga_s2am_ard_3-2-1_51KZB_2019-03-02_final
2019-03-02 11:32:02	ga_s2am_ard_3-2-1_51KYB_2019-03-02_final
2019-03-02 11:32:06	ga_s2am_ard_3-2-1_51KXB_2019-03-02_final
2019-03-02 11:32:21	ga_s2am_ard_3-2-1_51KXA_2019-03-02_final
2019-03-02 11:32:39	ga_s2am_ard_3-2-1_51KWV_2019-03-02_final
2019-03-02 11:32:42	ga_s2am_ard_3-2-1_51KVV_2019-03-02_final
2019-03-02 11:33:37	ga_s2am_ard_3-2-1_51KWR_2019-03-02_final
2019-03-02 11:33:40	ga_s2am_ard_3-2-1_51KVR_2019-03-02_final
2019-03-02 11:33:47	ga_s2am_ard_3-2-1_51KXQ_2019-03-02_final
2019-03-02 11:33:58	ga_s2am_ard_3-2-1_51KUQ_2019-03-02_final
2019-03-02 11:34:10	ga_s2am_ard_3-2-1_51JXN_2019-03-02_final
2019-03-02 11:34:20	ga_s2am_ard_3-2-1_51JWN_2019-03-02_final
2019-03-02 11:34:24	ga_s2am_ard_3-2-1_51JVN_2019-03-02_final
2019-03-02 11:34:27	ga_s2am_ard_3-2-1_51JUN_2019-03-02_final
2019-03-02 11:34:32	ga_s2am_ard_3-2-1_50JRT_2019-03-02_final
2019-03-02 11:34:41	ga_s2am_ard_3-2-1_51JUM_2019-03-02_final
2019-03-02 11:34:44	ga_s2am_ard_3-2-1_50JRS_2019-03-02_final
2019-03-02 11:34:49	ga_s2am_ard_3-2-1_51JWL_2019-03-02_final
2019-03-02 11:34:53	ga_s2am_ard_3-2-1_51JVL_2019-03-02_final
2019-03-02 11:34:56	ga_s2am_ard_3-2-1_51JUL_2019-03-02_final
2019-03-02 11:34:59	ga_s2am_ard_3-2-1_51JTL_2019-03-02_final
2019-03-02 11:35:03	ga_s2am_ard_3-2-1_51JWK_2019-03-02_final
2019-03-02 11:35:07	ga_s2am_ard_3-2-1_51JVK_2019-03-02_final
2019-03-02 11:35:14	ga_s2am_ard_3-2-1_51JWJ_2019-03-02_final
2019-03-02 11:35:21	ga_s2am_ard_3-2-1_51JVJ_2019-03-02_final
2019-03-02 11:35:25	ga_s2am_ard_3-2-1_51JUJ_2019-03-02_final
2019-03-02 11:35:28	ga_s2am_ard_3-2-1_51JTJ_2019-03-02_final
2019-03-02 11:35:36	ga_s2am_ard_3-2-1_51JVH_2019-03-02_final
2019-03-02 11:35:43	ga_s2am_ard_3-2-1_51JTH_2019-03-02_final
2019-03-02 11:35:45	ga_s2am_ard_3-2-1_50JQN_2019-03-02_final
2019-03-02 11:35:51	ga_s2am_ard_3-2-1_51JVG_2019-03-02_final
2019-03-02 11:35:57	ga_s2am_ard_3-2-1_51JTG_2019-03-02_final
2019-03-02 11:36:00	ga_s2am_ard_3-2-1_50JQM_2019-03-02_final
2019-03-02 11:36:05	ga_s2am_ard_3-2-1_51JVF_2019-03-02_final
2019-03-02 11:36:56	ga_s2am_ard_3-2-1_51HTC_2019-03-02_final

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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years