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
2019-11-14 09:43:43	ga_s2am_ard_3-2-1_56JKT_2019-11-14_final
2019-11-14 09:43:47	ga_s2am_ard_3-2-1_55JGN_2019-11-14_final
2019-11-14 09:43:50	ga_s2am_ard_3-2-1_55JFN_2019-11-14_final
2019-11-14 09:43:54	ga_s2am_ard_3-2-1_56JLS_2019-11-14_final
2019-11-14 09:43:57	ga_s2am_ard_3-2-1_55JHM_2019-11-14_final
2019-11-14 09:43:58	ga_s2am_ard_3-2-1_56JKS_2019-11-14_final
2019-11-14 09:44:01	ga_s2am_ard_3-2-1_55JGM_2019-11-14_final
2019-11-14 09:44:05	ga_s2am_ard_3-2-1_55JFM_2019-11-14_final
2019-11-14 09:44:16	ga_s2am_ard_3-2-1_55JGL_2019-11-14_final
2019-11-14 09:44:18	ga_s2am_ard_3-2-1_56JLQ_2019-11-14_final
2019-11-14 09:44:27	ga_s2am_ard_3-2-1_55JEL_2019-11-14_final
2019-11-14 09:44:30	ga_s2am_ard_3-2-1_55JGK_2019-11-14_final
2019-11-14 09:44:34	ga_s2am_ard_3-2-1_55JFK_2019-11-14_final
2019-11-14 09:44:41	ga_s2am_ard_3-2-1_56JKP_2019-11-14_final
2019-11-14 09:44:44	ga_s2am_ard_3-2-1_55JGJ_2019-11-14_final
2019-11-14 09:44:48	ga_s2am_ard_3-2-1_55JFJ_2019-11-14_final
2019-11-14 09:44:51	ga_s2am_ard_3-2-1_55JEJ_2019-11-14_final
2019-11-14 09:45:03	ga_s2am_ard_3-2-1_55JFH_2019-11-14_final
2019-11-14 09:45:06	ga_s2am_ard_3-2-1_55JEH_2019-11-14_final
2019-11-14 09:45:10	ga_s2am_ard_3-2-1_56JKM_2019-11-14_final
2019-11-14 09:45:13	ga_s2am_ard_3-2-1_55JGG_2019-11-14_final
2019-11-14 09:45:17	ga_s2am_ard_3-2-1_55JFG_2019-11-14_final
2019-11-14 09:45:21	ga_s2am_ard_3-2-1_55JEG_2019-11-14_final
2019-11-14 09:45:24	ga_s2am_ard_3-2-1_56JKL_2019-11-14_final
2019-11-14 09:45:27	ga_s2am_ard_3-2-1_55JGF_2019-11-14_final
2019-11-14 09:45:28	ga_s2am_ard_3-2-1_55JDG_2019-11-14_final
2019-11-14 09:45:32	ga_s2am_ard_3-2-1_55JFF_2019-11-14_final
2019-11-14 09:45:35	ga_s2am_ard_3-2-1_56HKK_2019-11-14_final
2019-11-14 09:45:35	ga_s2am_ard_3-2-1_55JEF_2019-11-14_final
2019-11-14 09:45:39	ga_s2am_ard_3-2-1_55JDF_2019-11-14_final
2019-11-14 09:45:46	ga_s2am_ard_3-2-1_55HFE_2019-11-14_final
2019-11-14 09:45:57	ga_s2am_ard_3-2-1_55HGD_2019-11-14_final
2019-11-14 09:46:00	ga_s2am_ard_3-2-1_55HFD_2019-11-14_final
2019-11-14 09:46:04	ga_s2am_ard_3-2-1_55HED_2019-11-14_final
2019-11-14 09:46:08	ga_s2am_ard_3-2-1_55HDD_2019-11-14_final
2019-11-14 09:46:09	ga_s2am_ard_3-2-1_55HGC_2019-11-14_final
2019-11-14 09:46:15	ga_s2am_ard_3-2-1_55HFC_2019-11-14_final
2019-11-14 09:46:19	ga_s2am_ard_3-2-1_55HEC_2019-11-14_final
2019-11-14 09:46:19	ga_s2am_ard_3-2-1_55HGB_2019-11-14_final
2019-11-14 09:46:22	ga_s2am_ard_3-2-1_55HDC_2019-11-14_final
2019-11-14 09:46:30	ga_s2am_ard_3-2-1_55HCC_2019-11-14_final
2019-11-14 09:46:33	ga_s2am_ard_3-2-1_55HEB_2019-11-14_final
2019-11-14 09:46:37	ga_s2am_ard_3-2-1_55HDB_2019-11-14_final
2019-11-14 09:46:41	ga_s2am_ard_3-2-1_55HCB_2019-11-14_final
2019-11-14 09:46:44	ga_s2am_ard_3-2-1_55HFA_2019-11-14_final
2019-11-14 09:46:48	ga_s2am_ard_3-2-1_55HEA_2019-11-14_final
2019-11-14 09:46:51	ga_s2am_ard_3-2-1_55HDA_2019-11-14_final
2019-11-14 09:46:54	ga_s2am_ard_3-2-1_55HCA_2019-11-14_final
2019-11-14 09:46:58	ga_s2am_ard_3-2-1_55HFV_2019-11-14_final
2019-11-14 09:47:02	ga_s2am_ard_3-2-1_55HEV_2019-11-14_final
2019-11-14 09:47:06	ga_s2am_ard_3-2-1_55HDV_2019-11-14_final
2019-11-14 09:47:09	ga_s2am_ard_3-2-1_55HCV_2019-11-14_final
2019-11-14 09:47:11	ga_s2am_ard_3-2-1_55HFU_2019-11-14_final.stac-item
2019-11-14 09:47:16	ga_s2am_ard_3-2-1_55HEU_2019-11-14_final
2019-11-14 09:47:20	ga_s2am_ard_3-2-1_55HDU_2019-11-14_final
2019-11-14 09:47:24	ga_s2am_ard_3-2-1_55HCU_2019-11-14_final
2019-11-14 09:47:31	ga_s2am_ard_3-2-1_55HET_2019-11-14_final
2019-11-14 09:47:31	ga_s2am_ard_3-2-1_55HBU_2019-11-14_final
2019-11-14 09:47:35	ga_s2am_ard_3-2-1_55HDT_2019-11-14_final
2019-11-14 09:47:45	ga_s2am_ard_3-2-1_55HES_2019-11-14_final
2019-11-14 09:47:49	ga_s2am_ard_3-2-1_55HDS_2019-11-14_final
2019-11-14 09:47:53	ga_s2am_ard_3-2-1_55HCS_2019-11-14_final
2019-11-14 09:47:56	ga_s2am_ard_3-2-1_55HBS_2019-11-14_final
2019-11-14 09:47:57	ga_s2am_ard_3-2-1_54HYB_2019-11-14_final
2019-11-14 09:48:00	ga_s2am_ard_3-2-1_55GER_2019-11-14_final
2019-11-14 09:48:04	ga_s2am_ard_3-2-1_55GDR_2019-11-14_final
2019-11-14 09:48:07	ga_s2am_ard_3-2-1_55GCR_2019-11-14_final
2019-11-14 09:48:11	ga_s2am_ard_3-2-1_55GBR_2019-11-14_final
2019-11-14 09:48:11	ga_s2am_ard_3-2-1_54GYA_2019-11-14_final
2019-11-14 09:48:13	ga_s2am_ard_3-2-1_55GEQ_2019-11-14_final
2019-11-14 09:48:18	ga_s2am_ard_3-2-1_55GDQ_2019-11-14_final
2019-11-14 09:48:22	ga_s2am_ard_3-2-1_55GCQ_2019-11-14_final
2019-11-14 09:48:24	ga_s2am_ard_3-2-1_55GEP_2019-11-14_final
2019-11-14 09:48:25	ga_s2am_ard_3-2-1_55GBQ_2019-11-14_final.stac-item
2019-11-14 09:48:25	ga_s2am_ard_3-2-1_54GYV_2019-11-14_final.stac-item
2019-11-14 09:48:32	ga_s2am_ard_3-2-1_55GDP_2019-11-14_final
2019-11-14 09:48:36	ga_s2am_ard_3-2-1_55GCP_2019-11-14_final
2019-11-14 09:48:47	ga_s2am_ard_3-2-1_55GDN_2019-11-14_final
2019-11-14 09:48:51	ga_s2am_ard_3-2-1_55GCN_2019-11-14_final
2019-11-14 09:49:00	ga_s2am_ard_3-2-1_55GDM_2019-11-14_final.stac-item
2019-11-14 09:49:02	ga_s2am_ard_3-2-1_55GCM_2019-11-14_final.stac-item
2019-11-14 11:26:21	ga_s2am_ard_3-2-1_51JWF_2019-11-14_final
2019-11-14 11:26:23	ga_s2am_ard_3-2-1_51JVF_2019-11-14_final
2019-11-14 11:26:24	ga_s2am_ard_3-2-1_51JUF_2019-11-14_final
2019-11-14 11:26:26	ga_s2am_ard_3-2-1_51HXE_2019-11-14_final
2019-11-14 11:26:28	ga_s2am_ard_3-2-1_51HWE_2019-11-14_final
2019-11-14 11:26:31	ga_s2am_ard_3-2-1_51HVE_2019-11-14_final
2019-11-14 11:26:34	ga_s2am_ard_3-2-1_51HUE_2019-11-14_final
2019-11-14 11:26:38	ga_s2am_ard_3-2-1_51HXD_2019-11-14_final
2019-11-14 11:26:42	ga_s2am_ard_3-2-1_51HWD_2019-11-14_final
2019-11-14 11:26:46	ga_s2am_ard_3-2-1_51HVD_2019-11-14_final
2019-11-14 11:26:49	ga_s2am_ard_3-2-1_51HUD_2019-11-14_final
2019-11-14 11:26:49	ga_s2am_ard_3-2-1_51HXC_2019-11-14_final.stac-item
2019-11-14 11:26:56	ga_s2am_ard_3-2-1_51HWC_2019-11-14_final.stac-item
2019-11-14 11:27:00	ga_s2am_ard_3-2-1_51HVC_2019-11-14_final
2019-11-14 11:27:04	ga_s2am_ard_3-2-1_51HUC_2019-11-14_final
2019-11-14 11:27:09	ga_s2am_ard_3-2-1_51HTC_2019-11-14_final
2019-11-14 11:27:10	ga_s2am_ard_3-2-1_51HWB_2019-11-14_final.stac-item
2019-11-14 11:27:12	ga_s2am_ard_3-2-1_51HVB_2019-11-14_final.stac-item
2019-11-14 11:27:14	ga_s2am_ard_3-2-1_51HUB_2019-11-14_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

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