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
2022-05-24 12:04:40	ga_s2am_ard_3-2-1_49KHP_2022-05-24_final
2022-05-24 12:04:40	ga_s2am_ard_3-2-1_50KKU_2022-05-24_final
2022-05-24 12:04:41	ga_s2am_ard_3-2-1_50JKT_2022-05-24_final
2022-05-24 12:04:42	ga_s2am_ard_3-2-1_49KGP_2022-05-24_final
2022-05-24 12:04:50	ga_s2am_ard_3-2-1_50JKT_2022-05-24_final
2022-05-24 12:04:53	ga_s2am_ard_3-2-1_49JGN_2022-05-24_final
2022-05-24 12:05:06	ga_s2am_ard_3-2-1_50JMR_2022-05-24_final
2022-05-24 12:05:22	ga_s2am_ard_3-2-1_49JGL_2022-05-24_final
2022-05-24 12:05:48	ga_s2am_ard_3-2-1_50JKP_2022-05-24_final
2022-05-24 12:05:51	ga_s2am_ard_3-2-1_49JGJ_2022-05-24_final
2022-05-24 12:05:58	ga_s2am_ard_3-2-1_50JLN_2022-05-24_final
2022-05-24 12:06:17	ga_s2am_ard_3-2-1_50JKM_2022-05-24_final
2022-05-25 09:51:26	ga_s2am_ard_3-2-1_55LFC_2022-05-25_final
2022-05-25 09:51:32	ga_s2am_ard_3-2-1_56KKG_2022-05-25_final.stac-item
2022-05-25 09:51:33	ga_s2am_ard_3-2-1_55KHB_2022-05-25_final.stac-item
2022-05-25 09:51:37	ga_s2am_ard_3-2-1_55KGB_2022-05-25_final
2022-05-25 09:53:11	ga_s2am_ard_3-2-1_55KER_2022-05-25_final
2022-05-25 09:53:32	ga_s2am_ard_3-2-1_55KGP_2022-05-25_final
2022-05-25 09:53:36	ga_s2am_ard_3-2-1_55KFP_2022-05-25_final
2022-05-25 09:53:45	ga_s2am_ard_3-2-1_55JGN_2022-05-25_final
2022-05-25 09:53:55	ga_s2am_ard_3-2-1_55JEN_2022-05-25_final
2022-05-25 09:53:55	ga_s2am_ard_3-2-1_55JGM_2022-05-25_final
2022-05-25 09:53:58	ga_s2am_ard_3-2-1_55JDN_2022-05-25_final
2022-05-25 09:54:20	ga_s2am_ard_3-2-1_55JFL_2022-05-25_final
2022-05-25 09:55:07	ga_s2am_ard_3-2-1_55JEH_2022-05-25_final
2022-05-25 09:55:11	ga_s2am_ard_3-2-1_55JDH_2022-05-25_final
2022-05-25 09:55:14	ga_s2am_ard_3-2-1_55JCH_2022-05-25_final
2022-05-25 09:55:18	ga_s2am_ard_3-2-1_55JBH_2022-05-25_final
2022-05-25 09:55:50	ga_s2am_ard_3-2-1_55HEE_2022-05-25_final
2022-05-25 09:55:54	ga_s2am_ard_3-2-1_55HDE_2022-05-25_final
2022-05-25 09:55:57	ga_s2am_ard_3-2-1_55HCE_2022-05-25_final
2022-05-25 09:56:04	ga_s2am_ard_3-2-1_54HYK_2022-05-25_final
2022-05-25 09:56:12	ga_s2am_ard_3-2-1_55HCD_2022-05-25_final
2022-05-25 09:56:15	ga_s2am_ard_3-2-1_55HBD_2022-05-25_final
2022-05-25 09:56:17	ga_s2am_ard_3-2-1_54HYJ_2022-05-25_final
2022-05-25 09:56:27	ga_s2am_ard_3-2-1_55HCC_2022-05-25_final
2022-05-25 09:56:30	ga_s2am_ard_3-2-1_55HBC_2022-05-25_final
2022-05-25 09:56:44	ga_s2am_ard_3-2-1_55HBB_2022-05-25_final
2022-05-25 09:56:46	ga_s2am_ard_3-2-1_54HYG_2022-05-25_final
2022-05-25 09:56:52	ga_s2am_ard_3-2-1_55HDA_2022-05-25_final
2022-05-25 09:56:56	ga_s2am_ard_3-2-1_55HCA_2022-05-25_final
2022-05-25 09:56:59	ga_s2am_ard_3-2-1_55HBA_2022-05-25_final
2022-05-25 09:57:00	ga_s2am_ard_3-2-1_54HYF_2022-05-25_final
2022-05-25 09:57:04	ga_s2am_ard_3-2-1_54HXF_2022-05-25_final
2022-05-25 09:57:15	ga_s2am_ard_3-2-1_55HDU_2022-05-25_final
2022-05-25 09:57:20	ga_s2am_ard_3-2-1_55HCU_2022-05-25_final
2022-05-25 09:57:22	ga_s2am_ard_3-2-1_55HBU_2022-05-25_final
2022-05-25 09:57:23	ga_s2am_ard_3-2-1_54HYD_2022-05-25_final
2022-05-25 09:57:25	ga_s2am_ard_3-2-1_54HXD_2022-05-25_final
2022-05-25 09:57:27	ga_s2am_ard_3-2-1_55HCU_2022-05-25_final
2022-05-25 09:57:29	ga_s2am_ard_3-2-1_55HBU_2022-05-25_final
2022-05-25 09:57:29	ga_s2am_ard_3-2-1_54HYD_2022-05-25_final
2022-05-25 09:57:33	ga_s2am_ard_3-2-1_54HXD_2022-05-25_final
2022-05-25 09:57:39	ga_s2am_ard_3-2-1_55HCT_2022-05-25_final
2022-05-25 09:57:43	ga_s2am_ard_3-2-1_55HBT_2022-05-25_final
2022-05-25 09:57:44	ga_s2am_ard_3-2-1_54HYC_2022-05-25_final
2022-05-25 09:57:48	ga_s2am_ard_3-2-1_54HXC_2022-05-25_final
2022-05-25 09:58:08	ga_s2am_ard_3-2-1_55GCR_2022-05-25_final
2022-05-25 09:58:12	ga_s2am_ard_3-2-1_55GBR_2022-05-25_final
2022-05-25 09:58:12	ga_s2am_ard_3-2-1_54GYA_2022-05-25_final
2022-05-25 11:31:25	ga_s2am_ard_3-2-1_52LBK_2022-05-25_final
2022-05-25 11:31:28	ga_s2am_ard_3-2-1_51LZE_2022-05-25_final
2022-05-25 11:31:31	ga_s2am_ard_3-2-1_51LYE_2022-05-25_final
2022-05-25 11:31:36	ga_s2am_ard_3-2-1_52LBJ_2022-05-25_final
2022-05-25 11:31:42	ga_s2am_ard_3-2-1_51LZD_2022-05-25_final
2022-05-25 11:31:46	ga_s2am_ard_3-2-1_51LYD_2022-05-25_final
2022-05-25 11:31:49	ga_s2am_ard_3-2-1_51LXD_2022-05-25_final
2022-05-25 11:32:04	ga_s2am_ard_3-2-1_51LXC_2022-05-25_final
2022-05-25 11:32:06	ga_s2am_ard_3-2-1_51KZB_2022-05-25_final
2022-05-25 11:32:07	ga_s2am_ard_3-2-1_51LWC_2022-05-25_final
2022-05-25 11:32:14	ga_s2am_ard_3-2-1_51KYB_2022-05-25_final
2022-05-25 11:32:39	ga_s2am_ard_3-2-1_51KVA_2022-05-25_final
2022-05-25 11:32:47	ga_s2am_ard_3-2-1_51KXV_2022-05-25_final
2022-05-25 11:32:54	ga_s2am_ard_3-2-1_51KVV_2022-05-25_final
2022-05-25 11:33:49	ga_s2am_ard_3-2-1_51KWR_2022-05-25_final
2022-05-25 11:33:52	ga_s2am_ard_3-2-1_51KVR_2022-05-25_final
2022-05-25 11:34:25	ga_s2am_ard_3-2-1_51KUP_2022-05-25_final
2022-05-25 11:34:43	ga_s2am_ard_3-2-1_51JTN_2022-05-25_final
2022-05-25 11:34:44	ga_s2am_ard_3-2-1_50JRT_2022-05-25_final
2022-05-25 11:35:26	ga_s2am_ard_3-2-1_51JWJ_2022-05-25_final
2022-05-25 11:35:34	ga_s2am_ard_3-2-1_51JVJ_2022-05-25_final
2022-05-25 11:35:44	ga_s2am_ard_3-2-1_50JQP_2022-05-25_final
2022-05-25 11:35:52	ga_s2am_ard_3-2-1_51JUH_2022-05-25_final
2022-05-25 11:36:10	ga_s2am_ard_3-2-1_51JTG_2022-05-25_final
2022-05-25 11:36:12	ga_s2am_ard_3-2-1_50JQM_2022-05-25_final
2022-05-25 11:36:27	ga_s2am_ard_3-2-1_50JQL_2022-05-25_final
2022-05-25 11:36:31	ga_s2am_ard_3-2-1_51HVE_2022-05-25_final
2022-05-25 11:36:35	ga_s2am_ard_3-2-1_51HUE_2022-05-25_final
2022-05-25 11:36:41	ga_s2am_ard_3-2-1_51HVD_2022-05-25_final
2022-05-25 11:36:41	ga_s2am_ard_3-2-1_50HQK_2022-05-25_final
2022-05-25 11:36:50	ga_s2am_ard_3-2-1_51HUD_2022-05-25_final
2022-05-25 11:36:54	ga_s2am_ard_3-2-1_51HTD_2022-05-25_final
2022-05-25 11:36:55	ga_s2am_ard_3-2-1_50HQJ_2022-05-25_final
2022-05-25 11:36:59	ga_s2am_ard_3-2-1_50HPJ_2022-05-25_final
2022-05-25 11:37:05	ga_s2am_ard_3-2-1_51HUC_2022-05-25_final
2022-05-25 11:37:10	ga_s2am_ard_3-2-1_50HQH_2022-05-25_final
2022-05-25 11:37:14	ga_s2am_ard_3-2-1_50HPH_2022-05-25_final
2022-05-25 11:37:19	ga_s2am_ard_3-2-1_51HUB_2022-05-25_final.stac-item
2022-05-25 11:37:23	ga_s2am_ard_3-2-1_51HTB_2022-05-25_final.stac-item
2022-05-25 11:37:24	ga_s2am_ard_3-2-1_50HQG_2022-05-25_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

All years