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
2019-06-29 12:05:16	ga_s2am_ard_3-2-1_50JKR_2019-06-29_final
2019-06-29 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2019-06-29_final
2019-06-29 12:05:31	ga_s2am_ard_3-2-1_50JKQ_2019-06-29_final
2019-06-29 12:05:34	ga_s2am_ard_3-2-1_49JGK_2019-06-29_final
2019-06-29 12:05:42	ga_s2am_ard_3-2-1_50JLP_2019-06-29_final
2019-06-29 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-06-29_final
2019-06-29 12:05:51	ga_s2am_ard_3-2-1_50JLN_2019-06-29_final
2019-06-29 12:05:53	ga_s2am_ard_3-2-1_49JGH_2019-06-29_final.stac-item
2019-06-29 12:05:54	ga_s2am_ard_3-2-1_49JGJ_2019-06-29_final
2019-06-29 12:05:57	ga_s2am_ard_3-2-1_50JLN_2019-06-29_final
2019-06-29 12:06:03	ga_s2am_ard_3-2-1_49JGH_2019-06-29_final.stac-item
2019-06-29 12:06:09	ga_s2am_ard_3-2-1_50JLM_2019-06-29_final
2019-06-29 12:06:19	ga_s2am_ard_3-2-1_50JLL_2019-06-29_final
2019-06-30 09:51:23	ga_s2am_ard_3-2-1_55LFC_2019-06-30_final
2019-06-30 09:52:10	ga_s2am_ard_3-2-1_55KEV_2019-06-30_final
2019-06-30 09:52:40	ga_s2am_ard_3-2-1_55KHS_2019-06-30_final
2019-06-30 09:53:30	ga_s2am_ard_3-2-1_55KGP_2019-06-30_final
2019-06-30 09:54:21	ga_s2am_ard_3-2-1_55JEL_2019-06-30_final
2019-06-30 09:54:24	ga_s2am_ard_3-2-1_55JDL_2019-06-30_final
2019-06-30 09:54:32	ga_s2am_ard_3-2-1_55JFK_2019-06-30_final
2019-06-30 09:54:42	ga_s2am_ard_3-2-1_55JCK_2019-06-30_final
2019-06-30 09:54:45	ga_s2am_ard_3-2-1_55JFJ_2019-06-30_final
2019-06-30 09:54:53	ga_s2am_ard_3-2-1_55JDJ_2019-06-30_final
2019-06-30 09:54:55	ga_s2am_ard_3-2-1_55JFH_2019-06-30_final
2019-06-30 09:54:57	ga_s2am_ard_3-2-1_55JCJ_2019-06-30_final
2019-06-30 09:55:04	ga_s2am_ard_3-2-1_55JEH_2019-06-30_final
2019-06-30 09:55:19	ga_s2am_ard_3-2-1_55JEG_2019-06-30_final
2019-06-30 09:55:23	ga_s2am_ard_3-2-1_55JDG_2019-06-30_final
2019-06-30 09:55:26	ga_s2am_ard_3-2-1_55JCG_2019-06-30_final
2019-06-30 09:55:41	ga_s2am_ard_3-2-1_55JCF_2019-06-30_final
2019-06-30 09:55:43	ga_s2am_ard_3-2-1_55JBF_2019-06-30_final
2019-06-30 09:55:47	ga_s2am_ard_3-2-1_55HEE_2019-06-30_final
2019-06-30 09:55:52	ga_s2am_ard_3-2-1_55HDE_2019-06-30_final
2019-06-30 09:55:55	ga_s2am_ard_3-2-1_55HCE_2019-06-30_final
2019-06-30 09:55:58	ga_s2am_ard_3-2-1_55HBE_2019-06-30_final
2019-06-30 09:55:59	ga_s2am_ard_3-2-1_55HED_2019-06-30_final
2019-06-30 09:56:01	ga_s2am_ard_3-2-1_54HYK_2019-06-30_final
2019-06-30 09:56:06	ga_s2am_ard_3-2-1_55HDD_2019-06-30_final
2019-06-30 09:56:13	ga_s2am_ard_3-2-1_55HBD_2019-06-30_final
2019-06-30 09:56:15	ga_s2am_ard_3-2-1_54HYJ_2019-06-30_final
2019-06-30 09:56:20	ga_s2am_ard_3-2-1_55HDC_2019-06-30_final
2019-06-30 09:56:35	ga_s2am_ard_3-2-1_55HDB_2019-06-30_final
2019-06-30 09:56:39	ga_s2am_ard_3-2-1_55HCB_2019-06-30_final
2019-06-30 09:56:50	ga_s2am_ard_3-2-1_55HDA_2019-06-30_final
2019-06-30 09:56:50	ga_s2am_ard_3-2-1_54HXG_2019-06-30_final
2019-06-30 09:56:57	ga_s2am_ard_3-2-1_55HBA_2019-06-30_final
2019-06-30 09:56:58	ga_s2am_ard_3-2-1_54HYF_2019-06-30_final
2019-06-30 09:57:13	ga_s2am_ard_3-2-1_55HDU_2019-06-30_final
2019-06-30 09:57:37	ga_s2am_ard_3-2-1_55HCT_2019-06-30_final
2019-06-30 09:57:40	ga_s2am_ard_3-2-1_55HBT_2019-06-30_final
2019-06-30 09:58:18	ga_s2am_ard_3-2-1_55GCQ_2019-06-30_final
2019-06-30 09:58:24	ga_s2am_ard_3-2-1_55GBQ_2019-06-30_final.stac-item
2019-06-30 09:58:24	ga_s2am_ard_3-2-1_54GYV_2019-06-30_final.stac-item
2019-06-30 09:58:28	ga_s2am_ard_3-2-1_55GCP_2019-06-30_final
2019-06-30 11:31:23	ga_s2am_ard_3-2-1_52LBK_2019-06-30_final
2019-06-30 11:31:25	ga_s2am_ard_3-2-1_51LZE_2019-06-30_final
2019-06-30 11:31:29	ga_s2am_ard_3-2-1_51LYE_2019-06-30_final
2019-06-30 11:31:34	ga_s2am_ard_3-2-1_52LBJ_2019-06-30_final
2019-06-30 11:31:40	ga_s2am_ard_3-2-1_51LZD_2019-06-30_final
2019-06-30 11:31:43	ga_s2am_ard_3-2-1_51LYD_2019-06-30_final
2019-06-30 11:32:04	ga_s2am_ard_3-2-1_51KZB_2019-06-30_final
2019-06-30 11:32:05	ga_s2am_ard_3-2-1_51LWC_2019-06-30_final
2019-06-30 11:32:19	ga_s2am_ard_3-2-1_51KWB_2019-06-30_final
2019-06-30 11:32:24	ga_s2am_ard_3-2-1_51KVB_2019-06-30_final
2019-06-30 11:32:34	ga_s2am_ard_3-2-1_51KWA_2019-06-30_final
2019-06-30 11:32:37	ga_s2am_ard_3-2-1_51KVA_2019-06-30_final
2019-06-30 11:32:48	ga_s2am_ard_3-2-1_51KWV_2019-06-30_final
2019-06-30 11:32:51	ga_s2am_ard_3-2-1_51KVV_2019-06-30_final
2019-06-30 11:34:41	ga_s2am_ard_3-2-1_51JTN_2019-06-30_final
2019-06-30 11:34:41	ga_s2am_ard_3-2-1_50JRT_2019-06-30_final
2019-06-30 11:34:54	ga_s2am_ard_3-2-1_50JRS_2019-06-30_final
2019-06-30 11:34:59	ga_s2am_ard_3-2-1_51JWL_2019-06-30_final
2019-06-30 11:35:02	ga_s2am_ard_3-2-1_51JVL_2019-06-30_final
2019-06-30 11:35:09	ga_s2am_ard_3-2-1_51JTL_2019-06-30_final
2019-06-30 11:35:13	ga_s2am_ard_3-2-1_51JWK_2019-06-30_final
2019-06-30 11:35:17	ga_s2am_ard_3-2-1_51JVK_2019-06-30_final
2019-06-30 11:35:20	ga_s2am_ard_3-2-1_51JUK_2019-06-30_final
2019-06-30 11:35:23	ga_s2am_ard_3-2-1_51JTK_2019-06-30_final
2019-06-30 11:35:24	ga_s2am_ard_3-2-1_51JWJ_2019-06-30_final
2019-06-30 11:35:31	ga_s2am_ard_3-2-1_51JVJ_2019-06-30_final
2019-06-30 11:35:35	ga_s2am_ard_3-2-1_51JUJ_2019-06-30_final
2019-06-30 11:35:42	ga_s2am_ard_3-2-1_50JQP_2019-06-30_final
2019-06-30 11:35:55	ga_s2am_ard_3-2-1_50JQN_2019-06-30_final
2019-06-30 11:36:01	ga_s2am_ard_3-2-1_51JVG_2019-06-30_final
2019-06-30 11:36:04	ga_s2am_ard_3-2-1_51JUG_2019-06-30_final
2019-06-30 11:36:19	ga_s2am_ard_3-2-1_51JUF_2019-06-30_final
2019-06-30 11:36:22	ga_s2am_ard_3-2-1_51JTF_2019-06-30_final
2019-06-30 11:36:24	ga_s2am_ard_3-2-1_50JQL_2019-06-30_final
2019-06-30 11:36:28	ga_s2am_ard_3-2-1_51HVE_2019-06-30_final
2019-06-30 11:36:31	ga_s2am_ard_3-2-1_50JPL_2019-06-30_final
2019-06-30 11:36:33	ga_s2am_ard_3-2-1_51HUE_2019-06-30_final
2019-06-30 11:36:36	ga_s2am_ard_3-2-1_51HTE_2019-06-30_final
2019-06-30 11:36:38	ga_s2am_ard_3-2-1_51HVD_2019-06-30_final
2019-06-30 11:36:39	ga_s2am_ard_3-2-1_50HQK_2019-06-30_final
2019-06-30 11:36:42	ga_s2am_ard_3-2-1_50HPK_2019-06-30_final
2019-06-30 11:36:51	ga_s2am_ard_3-2-1_51HTD_2019-06-30_final
2019-06-30 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2019-06-30_final
2019-06-30 11:37:02	ga_s2am_ard_3-2-1_51HUC_2019-06-30_final
2019-06-30 11:37:11	ga_s2am_ard_3-2-1_50HPH_2019-06-30_final
2019-06-30 11:37:17	ga_s2am_ard_3-2-1_51HUB_2019-06-30_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