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
2022-07-03 12:05:07	ga_s2am_ard_3-2-1_50JLS_2022-07-03_final
2022-07-03 12:05:21	ga_s2am_ard_3-2-1_49JFM_2022-07-03_final
2022-07-03 12:05:51	ga_s2am_ard_3-2-1_50JLP_2022-07-03_final
2022-07-03 12:05:54	ga_s2am_ard_3-2-1_50JKP_2022-07-03_final
2022-07-03 12:06:08	ga_s2am_ard_3-2-1_50JKN_2022-07-03_final
2022-07-03 12:06:17	ga_s2am_ard_3-2-1_50JLM_2022-07-03_final
2022-07-04 09:51:32	ga_s2am_ard_3-2-1_55LFC_2022-07-04_final
2022-07-04 09:51:38	ga_s2am_ard_3-2-1_56KKG_2022-07-04_final.stac-item
2022-07-04 09:51:39	ga_s2am_ard_3-2-1_55KHB_2022-07-04_final.stac-item
2022-07-04 09:51:43	ga_s2am_ard_3-2-1_55KGB_2022-07-04_final
2022-07-04 09:52:19	ga_s2am_ard_3-2-1_55KEV_2022-07-04_final
2022-07-04 09:52:48	ga_s2am_ard_3-2-1_55KHS_2022-07-04_final
2022-07-04 09:53:17	ga_s2am_ard_3-2-1_55KER_2022-07-04_final
2022-07-04 09:53:20	ga_s2am_ard_3-2-1_55KDR_2022-07-04_final
2022-07-04 09:53:24	ga_s2am_ard_3-2-1_55KGQ_2022-07-04_final
2022-07-04 09:53:38	ga_s2am_ard_3-2-1_55KGP_2022-07-04_final
2022-07-04 09:53:42	ga_s2am_ard_3-2-1_55KFP_2022-07-04_final
2022-07-04 09:53:57	ga_s2am_ard_3-2-1_55JFN_2022-07-04_final
2022-07-04 09:54:00	ga_s2am_ard_3-2-1_55JEN_2022-07-04_final
2022-07-04 09:54:04	ga_s2am_ard_3-2-1_55JDN_2022-07-04_final
2022-07-04 09:54:10	ga_s2am_ard_3-2-1_55JCN_2022-07-04_final
2022-07-04 09:54:11	ga_s2am_ard_3-2-1_55JFM_2022-07-04_final
2022-07-04 09:54:29	ga_s2am_ard_3-2-1_55JEL_2022-07-04_final
2022-07-04 09:54:33	ga_s2am_ard_3-2-1_55JDL_2022-07-04_final
2022-07-04 09:54:36	ga_s2am_ard_3-2-1_55JCL_2022-07-04_final
2022-07-04 09:54:40	ga_s2am_ard_3-2-1_55JFK_2022-07-04_final
2022-07-04 09:54:44	ga_s2am_ard_3-2-1_55JEK_2022-07-04_final
2022-07-04 09:54:51	ga_s2am_ard_3-2-1_55JCK_2022-07-04_final
2022-07-04 09:54:53	ga_s2am_ard_3-2-1_55JFJ_2022-07-04_final
2022-07-04 09:55:03	ga_s2am_ard_3-2-1_55JFH_2022-07-04_final
2022-07-04 09:55:05	ga_s2am_ard_3-2-1_55JCJ_2022-07-04_final
2022-07-04 09:55:13	ga_s2am_ard_3-2-1_55JEH_2022-07-04_final
2022-07-04 09:55:17	ga_s2am_ard_3-2-1_55JDH_2022-07-04_final
2022-07-04 09:55:20	ga_s2am_ard_3-2-1_55JCH_2022-07-04_final
2022-07-04 09:55:24	ga_s2am_ard_3-2-1_55JBH_2022-07-04_final
2022-07-04 09:55:34	ga_s2am_ard_3-2-1_55JCG_2022-07-04_final
2022-07-04 09:55:49	ga_s2am_ard_3-2-1_55JCF_2022-07-04_final
2022-07-04 09:55:56	ga_s2am_ard_3-2-1_55HEE_2022-07-04_final
2022-07-04 09:56:00	ga_s2am_ard_3-2-1_55HDE_2022-07-04_final
2022-07-04 09:56:03	ga_s2am_ard_3-2-1_55HCE_2022-07-04_final
2022-07-04 09:56:07	ga_s2am_ard_3-2-1_55HED_2022-07-04_final
2022-07-04 09:56:14	ga_s2am_ard_3-2-1_55HDD_2022-07-04_final
2022-07-04 09:56:21	ga_s2am_ard_3-2-1_55HBD_2022-07-04_final
2022-07-04 09:56:23	ga_s2am_ard_3-2-1_54HYJ_2022-07-04_final
2022-07-04 09:56:29	ga_s2am_ard_3-2-1_55HDC_2022-07-04_final
2022-07-04 09:56:39	ga_s2am_ard_3-2-1_55HDB_2022-07-04_final
2022-07-04 09:56:46	ga_s2am_ard_3-2-1_55HDB_2022-07-04_final
2022-07-04 09:57:02	ga_s2am_ard_3-2-1_55HCA_2022-07-04_final
2022-07-04 09:57:10	ga_s2am_ard_3-2-1_54HXF_2022-07-04_final
2022-07-04 09:57:31	ga_s2am_ard_3-2-1_55HCU_2022-07-04_final
2022-07-04 09:57:34	ga_s2am_ard_3-2-1_55HBU_2022-07-04_final
2022-07-04 09:57:35	ga_s2am_ard_3-2-1_54HYD_2022-07-04_final
2022-07-04 09:57:39	ga_s2am_ard_3-2-1_54HXD_2022-07-04_final
2022-07-04 09:57:45	ga_s2am_ard_3-2-1_55HCT_2022-07-04_final
2022-07-04 09:57:49	ga_s2am_ard_3-2-1_55HBT_2022-07-04_final
2022-07-04 09:57:50	ga_s2am_ard_3-2-1_54HYC_2022-07-04_final
2022-07-04 09:57:53	ga_s2am_ard_3-2-1_54HXC_2022-07-04_final
2022-07-04 09:57:58	ga_s2am_ard_3-2-1_54HWC_2022-07-04_final
2022-07-04 09:58:04	ga_s2am_ard_3-2-1_54HYB_2022-07-04_final
2022-07-04 11:31:31	ga_s2am_ard_3-2-1_52LBK_2022-07-04_final
2022-07-04 11:31:34	ga_s2am_ard_3-2-1_51LZE_2022-07-04_final
2022-07-04 11:31:37	ga_s2am_ard_3-2-1_51LYE_2022-07-04_final
2022-07-04 11:31:52	ga_s2am_ard_3-2-1_51LYD_2022-07-04_final
2022-07-04 11:31:55	ga_s2am_ard_3-2-1_51LXD_2022-07-04_final
2022-07-04 11:32:12	ga_s2am_ard_3-2-1_51KZB_2022-07-04_final
2022-07-04 11:32:13	ga_s2am_ard_3-2-1_51LWC_2022-07-04_final
2022-07-04 11:32:20	ga_s2am_ard_3-2-1_51KYB_2022-07-04_final
2022-07-04 11:32:24	ga_s2am_ard_3-2-1_51KXB_2022-07-04_final
2022-07-04 11:32:42	ga_s2am_ard_3-2-1_51KWA_2022-07-04_final
2022-07-04 11:32:53	ga_s2am_ard_3-2-1_51KXV_2022-07-04_final
2022-07-04 11:32:57	ga_s2am_ard_3-2-1_51KWV_2022-07-04_final
2022-07-04 11:33:00	ga_s2am_ard_3-2-1_51KVV_2022-07-04_final
2022-07-04 11:33:55	ga_s2am_ard_3-2-1_51KWR_2022-07-04_final
2022-07-04 11:33:58	ga_s2am_ard_3-2-1_51KVR_2022-07-04_final
2022-07-04 11:34:18	ga_s2am_ard_3-2-1_51KXP_2022-07-04_final
2022-07-04 11:34:30	ga_s2am_ard_3-2-1_51KUP_2022-07-04_final
2022-07-04 11:34:38	ga_s2am_ard_3-2-1_51KTP_2022-07-04_final
2022-07-04 11:34:38	ga_s2am_ard_3-2-1_51JWN_2022-07-04_final
2022-07-04 11:34:42	ga_s2am_ard_3-2-1_51JVN_2022-07-04_final
2022-07-04 11:34:45	ga_s2am_ard_3-2-1_51JUN_2022-07-04_final
2022-07-04 11:34:49	ga_s2am_ard_3-2-1_51JTN_2022-07-04_final
2022-07-04 11:35:07	ga_s2am_ard_3-2-1_51JWL_2022-07-04_final
2022-07-04 11:35:11	ga_s2am_ard_3-2-1_51JVL_2022-07-04_final
2022-07-04 11:35:21	ga_s2am_ard_3-2-1_51JWK_2022-07-04_final
2022-07-04 11:35:25	ga_s2am_ard_3-2-1_51JVK_2022-07-04_final
2022-07-04 11:35:29	ga_s2am_ard_3-2-1_51JUK_2022-07-04_final
2022-07-04 11:35:43	ga_s2am_ard_3-2-1_51JUJ_2022-07-04_final
2022-07-04 11:35:46	ga_s2am_ard_3-2-1_51JTJ_2022-07-04_final
2022-07-04 11:35:50	ga_s2am_ard_3-2-1_50JQP_2022-07-04_final
2022-07-04 11:35:54	ga_s2am_ard_3-2-1_51JVH_2022-07-04_final
2022-07-04 11:35:58	ga_s2am_ard_3-2-1_51JUH_2022-07-04_final
2022-07-04 11:36:01	ga_s2am_ard_3-2-1_51JTH_2022-07-04_final
2022-07-04 11:36:03	ga_s2am_ard_3-2-1_50JQN_2022-07-04_final
2022-07-04 11:36:12	ga_s2am_ard_3-2-1_51JUG_2022-07-04_final
2022-07-04 11:36:23	ga_s2am_ard_3-2-1_51JVF_2022-07-04_final
2022-07-04 11:36:39	ga_s2am_ard_3-2-1_50JPL_2022-07-04_final
2022-07-04 11:36:46	ga_s2am_ard_3-2-1_51HVD_2022-07-04_final
2022-07-04 11:36:59	ga_s2am_ard_3-2-1_51HTD_2022-07-04_final
2022-07-04 11:37:01	ga_s2am_ard_3-2-1_50HQJ_2022-07-04_final
2022-07-04 11:37:39	ga_s2am_ard_3-2-1_50HNG_2022-07-04_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