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
2019-11-08 09:26:34	ga_s2am_ard_3-2-1_56HKG_2019-11-07_final
2019-11-08 09:27:03	ga_s2am_ard_3-2-1_55HGV_2019-11-07_final
2019-11-08 09:27:17	ga_s2am_ard_3-2-1_55HGU_2019-11-07_final.stac-item
2019-11-08 09:27:52	ga_s2am_ard_3-2-1_55HFS_2019-11-07_final.stac-item
2019-11-08 09:28:33	ga_s2am_ard_3-2-1_55GFP_2019-11-07_final
2019-11-08 09:28:40	ga_s2am_ard_3-2-1_55GEP_2019-11-07_final
2019-11-08 09:28:47	ga_s2am_ard_3-2-1_55GFN_2019-11-07_final
2019-11-08 09:28:51	ga_s2am_ard_3-2-1_55GEN_2019-11-07_final
2019-11-08 09:29:03	ga_s2am_ard_3-2-1_55GEM_2019-11-07_final.stac-item
2019-11-08 11:00:17	ga_s2am_ard_3-2-1_53LKJ_2019-11-08_final.stac-item
2019-11-08 11:00:25	ga_s2am_ard_3-2-1_53LMH_2019-11-08_final.stac-item
2019-11-08 11:00:28	ga_s2am_ard_3-2-1_53LLH_2019-11-08_final.stac-item
2019-11-08 11:00:31	ga_s2am_ard_3-2-1_53LKH_2019-11-08_final
2019-11-08 11:00:33	ga_s2am_ard_3-2-1_52LHN_2019-11-08_final
2019-11-08 11:00:39	ga_s2am_ard_3-2-1_53LMG_2019-11-08_final
2019-11-08 11:00:40	ga_s2am_ard_3-2-1_52LGN_2019-11-08_final
2019-11-08 11:00:43	ga_s2am_ard_3-2-1_53LLG_2019-11-08_final
2019-11-08 11:00:46	ga_s2am_ard_3-2-1_53LKG_2019-11-08_final
2019-11-08 11:00:47	ga_s2am_ard_3-2-1_52LHM_2019-11-08_final
2019-11-08 11:00:51	ga_s2am_ard_3-2-1_53LMF_2019-11-08_final
2019-11-08 11:00:51	ga_s2am_ard_3-2-1_52LGM_2019-11-08_final
2019-11-08 11:01:00	ga_s2am_ard_3-2-1_53LKF_2019-11-08_final
2019-11-08 11:01:02	ga_s2am_ard_3-2-1_52LHL_2019-11-08_final
2019-11-08 11:01:05	ga_s2am_ard_3-2-1_52LGL_2019-11-08_final
2019-11-08 11:01:11	ga_s2am_ard_3-2-1_53LLE_2019-11-08_final
2019-11-08 11:01:15	ga_s2am_ard_3-2-1_53LKE_2019-11-08_final
2019-11-08 11:01:16	ga_s2am_ard_3-2-1_52LHK_2019-11-08_final
2019-11-08 11:01:20	ga_s2am_ard_3-2-1_52LGK_2019-11-08_final
2019-11-08 11:01:26	ga_s2am_ard_3-2-1_53LLD_2019-11-08_final
2019-11-08 11:01:29	ga_s2am_ard_3-2-1_53LKD_2019-11-08_final
2019-11-08 11:01:31	ga_s2am_ard_3-2-1_52LHJ_2019-11-08_final
2019-11-08 11:01:34	ga_s2am_ard_3-2-1_52LGJ_2019-11-08_final
2019-11-08 11:01:41	ga_s2am_ard_3-2-1_53LLC_2019-11-08_final
2019-11-08 11:01:42	ga_s2am_ard_3-2-1_52LFJ_2019-11-08_final
2019-11-08 11:01:44	ga_s2am_ard_3-2-1_53LKC_2019-11-08_final
2019-11-08 11:01:45	ga_s2am_ard_3-2-1_52LHH_2019-11-08_final
2019-11-08 11:01:49	ga_s2am_ard_3-2-1_52LGH_2019-11-08_final
2019-11-08 11:01:53	ga_s2am_ard_3-2-1_52LFH_2019-11-08_final
2019-11-08 11:01:54	ga_s2am_ard_3-2-1_53KLB_2019-11-08_final
2019-11-08 11:01:58	ga_s2am_ard_3-2-1_53KKB_2019-11-08_final
2019-11-08 11:02:00	ga_s2am_ard_3-2-1_52KHG_2019-11-08_final
2019-11-08 11:02:03	ga_s2am_ard_3-2-1_52KGG_2019-11-08_final
2019-11-08 11:02:06	ga_s2am_ard_3-2-1_53KLA_2019-11-08_final
2019-11-08 11:02:06	ga_s2am_ard_3-2-1_52KFG_2019-11-08_final
2019-11-08 11:02:13	ga_s2am_ard_3-2-1_53KKA_2019-11-08_final
2019-11-08 11:02:14	ga_s2am_ard_3-2-1_52KHF_2019-11-08_final
2019-11-08 11:02:18	ga_s2am_ard_3-2-1_52KGF_2019-11-08_final
2019-11-08 11:02:21	ga_s2am_ard_3-2-1_52KFF_2019-11-08_final
2019-11-08 11:02:27	ga_s2am_ard_3-2-1_53KKV_2019-11-08_final
2019-11-08 11:02:28	ga_s2am_ard_3-2-1_52KHE_2019-11-08_final
2019-11-08 11:02:32	ga_s2am_ard_3-2-1_52KGE_2019-11-08_final
2019-11-08 11:02:36	ga_s2am_ard_3-2-1_52KFE_2019-11-08_final
2019-11-08 11:02:42	ga_s2am_ard_3-2-1_53KKU_2019-11-08_final
2019-11-08 11:02:43	ga_s2am_ard_3-2-1_52KHD_2019-11-08_final
2019-11-08 11:02:47	ga_s2am_ard_3-2-1_52KGD_2019-11-08_final
2019-11-08 11:02:50	ga_s2am_ard_3-2-1_52KFD_2019-11-08_final
2019-11-08 11:02:54	ga_s2am_ard_3-2-1_52KED_2019-11-08_final
2019-11-08 11:02:57	ga_s2am_ard_3-2-1_53KKT_2019-11-08_final
2019-11-08 11:02:57	ga_s2am_ard_3-2-1_52KHC_2019-11-08_final
2019-11-08 11:03:01	ga_s2am_ard_3-2-1_52KGC_2019-11-08_final
2019-11-08 11:03:05	ga_s2am_ard_3-2-1_52KFC_2019-11-08_final
2019-11-08 11:03:08	ga_s2am_ard_3-2-1_52KEC_2019-11-08_final
2019-11-08 11:03:10	ga_s2am_ard_3-2-1_53KKS_2019-11-08_final
2019-11-08 11:03:12	ga_s2am_ard_3-2-1_52KHB_2019-11-08_final
2019-11-08 11:03:16	ga_s2am_ard_3-2-1_52KGB_2019-11-08_final
2019-11-08 11:03:19	ga_s2am_ard_3-2-1_52KFB_2019-11-08_final
2019-11-08 11:03:21	ga_s2am_ard_3-2-1_53KKR_2019-11-08_final
2019-11-08 11:03:22	ga_s2am_ard_3-2-1_52KEB_2019-11-08_final
2019-11-08 11:03:25	ga_s2am_ard_3-2-1_52KHA_2019-11-08_final
2019-11-08 11:03:30	ga_s2am_ard_3-2-1_52KGA_2019-11-08_final
2019-11-08 11:03:34	ga_s2am_ard_3-2-1_52KFA_2019-11-08_final
2019-11-08 11:03:35	ga_s2am_ard_3-2-1_52KHV_2019-11-08_final
2019-11-08 11:03:37	ga_s2am_ard_3-2-1_52KEA_2019-11-08_final
2019-11-08 11:03:44	ga_s2am_ard_3-2-1_52KGV_2019-11-08_final
2019-11-08 11:03:48	ga_s2am_ard_3-2-1_52KFV_2019-11-08_final
2019-11-08 11:03:52	ga_s2am_ard_3-2-1_52KEV_2019-11-08_final
2019-11-08 11:03:56	ga_s2am_ard_3-2-1_52KDV_2019-11-08_final
2019-11-08 11:03:59	ga_s2am_ard_3-2-1_52KGU_2019-11-08_final
2019-11-08 11:04:03	ga_s2am_ard_3-2-1_52KFU_2019-11-08_final
2019-11-08 11:04:06	ga_s2am_ard_3-2-1_52KEU_2019-11-08_final
2019-11-08 11:04:09	ga_s2am_ard_3-2-1_52KDU_2019-11-08_final
2019-11-08 11:04:13	ga_s2am_ard_3-2-1_52JGT_2019-11-08_final
2019-11-08 11:04:17	ga_s2am_ard_3-2-1_52JFT_2019-11-08_final
2019-11-08 11:04:21	ga_s2am_ard_3-2-1_52JET_2019-11-08_final
2019-11-08 11:04:24	ga_s2am_ard_3-2-1_52JDT_2019-11-08_final
2019-11-08 11:04:27	ga_s2am_ard_3-2-1_52JGS_2019-11-08_final
2019-11-08 11:04:31	ga_s2am_ard_3-2-1_52JFS_2019-11-08_final
2019-11-08 11:04:35	ga_s2am_ard_3-2-1_52JES_2019-11-08_final
2019-11-08 11:04:38	ga_s2am_ard_3-2-1_52JGR_2019-11-08_final
2019-11-08 11:04:38	ga_s2am_ard_3-2-1_52JDS_2019-11-08_final
2019-11-08 11:05:00	ga_s2am_ard_3-2-1_52JFQ_2019-11-08_final
2019-11-08 11:05:04	ga_s2am_ard_3-2-1_52JEQ_2019-11-08_final
2019-11-08 11:05:07	ga_s2am_ard_3-2-1_52JDQ_2019-11-08_final
2019-11-08 11:05:29	ga_s2am_ard_3-2-1_52JFN_2019-11-08_final
2019-11-08 11:05:33	ga_s2am_ard_3-2-1_52JEN_2019-11-08_final
2019-11-08 11:05:37	ga_s2am_ard_3-2-1_52JDN_2019-11-08_final
2019-11-08 11:05:40	ga_s2am_ard_3-2-1_52JCN_2019-11-08_final
2019-11-08 11:05:47	ga_s2am_ard_3-2-1_52JEM_2019-11-08_final
2019-11-08 11:05:51	ga_s2am_ard_3-2-1_52JDM_2019-11-08_final
2019-11-08 11:06:13	ga_s2am_ard_3-2-1_52JBL_2019-11-08_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

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