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
2022-07-15 09:26:44	ga_s2am_ard_3-2-1_56HKG_2022-07-14_final
2022-07-15 09:26:57	ga_s2am_ard_3-2-1_56HKF_2022-07-14_final
2022-07-15 09:27:13	ga_s2am_ard_3-2-1_55HGV_2022-07-14_final
2022-07-15 09:27:27	ga_s2am_ard_3-2-1_55HGU_2022-07-14_final.stac-item
2022-07-15 09:28:01	ga_s2am_ard_3-2-1_55HFS_2022-07-14_final.stac-item
2022-07-15 09:28:14	ga_s2am_ard_3-2-1_55GFR_2022-07-14_final
2022-07-15 09:28:28	ga_s2am_ard_3-2-1_55GFQ_2022-07-14_final
2022-07-15 09:28:43	ga_s2am_ard_3-2-1_55GFP_2022-07-14_final
2022-07-15 09:28:50	ga_s2am_ard_3-2-1_55GEP_2022-07-14_final
2022-07-15 09:28:55	ga_s2am_ard_3-2-1_55GFN_2022-07-14_final
2022-07-15 09:28:58	ga_s2am_ard_3-2-1_55GEN_2022-07-14_final
2022-07-15 09:29:02	ga_s2am_ard_3-2-1_55GFN_2022-07-14_final.stac-item
2022-07-15 09:29:04	ga_s2am_ard_3-2-1_55GEN_2022-07-14_final
2022-07-15 09:29:13	ga_s2am_ard_3-2-1_55GEM_2022-07-14_final.stac-item
2022-07-15 11:00:41	ga_s2am_ard_3-2-1_53LKH_2022-07-15_final
2022-07-15 11:00:43	ga_s2am_ard_3-2-1_52LHN_2022-07-15_final
2022-07-15 11:00:48	ga_s2am_ard_3-2-1_53LMG_2022-07-15_final
2022-07-15 11:00:49	ga_s2am_ard_3-2-1_52LGN_2022-07-15_final
2022-07-15 11:00:52	ga_s2am_ard_3-2-1_53LLG_2022-07-15_final
2022-07-15 11:00:56	ga_s2am_ard_3-2-1_53LKG_2022-07-15_final
2022-07-15 11:00:57	ga_s2am_ard_3-2-1_52LHM_2022-07-15_final
2022-07-15 11:01:01	ga_s2am_ard_3-2-1_53LMF_2022-07-15_final
2022-07-15 11:01:01	ga_s2am_ard_3-2-1_52LGM_2022-07-15_final
2022-07-15 11:01:25	ga_s2am_ard_3-2-1_53LKE_2022-07-15_final
2022-07-15 11:01:26	ga_s2am_ard_3-2-1_52LHK_2022-07-15_final
2022-07-15 11:01:30	ga_s2am_ard_3-2-1_52LGK_2022-07-15_final
2022-07-15 11:01:36	ga_s2am_ard_3-2-1_53LLD_2022-07-15_final
2022-07-15 11:01:39	ga_s2am_ard_3-2-1_53LKD_2022-07-15_final
2022-07-15 11:01:41	ga_s2am_ard_3-2-1_52LHJ_2022-07-15_final
2022-07-15 11:01:44	ga_s2am_ard_3-2-1_52LGJ_2022-07-15_final
2022-07-15 11:01:51	ga_s2am_ard_3-2-1_53LLC_2022-07-15_final
2022-07-15 11:01:51	ga_s2am_ard_3-2-1_52LFJ_2022-07-15_final
2022-07-15 11:02:02	ga_s2am_ard_3-2-1_52LFH_2022-07-15_final
2022-07-15 11:02:04	ga_s2am_ard_3-2-1_53KLB_2022-07-15_final
2022-07-15 11:02:08	ga_s2am_ard_3-2-1_53KKB_2022-07-15_final
2022-07-15 11:02:10	ga_s2am_ard_3-2-1_52KHG_2022-07-15_final
2022-07-15 11:02:13	ga_s2am_ard_3-2-1_52KGG_2022-07-15_final
2022-07-15 11:02:16	ga_s2am_ard_3-2-1_52KFG_2022-07-15_final
2022-07-15 11:02:23	ga_s2am_ard_3-2-1_53KKA_2022-07-15_final
2022-07-15 11:02:24	ga_s2am_ard_3-2-1_52KHF_2022-07-15_final
2022-07-15 11:02:28	ga_s2am_ard_3-2-1_52KGF_2022-07-15_final
2022-07-15 11:02:37	ga_s2am_ard_3-2-1_53KKV_2022-07-15_final
2022-07-15 11:02:38	ga_s2am_ard_3-2-1_52KHE_2022-07-15_final
2022-07-15 11:02:42	ga_s2am_ard_3-2-1_52KGE_2022-07-15_final
2022-07-15 11:02:46	ga_s2am_ard_3-2-1_52KFE_2022-07-15_final
2022-07-15 11:02:53	ga_s2am_ard_3-2-1_52KHD_2022-07-15_final
2022-07-15 11:03:07	ga_s2am_ard_3-2-1_52KHC_2022-07-15_final
2022-07-15 11:03:22	ga_s2am_ard_3-2-1_52KHB_2022-07-15_final
2022-07-15 11:03:29	ga_s2am_ard_3-2-1_52KFB_2022-07-15_final
2022-07-15 11:03:31	ga_s2am_ard_3-2-1_53KKR_2022-07-15_final
2022-07-15 11:03:35	ga_s2am_ard_3-2-1_52KHA_2022-07-15_final
2022-07-15 11:03:40	ga_s2am_ard_3-2-1_52KGA_2022-07-15_final
2022-07-15 11:03:43	ga_s2am_ard_3-2-1_52KFA_2022-07-15_final
2022-07-15 11:03:45	ga_s2am_ard_3-2-1_52KHV_2022-07-15_final
2022-07-15 11:03:47	ga_s2am_ard_3-2-1_52KEA_2022-07-15_final
2022-07-15 11:03:54	ga_s2am_ard_3-2-1_52KGV_2022-07-15_final
2022-07-15 11:03:58	ga_s2am_ard_3-2-1_52KFV_2022-07-15_final
2022-07-15 11:04:01	ga_s2am_ard_3-2-1_52KEV_2022-07-15_final
2022-07-15 11:04:06	ga_s2am_ard_3-2-1_52KDV_2022-07-15_final
2022-07-15 11:04:09	ga_s2am_ard_3-2-1_52KGU_2022-07-15_final
2022-07-15 11:04:12	ga_s2am_ard_3-2-1_52KFU_2022-07-15_final
2022-07-15 11:04:23	ga_s2am_ard_3-2-1_52JGT_2022-07-15_final
2022-07-15 11:04:27	ga_s2am_ard_3-2-1_52JFT_2022-07-15_final
2022-07-15 11:04:30	ga_s2am_ard_3-2-1_52JET_2022-07-15_final
2022-07-15 11:04:34	ga_s2am_ard_3-2-1_52JDT_2022-07-15_final
2022-07-15 11:04:37	ga_s2am_ard_3-2-1_52JGS_2022-07-15_final
2022-07-15 11:04:41	ga_s2am_ard_3-2-1_52JFS_2022-07-15_final
2022-07-15 11:04:45	ga_s2am_ard_3-2-1_52JES_2022-07-15_final
2022-07-15 11:04:48	ga_s2am_ard_3-2-1_52JGR_2022-07-15_final
2022-07-15 11:04:48	ga_s2am_ard_3-2-1_52JDS_2022-07-15_final
2022-07-15 11:04:56	ga_s2am_ard_3-2-1_52JFR_2022-07-15_final
2022-07-15 11:05:00	ga_s2am_ard_3-2-1_52JER_2022-07-15_final
2022-07-15 11:05:03	ga_s2am_ard_3-2-1_52JDR_2022-07-15_final
2022-07-15 11:05:08	ga_s2am_ard_3-2-1_52JCR_2022-07-15_final
2022-07-15 11:05:10	ga_s2am_ard_3-2-1_52JFQ_2022-07-15_final
2022-07-15 11:05:21	ga_s2am_ard_3-2-1_52JCQ_2022-07-15_final
2022-07-15 11:05:25	ga_s2am_ard_3-2-1_52JFP_2022-07-15_final
2022-07-15 11:05:28	ga_s2am_ard_3-2-1_52JEP_2022-07-15_final
2022-07-15 11:05:32	ga_s2am_ard_3-2-1_52JDP_2022-07-15_final
2022-07-15 11:05:39	ga_s2am_ard_3-2-1_52JFN_2022-07-15_final
2022-07-15 11:05:43	ga_s2am_ard_3-2-1_52JEN_2022-07-15_final
2022-07-15 11:05:46	ga_s2am_ard_3-2-1_52JDN_2022-07-15_final
2022-07-15 11:05:50	ga_s2am_ard_3-2-1_52JCN_2022-07-15_final
2022-07-15 11:05:51	ga_s2am_ard_3-2-1_52JFM_2022-07-15_final
2022-07-15 11:05:57	ga_s2am_ard_3-2-1_52JEM_2022-07-15_final
2022-07-15 11:06:01	ga_s2am_ard_3-2-1_52JDM_2022-07-15_final
2022-07-15 11:06:04	ga_s2am_ard_3-2-1_52JCM_2022-07-15_final
2022-07-15 11:06:09	ga_s2am_ard_3-2-1_52JEL_2022-07-15_final
2022-07-15 11:06:10	ga_s2am_ard_3-2-1_52JBM_2022-07-15_final
2022-07-15 11:06:11	ga_s2am_ard_3-2-1_52JDL_2022-07-15_final
2022-07-15 11:06:12	ga_s2am_ard_3-2-1_52JCM_2022-07-15_final
2022-07-15 11:06:13	ga_s2am_ard_3-2-1_52JCL_2022-07-15_final
2022-07-15 11:06:14	ga_s2am_ard_3-2-1_52JBM_2022-07-15_final
2022-07-15 11:06:14	ga_s2am_ard_3-2-1_52JBL_2022-07-15_final
2022-07-15 11:06:16	ga_s2am_ard_3-2-1_52JEL_2022-07-15_final
2022-07-15 11:06:17	ga_s2am_ard_3-2-1_52JDL_2022-07-15_final
2022-07-15 11:06:19	ga_s2am_ard_3-2-1_52JCL_2022-07-15_final
2022-07-15 11:06:22	ga_s2am_ard_3-2-1_52JBL_2022-07-15_final
2022-07-15 11:06:30	ga_s2am_ard_3-2-1_52HDK_2022-07-15_final.stac-item
2022-07-15 11:06:36	ga_s2am_ard_3-2-1_52HBK_2022-07-15_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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