Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2022-02-14 11:36:26	ga_s2am_ard_3-2-1_50JPL_2022-02-14_final.stac-item
2022-02-14 11:36:28	ga_s2am_ard_3-2-1_51HUE_2022-02-14_final.stac-item
2022-02-14 11:36:32	ga_s2am_ard_3-2-1_51HTE_2022-02-14_final.stac-item
2022-02-14 11:36:34	ga_s2am_ard_3-2-1_51HVD_2022-02-14_final.stac-item
2022-02-14 11:36:34	ga_s2am_ard_3-2-1_50HQK_2022-02-14_final.stac-item
2022-02-14 11:36:38	ga_s2am_ard_3-2-1_50HPK_2022-02-14_final.stac-item
2022-02-14 11:36:43	ga_s2am_ard_3-2-1_51HUD_2022-02-14_final.stac-item
2022-02-14 11:36:46	ga_s2am_ard_3-2-1_51HTD_2022-02-14_final.stac-item
2022-02-14 11:36:48	ga_s2am_ard_3-2-1_50HQJ_2022-02-14_final.stac-item
2022-02-14 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2022-02-14_final.stac-item
2022-02-14 11:36:57	ga_s2am_ard_3-2-1_51HUC_2022-02-14_final.stac-item
2022-02-14 11:37:01	ga_s2am_ard_3-2-1_51HTC_2022-02-14_final.stac-item
2022-02-14 11:37:03	ga_s2am_ard_3-2-1_50HQH_2022-02-14_final.stac-item
2022-02-14 11:37:07	ga_s2am_ard_3-2-1_50HPH_2022-02-14_final.stac-item
2022-02-15 09:25:40	ga_s2am_ard_3-2-1_56HMK_2022-02-14_final.stac-item
2022-02-15 09:25:43	ga_s2am_ard_3-2-1_56HLK_2022-02-14_final.stac-item
2022-02-15 09:25:54	ga_s2am_ard_3-2-1_56HMJ_2022-02-14_final.stac-item
2022-02-15 09:25:58	ga_s2am_ard_3-2-1_56HLJ_2022-02-14_final.stac-item
2022-02-15 09:26:32	ga_s2am_ard_3-2-1_56HKG_2022-02-14_final.stac-item
2022-02-15 09:26:45	ga_s2am_ard_3-2-1_56HKF_2022-02-14_final.stac-item
2022-02-15 09:28:38	ga_s2am_ard_3-2-1_55GEP_2022-02-14_final.stac-item
2022-02-15 09:28:49	ga_s2am_ard_3-2-1_55GEN_2022-02-14_final.stac-item
2022-02-15 11:01:52	ga_s2am_ard_3-2-1_53KLB_2022-02-15_final.stac-item
2022-02-15 11:01:56	ga_s2am_ard_3-2-1_53KKB_2022-02-15_final.stac-item
2022-02-15 11:01:57	ga_s2am_ard_3-2-1_52KHG_2022-02-15_final.stac-item
2022-02-15 11:02:01	ga_s2am_ard_3-2-1_52KGG_2022-02-15_final.stac-item
2022-02-15 11:02:03	ga_s2am_ard_3-2-1_53KLA_2022-02-15_final.stac-item
2022-02-15 11:02:04	ga_s2am_ard_3-2-1_52KFG_2022-02-15_final.stac-item
2022-02-15 11:02:11	ga_s2am_ard_3-2-1_53KKA_2022-02-15_final.stac-item
2022-02-15 11:02:12	ga_s2am_ard_3-2-1_52KHF_2022-02-15_final.stac-item
2022-02-15 11:02:15	ga_s2am_ard_3-2-1_52KGF_2022-02-15_final.stac-item
2022-02-15 11:02:19	ga_s2am_ard_3-2-1_52KFF_2022-02-15_final.stac-item
2022-02-15 11:02:25	ga_s2am_ard_3-2-1_53KKV_2022-02-15_final.stac-item
2022-02-15 11:02:26	ga_s2am_ard_3-2-1_52KHE_2022-02-15_final.stac-item
2022-02-15 11:02:30	ga_s2am_ard_3-2-1_52KGE_2022-02-15_final.stac-item
2022-02-15 11:02:33	ga_s2am_ard_3-2-1_52KFE_2022-02-15_final.stac-item
2022-02-15 11:02:40	ga_s2am_ard_3-2-1_53KKU_2022-02-15_final.stac-item
2022-02-15 11:02:40	ga_s2am_ard_3-2-1_52KHD_2022-02-15_final.stac-item
2022-02-15 11:02:44	ga_s2am_ard_3-2-1_52KGD_2022-02-15_final.stac-item
2022-02-15 11:02:48	ga_s2am_ard_3-2-1_52KFD_2022-02-15_final.stac-item
2022-02-15 11:02:52	ga_s2am_ard_3-2-1_52KED_2022-02-15_final.stac-item
2022-02-15 11:02:54	ga_s2am_ard_3-2-1_53KKT_2022-02-15_final.stac-item
2022-02-15 11:02:55	ga_s2am_ard_3-2-1_52KHC_2022-02-15_final.stac-item
2022-02-15 11:02:59	ga_s2am_ard_3-2-1_52KGC_2022-02-15_final.stac-item
2022-02-15 11:03:02	ga_s2am_ard_3-2-1_52KFC_2022-02-15_final.stac-item
2022-02-15 11:03:05	ga_s2am_ard_3-2-1_52KEC_2022-02-15_final.stac-item
2022-02-15 11:03:08	ga_s2am_ard_3-2-1_53KKS_2022-02-15_final.stac-item
2022-02-15 11:03:10	ga_s2am_ard_3-2-1_52KHB_2022-02-15_final.stac-item
2022-02-15 11:03:13	ga_s2am_ard_3-2-1_52KGB_2022-02-15_final.stac-item
2022-02-15 11:03:17	ga_s2am_ard_3-2-1_52KFB_2022-02-15_final.stac-item
2022-02-15 11:03:19	ga_s2am_ard_3-2-1_53KKR_2022-02-15_final.stac-item
2022-02-15 11:03:20	ga_s2am_ard_3-2-1_52KEB_2022-02-15_final.stac-item
2022-02-15 11:03:23	ga_s2am_ard_3-2-1_52KHA_2022-02-15_final.stac-item
2022-02-15 11:03:28	ga_s2am_ard_3-2-1_52KGA_2022-02-15_final.stac-item
2022-02-15 11:03:31	ga_s2am_ard_3-2-1_52KFA_2022-02-15_final.stac-item
2022-02-15 11:03:33	ga_s2am_ard_3-2-1_52KHV_2022-02-15_final.stac-item
2022-02-15 11:03:35	ga_s2am_ard_3-2-1_52KEA_2022-02-15_final.stac-item
2022-02-15 11:03:42	ga_s2am_ard_3-2-1_52KGV_2022-02-15_final.stac-item
2022-02-15 11:03:46	ga_s2am_ard_3-2-1_52KFV_2022-02-15_final.stac-item
2022-02-15 11:03:49	ga_s2am_ard_3-2-1_52KEV_2022-02-15_final.stac-item
2022-02-15 11:03:54	ga_s2am_ard_3-2-1_52KDV_2022-02-15_final.stac-item
2022-02-15 11:03:56	ga_s2am_ard_3-2-1_52KGU_2022-02-15_final.stac-item
2022-02-15 11:04:00	ga_s2am_ard_3-2-1_52KFU_2022-02-15_final.stac-item
2022-02-15 11:04:04	ga_s2am_ard_3-2-1_52KEU_2022-02-15_final.stac-item
2022-02-15 11:04:07	ga_s2am_ard_3-2-1_52KDU_2022-02-15_final.stac-item
2022-02-15 11:04:11	ga_s2am_ard_3-2-1_52JGT_2022-02-15_final.stac-item
2022-02-15 11:04:15	ga_s2am_ard_3-2-1_52JFT_2022-02-15_final.stac-item
2022-02-15 11:04:18	ga_s2am_ard_3-2-1_52JET_2022-02-15_final.stac-item
2022-02-15 11:04:21	ga_s2am_ard_3-2-1_52JDT_2022-02-15_final.stac-item
2022-02-15 11:04:25	ga_s2am_ard_3-2-1_52JGS_2022-02-15_final.stac-item
2022-02-15 11:04:29	ga_s2am_ard_3-2-1_52JFS_2022-02-15_final.stac-item
2022-02-15 11:04:33	ga_s2am_ard_3-2-1_52JES_2022-02-15_final.stac-item
2022-02-15 11:04:36	ga_s2am_ard_3-2-1_52JGR_2022-02-15_final.stac-item
2022-02-15 11:04:36	ga_s2am_ard_3-2-1_52JDS_2022-02-15_final.stac-item
2022-02-15 11:04:43	ga_s2am_ard_3-2-1_52JFR_2022-02-15_final.stac-item
2022-02-15 11:04:47	ga_s2am_ard_3-2-1_52JER_2022-02-15_final.stac-item
2022-02-15 11:04:51	ga_s2am_ard_3-2-1_52JDR_2022-02-15_final.stac-item
2022-02-15 11:04:56	ga_s2am_ard_3-2-1_52JCR_2022-02-15_final.stac-item
2022-02-15 11:04:58	ga_s2am_ard_3-2-1_52JFQ_2022-02-15_final.stac-item
2022-02-15 11:05:02	ga_s2am_ard_3-2-1_52JEQ_2022-02-15_final.stac-item
2022-02-15 11:05:05	ga_s2am_ard_3-2-1_52JDQ_2022-02-15_final.stac-item
2022-02-15 11:05:08	ga_s2am_ard_3-2-1_52JCQ_2022-02-15_final.stac-item
2022-02-15 11:05:13	ga_s2am_ard_3-2-1_52JFP_2022-02-15_final.stac-item
2022-02-15 11:05:16	ga_s2am_ard_3-2-1_52JEP_2022-02-15_final.stac-item
2022-02-15 11:05:20	ga_s2am_ard_3-2-1_52JDP_2022-02-15_final.stac-item
2022-02-15 11:05:23	ga_s2am_ard_3-2-1_52JCP_2022-02-15_final.stac-item
2022-02-15 11:05:27	ga_s2am_ard_3-2-1_52JFN_2022-02-15_final.stac-item
2022-02-15 11:05:31	ga_s2am_ard_3-2-1_52JEN_2022-02-15_final.stac-item
2022-02-15 11:05:34	ga_s2am_ard_3-2-1_52JDN_2022-02-15_final.stac-item
2022-02-15 11:05:38	ga_s2am_ard_3-2-1_52JCN_2022-02-15_final.stac-item
2022-02-15 11:05:39	ga_s2am_ard_3-2-1_52JFM_2022-02-15_final.stac-item
2022-02-15 11:05:45	ga_s2am_ard_3-2-1_52JEM_2022-02-15_final.stac-item
2022-02-15 11:05:49	ga_s2am_ard_3-2-1_52JDM_2022-02-15_final.stac-item
2022-02-15 11:05:52	ga_s2am_ard_3-2-1_52JCM_2022-02-15_final.stac-item
2022-02-15 11:05:58	ga_s2am_ard_3-2-1_52JBM_2022-02-15_final.stac-item
2022-02-15 11:06:00	ga_s2am_ard_3-2-1_52JEL_2022-02-15_final.stac-item
2022-02-15 11:06:03	ga_s2am_ard_3-2-1_52JDL_2022-02-15_final.stac-item
2022-02-15 11:06:07	ga_s2am_ard_3-2-1_52JCL_2022-02-15_final.stac-item
2022-02-15 11:06:10	ga_s2am_ard_3-2-1_52JBL_2022-02-15_final.stac-item
2022-02-15 11:06:24	ga_s2am_ard_3-2-1_52HBK_2022-02-15_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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