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
2023-12-04 10:54:58	ga_s2am_ard_3-2-1_53JLJ_2023-12-04_final
2023-12-05 10:20:07	ga_s2am_ard_3-2-1_54LXN_2023-12-05_final
2023-12-05 10:20:11	ga_s2am_ard_3-2-1_54LWN_2023-12-05_final
2023-12-05 10:27:05	ga_s2am_ard_3-2-1_53HQV_2023-12-05_final
2023-12-06 09:56:02	ga_s2am_ard_3-2-1_55HBD_2023-12-06_final
2023-12-06 09:56:33	ga_s2am_ard_3-2-1_54HYG_2023-12-06_final
2023-12-06 09:56:52	ga_s2am_ard_3-2-1_55HDV_2023-12-06_final
2023-12-06 09:58:13	ga_s2am_ard_3-2-1_55GBQ_2023-12-06_final
2023-12-06 11:33:59	ga_s2am_ard_3-2-1_51KXP_2023-12-06_final
2023-12-06 11:34:33	ga_s2am_ard_3-2-1_51JWM_2023-12-06_final
2023-12-06 11:34:51	ga_s2am_ard_3-2-1_51JVL_2023-12-06_final
2023-12-06 11:35:01	ga_s2am_ard_3-2-1_51JWK_2023-12-06_final
2023-12-06 11:35:31	ga_s2am_ard_3-2-1_51JVH_2023-12-06_final
2023-12-06 11:36:27	ga_s2am_ard_3-2-1_51HVD_2023-12-06_final
2023-12-07 09:27:08	ga_s2am_ard_3-2-1_55HGU_2023-12-06_final
2023-12-07 09:27:43	ga_s2am_ard_3-2-1_55HFS_2023-12-06_final
2023-12-07 11:00:53	ga_s2am_ard_3-2-1_52LHL_2023-12-07_final
2023-12-07 11:02:20	ga_s2am_ard_3-2-1_52KHE_2023-12-07_final
2023-12-07 11:03:10	ga_s2am_ard_3-2-1_52KFB_2023-12-07_final
2023-12-07 11:03:47	ga_s2am_ard_3-2-1_52KDV_2023-12-07_final
2023-12-07 11:04:37	ga_s2am_ard_3-2-1_52JFR_2023-12-07_final
2023-12-07 11:05:31	ga_s2am_ard_3-2-1_52JCN_2023-12-07_final
2023-12-07 11:05:53	ga_s2am_ard_3-2-1_52JEL_2023-12-07_final
2023-12-07 11:05:57	ga_s2am_ard_3-2-1_52JDL_2023-12-07_final
2023-12-07 11:06:00	ga_s2am_ard_3-2-1_52JCL_2023-12-07_final
2023-12-07 11:06:09	ga_s2am_ard_3-2-1_52HCK_2023-12-07_final
2023-12-07 11:06:11	ga_s2am_ard_3-2-1_52HBK_2023-12-07_final
2023-12-08 10:29:52	ga_s2am_ard_3-2-1_54LWP_2023-12-08_final
2023-12-08 10:30:02	ga_s2am_ard_3-2-1_54LXN_2023-12-08_final
2023-12-08 10:30:06	ga_s2am_ard_3-2-1_54LWN_2023-12-08_final
2023-12-08 10:30:50	ga_s2am_ard_3-2-1_54LWK_2023-12-08_final
2023-12-08 10:31:11	ga_s2am_ard_3-2-1_54LUJ_2023-12-08_final
2023-12-08 10:31:16	ga_s2am_ard_3-2-1_54LWH_2023-12-08_final
2023-12-08 10:31:25	ga_s2am_ard_3-2-1_54LUH_2023-12-08_final
2023-12-08 10:31:26	ga_s2am_ard_3-2-1_54KWG_2023-12-08_final
2023-12-08 10:31:43	ga_s2am_ard_3-2-1_54KTG_2023-12-08_final
2023-12-08 10:31:44	ga_s2am_ard_3-2-1_53KRB_2023-12-08_final
2023-12-08 10:32:06	ga_s2am_ard_3-2-1_54KVE_2023-12-08_final
2023-12-08 10:32:23	ga_s2am_ard_3-2-1_54KUD_2023-12-08_final
2023-12-08 10:32:31	ga_s2am_ard_3-2-1_53KQU_2023-12-08_final
2023-12-08 10:32:42	ga_s2am_ard_3-2-1_53KRT_2023-12-08_final
2023-12-08 10:32:45	ga_s2am_ard_3-2-1_53KQT_2023-12-08_final
2023-12-08 10:32:56	ga_s2am_ard_3-2-1_53KRS_2023-12-08_final
2023-12-08 10:33:06	ga_s2am_ard_3-2-1_53KPS_2023-12-08_final
2023-12-08 10:33:07	ga_s2am_ard_3-2-1_54KUA_2023-12-08_final
2023-12-08 10:33:10	ga_s2am_ard_3-2-1_54KTA_2023-12-08_final
2023-12-08 10:33:22	ga_s2am_ard_3-2-1_54KUV_2023-12-08_final
2023-12-08 10:33:27	ga_s2am_ard_3-2-1_53KQQ_2023-12-08_final
2023-12-08 10:33:30	ga_s2am_ard_3-2-1_54KUV_2023-12-08_final
2023-12-08 10:33:34	ga_s2am_ard_3-2-1_53KQQ_2023-12-08_final
2023-12-08 10:33:43	ga_s2am_ard_3-2-1_53KQP_2023-12-08_final
2023-12-08 10:33:46	ga_s2am_ard_3-2-1_54JUT_2023-12-08_final
2023-12-08 10:33:58	ga_s2am_ard_3-2-1_53JQN_2023-12-08_final
2023-12-08 10:34:08	ga_s2am_ard_3-2-1_53JNN_2023-12-08_final
2023-12-08 10:34:08	ga_s2am_ard_3-2-1_53JRM_2023-12-08_final
2023-12-08 10:34:08	ga_s2am_ard_3-2-1_54JTS_2023-12-08_final
2023-12-08 10:34:19	ga_s2am_ard_3-2-1_53JNM_2023-12-08_final
2023-12-08 10:34:30	ga_s2am_ard_3-2-1_53JPL_2023-12-08_final
2023-12-08 10:34:55	ga_s2am_ard_3-2-1_53JQJ_2023-12-08_final
2023-12-08 10:35:01	ga_s2am_ard_3-2-1_54JTN_2023-12-08_final
2023-12-08 10:35:02	ga_s2am_ard_3-2-1_53JQJ_2023-12-08_final
2023-12-08 10:35:02	ga_s2am_ard_3-2-1_54JTN_2023-12-08_final
2023-12-08 10:35:21	ga_s2am_ard_3-2-1_53JMH_2023-12-08_final
2023-12-08 10:35:32	ga_s2am_ard_3-2-1_53JNG_2023-12-08_final
2023-12-08 10:35:35	ga_s2am_ard_3-2-1_53JMG_2023-12-08_final
2023-12-08 10:35:39	ga_s2am_ard_3-2-1_53JQF_2023-12-08_final
2023-12-08 10:35:46	ga_s2am_ard_3-2-1_53JNF_2023-12-08_final
2023-12-08 10:36:01	ga_s2am_ard_3-2-1_53HNE_2023-12-08_final
2023-12-08 10:36:11	ga_s2am_ard_3-2-1_53HPD_2023-12-08_final
2023-12-08 10:36:22	ga_s2am_ard_3-2-1_53HLD_2023-12-08_final
2023-12-08 10:36:44	ga_s2am_ard_3-2-1_53HNB_2023-12-08_final
2023-12-08 10:36:53	ga_s2am_ard_3-2-1_53HPA_2023-12-08_final
2023-12-08 12:13:34	ga_s2am_ard_3-2-1_49KHS_2023-12-08_final
2023-12-08 12:13:48	ga_s2am_ard_3-2-1_50KKA_2023-12-08_final
2023-12-08 12:13:49	ga_s2am_ard_3-2-1_49KHR_2023-12-08_final
2023-12-08 12:14:02	ga_s2am_ard_3-2-1_50KKV_2023-12-08_final
2023-12-08 12:14:03	ga_s2am_ard_3-2-1_49KHQ_2023-12-08_final
2023-12-08 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2023-12-08_final
2023-12-08 12:14:13	ga_s2am_ard_3-2-1_50KKU_2023-12-08_final
2023-12-08 12:14:21	ga_s2am_ard_3-2-1_49KGP_2023-12-08_final
2023-12-08 12:14:25	ga_s2am_ard_3-2-1_49JHN_2023-12-08_final
2023-12-08 12:14:40	ga_s2am_ard_3-2-1_49JFN_2023-12-08_final
2023-12-08 12:14:50	ga_s2am_ard_3-2-1_49JGM_2023-12-08_final
2023-12-08 12:14:54	ga_s2am_ard_3-2-1_49JFM_2023-12-08_final
2023-12-08 12:15:05	ga_s2am_ard_3-2-1_49JGL_2023-12-08_final
2023-12-18 12:13:21	ga_s2am_ard_3-2-1_49KFU_2023-12-18_nrt
2023-12-18 12:13:25	ga_s2am_ard_3-2-1_49KHT_2023-12-18_nrt
2023-12-18 12:13:29	ga_s2am_ard_3-2-1_49KFT_2023-12-18_nrt
2023-12-18 12:13:43	ga_s2am_ard_3-2-1_49KFS_2023-12-18_nrt
2023-12-18 12:13:58	ga_s2am_ard_3-2-1_49KFR_2023-12-18_nrt
2023-12-18 12:14:27	ga_s2am_ard_3-2-1_49KFP_2023-12-18_nrt
2023-12-19 10:00:55	ga_s2am_ard_3-2-1_55LFD_2023-12-19_nrt
2023-12-19 10:07:43	ga_s2am_ard_3-2-1_54HUC_2023-12-19_nrt
2023-12-19 11:40:21	ga_s2am_ard_3-2-1_51LXJ_2023-12-19_nrt
2023-12-19 11:40:24	ga_s2am_ard_3-2-1_51LWJ_2023-12-19_nrt
2023-12-19 11:40:35	ga_s2am_ard_3-2-1_51LXH_2023-12-19_nrt
2023-12-19 11:40:39	ga_s2am_ard_3-2-1_51LWH_2023-12-19_nrt
2023-12-19 11:40:42	ga_s2am_ard_3-2-1_51LVH_2023-12-19_nrt
2023-12-19 11:40:50	ga_s2am_ard_3-2-1_51LXG_2023-12-19_nrt
2023-12-19 11:42:30	ga_s2am_ard_3-2-1_51KTA_2023-12-19_nrt

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

All years