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
2023-06-13 12:51:04	ga_s2am_ard_3-2-1_48LWP_2023-06-13_final
2023-07-03 12:51:04	ga_s2am_ard_3-2-1_48LWP_2023-07-03_final
2023-08-26 14:23:39	ga_s2am_ard_3-2-1_43FDB_2023-08-26_final
2023-08-26 14:23:41	ga_s2am_ard_3-2-1_42FYG_2023-08-26_final
2023-08-26 14:23:42	ga_s2am_ard_3-2-1_43FCB_2023-08-26_final
2023-08-26 14:23:49	ga_s2am_ard_3-2-1_42FYF_2023-08-26_final
2023-09-02 14:13:44	ga_s2am_ard_3-2-1_43FCB_2023-09-02_final
2023-09-02 14:13:49	ga_s2am_ard_3-2-1_42FYF_2023-09-02_final
2023-09-05 10:56:23	ga_s2am_ard_3-2-1_52HEK_2023-09-05_final
2023-09-11 12:51:04	ga_s2am_ard_3-2-1_48LWP_2023-09-11_final
2023-11-01 14:13:38	ga_s2am_ard_3-2-1_43FCB_2023-11-01_final
2023-11-04 14:23:32	ga_s2am_ard_3-2-1_43FDB_2023-11-04_final
2023-11-04 14:23:35	ga_s2am_ard_3-2-1_43FCB_2023-11-04_final
2023-11-04 14:23:42	ga_s2am_ard_3-2-1_42FYF_2023-11-04_final
2023-11-14 10:56:16	ga_s2am_ard_3-2-1_52HEK_2023-11-14_final
2023-11-14 14:23:34	ga_s2am_ard_3-2-1_43FCB_2023-11-14_final
2023-11-14 14:23:42	ga_s2am_ard_3-2-1_42FYF_2023-11-14_final
2023-11-21 14:13:33	ga_s2am_ard_3-2-1_43FDB_2023-11-21_final
2023-11-24 14:23:29	ga_s2am_ard_3-2-1_43FDB_2023-11-24_final
2023-11-24 14:23:31	ga_s2am_ard_3-2-1_43FCB_2023-11-24_final
2023-11-24 14:23:37	ga_s2am_ard_3-2-1_42FYF_2023-11-24_final
2023-12-01 14:13:30	ga_s2am_ard_3-2-1_43FCB_2023-12-01_final
2023-12-14 14:23:29	ga_s2am_ard_3-2-1_43FDB_2023-12-14_final
2023-12-14 14:23:31	ga_s2am_ard_3-2-1_43FCB_2023-12-14_final
2023-12-21 14:13:33	ga_s2am_ard_3-2-1_43FDB_2023-12-21_final
2023-12-21 14:13:35	ga_s2am_ard_3-2-1_42FYG_2023-12-21_final
2024-01-03 14:23:30	ga_s2am_ard_3-2-1_43FDB_2024-01-03_final
2024-01-03 14:23:32	ga_s2am_ard_3-2-1_43FCB_2024-01-03_final
2024-02-02 14:23:31	ga_s2am_ard_3-2-1_43FCB_2024-02-02_final
2024-02-09 14:13:32	ga_s2am_ard_3-2-1_43FDB_2024-02-09_final
2024-02-09 14:13:36	ga_s2am_ard_3-2-1_42FYG_2024-02-09_final
2024-02-22 14:23:31	ga_s2am_ard_3-2-1_43FDB_2024-02-22_final
2024-02-22 14:23:33	ga_s2am_ard_3-2-1_43FCB_2024-02-22_final
2024-02-29 14:13:36	ga_s2am_ard_3-2-1_43FDB_2024-02-29_final
2024-03-13 14:23:33	ga_s2am_ard_3-2-1_43FDB_2024-03-13_final
2024-03-13 14:23:43	ga_s2am_ard_3-2-1_42FYF_2024-03-13_final
2024-03-31 10:10:25	ga_s2am_ard_3-2-1_54LZM_2024-03-31_final
2024-04-02 14:23:34	ga_s2am_ard_3-2-1_42FYG_2024-04-02_final
2024-04-03 10:20:19	ga_s2am_ard_3-2-1_54LZM_2024-04-03_final
2024-04-06 10:31:29	ga_s2am_ard_3-2-1_54LUH_2024-04-06_final
2024-04-06 10:32:31	ga_s2am_ard_3-2-1_53KRU_2024-04-06_final
2024-04-06 10:33:00	ga_s2am_ard_3-2-1_54KTB_2024-04-06_final
2024-04-06 10:34:30	ga_s2am_ard_3-2-1_53JQL_2024-04-06_final
2024-04-06 10:34:59	ga_s2am_ard_3-2-1_53JQJ_2024-04-06_final
2024-04-06 10:36:52	ga_s2am_ard_3-2-1_53HMB_2024-04-06_final
2024-04-06 10:36:56	ga_s2am_ard_3-2-1_53HPA_2024-04-06_final
2024-04-06 12:13:37	ga_s2am_ard_3-2-1_50KKB_2024-04-06_final
2024-04-06 12:15:17	ga_s2am_ard_3-2-1_49JGK_2024-04-06_final
2024-04-07 10:01:16	ga_s2am_ard_3-2-1_55LEC_2024-04-07_final
2024-04-07 10:01:59	ga_s2am_ard_3-2-1_55KEV_2024-04-07_final
2024-04-07 10:02:03	ga_s2am_ard_3-2-1_55KFU_2024-04-07_final
2024-04-07 11:40:56	ga_s2am_ard_3-2-1_51LWG_2024-04-07_final
2024-04-07 11:40:59	ga_s2am_ard_3-2-1_51LVG_2024-04-07_final
2024-04-07 11:41:13	ga_s2am_ard_3-2-1_51LVF_2024-04-07_final
2024-04-07 11:41:24	ga_s2am_ard_3-2-1_51LWE_2024-04-07_final
2024-04-07 11:41:28	ga_s2am_ard_3-2-1_51LVE_2024-04-07_final
2024-04-07 11:41:31	ga_s2am_ard_3-2-1_51LUE_2024-04-07_final
2024-04-07 11:41:46	ga_s2am_ard_3-2-1_51LUD_2024-04-07_final
2024-04-07 11:44:36	ga_s2am_ard_3-2-1_50JPT_2024-04-07_final
2024-04-07 11:46:46	ga_s2am_ard_3-2-1_50HPJ_2024-04-07_final
2024-04-17 10:07:52	ga_s2am_ard_3-2-1_54HXB_2024-04-17_nrt
2024-04-17 11:40:27	ga_s2am_ard_3-2-1_51LXJ_2024-04-17_nrt
2024-04-17 11:40:34	ga_s2am_ard_3-2-1_51LVJ_2024-04-17_nrt
2024-04-17 11:40:42	ga_s2am_ard_3-2-1_51LXH_2024-04-17_nrt
2024-04-17 11:40:49	ga_s2am_ard_3-2-1_51LVH_2024-04-17_nrt
2024-04-17 11:40:57	ga_s2am_ard_3-2-1_51LXG_2024-04-17_nrt
2024-04-17 11:41:20	ga_s2am_ard_3-2-1_51LXE_2024-04-17_nrt
2024-04-17 11:41:44	ga_s2am_ard_3-2-1_51LWD_2024-04-17_nrt
2024-04-17 11:41:47	ga_s2am_ard_3-2-1_51LVD_2024-04-17_nrt
2024-04-17 11:42:08	ga_s2am_ard_3-2-1_51LTC_2024-04-17_nrt
2024-04-17 11:42:10	ga_s2am_ard_3-2-1_50LRH_2024-04-17_nrt
2024-04-17 11:42:23	ga_s2am_ard_3-2-1_50KRG_2024-04-17_nrt
2024-04-17 11:42:30	ga_s2am_ard_3-2-1_50KRG_2024-04-17_nrt
2024-04-17 11:42:30	ga_s2am_ard_3-2-1_51KTB_2024-04-17_nrt
2024-04-17 11:42:30	ga_s2am_ard_3-2-1_51KTA_2024-04-17_nrt
2024-04-17 11:42:30	ga_s2am_ard_3-2-1_50KRF_2024-04-17_nrt
2024-04-17 11:42:37	ga_s2am_ard_3-2-1_51KTA_2024-04-17_nrt
2024-04-17 11:42:38	ga_s2am_ard_3-2-1_50KRF_2024-04-17_nrt
2024-04-17 11:42:53	ga_s2am_ard_3-2-1_50KRE_2024-04-17_nrt
2024-04-17 11:47:32	ga_s2am_ard_3-2-1_50HPF_2024-04-17_nrt
2024-04-17 11:47:34	ga_s2am_ard_3-2-1_50HNF_2024-04-17_nrt
2024-04-17 11:47:36	ga_s2am_ard_3-2-1_50HMF_2024-04-17_nrt
2024-04-17 11:47:37	ga_s2am_ard_3-2-1_50HLF_2024-04-17_nrt
2024-04-18 09:32:54	ga_s2am_ard_3-2-1_56KPA_2024-04-18_nrt
2024-04-18 09:33:10	ga_s2am_ard_3-2-1_56KNV_2024-04-18_nrt
2024-04-18 09:33:20	ga_s2am_ard_3-2-1_56KPU_2024-04-18_nrt
2024-04-18 09:33:24	ga_s2am_ard_3-2-1_56KNU_2024-04-18_nrt
2024-04-18 09:36:16	ga_s2am_ard_3-2-1_55HGC_2024-04-18_nrt
2024-04-18 09:37:57	ga_s2am_ard_3-2-1_56GKA_2024-04-18_nrt
2024-04-18 09:38:11	ga_s2am_ard_3-2-1_56GKV_2024-04-18_nrt
2024-04-18 09:38:23	ga_s2am_ard_3-2-1_56GKU_2024-04-18_nrt
2024-04-18 09:38:59	ga_s2am_ard_3-2-1_55GFM_2024-04-18_nrt
2024-04-18 11:10:14	ga_s2am_ard_3-2-1_52LHP_2024-04-18_nrt
2024-04-18 11:10:18	ga_s2am_ard_3-2-1_52LGP_2024-04-18_nrt
2024-04-18 11:10:21	ga_s2am_ard_3-2-1_52LFP_2024-04-18_nrt
2024-04-18 11:10:24	ga_s2am_ard_3-2-1_52LEP_2024-04-18_nrt
2024-04-18 11:10:39	ga_s2am_ard_3-2-1_52LEN_2024-04-18_nrt
2024-04-18 11:10:46	ga_s2am_ard_3-2-1_52LEN_2024-04-18_nrt
2024-04-18 11:10:46	ga_s2am_ard_3-2-1_52LEM_2024-04-18_nrt
2024-04-18 11:10:53	ga_s2am_ard_3-2-1_52LEM_2024-04-18_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