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
2023-01-03 11:42:12	ga_s2am_ard_3-2-1_51KVB_2023-01-03_final.stac-item
2023-01-03 11:42:20	ga_s2am_ard_3-2-1_51KWA_2023-01-03_final.stac-item
2023-01-03 11:43:10	ga_s2am_ard_3-2-1_51KVT_2023-01-03_final.stac-item
2023-01-03 11:43:28	ga_s2am_ard_3-2-1_51KUS_2023-01-03_final.stac-item
2023-01-03 11:43:35	ga_s2am_ard_3-2-1_50KQB_2023-01-03_final.stac-item
2023-01-03 11:43:50	ga_s2am_ard_3-2-1_50KQA_2023-01-03_final.stac-item
2023-01-03 11:44:12	ga_s2am_ard_3-2-1_51KUP_2023-01-03_final.stac-item
2023-01-03 11:44:15	ga_s2am_ard_3-2-1_50KRU_2023-01-03_final.stac-item
2023-01-03 11:44:15	ga_s2am_ard_3-2-1_51KTP_2023-01-03_final.stac-item
2023-01-03 11:44:26	ga_s2am_ard_3-2-1_51JUN_2023-01-03_final.stac-item
2023-01-03 11:44:30	ga_s2am_ard_3-2-1_50JRT_2023-01-03_final.stac-item
2023-01-03 11:44:33	ga_s2am_ard_3-2-1_50JQT_2023-01-03_final.stac-item
2023-01-03 11:44:44	ga_s2am_ard_3-2-1_51JTM_2023-01-03_final.stac-item
2023-01-03 11:45:06	ga_s2am_ard_3-2-1_50JPR_2023-01-03_final.stac-item
2023-01-03 11:45:28	ga_s2am_ard_3-2-1_51JTJ_2023-01-03_final.stac-item
2023-01-03 11:45:38	ga_s2am_ard_3-2-1_50JNP_2023-01-03_final.stac-item
2023-01-03 11:46:00	ga_s2am_ard_3-2-1_50JQM_2023-01-03_final.stac-item
2023-01-03 11:46:18	ga_s2am_ard_3-2-1_50JPL_2023-01-03_final.stac-item
2023-01-03 11:46:22	ga_s2am_ard_3-2-1_50JNL_2023-01-03_final.stac-item
2023-01-03 11:46:33	ga_s2am_ard_3-2-1_50HPK_2023-01-03_final.stac-item
2023-01-03 11:46:36	ga_s2am_ard_3-2-1_50HNK_2023-01-03_final.stac-item
2023-01-03 11:46:40	ga_s2am_ard_3-2-1_50HMK_2023-01-03_final.stac-item
2023-01-03 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2023-01-03_final.stac-item
2023-01-03 11:47:01	ga_s2am_ard_3-2-1_50HPH_2023-01-03_final.stac-item
2023-01-03 11:47:05	ga_s2am_ard_3-2-1_50HNH_2023-01-03_final.stac-item
2023-01-04 11:13:28	ga_s2am_ard_3-2-1_51KZS_2023-01-04_final.stac-item
2023-01-04 11:14:08	ga_s2am_ard_3-2-1_51KZP_2023-01-04_final.stac-item
2023-01-04 11:14:22	ga_s2am_ard_3-2-1_51JZN_2023-01-04_final.stac-item
2023-01-04 11:15:24	ga_s2am_ard_3-2-1_51JYJ_2023-01-04_final.stac-item
2023-01-04 11:16:21	ga_s2am_ard_3-2-1_51HYE_2023-01-04_final.stac-item
2023-01-04 11:16:36	ga_s2am_ard_3-2-1_51HYD_2023-01-04_final.stac-item
2023-01-06 11:53:23	ga_s2am_ard_3-2-1_50KNC_2023-01-06_final.stac-item
2023-01-06 11:53:30	ga_s2am_ard_3-2-1_50KMC_2023-01-06_final.stac-item
2023-01-06 11:53:31	ga_s2am_ard_3-2-1_50KQB_2023-01-06_final.stac-item
2023-01-06 11:53:45	ga_s2am_ard_3-2-1_50KQA_2023-01-06_final.stac-item
2023-01-06 11:54:12	ga_s2am_ard_3-2-1_50KQU_2023-01-06_final.stac-item
2023-01-06 11:54:21	ga_s2am_ard_3-2-1_50KNU_2023-01-06_final.stac-item
2023-01-06 11:54:22	ga_s2am_ard_3-2-1_50JQT_2023-01-06_final.stac-item
2023-01-06 11:54:36	ga_s2am_ard_3-2-1_50JNT_2023-01-06_final.stac-item
2023-01-06 11:54:43	ga_s2am_ard_3-2-1_50JLT_2023-01-06_final.stac-item
2023-01-06 11:54:57	ga_s2am_ard_3-2-1_50JLS_2023-01-06_final.stac-item
2023-01-06 11:55:01	ga_s2am_ard_3-2-1_50JPR_2023-01-06_final.stac-item
2023-01-06 11:55:08	ga_s2am_ard_3-2-1_50JMR_2023-01-06_final.stac-item
2023-01-06 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2023-01-06_final.stac-item
2023-01-06 11:55:34	ga_s2am_ard_3-2-1_50JNP_2023-01-06_final.stac-item
2023-01-06 11:55:41	ga_s2am_ard_3-2-1_50JLP_2023-01-06_final.stac-item
2023-01-06 11:56:06	ga_s2am_ard_3-2-1_50JMM_2023-01-06_final.stac-item
2023-01-06 11:56:10	ga_s2am_ard_3-2-1_50JLM_2023-01-06_final.stac-item
2023-01-06 11:56:13	ga_s2am_ard_3-2-1_50JKM_2023-01-06_final.stac-item
2023-01-06 11:56:17	ga_s2am_ard_3-2-1_50JNL_2023-01-06_final.stac-item
2023-01-06 11:56:24	ga_s2am_ard_3-2-1_50JLL_2023-01-06_final.stac-item
2023-01-06 11:56:29	ga_s2am_ard_3-2-1_50HNK_2023-01-06_final.stac-item
2023-01-06 11:56:35	ga_s2am_ard_3-2-1_50HMK_2023-01-06_final.stac-item
2023-01-06 11:57:08	ga_s2am_ard_3-2-1_50HLH_2023-01-06_final.stac-item
2023-01-07 11:22:11	ga_s2am_ard_3-2-1_51KYB_2023-01-07_final.stac-item
2023-01-07 11:22:55	ga_s2am_ard_3-2-1_51KYU_2023-01-07_final.stac-item
2023-01-07 11:24:03	ga_s2am_ard_3-2-1_51KZP_2023-01-07_final.stac-item
2023-01-07 11:24:10	ga_s2am_ard_3-2-1_51KXP_2023-01-07_final.stac-item
2023-01-07 11:24:18	ga_s2am_ard_3-2-1_51JZN_2023-01-07_final.stac-item
2023-01-07 11:24:28	ga_s2am_ard_3-2-1_51JWN_2023-01-07_final.stac-item
2023-01-07 11:24:43	ga_s2am_ard_3-2-1_51JWM_2023-01-07_final.stac-item
2023-01-07 11:24:54	ga_s2am_ard_3-2-1_51JXL_2023-01-07_final.stac-item
2023-01-07 11:25:02	ga_s2am_ard_3-2-1_51JVL_2023-01-07_final.stac-item
2023-01-07 11:25:04	ga_s2am_ard_3-2-1_51JYK_2023-01-07_final.stac-item
2023-01-07 11:25:08	ga_s2am_ard_3-2-1_51JXK_2023-01-07_final.stac-item
2023-01-07 11:25:19	ga_s2am_ard_3-2-1_51JYJ_2023-01-07_final.stac-item
2023-01-07 11:25:44	ga_s2am_ard_3-2-1_51JVH_2023-01-07_final.stac-item
2023-01-07 11:26:04	ga_s2am_ard_3-2-1_51JUG_2023-01-07_final.stac-item
2023-01-07 11:27:00	ga_s2am_ard_3-2-1_51HUC_2023-01-07_final.stac-item
2023-01-09 12:03:18	ga_s2am_ard_3-2-1_50KNC_2023-01-09_final.stac-item
2023-01-09 12:03:22	ga_s2am_ard_3-2-1_50KMC_2023-01-09_final.stac-item
2023-01-09 12:03:25	ga_s2am_ard_3-2-1_50KLC_2023-01-09_final.stac-item
2023-01-09 12:03:54	ga_s2am_ard_3-2-1_50KLA_2023-01-09_final.stac-item
2023-01-09 12:03:58	ga_s2am_ard_3-2-1_49KHR_2023-01-09_final.stac-item
2023-01-09 12:04:26	ga_s2am_ard_3-2-1_49KHP_2023-01-09_final.stac-item
2023-01-09 12:04:26	ga_s2am_ard_3-2-1_50KKU_2023-01-09_final.stac-item
2023-01-09 12:04:38	ga_s2am_ard_3-2-1_50JLT_2023-01-09_final.stac-item
2023-01-09 12:04:41	ga_s2am_ard_3-2-1_49JHN_2023-01-09_final.stac-item
2023-01-09 12:04:41	ga_s2am_ard_3-2-1_50JKT_2023-01-09_final.stac-item
2023-01-09 12:04:44	ga_s2am_ard_3-2-1_49JGN_2023-01-09_final.stac-item
2023-01-09 12:04:52	ga_s2am_ard_3-2-1_50JLS_2023-01-09_final.stac-item
2023-01-09 12:04:55	ga_s2am_ard_3-2-1_49JHM_2023-01-09_final.stac-item
2023-01-09 12:04:55	ga_s2am_ard_3-2-1_50JKS_2023-01-09_final.stac-item
2023-01-09 12:04:57	ga_s2am_ard_3-2-1_50JMR_2023-01-09_final.stac-item
2023-01-09 12:05:10	ga_s2am_ard_3-2-1_50JKR_2023-01-09_final.stac-item
2023-01-09 12:05:13	ga_s2am_ard_3-2-1_49JGL_2023-01-09_final.stac-item
2023-01-09 12:05:21	ga_s2am_ard_3-2-1_50JLQ_2023-01-09_final.stac-item
2023-01-09 12:05:28	ga_s2am_ard_3-2-1_49JGK_2023-01-09_final.stac-item
2023-01-09 12:05:36	ga_s2am_ard_3-2-1_50JLP_2023-01-09_final.stac-item
2023-01-09 12:06:03	ga_s2am_ard_3-2-1_50JLM_2023-01-09_final.stac-item
2023-01-09 12:06:08	ga_s2am_ard_3-2-1_50JKM_2023-01-09_final.stac-item
2023-01-09 12:06:12	ga_s2am_ard_3-2-1_50JLL_2023-01-09_final.stac-item
2023-01-10 11:32:18	ga_s2am_ard_3-2-1_51KVB_2023-01-10_final.stac-item
2023-01-10 11:33:40	ga_s2am_ard_3-2-1_51KWR_2023-01-10_final.stac-item
2023-01-10 11:34:38	ga_s2am_ard_3-2-1_51JWM_2023-01-10_final.stac-item
2023-01-10 11:34:41	ga_s2am_ard_3-2-1_51JVM_2023-01-10_final.stac-item
2023-01-10 11:35:43	ga_s2am_ard_3-2-1_51JUH_2023-01-10_final.stac-item
2023-01-10 11:36:25	ga_s2am_ard_3-2-1_50JPL_2023-01-10_final.stac-item
2023-01-10 11:36:27	ga_s2am_ard_3-2-1_51HUE_2023-01-10_final.stac-item
2023-01-20 11:37:23	ga_s2am_ard_3-2-1_51HTA_2023-01-20_nrt.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

All years