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
2022-10-14 10:35:57	ga_s2am_ard_3-2-1_53JNF_2022-10-14_final.stac-item
2022-10-14 10:36:00	ga_s2am_ard_3-2-1_53JMF_2022-10-14_final.stac-item
2022-10-14 10:36:01	ga_s2am_ard_3-2-1_53HQE_2022-10-14_final.stac-item
2022-10-14 10:36:07	ga_s2am_ard_3-2-1_53HPE_2022-10-14_final.stac-item
2022-10-14 10:36:11	ga_s2am_ard_3-2-1_53HNE_2022-10-14_final.stac-item
2022-10-14 10:36:15	ga_s2am_ard_3-2-1_53HME_2022-10-14_final.stac-item
2022-10-14 10:36:21	ga_s2am_ard_3-2-1_53HLE_2022-10-14_final.stac-item
2022-10-14 10:36:22	ga_s2am_ard_3-2-1_53HPD_2022-10-14_final.stac-item
2022-10-14 10:36:26	ga_s2am_ard_3-2-1_53HND_2022-10-14_final.stac-item
2022-10-14 10:36:29	ga_s2am_ard_3-2-1_53HMD_2022-10-14_final.stac-item
2022-10-14 10:36:33	ga_s2am_ard_3-2-1_53HLD_2022-10-14_final.stac-item
2022-10-14 10:36:37	ga_s2am_ard_3-2-1_53HPC_2022-10-14_final.stac-item
2022-10-14 10:36:40	ga_s2am_ard_3-2-1_53HNC_2022-10-14_final.stac-item
2022-10-14 10:36:51	ga_s2am_ard_3-2-1_53HPB_2022-10-14_final.stac-item
2022-10-14 10:36:55	ga_s2am_ard_3-2-1_53HNB_2022-10-14_final.stac-item
2022-10-14 10:37:03	ga_s2am_ard_3-2-1_53HPA_2022-10-14_final.stac-item
2022-10-14 12:13:44	ga_s2am_ard_3-2-1_50KKB_2022-10-14_final.stac-item
2022-10-14 12:13:59	ga_s2am_ard_3-2-1_50KKA_2022-10-14_final.stac-item
2022-10-14 12:13:59	ga_s2am_ard_3-2-1_49KHR_2022-10-14_final.stac-item
2022-10-14 12:14:03	ga_s2am_ard_3-2-1_49KGR_2022-10-14_final.stac-item
2022-10-14 12:14:10	ga_s2am_ard_3-2-1_50KKV_2022-10-14_final.stac-item
2022-10-14 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2022-10-14_final.stac-item
2022-10-14 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2022-10-14_final.stac-item
2022-10-14 12:14:16	ga_s2am_ard_3-2-1_50KKV_2022-10-14_final.stac-item
2022-10-14 12:14:17	ga_s2am_ard_3-2-1_49KHQ_2022-10-14_final.stac-item
2022-10-14 12:14:19	ga_s2am_ard_3-2-1_49KGQ_2022-10-14_final.stac-item
2022-10-14 12:14:23	ga_s2am_ard_3-2-1_50KKU_2022-10-14_final.stac-item
2022-10-14 12:14:26	ga_s2am_ard_3-2-1_49KHP_2022-10-14_final.stac-item
2022-10-14 12:14:31	ga_s2am_ard_3-2-1_49KGP_2022-10-14_final.stac-item
2022-10-14 12:14:36	ga_s2am_ard_3-2-1_49JHN_2022-10-14_final.stac-item
2022-10-14 12:14:46	ga_s2am_ard_3-2-1_49JGN_2022-10-14_final.stac-item
2022-10-14 12:14:50	ga_s2am_ard_3-2-1_49JFN_2022-10-14_final.stac-item
2022-10-14 12:15:01	ga_s2am_ard_3-2-1_49JGM_2022-10-14_final.stac-item
2022-10-14 12:15:04	ga_s2am_ard_3-2-1_49JFM_2022-10-14_final.stac-item
2022-10-14 12:15:15	ga_s2am_ard_3-2-1_49JGL_2022-10-14_final.stac-item
2022-10-14 12:15:24	ga_s2am_ard_3-2-1_49JGK_2022-10-14_final.stac-item
2022-10-15 10:04:15	ga_s2am_ard_3-2-1_54JYS_2022-10-15_final.stac-item
2022-10-15 10:04:26	ga_s2am_ard_3-2-1_55JBL_2022-10-15_final.stac-item
2022-10-15 10:04:29	ga_s2am_ard_3-2-1_54JYR_2022-10-15_final.stac-item
2022-10-15 10:04:37	ga_s2am_ard_3-2-1_54JXR_2022-10-15_final.stac-item
2022-10-15 10:04:41	ga_s2am_ard_3-2-1_55JBK_2022-10-15_final.stac-item
2022-10-15 10:04:44	ga_s2am_ard_3-2-1_54JYQ_2022-10-15_final.stac-item
2022-10-15 10:04:48	ga_s2am_ard_3-2-1_54JXQ_2022-10-15_final.stac-item
2022-10-15 10:04:55	ga_s2am_ard_3-2-1_55JBJ_2022-10-15_final.stac-item
2022-10-15 10:04:58	ga_s2am_ard_3-2-1_54JYP_2022-10-15_final.stac-item
2022-10-15 10:05:02	ga_s2am_ard_3-2-1_54JXP_2022-10-15_final.stac-item
2022-10-15 10:05:10	ga_s2am_ard_3-2-1_55JBH_2022-10-15_final.stac-item
2022-10-15 10:05:13	ga_s2am_ard_3-2-1_54JYN_2022-10-15_final.stac-item
2022-10-15 10:05:16	ga_s2am_ard_3-2-1_54JXN_2022-10-15_final.stac-item
2022-10-15 10:05:21	ga_s2am_ard_3-2-1_55JCG_2022-10-15_final.stac-item
2022-10-15 10:05:24	ga_s2am_ard_3-2-1_55JBG_2022-10-15_final.stac-item
2022-10-15 10:05:27	ga_s2am_ard_3-2-1_54JYM_2022-10-15_final.stac-item
2022-10-15 10:05:31	ga_s2am_ard_3-2-1_54JXM_2022-10-15_final.stac-item
2022-10-15 10:05:33	ga_s2am_ard_3-2-1_55JCF_2022-10-15_final.stac-item
2022-10-15 10:05:35	ga_s2am_ard_3-2-1_55JBF_2022-10-15_final.stac-item
2022-10-15 10:05:37	ga_s2am_ard_3-2-1_54JYL_2022-10-15_final.stac-item
2022-10-15 10:05:37	ga_s2am_ard_3-2-1_54JWM_2022-10-15_final.stac-item
2022-10-15 10:05:39	ga_s2am_ard_3-2-1_54JXM_2022-10-15_final.stac-item
2022-10-15 10:05:39	ga_s2am_ard_3-2-1_54JXL_2022-10-15_final.stac-item
2022-10-15 10:05:39	ga_s2am_ard_3-2-1_55JCF_2022-10-15_final.stac-item
2022-10-15 10:05:40	ga_s2am_ard_3-2-1_54JWM_2022-10-15_final.stac-item
2022-10-15 10:05:41	ga_s2am_ard_3-2-1_54JWL_2022-10-15_final.stac-item
2022-10-15 10:05:42	ga_s2am_ard_3-2-1_55JBF_2022-10-15_final.stac-item
2022-10-15 10:05:43	ga_s2am_ard_3-2-1_55HCE_2022-10-15_final.stac-item
2022-10-15 10:05:43	ga_s2am_ard_3-2-1_54JYL_2022-10-15_final.stac-item
2022-10-15 10:05:45	ga_s2am_ard_3-2-1_54JXL_2022-10-15_final.stac-item
2022-10-15 10:05:49	ga_s2am_ard_3-2-1_54JWL_2022-10-15_final.stac-item
2022-10-15 10:05:53	ga_s2am_ard_3-2-1_55HBE_2022-10-15_final.stac-item
2022-10-15 10:05:56	ga_s2am_ard_3-2-1_54HYK_2022-10-15_final.stac-item
2022-10-15 10:06:00	ga_s2am_ard_3-2-1_54HXK_2022-10-15_final.stac-item
2022-10-15 10:06:03	ga_s2am_ard_3-2-1_54HWK_2022-10-15_final.stac-item
2022-10-15 10:06:08	ga_s2am_ard_3-2-1_55HBD_2022-10-15_final.stac-item
2022-10-15 10:06:10	ga_s2am_ard_3-2-1_54HYJ_2022-10-15_final.stac-item
2022-10-15 10:06:14	ga_s2am_ard_3-2-1_54HXJ_2022-10-15_final.stac-item
2022-10-15 10:06:18	ga_s2am_ard_3-2-1_54HWJ_2022-10-15_final.stac-item
2022-10-15 10:06:23	ga_s2am_ard_3-2-1_55HBC_2022-10-15_final.stac-item
2022-10-15 10:06:24	ga_s2am_ard_3-2-1_54HYH_2022-10-15_final.stac-item
2022-10-15 10:06:29	ga_s2am_ard_3-2-1_54HXH_2022-10-15_final.stac-item
2022-10-15 10:06:32	ga_s2am_ard_3-2-1_54HWH_2022-10-15_final.stac-item
2022-10-15 10:06:37	ga_s2am_ard_3-2-1_55HBB_2022-10-15_final.stac-item
2022-10-15 10:06:38	ga_s2am_ard_3-2-1_54HVH_2022-10-15_final.stac-item
2022-10-15 10:06:39	ga_s2am_ard_3-2-1_54HYG_2022-10-15_final.stac-item
2022-10-15 10:06:43	ga_s2am_ard_3-2-1_54HXG_2022-10-15_final.stac-item
2022-10-15 10:06:47	ga_s2am_ard_3-2-1_54HWG_2022-10-15_final.stac-item
2022-10-15 10:06:50	ga_s2am_ard_3-2-1_55HBA_2022-10-15_final.stac-item
2022-10-15 10:06:50	ga_s2am_ard_3-2-1_54HVG_2022-10-15_final.stac-item
2022-10-15 10:06:54	ga_s2am_ard_3-2-1_54HYF_2022-10-15_final.stac-item
2022-10-15 10:06:58	ga_s2am_ard_3-2-1_54HXF_2022-10-15_final.stac-item
2022-10-15 10:07:00	ga_s2am_ard_3-2-1_55HBV_2022-10-15_final.stac-item
2022-10-15 10:07:01	ga_s2am_ard_3-2-1_54HWF_2022-10-15_final.stac-item
2022-10-15 10:07:05	ga_s2am_ard_3-2-1_54HVF_2022-10-15_final.stac-item
2022-10-15 10:07:07	ga_s2am_ard_3-2-1_54HYE_2022-10-15_final.stac-item
2022-10-15 10:07:12	ga_s2am_ard_3-2-1_54HXE_2022-10-15_final.stac-item
2022-10-15 10:07:16	ga_s2am_ard_3-2-1_54HWE_2022-10-15_final.stac-item
2022-10-15 10:07:18	ga_s2am_ard_3-2-1_54HYD_2022-10-15_final.stac-item
2022-10-15 10:07:19	ga_s2am_ard_3-2-1_54HVE_2022-10-15_final.stac-item
2022-10-15 10:07:26	ga_s2am_ard_3-2-1_54HXD_2022-10-15_final.stac-item
2022-10-15 10:07:30	ga_s2am_ard_3-2-1_54HWD_2022-10-15_final.stac-item
2022-10-15 10:07:34	ga_s2am_ard_3-2-1_54HVD_2022-10-15_final.stac-item
2022-10-15 10:07:41	ga_s2am_ard_3-2-1_54HXC_2022-10-15_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

All years