Search ga_s2bm_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

67 results

Time (local)	Label
2019-09-23 11:31:18	ga_s2bm_ard_3-2-1_52LBK_2019-09-23_final.stac-item
2019-09-23 11:31:20	ga_s2bm_ard_3-2-1_51LZE_2019-09-23_final.stac-item
2019-09-23 11:31:24	ga_s2bm_ard_3-2-1_51LYE_2019-09-23_final.stac-item
2019-09-23 11:31:29	ga_s2bm_ard_3-2-1_52LBJ_2019-09-23_final.stac-item
2019-09-23 11:31:30	ga_s2bm_ard_3-2-1_51LWE_2019-09-23_final.stac-item
2019-09-23 11:31:35	ga_s2bm_ard_3-2-1_51LZD_2019-09-23_final.stac-item
2019-09-23 11:31:38	ga_s2bm_ard_3-2-1_51LYD_2019-09-23_final.stac-item
2019-09-23 11:31:42	ga_s2bm_ard_3-2-1_51LXD_2019-09-23_final.stac-item
2019-09-23 11:31:48	ga_s2bm_ard_3-2-1_51LZC_2019-09-23_final.stac-item
2019-09-23 11:31:53	ga_s2bm_ard_3-2-1_51LYC_2019-09-23_final.stac-item
2019-09-23 11:31:56	ga_s2bm_ard_3-2-1_51LXC_2019-09-23_final.stac-item
2019-09-23 11:31:59	ga_s2bm_ard_3-2-1_51KZB_2019-09-23_final.stac-item
2019-09-23 11:32:00	ga_s2bm_ard_3-2-1_51LWC_2019-09-23_final.stac-item
2019-09-23 11:32:07	ga_s2bm_ard_3-2-1_51KYB_2019-09-23_final.stac-item
2019-09-23 11:32:11	ga_s2bm_ard_3-2-1_51KXB_2019-09-23_final.stac-item
2019-09-23 11:32:14	ga_s2bm_ard_3-2-1_51KWB_2019-09-23_final.stac-item
2019-09-23 11:32:19	ga_s2bm_ard_3-2-1_51KVB_2019-09-23_final.stac-item
2019-09-23 11:32:21	ga_s2bm_ard_3-2-1_51KYA_2019-09-23_final.stac-item
2019-09-23 11:32:25	ga_s2bm_ard_3-2-1_51KXA_2019-09-23_final.stac-item
2019-09-23 11:32:28	ga_s2bm_ard_3-2-1_51KWA_2019-09-23_final.stac-item
2019-09-23 11:32:32	ga_s2bm_ard_3-2-1_51KVA_2019-09-23_final.stac-item
2019-09-23 11:32:36	ga_s2bm_ard_3-2-1_51KYV_2019-09-23_final.stac-item
2019-09-23 11:32:40	ga_s2bm_ard_3-2-1_51KXV_2019-09-23_final.stac-item
2019-09-23 11:32:43	ga_s2bm_ard_3-2-1_51KWV_2019-09-23_final.stac-item
2019-09-23 11:32:46	ga_s2bm_ard_3-2-1_51KVV_2019-09-23_final.stac-item
2019-09-23 11:32:50	ga_s2bm_ard_3-2-1_51KYU_2019-09-23_final.stac-item
2019-09-23 11:32:54	ga_s2bm_ard_3-2-1_51KXU_2019-09-23_final.stac-item
2019-09-23 11:32:58	ga_s2bm_ard_3-2-1_51KWU_2019-09-23_final.stac-item
2019-09-23 11:33:01	ga_s2bm_ard_3-2-1_51KVU_2019-09-23_final.stac-item
2019-09-23 11:33:02	ga_s2bm_ard_3-2-1_51KYT_2019-09-23_final.stac-item
2019-09-23 11:33:08	ga_s2bm_ard_3-2-1_51KXT_2019-09-23_final.stac-item
2019-09-23 11:33:12	ga_s2bm_ard_3-2-1_51KWT_2019-09-23_final.stac-item
2019-09-23 11:33:16	ga_s2bm_ard_3-2-1_51KVT_2019-09-23_final.stac-item
2019-09-23 11:33:22	ga_s2bm_ard_3-2-1_51KUT_2019-09-23_final.stac-item
2019-09-23 11:33:23	ga_s2bm_ard_3-2-1_51KXS_2019-09-23_final.stac-item
2019-09-23 11:33:27	ga_s2bm_ard_3-2-1_51KWS_2019-09-23_final.stac-item
2019-09-23 11:33:30	ga_s2bm_ard_3-2-1_51KVS_2019-09-23_final.stac-item
2019-09-23 11:33:34	ga_s2bm_ard_3-2-1_51KUS_2019-09-23_final.stac-item
2019-09-23 11:33:38	ga_s2bm_ard_3-2-1_51KXR_2019-09-23_final.stac-item
2019-09-23 11:33:41	ga_s2bm_ard_3-2-1_51KWR_2019-09-23_final.stac-item
2019-09-23 11:33:45	ga_s2bm_ard_3-2-1_51KVR_2019-09-23_final.stac-item
2019-09-23 11:33:47	ga_s2bm_ard_3-2-1_51KUR_2019-09-23_final.stac-item
2019-09-23 11:33:52	ga_s2bm_ard_3-2-1_51KXQ_2019-09-23_final.stac-item
2019-09-23 11:33:56	ga_s2bm_ard_3-2-1_51KWQ_2019-09-23_final.stac-item
2019-09-23 11:33:59	ga_s2bm_ard_3-2-1_51KVQ_2019-09-23_final.stac-item
2019-09-23 11:34:02	ga_s2bm_ard_3-2-1_51KUQ_2019-09-23_final.stac-item
2019-09-23 11:34:05	ga_s2bm_ard_3-2-1_51KXP_2019-09-23_final.stac-item
2019-09-23 11:34:10	ga_s2bm_ard_3-2-1_51KWP_2019-09-23_final.stac-item
2019-09-23 11:34:14	ga_s2bm_ard_3-2-1_51KVP_2019-09-23_final.stac-item
2019-09-23 11:34:15	ga_s2bm_ard_3-2-1_51JXN_2019-09-23_final.stac-item
2019-09-23 11:34:17	ga_s2bm_ard_3-2-1_51KUP_2019-09-23_final.stac-item
2019-09-23 11:34:25	ga_s2bm_ard_3-2-1_51JWN_2019-09-23_final.stac-item
2019-09-23 11:34:28	ga_s2bm_ard_3-2-1_51JVN_2019-09-23_final.stac-item
2019-09-23 11:34:31	ga_s2bm_ard_3-2-1_51JUN_2019-09-23_final.stac-item
2019-09-23 11:34:36	ga_s2bm_ard_3-2-1_51JTN_2019-09-23_final.stac-item
2019-09-23 11:34:36	ga_s2bm_ard_3-2-1_50JRT_2019-09-23_final.stac-item
2019-09-23 11:34:39	ga_s2bm_ard_3-2-1_51JWM_2019-09-23_final.stac-item
2019-09-23 11:34:43	ga_s2bm_ard_3-2-1_51JVM_2019-09-23_final.stac-item
2019-09-23 11:34:46	ga_s2bm_ard_3-2-1_51JUM_2019-09-23_final.stac-item
2019-09-23 11:34:49	ga_s2bm_ard_3-2-1_50JRS_2019-09-23_final.stac-item
2019-09-23 11:34:49	ga_s2bm_ard_3-2-1_51JTM_2019-09-23_final.stac-item
2019-09-23 11:34:54	ga_s2bm_ard_3-2-1_51JWL_2019-09-23_final.stac-item
2019-09-23 11:34:56	ga_s2bm_ard_3-2-1_51JVL_2019-09-23_final.stac-item
2019-09-23 11:34:58	ga_s2bm_ard_3-2-1_51JUL_2019-09-23_final.stac-item
2019-09-23 11:34:59	ga_s2bm_ard_3-2-1_51JTL_2019-09-23_final.stac-item
2019-09-23 11:35:01	ga_s2bm_ard_3-2-1_51JWK_2019-09-23_final.stac-item
2019-09-23 11:35:03	ga_s2bm_ard_3-2-1_51JVK_2019-09-23_final.stac-item

Return to ga_s2bm_ard_3 whole collection overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years