Search ga_s2bm_ard_3 across November 2019

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2019-11-05 11:44:13	ga_s2bm_ard_3-2-1_51KUP_2019-11-05_final
2019-11-05 11:44:16	ga_s2bm_ard_3-2-1_50KRU_2019-11-05_final
2019-11-05 11:44:16	ga_s2bm_ard_3-2-1_51KTP_2019-11-05_final
2019-11-05 11:44:20	ga_s2bm_ard_3-2-1_50KQU_2019-11-05_final
2019-11-05 11:44:23	ga_s2bm_ard_3-2-1_50KPU_2019-11-05_final
2019-11-05 11:44:27	ga_s2bm_ard_3-2-1_51JUN_2019-11-05_final
2019-11-05 11:44:31	ga_s2bm_ard_3-2-1_50JRT_2019-11-05_final
2019-11-05 11:44:31	ga_s2bm_ard_3-2-1_51JTN_2019-11-05_final
2019-11-05 11:44:34	ga_s2bm_ard_3-2-1_50JQT_2019-11-05_final
2019-11-05 11:44:38	ga_s2bm_ard_3-2-1_50JPT_2019-11-05_final
2019-11-05 11:44:41	ga_s2bm_ard_3-2-1_51JUM_2019-11-05_final
2019-11-05 11:44:45	ga_s2bm_ard_3-2-1_50JRS_2019-11-05_final
2019-11-05 11:44:45	ga_s2bm_ard_3-2-1_51JTM_2019-11-05_final
2019-11-05 11:44:49	ga_s2bm_ard_3-2-1_50JQS_2019-11-05_final
2019-11-05 11:44:51	ga_s2bm_ard_3-2-1_51JUL_2019-11-05_final
2019-11-05 11:44:52	ga_s2bm_ard_3-2-1_50JPS_2019-11-05_final
2019-11-05 11:45:00	ga_s2bm_ard_3-2-1_51JTL_2019-11-05_final
2019-11-05 11:45:03	ga_s2bm_ard_3-2-1_50JQR_2019-11-05_final
2019-11-05 11:45:07	ga_s2bm_ard_3-2-1_50JPR_2019-11-05_final
2019-11-05 11:45:11	ga_s2bm_ard_3-2-1_50JNR_2019-11-05_final
2019-11-05 11:45:14	ga_s2bm_ard_3-2-1_51JTK_2019-11-05_final
2019-11-05 11:45:18	ga_s2bm_ard_3-2-1_50JQQ_2019-11-05_final
2019-11-05 11:45:21	ga_s2bm_ard_3-2-1_50JPQ_2019-11-05_final
2019-11-05 11:45:25	ga_s2bm_ard_3-2-1_50JNQ_2019-11-05_final
2019-11-05 11:45:29	ga_s2bm_ard_3-2-1_51JTJ_2019-11-05_final
2019-11-05 11:45:32	ga_s2bm_ard_3-2-1_50JQP_2019-11-05_final
2019-11-05 11:45:36	ga_s2bm_ard_3-2-1_50JPP_2019-11-05_final
2019-11-05 11:45:39	ga_s2bm_ard_3-2-1_50JNP_2019-11-05_final
2019-11-05 11:45:44	ga_s2bm_ard_3-2-1_51JTH_2019-11-05_final
2019-11-05 11:45:46	ga_s2bm_ard_3-2-1_50JQN_2019-11-05_final
2019-11-05 11:45:50	ga_s2bm_ard_3-2-1_50JPN_2019-11-05_final
2019-11-05 11:45:54	ga_s2bm_ard_3-2-1_50JNN_2019-11-05_final
2019-11-05 11:45:57	ga_s2bm_ard_3-2-1_51JTG_2019-11-05_final
2019-11-05 11:46:01	ga_s2bm_ard_3-2-1_50JQM_2019-11-05_final
2019-11-05 11:46:05	ga_s2bm_ard_3-2-1_50JPM_2019-11-05_final
2019-11-05 11:46:08	ga_s2bm_ard_3-2-1_51JTF_2019-11-05_final
2019-11-05 11:46:08	ga_s2bm_ard_3-2-1_50JNM_2019-11-05_final
2019-11-05 11:46:13	ga_s2bm_ard_3-2-1_50JMM_2019-11-05_final
2019-11-05 11:46:15	ga_s2bm_ard_3-2-1_50JQL_2019-11-05_final
2019-11-05 11:46:19	ga_s2bm_ard_3-2-1_50JPL_2019-11-05_final
2019-11-05 11:46:23	ga_s2bm_ard_3-2-1_50JNL_2019-11-05_final
2019-11-05 11:46:26	ga_s2bm_ard_3-2-1_50JML_2019-11-05_final
2019-11-05 11:46:30	ga_s2bm_ard_3-2-1_50HQK_2019-11-05_final
2019-11-05 11:46:34	ga_s2bm_ard_3-2-1_50HPK_2019-11-05_final
2019-11-05 11:46:37	ga_s2bm_ard_3-2-1_50HNK_2019-11-05_final
2019-11-05 11:46:41	ga_s2bm_ard_3-2-1_50HMK_2019-11-05_final
2019-11-05 11:46:43	ga_s2bm_ard_3-2-1_50HQJ_2019-11-05_final
2019-11-05 11:46:48	ga_s2bm_ard_3-2-1_50HPJ_2019-11-05_final
2019-11-05 11:46:52	ga_s2bm_ard_3-2-1_50HNJ_2019-11-05_final
2019-11-09 11:26:43	ga_s2bm_ard_3-2-1_51HVD_2019-11-09_final
2019-11-10 10:50:34	ga_s2bm_ard_3-2-1_53LPG_2019-11-10_final
2019-11-12 11:34:31	ga_s2bm_ard_3-2-1_51JUN_2019-11-12_final
2019-11-12 11:34:35	ga_s2bm_ard_3-2-1_51JTN_2019-11-12_final
2019-11-12 11:34:36	ga_s2bm_ard_3-2-1_50JRT_2019-11-12_final
2019-11-12 11:34:39	ga_s2bm_ard_3-2-1_51JWM_2019-11-12_final
2019-11-12 11:34:42	ga_s2bm_ard_3-2-1_51JVM_2019-11-12_final
2019-11-12 11:34:45	ga_s2bm_ard_3-2-1_51JUM_2019-11-12_final
2019-11-12 11:34:48	ga_s2bm_ard_3-2-1_50JRS_2019-11-12_final
2019-11-12 11:34:48	ga_s2bm_ard_3-2-1_51JTM_2019-11-12_final
2019-11-12 11:34:53	ga_s2bm_ard_3-2-1_51JWL_2019-11-12_final
2019-11-12 11:34:57	ga_s2bm_ard_3-2-1_51JVL_2019-11-12_final
2019-11-12 11:35:00	ga_s2bm_ard_3-2-1_51JUL_2019-11-12_final
2019-11-12 11:35:03	ga_s2bm_ard_3-2-1_51JTL_2019-11-12_final
2019-11-12 11:35:07	ga_s2bm_ard_3-2-1_51JWK_2019-11-12_final
2019-11-12 11:35:11	ga_s2bm_ard_3-2-1_51JVK_2019-11-12_final
2019-11-12 11:35:15	ga_s2bm_ard_3-2-1_51JUK_2019-11-12_final
2019-11-12 11:35:18	ga_s2bm_ard_3-2-1_51JTK_2019-11-12_final
2019-11-12 11:35:18	ga_s2bm_ard_3-2-1_51JWJ_2019-11-12_final
2019-11-12 11:35:26	ga_s2bm_ard_3-2-1_51JVJ_2019-11-12_final
2019-11-12 11:35:29	ga_s2bm_ard_3-2-1_51JUJ_2019-11-12_final
2019-11-12 11:35:33	ga_s2bm_ard_3-2-1_51JTJ_2019-11-12_final
2019-11-12 11:35:36	ga_s2bm_ard_3-2-1_50JQP_2019-11-12_final
2019-11-12 11:35:40	ga_s2bm_ard_3-2-1_51JVH_2019-11-12_final
2019-11-12 11:35:44	ga_s2bm_ard_3-2-1_51JUH_2019-11-12_final
2019-11-12 11:35:47	ga_s2bm_ard_3-2-1_51JTH_2019-11-12_final
2019-11-12 11:35:49	ga_s2bm_ard_3-2-1_50JQN_2019-11-12_final
2019-11-12 11:35:55	ga_s2bm_ard_3-2-1_51JVG_2019-11-12_final
2019-11-12 11:35:58	ga_s2bm_ard_3-2-1_51JUG_2019-11-12_final
2019-11-12 11:36:02	ga_s2bm_ard_3-2-1_51JTG_2019-11-12_final
2019-11-12 11:36:04	ga_s2bm_ard_3-2-1_50JQM_2019-11-12_final
2019-11-12 11:36:09	ga_s2bm_ard_3-2-1_51JVF_2019-11-12_final
2019-11-12 11:36:12	ga_s2bm_ard_3-2-1_51JUF_2019-11-12_final
2019-11-12 11:36:13	ga_s2bm_ard_3-2-1_51JTF_2019-11-12_final
2019-11-12 11:36:14	ga_s2bm_ard_3-2-1_50JQL_2019-11-12_final
2019-11-12 11:36:16	ga_s2bm_ard_3-2-1_51JVF_2019-11-12_final
2019-11-12 11:36:17	ga_s2bm_ard_3-2-1_51HVE_2019-11-12_final
2019-11-12 11:36:18	ga_s2bm_ard_3-2-1_51HUE_2019-11-12_final
2019-11-12 11:36:18	ga_s2bm_ard_3-2-1_51JUF_2019-11-12_final
2019-11-12 11:36:20	ga_s2bm_ard_3-2-1_51JTF_2019-11-12_final
2019-11-12 11:36:21	ga_s2bm_ard_3-2-1_50JQL_2019-11-12_final
2019-11-12 11:36:23	ga_s2bm_ard_3-2-1_51HVE_2019-11-12_final
2019-11-12 11:36:26	ga_s2bm_ard_3-2-1_50JPL_2019-11-12_final
2019-11-12 11:36:27	ga_s2bm_ard_3-2-1_51HUE_2019-11-12_final
2019-11-12 11:36:31	ga_s2bm_ard_3-2-1_51HTE_2019-11-12_final
2019-11-12 11:36:33	ga_s2bm_ard_3-2-1_51HVD_2019-11-12_final
2019-11-12 11:36:33	ga_s2bm_ard_3-2-1_50HQK_2019-11-12_final
2019-11-12 11:36:37	ga_s2bm_ard_3-2-1_50HPK_2019-11-12_final
2019-11-12 11:36:42	ga_s2bm_ard_3-2-1_51HUD_2019-11-12_final
2019-11-12 11:36:46	ga_s2bm_ard_3-2-1_51HTD_2019-11-12_final
2019-11-12 11:36:47	ga_s2bm_ard_3-2-1_50HQJ_2019-11-12_final

Return to ga_s2bm_ard_3 across November 2019 overview

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

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2019

November

All days