Search ga_s2bm_ard_3 on 7th October 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
2019-10-07 09:32:53	ga_s2bm_ard_3-2-1_56KNA_2019-10-07_final.stac-item
2019-10-07 09:32:56	ga_s2bm_ard_3-2-1_56KMA_2019-10-07_final
2019-10-07 09:33:25	ga_s2bm_ard_3-2-1_56KMU_2019-10-07_final
2019-10-07 09:33:29	ga_s2bm_ard_3-2-1_56KLU_2019-10-07_final
2019-10-07 09:33:51	ga_s2bm_ard_3-2-1_56JNS_2019-10-07_final
2019-10-07 09:33:55	ga_s2bm_ard_3-2-1_56JMS_2019-10-07_final
2019-10-07 09:34:02	ga_s2bm_ard_3-2-1_55JHM_2019-10-07_final
2019-10-07 09:34:02	ga_s2bm_ard_3-2-1_56JKS_2019-10-07_final
2019-10-07 09:34:15	ga_s2bm_ard_3-2-1_56JKR_2019-10-07_final
2019-10-07 09:34:27	ga_s2bm_ard_3-2-1_56JLQ_2019-10-07_final
2019-10-07 09:34:34	ga_s2bm_ard_3-2-1_56JNP_2019-10-07_final.stac-item
2019-10-07 09:34:38	ga_s2bm_ard_3-2-1_56JMP_2019-10-07_final
2019-10-07 09:34:56	ga_s2bm_ard_3-2-1_56JLN_2019-10-07_final
2019-10-07 09:35:11	ga_s2bm_ard_3-2-1_56JLM_2019-10-07_final
2019-10-07 09:35:28	ga_s2bm_ard_3-2-1_56JKL_2019-10-07_final
2019-10-07 09:35:31	ga_s2bm_ard_3-2-1_55JGF_2019-10-07_final
2019-10-07 09:35:40	ga_s2bm_ard_3-2-1_56HLK_2019-10-07_final
2019-10-07 09:35:49	ga_s2bm_ard_3-2-1_56HMJ_2019-10-07_final
2019-10-07 09:35:51	ga_s2bm_ard_3-2-1_55HFE_2019-10-07_final
2019-10-07 09:36:09	ga_s2bm_ard_3-2-1_56HLH_2019-10-07_final.stac-item
2019-10-07 09:36:18	ga_s2bm_ard_3-2-1_55HFC_2019-10-07_final
2019-10-07 09:36:27	ga_s2bm_ard_3-2-1_56HKG_2019-10-07_final
2019-10-07 09:36:28	ga_s2bm_ard_3-2-1_55HGB_2019-10-07_final
2019-10-07 09:36:57	ga_s2bm_ard_3-2-1_55HGV_2019-10-07_final
2019-10-07 09:37:01	ga_s2bm_ard_3-2-1_55HFV_2019-10-07_final
2019-10-07 09:37:30	ga_s2bm_ard_3-2-1_55HFT_2019-10-07_final.stac-item
2019-10-07 09:37:34	ga_s2bm_ard_3-2-1_55HET_2019-10-07_final
2019-10-07 09:37:41	ga_s2bm_ard_3-2-1_55HDT_2019-10-07_final
2019-10-07 09:37:44	ga_s2bm_ard_3-2-1_55HFS_2019-10-07_final.stac-item
2019-10-07 09:37:48	ga_s2bm_ard_3-2-1_55HES_2019-10-07_final
2019-10-07 09:37:52	ga_s2bm_ard_3-2-1_55HDS_2019-10-07_final
2019-10-07 09:38:23	ga_s2bm_ard_3-2-1_55GFP_2019-10-07_final
2019-10-07 09:38:25	ga_s2bm_ard_3-2-1_55GEP_2019-10-07_final
2019-10-07 09:38:26	ga_s2bm_ard_3-2-1_55GDP_2019-10-07_final
2019-10-07 09:38:30	ga_s2bm_ard_3-2-1_55GFP_2019-10-07_final
2019-10-07 09:38:32	ga_s2bm_ard_3-2-1_55GEP_2019-10-07_final
2019-10-07 09:38:35	ga_s2bm_ard_3-2-1_55GDP_2019-10-07_final
2019-10-07 09:38:41	ga_s2bm_ard_3-2-1_55GCP_2019-10-07_final
2019-10-07 09:38:42	ga_s2bm_ard_3-2-1_55GFN_2019-10-07_final
2019-10-07 09:38:46	ga_s2bm_ard_3-2-1_55GEN_2019-10-07_final
2019-10-07 09:38:50	ga_s2bm_ard_3-2-1_55GDN_2019-10-07_final
2019-10-07 09:38:53	ga_s2bm_ard_3-2-1_55GCN_2019-10-07_final
2019-10-07 09:39:00	ga_s2bm_ard_3-2-1_55GEM_2019-10-07_final.stac-item
2019-10-07 09:39:03	ga_s2bm_ard_3-2-1_55GDM_2019-10-07_final.stac-item
2019-10-07 09:39:05	ga_s2bm_ard_3-2-1_55GCM_2019-10-07_final.stac-item
2019-10-07 11:10:26	ga_s2bm_ard_3-2-1_52LHN_2019-10-07_final
2019-10-07 11:10:30	ga_s2bm_ard_3-2-1_52LGN_2019-10-07_final
2019-10-07 11:11:13	ga_s2bm_ard_3-2-1_52LGK_2019-10-07_final
2019-10-07 11:11:28	ga_s2bm_ard_3-2-1_52LGJ_2019-10-07_final
2019-10-07 11:11:31	ga_s2bm_ard_3-2-1_52LFJ_2019-10-07_final
2019-10-07 11:11:41	ga_s2bm_ard_3-2-1_52LGH_2019-10-07_final
2019-10-07 11:11:46	ga_s2bm_ard_3-2-1_52LFH_2019-10-07_final
2019-10-07 11:11:49	ga_s2bm_ard_3-2-1_52LEH_2019-10-07_final
2019-10-07 11:11:52	ga_s2bm_ard_3-2-1_52LDH_2019-10-07_final
2019-10-07 11:12:04	ga_s2bm_ard_3-2-1_52KEG_2019-10-07_final
2019-10-07 11:12:07	ga_s2bm_ard_3-2-1_52KDG_2019-10-07_final
2019-10-07 11:12:14	ga_s2bm_ard_3-2-1_52KFF_2019-10-07_final
2019-10-07 11:12:18	ga_s2bm_ard_3-2-1_52KEF_2019-10-07_final
2019-10-07 11:12:21	ga_s2bm_ard_3-2-1_52KDF_2019-10-07_final
2019-10-07 11:12:24	ga_s2bm_ard_3-2-1_52KCF_2019-10-07_final
2019-10-07 11:12:29	ga_s2bm_ard_3-2-1_52KFE_2019-10-07_final
2019-10-07 11:12:39	ga_s2bm_ard_3-2-1_52KCE_2019-10-07_final
2019-10-07 11:12:43	ga_s2bm_ard_3-2-1_52KFD_2019-10-07_final
2019-10-07 11:12:47	ga_s2bm_ard_3-2-1_52KED_2019-10-07_final
2019-10-07 11:12:51	ga_s2bm_ard_3-2-1_52KDD_2019-10-07_final
2019-10-07 11:12:54	ga_s2bm_ard_3-2-1_52KCD_2019-10-07_final
2019-10-07 11:12:55	ga_s2bm_ard_3-2-1_52KFC_2019-10-07_final
2019-10-07 11:13:08	ga_s2bm_ard_3-2-1_52KCC_2019-10-07_final
2019-10-07 11:13:14	ga_s2bm_ard_3-2-1_52KBC_2019-10-07_final
2019-10-07 11:13:23	ga_s2bm_ard_3-2-1_52KCB_2019-10-07_final
2019-10-07 11:13:26	ga_s2bm_ard_3-2-1_52KBB_2019-10-07_final
2019-10-07 11:13:30	ga_s2bm_ard_3-2-1_51KZS_2019-10-07_final
2019-10-07 11:13:31	ga_s2bm_ard_3-2-1_52KEA_2019-10-07_final
2019-10-07 11:13:34	ga_s2bm_ard_3-2-1_52KDA_2019-10-07_final
2019-10-07 11:13:37	ga_s2bm_ard_3-2-1_52KCA_2019-10-07_final
2019-10-07 11:13:41	ga_s2bm_ard_3-2-1_51KZR_2019-10-07_final
2019-10-07 11:13:55	ga_s2bm_ard_3-2-1_51KZQ_2019-10-07_final
2019-10-07 11:13:55	ga_s2bm_ard_3-2-1_52KBV_2019-10-07_final
2019-10-07 11:13:58	ga_s2bm_ard_3-2-1_52KEU_2019-10-07_final
2019-10-07 11:14:03	ga_s2bm_ard_3-2-1_52KDU_2019-10-07_final
2019-10-07 11:14:07	ga_s2bm_ard_3-2-1_52KCU_2019-10-07_final
2019-10-07 11:14:10	ga_s2bm_ard_3-2-1_51KZP_2019-10-07_final
2019-10-07 11:14:24	ga_s2bm_ard_3-2-1_51JZN_2019-10-07_final
2019-10-07 11:14:32	ga_s2bm_ard_3-2-1_52JDS_2019-10-07_final
2019-10-07 11:14:38	ga_s2bm_ard_3-2-1_51JZM_2019-10-07_final
2019-10-07 11:14:52	ga_s2bm_ard_3-2-1_52JBR_2019-10-07_final
2019-10-07 11:14:54	ga_s2bm_ard_3-2-1_51JYL_2019-10-07_final
2019-10-07 11:14:58	ga_s2bm_ard_3-2-1_52JCQ_2019-10-07_final
2019-10-07 11:14:59	ga_s2bm_ard_3-2-1_52JBR_2019-10-07_final
2019-10-07 11:15:01	ga_s2bm_ard_3-2-1_51JYL_2019-10-07_final
2019-10-07 11:15:05	ga_s2bm_ard_3-2-1_52JCQ_2019-10-07_final
2019-10-07 11:15:13	ga_s2bm_ard_3-2-1_52JDP_2019-10-07_final
2019-10-07 11:15:34	ga_s2bm_ard_3-2-1_52JCN_2019-10-07_final
2019-10-07 11:15:43	ga_s2bm_ard_3-2-1_51JXH_2019-10-07_final
2019-10-07 11:15:48	ga_s2bm_ard_3-2-1_52JCM_2019-10-07_final
2019-10-07 11:15:58	ga_s2bm_ard_3-2-1_51JXG_2019-10-07_final
2019-10-07 11:16:06	ga_s2bm_ard_3-2-1_52JBL_2019-10-07_final
2019-10-07 11:16:09	ga_s2bm_ard_3-2-1_51JYF_2019-10-07_final
2019-10-07 11:16:17	ga_s2bm_ard_3-2-1_52HCK_2019-10-07_final.stac-item
2019-10-07 11:16:27	ga_s2bm_ard_3-2-1_51HXE_2019-10-07_final

Return to ga_s2bm_ard_3 on 7th October 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

October

7th