Search ga_s2bm_ard_3 on 30th 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
2019-10-30 09:41:24	ga_s2bm_ard_3-2-1_56KMG_2019-10-30_final.stac-item
2019-10-30 09:41:28	ga_s2bm_ard_3-2-1_56KLG_2019-10-30_final.stac-item
2019-10-30 09:41:30	ga_s2bm_ard_3-2-1_56KKG_2019-10-30_final.stac-item
2019-10-30 09:41:33	ga_s2bm_ard_3-2-1_55KHB_2019-10-30_final.stac-item
2019-10-30 09:41:39	ga_s2bm_ard_3-2-1_56KMF_2019-10-30_final.stac-item
2019-10-30 09:41:42	ga_s2bm_ard_3-2-1_56KLF_2019-10-30_final
2019-10-30 09:42:37	ga_s2bm_ard_3-2-1_56KMB_2019-10-30_final.stac-item
2019-10-30 09:42:40	ga_s2bm_ard_3-2-1_56KLB_2019-10-30_final
2019-10-30 09:42:44	ga_s2bm_ard_3-2-1_56KKB_2019-10-30_final
2019-10-30 09:42:44	ga_s2bm_ard_3-2-1_55KHS_2019-10-30_final
2019-10-30 09:42:47	ga_s2bm_ard_3-2-1_55KGS_2019-10-30_final
2019-10-30 09:42:50	ga_s2bm_ard_3-2-1_56KMA_2019-10-30_final
2019-10-30 09:42:58	ga_s2bm_ard_3-2-1_56KKA_2019-10-30_final
2019-10-30 09:42:58	ga_s2bm_ard_3-2-1_55KHR_2019-10-30_final
2019-10-30 09:43:02	ga_s2bm_ard_3-2-1_55KGR_2019-10-30_final
2019-10-30 09:43:13	ga_s2bm_ard_3-2-1_56KKV_2019-10-30_final
2019-10-30 09:43:13	ga_s2bm_ard_3-2-1_55KHQ_2019-10-30_final
2019-10-30 09:43:24	ga_s2bm_ard_3-2-1_56KLU_2019-10-30_final
2019-10-30 09:43:27	ga_s2bm_ard_3-2-1_55KHP_2019-10-30_final
2019-10-30 09:43:35	ga_s2bm_ard_3-2-1_55KFP_2019-10-30_final
2019-10-30 09:43:39	ga_s2bm_ard_3-2-1_56JLT_2019-10-30_final
2019-10-30 09:43:42	ga_s2bm_ard_3-2-1_55JHN_2019-10-30_final
2019-10-30 09:43:42	ga_s2bm_ard_3-2-1_56JKT_2019-10-30_final
2019-10-30 09:43:45	ga_s2bm_ard_3-2-1_55JGN_2019-10-30_final
2019-10-30 09:43:49	ga_s2bm_ard_3-2-1_55JFN_2019-10-30_final
2019-10-30 09:43:53	ga_s2bm_ard_3-2-1_56JLS_2019-10-30_final
2019-10-30 09:43:56	ga_s2bm_ard_3-2-1_55JHM_2019-10-30_final
2019-10-30 09:43:56	ga_s2bm_ard_3-2-1_56JKS_2019-10-30_final
2019-10-30 09:44:00	ga_s2bm_ard_3-2-1_55JGM_2019-10-30_final
2019-10-30 09:44:03	ga_s2bm_ard_3-2-1_55JFM_2019-10-30_final
2019-10-30 09:44:06	ga_s2bm_ard_3-2-1_56JLR_2019-10-30_final
2019-10-30 09:44:37	ga_s2bm_ard_3-2-1_55JEK_2019-10-30_final
2019-10-30 09:44:43	ga_s2bm_ard_3-2-1_55JGJ_2019-10-30_final
2019-10-30 09:44:58	ga_s2bm_ard_3-2-1_55JGH_2019-10-30_final
2019-10-30 09:45:30	ga_s2bm_ard_3-2-1_55JFF_2019-10-30_final
2019-10-30 09:45:43	ga_s2bm_ard_3-2-1_55HEE_2019-10-30_final
2019-10-30 09:45:45	ga_s2bm_ard_3-2-1_55HDE_2019-10-30_final
2019-10-30 09:45:50	ga_s2bm_ard_3-2-1_55HEE_2019-10-30_final
2019-10-30 09:45:52	ga_s2bm_ard_3-2-1_55HDE_2019-10-30_final
2019-10-30 09:45:55	ga_s2bm_ard_3-2-1_55HGD_2019-10-30_final
2019-10-30 09:45:59	ga_s2bm_ard_3-2-1_55HFD_2019-10-30_final
2019-10-30 09:46:42	ga_s2bm_ard_3-2-1_55HFA_2019-10-30_final
2019-10-30 09:46:53	ga_s2bm_ard_3-2-1_55HCA_2019-10-30_final
2019-10-30 09:47:10	ga_s2bm_ard_3-2-1_55HFU_2019-10-30_final.stac-item
2019-10-30 09:47:15	ga_s2bm_ard_3-2-1_55HEU_2019-10-30_final
2019-10-30 09:47:19	ga_s2bm_ard_3-2-1_55HDU_2019-10-30_final
2019-10-30 09:47:22	ga_s2bm_ard_3-2-1_55HCU_2019-10-30_final
2019-10-30 09:47:51	ga_s2bm_ard_3-2-1_55HCS_2019-10-30_final
2019-10-30 09:47:54	ga_s2bm_ard_3-2-1_55HBS_2019-10-30_final
2019-10-30 11:21:22	ga_s2bm_ard_3-2-1_52LCK_2019-10-30_final.stac-item
2019-10-30 11:21:39	ga_s2bm_ard_3-2-1_52LBJ_2019-10-30_final
2019-10-30 11:21:41	ga_s2bm_ard_3-2-1_51LZD_2019-10-30_final
2019-10-30 11:22:01	ga_s2bm_ard_3-2-1_52KDG_2019-10-30_final
2019-10-30 11:22:05	ga_s2bm_ard_3-2-1_52KCG_2019-10-30_final
2019-10-30 11:22:08	ga_s2bm_ard_3-2-1_52KBG_2019-10-30_final
2019-10-30 11:22:09	ga_s2bm_ard_3-2-1_51KZB_2019-10-30_final
2019-10-30 11:22:13	ga_s2bm_ard_3-2-1_51KYB_2019-10-30_final
2019-10-30 11:22:13	ga_s2bm_ard_3-2-1_52KDF_2019-10-30_final
2019-10-30 11:22:20	ga_s2bm_ard_3-2-1_52KCF_2019-10-30_final
2019-10-30 11:22:23	ga_s2bm_ard_3-2-1_52KBF_2019-10-30_final
2019-10-30 11:22:24	ga_s2bm_ard_3-2-1_51KZA_2019-10-30_final
2019-10-30 11:22:27	ga_s2bm_ard_3-2-1_51KYA_2019-10-30_final
2019-10-30 11:23:17	ga_s2bm_ard_3-2-1_52KCB_2019-10-30_final
2019-10-30 11:23:21	ga_s2bm_ard_3-2-1_52KBB_2019-10-30_final
2019-10-30 11:23:22	ga_s2bm_ard_3-2-1_51KZS_2019-10-30_final
2019-10-30 11:23:25	ga_s2bm_ard_3-2-1_51KYS_2019-10-30_final
2019-10-30 11:23:29	ga_s2bm_ard_3-2-1_51KXS_2019-10-30_final
2019-10-30 11:23:36	ga_s2bm_ard_3-2-1_52KBA_2019-10-30_final
2019-10-30 11:23:36	ga_s2bm_ard_3-2-1_51KZR_2019-10-30_final
2019-10-30 11:23:40	ga_s2bm_ard_3-2-1_51KYR_2019-10-30_final
2019-10-30 11:23:50	ga_s2bm_ard_3-2-1_52KBV_2019-10-30_final
2019-10-30 11:23:50	ga_s2bm_ard_3-2-1_51KZQ_2019-10-30_final
2019-10-30 11:24:03	ga_s2bm_ard_3-2-1_51KWQ_2019-10-30_final
2019-10-30 11:24:05	ga_s2bm_ard_3-2-1_51KZP_2019-10-30_final
2019-10-30 11:24:12	ga_s2bm_ard_3-2-1_51KXP_2019-10-30_final
2019-10-30 11:24:16	ga_s2bm_ard_3-2-1_51KWP_2019-10-30_final
2019-10-30 11:24:20	ga_s2bm_ard_3-2-1_51JZN_2019-10-30_final
2019-10-30 11:24:20	ga_s2bm_ard_3-2-1_52JBT_2019-10-30_final
2019-10-30 11:24:23	ga_s2bm_ard_3-2-1_51JYN_2019-10-30_final
2019-10-30 11:24:27	ga_s2bm_ard_3-2-1_51JXN_2019-10-30_final
2019-10-30 11:24:30	ga_s2bm_ard_3-2-1_51JWN_2019-10-30_final
2019-10-30 11:24:33	ga_s2bm_ard_3-2-1_51JZM_2019-10-30_final
2019-10-30 11:24:33	ga_s2bm_ard_3-2-1_52JBS_2019-10-30_final
2019-10-30 11:24:38	ga_s2bm_ard_3-2-1_51JYM_2019-10-30_final
2019-10-30 11:24:41	ga_s2bm_ard_3-2-1_51JXM_2019-10-30_final
2019-10-30 11:24:43	ga_s2bm_ard_3-2-1_51JWM_2019-10-30_final
2019-10-30 11:24:47	ga_s2bm_ard_3-2-1_51JYM_2019-10-30_final
2019-10-30 11:24:48	ga_s2bm_ard_3-2-1_51JXL_2019-10-30_final
2019-10-30 11:24:48	ga_s2bm_ard_3-2-1_51JXM_2019-10-30_final
2019-10-30 11:24:49	ga_s2bm_ard_3-2-1_51JWM_2019-10-30_final
2019-10-30 11:25:10	ga_s2bm_ard_3-2-1_51JXK_2019-10-30_final
2019-10-30 11:25:14	ga_s2bm_ard_3-2-1_51JWK_2019-10-30_final
2019-10-30 11:25:17	ga_s2bm_ard_3-2-1_51JVK_2019-10-30_final
2019-10-30 11:25:35	ga_s2bm_ard_3-2-1_51JYH_2019-10-30_final
2019-10-30 11:26:08	ga_s2bm_ard_3-2-1_51JXF_2019-10-30_final
2019-10-30 11:26:19	ga_s2bm_ard_3-2-1_51JUF_2019-10-30_final
2019-10-30 11:26:26	ga_s2bm_ard_3-2-1_51HWE_2019-10-30_final
2019-10-30 11:26:37	ga_s2bm_ard_3-2-1_51HXD_2019-10-30_final
2019-10-30 11:26:41	ga_s2bm_ard_3-2-1_51HWD_2019-10-30_final
2019-10-30 11:26:44	ga_s2bm_ard_3-2-1_51HVD_2019-10-30_final

Return to ga_s2bm_ard_3 on 30th 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

30th