Search ga_s2bm_ard_3 on 10th 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
2019-10-10 09:41:46	ga_s2bm_ard_3-2-1_56KKF_2019-10-10_final
2019-10-10 09:41:53	ga_s2bm_ard_3-2-1_56KME_2019-10-10_final.stac-item
2019-10-10 09:42:08	ga_s2bm_ard_3-2-1_56KMD_2019-10-10_final.stac-item
2019-10-10 09:42:12	ga_s2bm_ard_3-2-1_56KLD_2019-10-10_final
2019-10-10 09:42:37	ga_s2bm_ard_3-2-1_56KMB_2019-10-10_final.stac-item
2019-10-10 09:42:41	ga_s2bm_ard_3-2-1_56KLB_2019-10-10_final
2019-10-10 09:42:44	ga_s2bm_ard_3-2-1_56KKB_2019-10-10_final
2019-10-10 09:42:47	ga_s2bm_ard_3-2-1_55KGS_2019-10-10_final
2019-10-10 09:42:51	ga_s2bm_ard_3-2-1_56KMA_2019-10-10_final
2019-10-10 09:42:58	ga_s2bm_ard_3-2-1_56KKA_2019-10-10_final
2019-10-10 09:43:02	ga_s2bm_ard_3-2-1_55KGR_2019-10-10_final
2019-10-10 09:43:13	ga_s2bm_ard_3-2-1_56KKV_2019-10-10_final
2019-10-10 09:43:17	ga_s2bm_ard_3-2-1_55KGQ_2019-10-10_final
2019-10-10 09:43:24	ga_s2bm_ard_3-2-1_56KLU_2019-10-10_final
2019-10-10 09:43:28	ga_s2bm_ard_3-2-1_56KKU_2019-10-10_final
2019-10-10 09:43:31	ga_s2bm_ard_3-2-1_55KGP_2019-10-10_final
2019-10-10 09:43:36	ga_s2bm_ard_3-2-1_55KFP_2019-10-10_final
2019-10-10 09:43:42	ga_s2bm_ard_3-2-1_55JHN_2019-10-10_final
2019-10-10 09:43:42	ga_s2bm_ard_3-2-1_56JKT_2019-10-10_final
2019-10-10 09:43:46	ga_s2bm_ard_3-2-1_55JGN_2019-10-10_final
2019-10-10 09:43:53	ga_s2bm_ard_3-2-1_56JLS_2019-10-10_final
2019-10-10 09:43:56	ga_s2bm_ard_3-2-1_55JHM_2019-10-10_final
2019-10-10 09:43:57	ga_s2bm_ard_3-2-1_56JKS_2019-10-10_final
2019-10-10 09:44:00	ga_s2bm_ard_3-2-1_55JGM_2019-10-10_final
2019-10-10 09:44:04	ga_s2bm_ard_3-2-1_55JFM_2019-10-10_final
2019-10-10 09:44:17	ga_s2bm_ard_3-2-1_56JLQ_2019-10-10_final
2019-10-10 09:44:50	ga_s2bm_ard_3-2-1_55JEJ_2019-10-10_final
2019-10-10 09:44:55	ga_s2bm_ard_3-2-1_56JKN_2019-10-10_final
2019-10-10 09:44:58	ga_s2bm_ard_3-2-1_55JGH_2019-10-10_final
2019-10-10 09:45:05	ga_s2bm_ard_3-2-1_55JEH_2019-10-10_final
2019-10-10 09:45:09	ga_s2bm_ard_3-2-1_56JKM_2019-10-10_final
2019-10-10 09:46:00	ga_s2bm_ard_3-2-1_55HFD_2019-10-10_final
2019-10-10 09:46:03	ga_s2bm_ard_3-2-1_55HED_2019-10-10_final
2019-10-10 09:46:07	ga_s2bm_ard_3-2-1_55HDD_2019-10-10_final
2019-10-10 09:46:18	ga_s2bm_ard_3-2-1_55HGB_2019-10-10_final
2019-10-10 09:46:56	ga_s2bm_ard_3-2-1_55HFV_2019-10-10_final
2019-10-10 09:46:58	ga_s2bm_ard_3-2-1_55HEV_2019-10-10_final
2019-10-10 09:47:00	ga_s2bm_ard_3-2-1_55HDV_2019-10-10_final
2019-10-10 09:47:01	ga_s2bm_ard_3-2-1_55HCV_2019-10-10_final
2019-10-10 09:47:03	ga_s2bm_ard_3-2-1_55HFV_2019-10-10_final
2019-10-10 09:47:05	ga_s2bm_ard_3-2-1_55HEV_2019-10-10_final
2019-10-10 09:47:07	ga_s2bm_ard_3-2-1_55HDV_2019-10-10_final
2019-10-10 09:47:09	ga_s2bm_ard_3-2-1_55HCV_2019-10-10_final
2019-10-10 09:47:52	ga_s2bm_ard_3-2-1_55HCS_2019-10-10_final
2019-10-10 09:47:55	ga_s2bm_ard_3-2-1_55HBS_2019-10-10_final
2019-10-10 09:47:59	ga_s2bm_ard_3-2-1_55GER_2019-10-10_final
2019-10-10 09:48:03	ga_s2bm_ard_3-2-1_55GDR_2019-10-10_final
2019-10-10 09:48:06	ga_s2bm_ard_3-2-1_55GCR_2019-10-10_final
2019-10-10 09:48:10	ga_s2bm_ard_3-2-1_55GBR_2019-10-10_final
2019-10-10 09:48:10	ga_s2bm_ard_3-2-1_54GYA_2019-10-10_final
2019-10-10 09:48:12	ga_s2bm_ard_3-2-1_55GEQ_2019-10-10_final
2019-10-10 09:48:17	ga_s2bm_ard_3-2-1_55GDQ_2019-10-10_final
2019-10-10 09:48:21	ga_s2bm_ard_3-2-1_55GCQ_2019-10-10_final
2019-10-10 09:48:24	ga_s2bm_ard_3-2-1_55GBQ_2019-10-10_final.stac-item
2019-10-10 09:48:24	ga_s2bm_ard_3-2-1_54GYV_2019-10-10_final.stac-item
2019-10-10 09:48:46	ga_s2bm_ard_3-2-1_55GDN_2019-10-10_final
2019-10-10 09:48:50	ga_s2bm_ard_3-2-1_55GCN_2019-10-10_final
2019-10-10 09:48:59	ga_s2bm_ard_3-2-1_55GDM_2019-10-10_final.stac-item
2019-10-10 09:49:01	ga_s2bm_ard_3-2-1_55GCM_2019-10-10_final.stac-item
2019-10-10 11:21:22	ga_s2bm_ard_3-2-1_52LCK_2019-10-10_final.stac-item
2019-10-10 11:21:25	ga_s2bm_ard_3-2-1_52LBK_2019-10-10_final
2019-10-10 11:21:26	ga_s2bm_ard_3-2-1_51LZE_2019-10-10_final
2019-10-10 11:21:33	ga_s2bm_ard_3-2-1_52LDJ_2019-10-10_final
2019-10-10 11:21:40	ga_s2bm_ard_3-2-1_52LBJ_2019-10-10_final
2019-10-10 11:21:41	ga_s2bm_ard_3-2-1_51LZD_2019-10-10_final
2019-10-10 11:22:23	ga_s2bm_ard_3-2-1_52KBF_2019-10-10_final
2019-10-10 11:22:24	ga_s2bm_ard_3-2-1_51KZA_2019-10-10_final
2019-10-10 11:22:28	ga_s2bm_ard_3-2-1_51KYA_2019-10-10_final
2019-10-10 11:22:34	ga_s2bm_ard_3-2-1_52KCE_2019-10-10_final
2019-10-10 11:22:49	ga_s2bm_ard_3-2-1_52KCD_2019-10-10_final
2019-10-10 11:23:01	ga_s2bm_ard_3-2-1_51KXU_2019-10-10_final
2019-10-10 11:23:04	ga_s2bm_ard_3-2-1_52KCC_2019-10-10_final
2019-10-10 11:23:18	ga_s2bm_ard_3-2-1_52KBB_2019-10-10_final
2019-10-10 11:23:20	ga_s2bm_ard_3-2-1_51KYS_2019-10-10_final
2019-10-10 11:23:25	ga_s2bm_ard_3-2-1_52KBB_2019-10-10_final
2019-10-10 11:23:27	ga_s2bm_ard_3-2-1_51KYS_2019-10-10_final
2019-10-10 11:23:36	ga_s2bm_ard_3-2-1_52KBA_2019-10-10_final
2019-10-10 11:23:40	ga_s2bm_ard_3-2-1_51KYR_2019-10-10_final
2019-10-10 11:23:51	ga_s2bm_ard_3-2-1_52KBV_2019-10-10_final
2019-10-10 11:23:55	ga_s2bm_ard_3-2-1_51KYQ_2019-10-10_final
2019-10-10 11:24:05	ga_s2bm_ard_3-2-1_52KBU_2019-10-10_final
2019-10-10 11:24:09	ga_s2bm_ard_3-2-1_51KYP_2019-10-10_final
2019-10-10 11:24:13	ga_s2bm_ard_3-2-1_51KXP_2019-10-10_final
2019-10-10 11:24:20	ga_s2bm_ard_3-2-1_51JZN_2019-10-10_final
2019-10-10 11:24:20	ga_s2bm_ard_3-2-1_52JBT_2019-10-10_final
2019-10-10 11:24:24	ga_s2bm_ard_3-2-1_51JYN_2019-10-10_final
2019-10-10 11:24:33	ga_s2bm_ard_3-2-1_51JZM_2019-10-10_final
2019-10-10 11:24:33	ga_s2bm_ard_3-2-1_52JBS_2019-10-10_final
2019-10-10 11:24:38	ga_s2bm_ard_3-2-1_51JYM_2019-10-10_final
2019-10-10 11:24:45	ga_s2bm_ard_3-2-1_51JWM_2019-10-10_final
2019-10-10 11:24:52	ga_s2bm_ard_3-2-1_51JYL_2019-10-10_final
2019-10-10 11:25:29	ga_s2bm_ard_3-2-1_51JWJ_2019-10-10_final
2019-10-10 11:25:32	ga_s2bm_ard_3-2-1_51JVJ_2019-10-10_final
2019-10-10 11:25:35	ga_s2bm_ard_3-2-1_51JYH_2019-10-10_final
2019-10-10 11:25:43	ga_s2bm_ard_3-2-1_51JWH_2019-10-10_final
2019-10-10 11:25:46	ga_s2bm_ard_3-2-1_51JYG_2019-10-10_final
2019-10-10 11:25:47	ga_s2bm_ard_3-2-1_51JVH_2019-10-10_final
2019-10-10 11:26:27	ga_s2bm_ard_3-2-1_51HWE_2019-10-10_final
2019-10-10 11:26:37	ga_s2bm_ard_3-2-1_51HXD_2019-10-10_final
2019-10-10 11:26:41	ga_s2bm_ard_3-2-1_51HWD_2019-10-10_final

Return to ga_s2bm_ard_3 on 10th 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

10th