Search ga_s2bm_ard_3 on 9th September 2023

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

First 100 results (query limit)

Time (local)	Label
2023-09-09 09:39:39	ga_s2bm_ard_3-2-1_56LPP_2023-09-09_nrt
2023-09-09 09:39:43	ga_s2bm_ard_3-2-1_56LNP_2023-09-09_nrt
2023-09-09 09:39:46	ga_s2bm_ard_3-2-1_56LMP_2023-09-09_nrt
2023-09-09 09:39:53	ga_s2bm_ard_3-2-1_56LLP_2023-09-09_nrt
2023-09-09 09:39:54	ga_s2bm_ard_3-2-1_56LPN_2023-09-09_nrt
2023-09-09 09:39:57	ga_s2bm_ard_3-2-1_56LNN_2023-09-09_nrt
2023-09-09 09:40:00	ga_s2bm_ard_3-2-1_56LMN_2023-09-09_nrt
2023-09-09 09:40:04	ga_s2bm_ard_3-2-1_56LLN_2023-09-09_nrt
2023-09-09 09:47:13	ga_s2bm_ard_3-2-1_55HFU_2023-09-09_final
2023-09-09 09:47:19	ga_s2bm_ard_3-2-1_55HEU_2023-09-09_final
2023-09-09 09:47:22	ga_s2bm_ard_3-2-1_55HDU_2023-09-09_final
2023-09-09 09:47:23	ga_s2bm_ard_3-2-1_55HFT_2023-09-09_final
2023-09-09 09:47:26	ga_s2bm_ard_3-2-1_55HCU_2023-09-09_final
2023-09-09 09:47:33	ga_s2bm_ard_3-2-1_55HET_2023-09-09_final
2023-09-09 09:47:33	ga_s2bm_ard_3-2-1_55HBU_2023-09-09_final
2023-09-09 09:47:37	ga_s2bm_ard_3-2-1_55HDT_2023-09-09_final
2023-09-09 09:47:40	ga_s2bm_ard_3-2-1_55HCT_2023-09-09_final
2023-09-09 09:47:44	ga_s2bm_ard_3-2-1_55HBT_2023-09-09_final
2023-09-09 09:47:48	ga_s2bm_ard_3-2-1_55HES_2023-09-09_final
2023-09-09 09:47:48	ga_s2bm_ard_3-2-1_54HYC_2023-09-09_final
2023-09-09 09:47:51	ga_s2bm_ard_3-2-1_55HDS_2023-09-09_final
2023-09-09 09:47:55	ga_s2bm_ard_3-2-1_55HCS_2023-09-09_final
2023-09-09 09:47:58	ga_s2bm_ard_3-2-1_55HBS_2023-09-09_final
2023-09-09 09:47:59	ga_s2bm_ard_3-2-1_54HYB_2023-09-09_final
2023-09-09 09:48:02	ga_s2bm_ard_3-2-1_55GER_2023-09-09_final
2023-09-09 09:48:06	ga_s2bm_ard_3-2-1_55GDR_2023-09-09_final
2023-09-09 09:48:09	ga_s2bm_ard_3-2-1_55GCR_2023-09-09_final
2023-09-09 09:48:13	ga_s2bm_ard_3-2-1_55GBR_2023-09-09_final
2023-09-09 09:48:13	ga_s2bm_ard_3-2-1_54GYA_2023-09-09_final
2023-09-09 09:48:15	ga_s2bm_ard_3-2-1_55GEQ_2023-09-09_final
2023-09-09 09:48:20	ga_s2bm_ard_3-2-1_55GDQ_2023-09-09_final
2023-09-09 09:48:24	ga_s2bm_ard_3-2-1_55GCQ_2023-09-09_final
2023-09-09 09:48:26	ga_s2bm_ard_3-2-1_55GEP_2023-09-09_final
2023-09-09 09:48:27	ga_s2bm_ard_3-2-1_55GBQ_2023-09-09_final
2023-09-09 09:48:27	ga_s2bm_ard_3-2-1_54GYV_2023-09-09_final
2023-09-09 09:48:35	ga_s2bm_ard_3-2-1_55GDP_2023-09-09_final
2023-09-09 09:48:39	ga_s2bm_ard_3-2-1_55GCP_2023-09-09_final
2023-09-09 09:48:42	ga_s2bm_ard_3-2-1_54GYU_2023-09-09_nrt
2023-09-09 09:48:42	ga_s2bm_ard_3-2-1_55GBP_2023-09-09_nrt
2023-09-09 09:48:47	ga_s2bm_ard_3-2-1_54GXU_2023-09-09_nrt
2023-09-09 09:48:49	ga_s2bm_ard_3-2-1_55GDN_2023-09-09_final
2023-09-09 09:48:53	ga_s2bm_ard_3-2-1_55GCN_2023-09-09_final
2023-09-09 09:48:56	ga_s2bm_ard_3-2-1_54GYT_2023-09-09_nrt
2023-09-09 09:48:59	ga_s2bm_ard_3-2-1_54GXT_2023-09-09_nrt
2023-09-09 09:49:01	ga_s2bm_ard_3-2-1_55GDM_2023-09-09_final
2023-09-09 09:49:03	ga_s2bm_ard_3-2-1_55GCM_2023-09-09_final
2023-09-09 09:49:04	ga_s2bm_ard_3-2-1_54GYS_2023-09-09_nrt
2023-09-09 09:49:06	ga_s2bm_ard_3-2-1_54GXS_2023-09-09_nrt
2023-09-09 11:20:20	ga_s2bm_ard_3-2-1_52LEP_2023-09-09_nrt
2023-09-09 11:20:24	ga_s2bm_ard_3-2-1_52LDP_2023-09-09_nrt
2023-09-09 11:20:27	ga_s2bm_ard_3-2-1_52LCP_2023-09-09_nrt
2023-09-09 11:20:30	ga_s2bm_ard_3-2-1_52LBP_2023-09-09_nrt
2023-09-09 11:20:35	ga_s2bm_ard_3-2-1_52LEN_2023-09-09_nrt
2023-09-09 11:20:38	ga_s2bm_ard_3-2-1_52LDN_2023-09-09_nrt
2023-09-09 11:20:41	ga_s2bm_ard_3-2-1_52LCN_2023-09-09_nrt
2023-09-09 11:20:44	ga_s2bm_ard_3-2-1_52LBN_2023-09-09_nrt
2023-09-09 11:20:49	ga_s2bm_ard_3-2-1_52LEM_2023-09-09_nrt
2023-09-09 11:20:50	ga_s2bm_ard_3-2-1_51LZH_2023-09-09_nrt
2023-09-09 11:20:53	ga_s2bm_ard_3-2-1_52LDM_2023-09-09_nrt
2023-09-09 11:20:56	ga_s2bm_ard_3-2-1_52LCM_2023-09-09_nrt
2023-09-09 11:20:59	ga_s2bm_ard_3-2-1_52LBM_2023-09-09_nrt
2023-09-09 11:21:01	ga_s2bm_ard_3-2-1_51LZG_2023-09-09_nrt
2023-09-09 11:21:02	ga_s2bm_ard_3-2-1_52LEL_2023-09-09_final
2023-09-09 11:21:07	ga_s2bm_ard_3-2-1_52LDL_2023-09-09_nrt
2023-09-09 11:21:11	ga_s2bm_ard_3-2-1_52LCL_2023-09-09_nrt
2023-09-09 11:21:12	ga_s2bm_ard_3-2-1_52LEK_2023-09-09_final
2023-09-09 11:21:14	ga_s2bm_ard_3-2-1_52LBL_2023-09-09_nrt
2023-09-09 11:21:15	ga_s2bm_ard_3-2-1_51LZF_2023-09-09_nrt
2023-09-09 11:21:21	ga_s2bm_ard_3-2-1_52LDK_2023-09-09_nrt
2023-09-09 11:21:25	ga_s2bm_ard_3-2-1_52LCK_2023-09-09_final
2023-09-09 11:21:28	ga_s2bm_ard_3-2-1_52LBK_2023-09-09_final
2023-09-09 11:21:29	ga_s2bm_ard_3-2-1_51LZE_2023-09-09_final
2023-09-09 11:21:36	ga_s2bm_ard_3-2-1_52LDJ_2023-09-09_final
2023-09-09 11:21:40	ga_s2bm_ard_3-2-1_52LCJ_2023-09-09_final
2023-09-09 11:21:43	ga_s2bm_ard_3-2-1_52LBJ_2023-09-09_final
2023-09-09 11:21:44	ga_s2bm_ard_3-2-1_51LZD_2023-09-09_final
2023-09-09 11:21:51	ga_s2bm_ard_3-2-1_52LDH_2023-09-09_final
2023-09-09 11:21:54	ga_s2bm_ard_3-2-1_52LCH_2023-09-09_final
2023-09-09 11:21:57	ga_s2bm_ard_3-2-1_52LBH_2023-09-09_final
2023-09-09 11:21:58	ga_s2bm_ard_3-2-1_51LZC_2023-09-09_final
2023-09-09 11:22:03	ga_s2bm_ard_3-2-1_51LYC_2023-09-09_final
2023-09-09 11:22:04	ga_s2bm_ard_3-2-1_52KDG_2023-09-09_final
2023-09-09 11:22:09	ga_s2bm_ard_3-2-1_52KCG_2023-09-09_final
2023-09-09 11:25:57	ga_s2bm_ard_3-2-1_51JXG_2023-09-09_final
2023-09-09 11:26:04	ga_s2bm_ard_3-2-1_51JVG_2023-09-09_final
2023-09-09 11:26:09	ga_s2bm_ard_3-2-1_51JUG_2023-09-09_final
2023-09-09 11:26:11	ga_s2bm_ard_3-2-1_51JXF_2023-09-09_final
2023-09-09 11:26:19	ga_s2bm_ard_3-2-1_51JVF_2023-09-09_final
2023-09-09 11:26:22	ga_s2bm_ard_3-2-1_51JUF_2023-09-09_final
2023-09-09 11:26:26	ga_s2bm_ard_3-2-1_51HXE_2023-09-09_final
2023-09-09 11:26:30	ga_s2bm_ard_3-2-1_51HWE_2023-09-09_final
2023-09-09 11:26:33	ga_s2bm_ard_3-2-1_51HVE_2023-09-09_final
2023-09-09 11:26:40	ga_s2bm_ard_3-2-1_51HXD_2023-09-09_final
2023-09-09 11:26:44	ga_s2bm_ard_3-2-1_51HWD_2023-09-09_final
2023-09-09 11:26:48	ga_s2bm_ard_3-2-1_51HVD_2023-09-09_final
2023-09-09 11:26:51	ga_s2bm_ard_3-2-1_51HXC_2023-09-09_final
2023-09-09 11:26:58	ga_s2bm_ard_3-2-1_51HWC_2023-09-09_final
2023-09-09 11:27:02	ga_s2bm_ard_3-2-1_51HVC_2023-09-09_final
2023-09-09 11:27:11	ga_s2bm_ard_3-2-1_51HWB_2023-09-09_final
2023-09-09 11:27:11	ga_s2bm_ard_3-2-1_51HTC_2023-09-09_final

Return to ga_s2bm_ard_3 on 9th September 2023 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

2023

September

9th