Search ga_s2bm_ard_3 on 14th February 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
2023-02-14 09:49:35	ga_s2bm_ard_3-2-1_56LMP_2023-02-14_nrt.stac-item
2023-02-14 09:49:39	ga_s2bm_ard_3-2-1_56LLP_2023-02-14_nrt.stac-item
2023-02-14 09:49:42	ga_s2bm_ard_3-2-1_56LKP_2023-02-14_nrt.stac-item
2023-02-14 09:49:43	ga_s2bm_ard_3-2-1_55LHJ_2023-02-14_nrt.stac-item
2023-02-14 09:49:47	ga_s2bm_ard_3-2-1_56LMN_2023-02-14_nrt.stac-item
2023-02-14 09:49:48	ga_s2bm_ard_3-2-1_55LGJ_2023-02-14_nrt.stac-item
2023-02-14 09:49:53	ga_s2bm_ard_3-2-1_56LLN_2023-02-14_nrt.stac-item
2023-02-14 09:49:56	ga_s2bm_ard_3-2-1_56LKN_2023-02-14_nrt.stac-item
2023-02-14 09:49:57	ga_s2bm_ard_3-2-1_55LHH_2023-02-14_nrt.stac-item
2023-02-14 09:49:57	ga_s2bm_ard_3-2-1_56LMM_2023-02-14_nrt.stac-item
2023-02-14 09:49:59	ga_s2bm_ard_3-2-1_55LGH_2023-02-14_nrt.stac-item
2023-02-14 09:50:02	ga_s2bm_ard_3-2-1_56LLM_2023-02-14_nrt.stac-item
2023-02-14 09:50:03	ga_s2bm_ard_3-2-1_56LKM_2023-02-14_nrt.stac-item
2023-02-14 09:50:04	ga_s2bm_ard_3-2-1_55LHG_2023-02-14_nrt.stac-item
2023-02-14 09:50:58	ga_s2bm_ard_3-2-1_56LLJ_2023-02-14_nrt.stac-item
2023-02-14 09:51:00	ga_s2bm_ard_3-2-1_56LKJ_2023-02-14_nrt.stac-item
2023-02-14 09:51:00	ga_s2bm_ard_3-2-1_55LHD_2023-02-14_nrt.stac-item
2023-02-14 09:51:02	ga_s2bm_ard_3-2-1_55LGD_2023-02-14_nrt.stac-item
2023-02-14 09:51:02	ga_s2bm_ard_3-2-1_56LLH_2023-02-14_nrt.stac-item
2023-02-14 09:51:04	ga_s2bm_ard_3-2-1_55LFD_2023-02-14_nrt.stac-item
2023-02-14 09:51:09	ga_s2bm_ard_3-2-1_56LKH_2023-02-14_nrt.stac-item
2023-02-14 09:51:14	ga_s2bm_ard_3-2-1_55LGC_2023-02-14_final
2023-02-14 09:51:17	ga_s2bm_ard_3-2-1_55LFC_2023-02-14_final
2023-02-14 09:51:28	ga_s2bm_ard_3-2-1_55KGB_2023-02-14_final
2023-02-14 09:51:32	ga_s2bm_ard_3-2-1_55KFB_2023-02-14_final
2023-02-14 09:51:38	ga_s2bm_ard_3-2-1_56KKF_2023-02-14_final
2023-02-14 09:51:39	ga_s2bm_ard_3-2-1_55KHA_2023-02-14_nrt.stac-item
2023-02-14 09:51:43	ga_s2bm_ard_3-2-1_55KGA_2023-02-14_nrt.stac-item
2023-02-14 09:51:46	ga_s2bm_ard_3-2-1_55KFA_2023-02-14_final
2023-02-14 09:51:52	ga_s2bm_ard_3-2-1_55KEA_2023-02-14_nrt.stac-item
2023-02-14 09:51:53	ga_s2bm_ard_3-2-1_56KKE_2023-02-14_nrt.stac-item
2023-02-14 09:51:53	ga_s2bm_ard_3-2-1_55KHV_2023-02-14_nrt.stac-item
2023-02-14 09:51:57	ga_s2bm_ard_3-2-1_55KGV_2023-02-14_nrt.stac-item
2023-02-14 09:52:01	ga_s2bm_ard_3-2-1_55KFV_2023-02-14_nrt.stac-item
2023-02-14 09:52:04	ga_s2bm_ard_3-2-1_55KEV_2023-02-14_final
2023-02-14 09:52:06	ga_s2bm_ard_3-2-1_56KKD_2023-02-14_nrt.stac-item
2023-02-14 09:52:08	ga_s2bm_ard_3-2-1_55KHU_2023-02-14_nrt.stac-item
2023-02-14 09:52:12	ga_s2bm_ard_3-2-1_55KGU_2023-02-14_final
2023-02-14 09:52:15	ga_s2bm_ard_3-2-1_55KFU_2023-02-14_final
2023-02-14 09:52:18	ga_s2bm_ard_3-2-1_56KKC_2023-02-14_nrt.stac-item
2023-02-14 09:52:18	ga_s2bm_ard_3-2-1_55KEU_2023-02-14_final
2023-02-14 09:52:22	ga_s2bm_ard_3-2-1_55KHT_2023-02-14_nrt.stac-item
2023-02-14 09:52:26	ga_s2bm_ard_3-2-1_55KGT_2023-02-14_final
2023-02-14 09:52:30	ga_s2bm_ard_3-2-1_55KFT_2023-02-14_final
2023-02-14 09:52:33	ga_s2bm_ard_3-2-1_55KET_2023-02-14_final
2023-02-14 09:52:34	ga_s2bm_ard_3-2-1_55KHS_2023-02-14_final
2023-02-14 09:52:40	ga_s2bm_ard_3-2-1_55KGS_2023-02-14_nrt.stac-item
2023-02-14 09:52:40	ga_s2bm_ard_3-2-1_55KGS_2023-02-14_final
2023-02-14 09:52:44	ga_s2bm_ard_3-2-1_55KFS_2023-02-14_final
2023-02-14 09:52:48	ga_s2bm_ard_3-2-1_55KES_2023-02-14_final
2023-02-14 09:52:54	ga_s2bm_ard_3-2-1_55KDS_2023-02-14_final
2023-02-14 09:52:55	ga_s2bm_ard_3-2-1_55KGR_2023-02-14_final
2023-02-14 09:55:23	ga_s2bm_ard_3-2-1_55JBG_2023-02-14_final
2023-02-14 09:55:53	ga_s2bm_ard_3-2-1_55HED_2023-02-14_final
2023-02-14 09:56:00	ga_s2bm_ard_3-2-1_55HDD_2023-02-14_final
2023-02-14 09:56:18	ga_s2bm_ard_3-2-1_55HCC_2023-02-14_final
2023-02-14 09:56:43	ga_s2bm_ard_3-2-1_55HDA_2023-02-14_final
2023-02-14 09:57:05	ga_s2bm_ard_3-2-1_55HBV_2023-02-14_final
2023-02-14 11:35:14	ga_s2bm_ard_3-2-1_51JUK_2023-02-14_final
2023-02-14 11:35:17	ga_s2bm_ard_3-2-1_51JTK_2023-02-14_final
2023-02-14 11:35:18	ga_s2bm_ard_3-2-1_51JWJ_2023-02-14_final
2023-02-14 11:35:25	ga_s2bm_ard_3-2-1_51JVJ_2023-02-14_final
2023-02-14 11:35:29	ga_s2bm_ard_3-2-1_51JUJ_2023-02-14_final
2023-02-14 11:35:32	ga_s2bm_ard_3-2-1_51JTJ_2023-02-14_final
2023-02-14 11:35:35	ga_s2bm_ard_3-2-1_50JQP_2023-02-14_final
2023-02-14 11:35:39	ga_s2bm_ard_3-2-1_51JVH_2023-02-14_final
2023-02-14 11:35:43	ga_s2bm_ard_3-2-1_51JUH_2023-02-14_final
2023-02-14 11:35:46	ga_s2bm_ard_3-2-1_51JTH_2023-02-14_final
2023-02-14 11:35:49	ga_s2bm_ard_3-2-1_50JQN_2023-02-14_final
2023-02-14 11:35:54	ga_s2bm_ard_3-2-1_51JVG_2023-02-14_final
2023-02-14 11:35:58	ga_s2bm_ard_3-2-1_51JUG_2023-02-14_final
2023-02-14 11:36:01	ga_s2bm_ard_3-2-1_51JTG_2023-02-14_final
2023-02-14 11:36:03	ga_s2bm_ard_3-2-1_50JQM_2023-02-14_final
2023-02-14 11:36:09	ga_s2bm_ard_3-2-1_51JVF_2023-02-14_final
2023-02-14 11:36:12	ga_s2bm_ard_3-2-1_51JUF_2023-02-14_final
2023-02-14 11:36:16	ga_s2bm_ard_3-2-1_51JTF_2023-02-14_final
2023-02-14 11:36:18	ga_s2bm_ard_3-2-1_50JQL_2023-02-14_final
2023-02-14 11:36:22	ga_s2bm_ard_3-2-1_51HVE_2023-02-14_final
2023-02-14 11:36:25	ga_s2bm_ard_3-2-1_50JPL_2023-02-14_final
2023-02-14 11:36:27	ga_s2bm_ard_3-2-1_51HUE_2023-02-14_final
2023-02-14 11:36:30	ga_s2bm_ard_3-2-1_51HTE_2023-02-14_final
2023-02-14 11:36:32	ga_s2bm_ard_3-2-1_51HVD_2023-02-14_final
2023-02-14 11:36:32	ga_s2bm_ard_3-2-1_50HQK_2023-02-14_final
2023-02-14 11:36:36	ga_s2bm_ard_3-2-1_50HPK_2023-02-14_final
2023-02-14 11:36:41	ga_s2bm_ard_3-2-1_51HUD_2023-02-14_final
2023-02-14 11:36:45	ga_s2bm_ard_3-2-1_51HTD_2023-02-14_final
2023-02-14 11:36:47	ga_s2bm_ard_3-2-1_50HQJ_2023-02-14_final
2023-02-14 11:36:50	ga_s2bm_ard_3-2-1_50HPJ_2023-02-14_final
2023-02-14 11:36:56	ga_s2bm_ard_3-2-1_51HUC_2023-02-14_final
2023-02-14 11:36:59	ga_s2bm_ard_3-2-1_51HTC_2023-02-14_final
2023-02-14 11:37:01	ga_s2bm_ard_3-2-1_50HQH_2023-02-14_final
2023-02-14 11:37:05	ga_s2bm_ard_3-2-1_50HPH_2023-02-14_final
2023-02-14 11:37:16	ga_s2bm_ard_3-2-1_50HQG_2023-02-14_final
2023-02-14 11:37:19	ga_s2bm_ard_3-2-1_50HPG_2023-02-14_final
2023-02-14 11:37:24	ga_s2bm_ard_3-2-1_51HUA_2023-02-14_nrt.stac-item
2023-02-14 11:37:25	ga_s2bm_ard_3-2-1_50HNG_2023-02-14_final
2023-02-14 11:37:27	ga_s2bm_ard_3-2-1_51HTA_2023-02-14_nrt.stac-item
2023-02-14 11:37:28	ga_s2bm_ard_3-2-1_50HQF_2023-02-14_nrt.stac-item
2023-02-14 11:37:29	ga_s2bm_ard_3-2-1_50HPF_2023-02-14_nrt.stac-item
2023-02-14 11:37:31	ga_s2bm_ard_3-2-1_50HNF_2023-02-14_nrt.stac-item

Return to ga_s2bm_ard_3 on 14th February 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

February

14th