Search ga_s2bm_ard_3 on 15th 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
2023-02-15 09:22:51	ga_s2bm_ard_3-2-1_56KPA_2023-02-14_nrt.stac-item
2023-02-15 09:23:06	ga_s2bm_ard_3-2-1_56KPV_2023-02-14_nrt.stac-item
2023-02-15 09:23:20	ga_s2bm_ard_3-2-1_56KPU_2023-02-14_nrt.stac-item
2023-02-15 09:23:25	ga_s2bm_ard_3-2-1_56KNU_2023-02-14_nrt.stac-item
2023-02-15 09:23:35	ga_s2bm_ard_3-2-1_56JPT_2023-02-14_nrt.stac-item
2023-02-15 09:23:38	ga_s2bm_ard_3-2-1_56JNT_2023-02-14_final
2023-02-15 09:23:49	ga_s2bm_ard_3-2-1_56JPS_2023-02-14_nrt.stac-item
2023-02-15 09:23:53	ga_s2bm_ard_3-2-1_56JNS_2023-02-14_final
2023-02-15 09:24:04	ga_s2bm_ard_3-2-1_56JPR_2023-02-14_nrt.stac-item
2023-02-15 09:24:07	ga_s2bm_ard_3-2-1_56JNR_2023-02-14_final
2023-02-15 09:24:18	ga_s2bm_ard_3-2-1_56JPQ_2023-02-14_nrt.stac-item
2023-02-15 09:24:22	ga_s2bm_ard_3-2-1_56JNQ_2023-02-14_final
2023-02-15 09:24:26	ga_s2bm_ard_3-2-1_56JMQ_2023-02-14_final
2023-02-15 09:24:33	ga_s2bm_ard_3-2-1_56JPP_2023-02-14_nrt.stac-item
2023-02-15 09:24:36	ga_s2bm_ard_3-2-1_56JNP_2023-02-14_final
2023-02-15 09:24:39	ga_s2bm_ard_3-2-1_56JMP_2023-02-14_final
2023-02-15 09:24:47	ga_s2bm_ard_3-2-1_56JPN_2023-02-14_nrt.stac-item
2023-02-15 09:24:51	ga_s2bm_ard_3-2-1_56JNN_2023-02-14_final
2023-02-15 09:24:54	ga_s2bm_ard_3-2-1_56JMN_2023-02-14_final
2023-02-15 09:25:02	ga_s2bm_ard_3-2-1_56JPM_2023-02-14_nrt.stac-item
2023-02-15 09:25:05	ga_s2bm_ard_3-2-1_56JNM_2023-02-14_final
2023-02-15 09:25:09	ga_s2bm_ard_3-2-1_56JMM_2023-02-14_nrt.stac-item
2023-02-15 09:25:09	ga_s2bm_ard_3-2-1_56JMM_2023-02-14_final
2023-02-15 09:25:16	ga_s2bm_ard_3-2-1_56JPL_2023-02-14_nrt.stac-item
2023-02-15 09:25:20	ga_s2bm_ard_3-2-1_56JNL_2023-02-14_final
2023-02-15 09:25:23	ga_s2bm_ard_3-2-1_56JML_2023-02-14_final
2023-02-15 09:25:28	ga_s2bm_ard_3-2-1_56JLL_2023-02-14_final
2023-02-15 09:25:30	ga_s2bm_ard_3-2-1_56HPK_2023-02-14_nrt.stac-item
2023-02-15 09:25:34	ga_s2bm_ard_3-2-1_56HNK_2023-02-14_nrt.stac-item
2023-02-15 09:25:38	ga_s2bm_ard_3-2-1_56HMK_2023-02-14_final
2023-02-15 09:25:41	ga_s2bm_ard_3-2-1_56HLK_2023-02-14_final
2023-02-15 09:25:45	ga_s2bm_ard_3-2-1_56HPJ_2023-02-14_nrt.stac-item
2023-02-15 09:25:49	ga_s2bm_ard_3-2-1_56HNJ_2023-02-14_nrt.stac-item
2023-02-15 09:25:52	ga_s2bm_ard_3-2-1_56HMJ_2023-02-14_final
2023-02-15 09:25:55	ga_s2bm_ard_3-2-1_56HLJ_2023-02-14_final
2023-02-15 09:25:59	ga_s2bm_ard_3-2-1_56HPH_2023-02-14_nrt.stac-item
2023-02-15 09:26:03	ga_s2bm_ard_3-2-1_56HNH_2023-02-14_nrt.stac-item
2023-02-15 09:26:07	ga_s2bm_ard_3-2-1_56HMH_2023-02-14_nrt.stac-item
2023-02-15 09:26:10	ga_s2bm_ard_3-2-1_56HPG_2023-02-14_nrt.stac-item
2023-02-15 09:26:10	ga_s2bm_ard_3-2-1_56HLH_2023-02-14_final
2023-02-15 09:26:17	ga_s2bm_ard_3-2-1_56HNG_2023-02-14_nrt.stac-item
2023-02-15 09:26:21	ga_s2bm_ard_3-2-1_56HMG_2023-02-14_nrt.stac-item
2023-02-15 09:26:25	ga_s2bm_ard_3-2-1_56HLG_2023-02-14_final
2023-02-15 09:26:30	ga_s2bm_ard_3-2-1_56HKG_2023-02-14_final
2023-02-15 09:26:32	ga_s2bm_ard_3-2-1_56HNF_2023-02-14_nrt.stac-item
2023-02-15 09:26:36	ga_s2bm_ard_3-2-1_56HMF_2023-02-14_nrt.stac-item
2023-02-15 09:26:39	ga_s2bm_ard_3-2-1_56HLF_2023-02-14_nrt.stac-item
2023-02-15 09:26:43	ga_s2bm_ard_3-2-1_56HKF_2023-02-14_final
2023-02-15 09:26:47	ga_s2bm_ard_3-2-1_56HNE_2023-02-14_nrt.stac-item
2023-02-15 09:26:50	ga_s2bm_ard_3-2-1_56HME_2023-02-14_nrt.stac-item
2023-02-15 09:26:54	ga_s2bm_ard_3-2-1_56HLE_2023-02-14_nrt.stac-item
2023-02-15 09:26:57	ga_s2bm_ard_3-2-1_56HKE_2023-02-14_nrt.stac-item
2023-02-15 09:26:59	ga_s2bm_ard_3-2-1_55HGV_2023-02-14_final
2023-02-15 09:27:01	ga_s2bm_ard_3-2-1_56HND_2023-02-14_nrt.stac-item
2023-02-15 09:27:05	ga_s2bm_ard_3-2-1_56HMD_2023-02-14_nrt.stac-item
2023-02-15 09:27:08	ga_s2bm_ard_3-2-1_56HLD_2023-02-14_nrt.stac-item
2023-02-15 11:02:38	ga_s2bm_ard_3-2-1_53KKU_2023-02-15_final
2023-02-15 11:02:38	ga_s2bm_ard_3-2-1_52KHD_2023-02-15_nrt.stac-item
2023-02-15 11:02:38	ga_s2bm_ard_3-2-1_52KHD_2023-02-15_final
2023-02-15 11:02:42	ga_s2bm_ard_3-2-1_52KGD_2023-02-15_final
2023-02-15 11:02:46	ga_s2bm_ard_3-2-1_52KFD_2023-02-15_final
2023-02-15 11:02:50	ga_s2bm_ard_3-2-1_52KED_2023-02-15_final
2023-02-15 11:02:52	ga_s2bm_ard_3-2-1_53KKT_2023-02-15_final
2023-02-15 11:02:53	ga_s2bm_ard_3-2-1_52KHC_2023-02-15_final
2023-02-15 11:02:57	ga_s2bm_ard_3-2-1_52KGC_2023-02-15_final
2023-02-15 11:03:00	ga_s2bm_ard_3-2-1_52KFC_2023-02-15_final
2023-02-15 11:03:03	ga_s2bm_ard_3-2-1_52KEC_2023-02-15_final
2023-02-15 11:03:05	ga_s2bm_ard_3-2-1_53KKS_2023-02-15_final
2023-02-15 11:03:07	ga_s2bm_ard_3-2-1_52KHB_2023-02-15_final
2023-02-15 11:03:09	ga_s2bm_ard_3-2-1_52KGB_2023-02-15_final
2023-02-15 11:03:11	ga_s2bm_ard_3-2-1_52KFB_2023-02-15_final
2023-02-15 11:03:12	ga_s2bm_ard_3-2-1_52KEB_2023-02-15_final
2023-02-15 11:03:13	ga_s2bm_ard_3-2-1_53KKS_2023-02-15_final
2023-02-15 11:03:14	ga_s2bm_ard_3-2-1_52KHB_2023-02-15_final
2023-02-15 11:03:15	ga_s2bm_ard_3-2-1_52KGB_2023-02-15_final
2023-02-15 11:03:17	ga_s2bm_ard_3-2-1_52KFB_2023-02-15_final
2023-02-15 11:03:17	ga_s2bm_ard_3-2-1_53KKR_2023-02-15_final
2023-02-15 11:03:19	ga_s2bm_ard_3-2-1_52KEB_2023-02-15_final
2023-02-15 11:03:21	ga_s2bm_ard_3-2-1_52KHA_2023-02-15_final
2023-02-15 11:03:26	ga_s2bm_ard_3-2-1_52KGA_2023-02-15_final
2023-02-15 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2023-02-15_final
2023-02-15 11:03:31	ga_s2bm_ard_3-2-1_52KHV_2023-02-15_final
2023-02-15 11:03:33	ga_s2bm_ard_3-2-1_52KEA_2023-02-15_final
2023-02-15 11:03:40	ga_s2bm_ard_3-2-1_52KGV_2023-02-15_final
2023-02-15 11:03:44	ga_s2bm_ard_3-2-1_52KFV_2023-02-15_final
2023-02-15 11:03:47	ga_s2bm_ard_3-2-1_52KEV_2023-02-15_final
2023-02-15 11:03:52	ga_s2bm_ard_3-2-1_52KDV_2023-02-15_final
2023-02-15 11:03:54	ga_s2bm_ard_3-2-1_52KGU_2023-02-15_final
2023-02-15 11:03:58	ga_s2bm_ard_3-2-1_52KFU_2023-02-15_final
2023-02-15 11:04:02	ga_s2bm_ard_3-2-1_52KEU_2023-02-15_final
2023-02-15 11:04:05	ga_s2bm_ard_3-2-1_52KDU_2023-02-15_final
2023-02-15 11:04:09	ga_s2bm_ard_3-2-1_52JGT_2023-02-15_final
2023-02-15 11:04:16	ga_s2bm_ard_3-2-1_52JET_2023-02-15_nrt.stac-item
2023-02-15 11:04:16	ga_s2bm_ard_3-2-1_52JET_2023-02-15_final
2023-02-15 11:04:19	ga_s2bm_ard_3-2-1_52JDT_2023-02-15_nrt.stac-item
2023-02-15 11:04:19	ga_s2bm_ard_3-2-1_52JDT_2023-02-15_final
2023-02-15 11:04:27	ga_s2bm_ard_3-2-1_52JFS_2023-02-15_nrt.stac-item
2023-02-15 11:04:27	ga_s2bm_ard_3-2-1_52JFS_2023-02-15_final
2023-02-15 11:04:31	ga_s2bm_ard_3-2-1_52JES_2023-02-15_final
2023-02-15 11:04:34	ga_s2bm_ard_3-2-1_52JGR_2023-02-15_final

Return to ga_s2bm_ard_3 on 15th 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

15th