Search ga_s2bm_ard_3 on 22nd 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
2023-02-22 09:14:43	ga_s2bm_ard_3-2-1_56JPP_2023-02-21_nrt.stac-item
2023-02-22 09:14:53	ga_s2bm_ard_3-2-1_56JPN_2023-02-21_nrt.stac-item
2023-02-22 09:15:07	ga_s2bm_ard_3-2-1_56JPM_2023-02-21_nrt.stac-item
2023-02-22 09:15:22	ga_s2bm_ard_3-2-1_56JPL_2023-02-21_nrt.stac-item
2023-02-22 09:15:29	ga_s2bm_ard_3-2-1_56HPK_2023-02-21_nrt.stac-item
2023-02-22 10:50:02	ga_s2bm_ard_3-2-1_53LQJ_2023-02-22_nrt.stac-item
2023-02-22 10:50:06	ga_s2bm_ard_3-2-1_53LPJ_2023-02-22_nrt.stac-item
2023-02-22 10:50:09	ga_s2bm_ard_3-2-1_53LNJ_2023-02-22_nrt.stac-item
2023-02-22 10:50:12	ga_s2bm_ard_3-2-1_53LMJ_2023-02-22_nrt.stac-item
2023-02-22 10:50:16	ga_s2bm_ard_3-2-1_53LQH_2023-02-22_nrt.stac-item
2023-02-22 10:50:27	ga_s2bm_ard_3-2-1_53LQG_2023-02-22_final
2023-02-22 10:50:34	ga_s2bm_ard_3-2-1_53LPG_2023-02-22_final
2023-02-22 10:50:38	ga_s2bm_ard_3-2-1_53LNG_2023-02-22_final
2023-02-22 10:50:41	ga_s2bm_ard_3-2-1_53LMG_2023-02-22_final
2023-02-22 10:50:47	ga_s2bm_ard_3-2-1_53LLG_2023-02-22_final
2023-02-22 10:50:49	ga_s2bm_ard_3-2-1_53LPF_2023-02-22_final
2023-02-22 10:50:53	ga_s2bm_ard_3-2-1_53LNF_2023-02-22_final
2023-02-22 10:50:56	ga_s2bm_ard_3-2-1_53LMF_2023-02-22_final
2023-02-22 10:50:59	ga_s2bm_ard_3-2-1_53LLF_2023-02-22_final
2023-02-22 10:51:04	ga_s2bm_ard_3-2-1_53LPE_2023-02-22_nrt.stac-item
2023-02-22 10:51:04	ga_s2bm_ard_3-2-1_53LPE_2023-02-22_final
2023-02-22 10:51:07	ga_s2bm_ard_3-2-1_53LNE_2023-02-22_nrt.stac-item
2023-02-22 10:51:07	ga_s2bm_ard_3-2-1_53LNE_2023-02-22_final
2023-02-22 10:51:10	ga_s2bm_ard_3-2-1_53LME_2023-02-22_final
2023-02-22 10:51:13	ga_s2bm_ard_3-2-1_53LLE_2023-02-22_final
2023-02-22 10:51:18	ga_s2bm_ard_3-2-1_53LPD_2023-02-22_final
2023-02-22 10:51:22	ga_s2bm_ard_3-2-1_53LND_2023-02-22_final
2023-02-22 10:51:25	ga_s2bm_ard_3-2-1_53LMD_2023-02-22_final
2023-02-22 10:51:28	ga_s2bm_ard_3-2-1_53LLD_2023-02-22_final
2023-02-22 10:51:30	ga_s2bm_ard_3-2-1_53LPC_2023-02-22_final
2023-02-22 10:51:32	ga_s2bm_ard_3-2-1_53LNC_2023-02-22_final
2023-02-22 10:51:34	ga_s2bm_ard_3-2-1_53LMC_2023-02-22_final
2023-02-22 10:51:35	ga_s2bm_ard_3-2-1_53LLD_2023-02-22_final
2023-02-22 10:51:36	ga_s2bm_ard_3-2-1_53LLC_2023-02-22_final
2023-02-22 10:51:36	ga_s2bm_ard_3-2-1_53LPC_2023-02-22_final
2023-02-22 10:51:39	ga_s2bm_ard_3-2-1_53LNC_2023-02-22_final
2023-02-22 10:51:41	ga_s2bm_ard_3-2-1_53KPB_2023-02-22_final
2023-02-22 10:51:41	ga_s2bm_ard_3-2-1_53LMC_2023-02-22_final
2023-02-22 10:51:43	ga_s2bm_ard_3-2-1_53LLC_2023-02-22_final
2023-02-22 10:51:50	ga_s2bm_ard_3-2-1_53KNB_2023-02-22_final
2023-02-22 10:51:54	ga_s2bm_ard_3-2-1_53KMB_2023-02-22_final
2023-02-22 10:51:57	ga_s2bm_ard_3-2-1_53KLB_2023-02-22_final
2023-02-22 10:52:01	ga_s2bm_ard_3-2-1_53KKB_2023-02-22_final
2023-02-22 10:52:05	ga_s2bm_ard_3-2-1_53KNA_2023-02-22_final
2023-02-22 10:52:08	ga_s2bm_ard_3-2-1_53KMA_2023-02-22_final
2023-02-22 10:52:12	ga_s2bm_ard_3-2-1_53KLA_2023-02-22_final
2023-02-22 10:52:15	ga_s2bm_ard_3-2-1_53KKA_2023-02-22_final
2023-02-22 10:52:19	ga_s2bm_ard_3-2-1_52KHF_2023-02-22_final
2023-02-22 10:52:20	ga_s2bm_ard_3-2-1_53KNV_2023-02-22_final
2023-02-22 10:52:23	ga_s2bm_ard_3-2-1_53KMV_2023-02-22_final
2023-02-22 10:52:26	ga_s2bm_ard_3-2-1_53KLV_2023-02-22_final
2023-02-22 10:52:29	ga_s2bm_ard_3-2-1_53KKV_2023-02-22_final
2023-02-22 10:52:31	ga_s2bm_ard_3-2-1_52KHE_2023-02-22_final
2023-02-22 10:52:33	ga_s2bm_ard_3-2-1_53KNU_2023-02-22_final
2023-02-22 10:52:38	ga_s2bm_ard_3-2-1_53KMU_2023-02-22_final
2023-02-22 10:52:41	ga_s2bm_ard_3-2-1_53KLU_2023-02-22_final
2023-02-22 10:52:44	ga_s2bm_ard_3-2-1_53KKU_2023-02-22_final
2023-02-22 10:52:44	ga_s2bm_ard_3-2-1_52KHD_2023-02-22_final
2023-02-22 10:52:45	ga_s2bm_ard_3-2-1_53KNT_2023-02-22_final
2023-02-22 10:52:52	ga_s2bm_ard_3-2-1_53KMT_2023-02-22_final
2023-02-22 10:52:55	ga_s2bm_ard_3-2-1_53KLT_2023-02-22_final
2023-02-22 10:52:59	ga_s2bm_ard_3-2-1_53KKT_2023-02-22_final
2023-02-22 10:52:59	ga_s2bm_ard_3-2-1_52KHC_2023-02-22_final
2023-02-22 10:53:06	ga_s2bm_ard_3-2-1_53KMS_2023-02-22_final
2023-02-22 10:53:10	ga_s2bm_ard_3-2-1_53KLS_2023-02-22_final
2023-02-22 10:53:13	ga_s2bm_ard_3-2-1_53KKS_2023-02-22_final
2023-02-22 10:53:14	ga_s2bm_ard_3-2-1_52KHB_2023-02-22_final
2023-02-22 10:53:20	ga_s2bm_ard_3-2-1_52KGB_2023-02-22_final
2023-02-22 10:53:21	ga_s2bm_ard_3-2-1_53KMR_2023-02-22_final
2023-02-22 10:53:25	ga_s2bm_ard_3-2-1_53KLR_2023-02-22_nrt.stac-item
2023-02-22 10:53:25	ga_s2bm_ard_3-2-1_53KLR_2023-02-22_final
2023-02-22 10:53:28	ga_s2bm_ard_3-2-1_53KKR_2023-02-22_final
2023-02-22 10:53:28	ga_s2bm_ard_3-2-1_52KHA_2023-02-22_final
2023-02-22 10:53:32	ga_s2bm_ard_3-2-1_52KGA_2023-02-22_final
2023-02-22 10:53:36	ga_s2bm_ard_3-2-1_53KMQ_2023-02-22_final
2023-02-22 10:53:39	ga_s2bm_ard_3-2-1_53KLQ_2023-02-22_final
2023-02-22 10:53:42	ga_s2bm_ard_3-2-1_53KKQ_2023-02-22_final
2023-02-22 10:53:42	ga_s2bm_ard_3-2-1_52KHV_2023-02-22_final
2023-02-22 10:53:46	ga_s2bm_ard_3-2-1_52KGV_2023-02-22_final
2023-02-22 10:53:49	ga_s2bm_ard_3-2-1_53KMP_2023-02-22_final
2023-02-22 10:53:54	ga_s2bm_ard_3-2-1_53KLP_2023-02-22_final
2023-02-22 10:53:57	ga_s2bm_ard_3-2-1_53KKP_2023-02-22_final
2023-02-22 10:53:57	ga_s2bm_ard_3-2-1_52KHU_2023-02-22_final
2023-02-22 10:53:59	ga_s2bm_ard_3-2-1_53JMN_2023-02-22_final
2023-02-22 10:54:01	ga_s2bm_ard_3-2-1_52KGU_2023-02-22_nrt.stac-item
2023-02-22 10:54:01	ga_s2bm_ard_3-2-1_52KGU_2023-02-22_final
2023-02-22 10:54:08	ga_s2bm_ard_3-2-1_53JLN_2023-02-22_final
2023-02-22 10:54:10	ga_s2bm_ard_3-2-1_52JHT_2023-02-22_final
2023-02-22 10:54:10	ga_s2bm_ard_3-2-1_53JKN_2023-02-22_final
2023-02-22 10:54:15	ga_s2bm_ard_3-2-1_53JLM_2023-02-22_final
2023-02-22 10:54:15	ga_s2bm_ard_3-2-1_53JLN_2023-02-22_final
2023-02-22 10:54:26	ga_s2bm_ard_3-2-1_53JKM_2023-02-22_final
2023-02-22 10:54:37	ga_s2bm_ard_3-2-1_53JLL_2023-02-22_final
2023-02-22 10:54:41	ga_s2bm_ard_3-2-1_53JKL_2023-02-22_final
2023-02-22 10:54:47	ga_s2bm_ard_3-2-1_52JFR_2023-02-22_final
2023-02-22 10:54:55	ga_s2bm_ard_3-2-1_53JKK_2023-02-22_final
2023-02-22 10:55:05	ga_s2bm_ard_3-2-1_53JLJ_2023-02-22_final
2023-02-22 10:55:10	ga_s2bm_ard_3-2-1_53JKJ_2023-02-22_final
2023-02-22 10:55:15	ga_s2bm_ard_3-2-1_53JLH_2023-02-22_final
2023-02-22 10:55:24	ga_s2bm_ard_3-2-1_53JKH_2023-02-22_final

Return to ga_s2bm_ard_3 on 22nd 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

22nd