Search ga_s2bm_ard_3 across October 2022

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 s2cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s2cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s2cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s2cloudless 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
2022-10-14 11:26:21	ga_s2bm_ard_3-2-1_51HXE_2022-10-14_final
2022-10-14 11:26:25	ga_s2bm_ard_3-2-1_51HWE_2022-10-14_final
2022-10-14 11:26:28	ga_s2bm_ard_3-2-1_51HVE_2022-10-14_final
2022-10-14 11:26:31	ga_s2bm_ard_3-2-1_51HUE_2022-10-14_final
2022-10-14 11:26:35	ga_s2bm_ard_3-2-1_51HXD_2022-10-14_final
2022-10-14 11:26:39	ga_s2bm_ard_3-2-1_51HWD_2022-10-14_final
2022-10-14 11:26:43	ga_s2bm_ard_3-2-1_51HVD_2022-10-14_final
2022-10-14 11:26:46	ga_s2bm_ard_3-2-1_51HUD_2022-10-14_final
2022-10-14 11:26:46	ga_s2bm_ard_3-2-1_51HXC_2022-10-14_final
2022-10-14 11:26:53	ga_s2bm_ard_3-2-1_51HWC_2022-10-14_final
2022-10-14 11:26:57	ga_s2bm_ard_3-2-1_51HVC_2022-10-14_final
2022-10-14 11:27:01	ga_s2bm_ard_3-2-1_51HUC_2022-10-14_final
2022-10-14 11:27:06	ga_s2bm_ard_3-2-1_51HTC_2022-10-14_final
2022-10-14 11:27:07	ga_s2bm_ard_3-2-1_51HWB_2022-10-14_final
2022-10-14 11:27:09	ga_s2bm_ard_3-2-1_51HVB_2022-10-14_final
2022-10-14 11:27:11	ga_s2bm_ard_3-2-1_51HUB_2022-10-14_final
2022-10-14 11:27:13	ga_s2bm_ard_3-2-1_51HTB_2022-10-14_final
2022-10-15 09:14:36	ga_s2bm_ard_3-2-1_57JVH_2022-10-14_interim
2022-10-15 10:50:19	ga_s2bm_ard_3-2-1_53LPH_2022-10-15_final
2022-10-15 10:50:23	ga_s2bm_ard_3-2-1_53LNH_2022-10-15_final
2022-10-15 10:50:26	ga_s2bm_ard_3-2-1_53LMH_2022-10-15_final
2022-10-15 10:50:27	ga_s2bm_ard_3-2-1_53LQG_2022-10-15_final
2022-10-15 10:50:34	ga_s2bm_ard_3-2-1_53LPG_2022-10-15_final
2022-10-15 10:50:37	ga_s2bm_ard_3-2-1_53LNG_2022-10-15_final
2022-10-15 10:50:41	ga_s2bm_ard_3-2-1_53LMG_2022-10-15_final
2022-10-15 10:50:47	ga_s2bm_ard_3-2-1_53LLG_2022-10-15_final
2022-10-15 10:50:48	ga_s2bm_ard_3-2-1_53LPF_2022-10-15_final
2022-10-15 10:50:52	ga_s2bm_ard_3-2-1_53LNF_2022-10-15_final
2022-10-15 10:50:55	ga_s2bm_ard_3-2-1_53LMF_2022-10-15_final
2022-10-15 10:50:59	ga_s2bm_ard_3-2-1_53LLF_2022-10-15_final
2022-10-15 10:51:03	ga_s2bm_ard_3-2-1_53LPE_2022-10-15_final
2022-10-15 10:51:06	ga_s2bm_ard_3-2-1_53LNE_2022-10-15_final
2022-10-15 10:51:10	ga_s2bm_ard_3-2-1_53LME_2022-10-15_final
2022-10-15 10:51:13	ga_s2bm_ard_3-2-1_53LLE_2022-10-15_final
2022-10-15 10:51:17	ga_s2bm_ard_3-2-1_53LPD_2022-10-15_final
2022-10-15 10:51:21	ga_s2bm_ard_3-2-1_53LND_2022-10-15_final
2022-10-15 10:51:24	ga_s2bm_ard_3-2-1_53LMD_2022-10-15_final
2022-10-15 10:51:27	ga_s2bm_ard_3-2-1_53LLD_2022-10-15_final
2022-10-15 10:51:29	ga_s2bm_ard_3-2-1_53LPC_2022-10-15_final
2022-10-15 10:51:32	ga_s2bm_ard_3-2-1_53LNC_2022-10-15_final
2022-10-15 10:51:33	ga_s2bm_ard_3-2-1_53LMC_2022-10-15_final
2022-10-15 10:51:34	ga_s2bm_ard_3-2-1_53LLD_2022-10-15_final
2022-10-15 10:51:35	ga_s2bm_ard_3-2-1_53LLC_2022-10-15_final
2022-10-15 10:51:35	ga_s2bm_ard_3-2-1_53LPC_2022-10-15_final
2022-10-15 10:51:38	ga_s2bm_ard_3-2-1_53LNC_2022-10-15_final
2022-10-15 10:51:40	ga_s2bm_ard_3-2-1_53LMC_2022-10-15_final
2022-10-15 10:51:40	ga_s2bm_ard_3-2-1_53KPB_2022-10-15_final
2022-10-15 10:51:42	ga_s2bm_ard_3-2-1_53LLC_2022-10-15_final
2022-10-15 10:51:50	ga_s2bm_ard_3-2-1_53KNB_2022-10-15_final
2022-10-15 10:51:53	ga_s2bm_ard_3-2-1_53KMB_2022-10-15_final
2022-10-15 10:51:57	ga_s2bm_ard_3-2-1_53KLB_2022-10-15_final
2022-10-15 10:52:01	ga_s2bm_ard_3-2-1_53KKB_2022-10-15_final
2022-10-15 10:52:04	ga_s2bm_ard_3-2-1_53KNA_2022-10-15_final
2022-10-15 10:52:08	ga_s2bm_ard_3-2-1_53KMA_2022-10-15_final
2022-10-15 10:52:11	ga_s2bm_ard_3-2-1_53KLA_2022-10-15_final
2022-10-15 10:52:14	ga_s2bm_ard_3-2-1_53KKA_2022-10-15_final
2022-10-15 10:52:19	ga_s2bm_ard_3-2-1_52KHF_2022-10-15_final
2022-10-15 10:52:19	ga_s2bm_ard_3-2-1_53KNV_2022-10-15_final
2022-10-15 10:52:22	ga_s2bm_ard_3-2-1_53KMV_2022-10-15_final
2022-10-15 10:52:26	ga_s2bm_ard_3-2-1_53KLV_2022-10-15_final
2022-10-15 10:52:29	ga_s2bm_ard_3-2-1_53KKV_2022-10-15_final
2022-10-15 10:52:30	ga_s2bm_ard_3-2-1_52KHE_2022-10-15_final
2022-10-15 10:52:33	ga_s2bm_ard_3-2-1_53KNU_2022-10-15_final
2022-10-15 10:52:37	ga_s2bm_ard_3-2-1_53KMU_2022-10-15_final
2022-10-15 10:52:40	ga_s2bm_ard_3-2-1_53KLU_2022-10-15_final
2022-10-15 10:52:43	ga_s2bm_ard_3-2-1_53KKU_2022-10-15_final
2022-10-15 10:52:44	ga_s2bm_ard_3-2-1_52KHD_2022-10-15_final
2022-10-15 10:52:44	ga_s2bm_ard_3-2-1_53KNT_2022-10-15_final
2022-10-15 10:52:51	ga_s2bm_ard_3-2-1_53KMT_2022-10-15_final
2022-10-15 10:52:55	ga_s2bm_ard_3-2-1_53KLT_2022-10-15_final
2022-10-15 10:52:58	ga_s2bm_ard_3-2-1_53KKT_2022-10-15_final
2022-10-15 10:52:59	ga_s2bm_ard_3-2-1_52KHC_2022-10-15_final
2022-10-15 10:53:06	ga_s2bm_ard_3-2-1_53KMS_2022-10-15_final
2022-10-15 10:53:09	ga_s2bm_ard_3-2-1_53KLS_2022-10-15_final
2022-10-15 10:53:12	ga_s2bm_ard_3-2-1_53KKS_2022-10-15_final
2022-10-15 10:53:13	ga_s2bm_ard_3-2-1_52KHB_2022-10-15_final
2022-10-15 10:53:19	ga_s2bm_ard_3-2-1_52KGB_2022-10-15_final
2022-10-15 10:53:21	ga_s2bm_ard_3-2-1_53KMR_2022-10-15_final
2022-10-15 10:53:24	ga_s2bm_ard_3-2-1_53KLR_2022-10-15_final
2022-10-15 10:53:27	ga_s2bm_ard_3-2-1_53KKR_2022-10-15_final
2022-10-20 11:44:37	ga_s2bm_ard_3-2-1_50JPT_2022-10-20_final
2022-10-20 11:45:06	ga_s2bm_ard_3-2-1_50JPR_2022-10-20_final
2022-10-20 11:45:11	ga_s2bm_ard_3-2-1_50JNR_2022-10-20_final
2022-10-20 11:45:17	ga_s2bm_ard_3-2-1_50JQQ_2022-10-20_final
2022-10-20 11:45:21	ga_s2bm_ard_3-2-1_50JPQ_2022-10-20_final
2022-10-20 11:45:24	ga_s2bm_ard_3-2-1_50JNQ_2022-10-20_final
2022-10-20 11:45:39	ga_s2bm_ard_3-2-1_50JNP_2022-10-20_final
2022-10-20 11:45:50	ga_s2bm_ard_3-2-1_50JPN_2022-10-20_final
2022-10-20 11:45:53	ga_s2bm_ard_3-2-1_50JNN_2022-10-20_final
2022-10-20 11:46:04	ga_s2bm_ard_3-2-1_50JPM_2022-10-20_final
2022-10-20 11:46:08	ga_s2bm_ard_3-2-1_50JNM_2022-10-20_final
2022-10-20 11:46:12	ga_s2bm_ard_3-2-1_50JMM_2022-10-20_final
2022-10-20 11:46:15	ga_s2bm_ard_3-2-1_50JQL_2022-10-20_final
2022-10-20 11:46:18	ga_s2bm_ard_3-2-1_50JPL_2022-10-20_final
2022-10-20 11:46:22	ga_s2bm_ard_3-2-1_50JNL_2022-10-20_final
2022-10-20 11:46:25	ga_s2bm_ard_3-2-1_50JML_2022-10-20_final
2022-10-20 11:46:29	ga_s2bm_ard_3-2-1_50HQK_2022-10-20_final
2022-10-20 11:46:33	ga_s2bm_ard_3-2-1_50HPK_2022-10-20_final
2022-10-20 11:46:37	ga_s2bm_ard_3-2-1_50HNK_2022-10-20_final
2022-10-20 11:46:40	ga_s2bm_ard_3-2-1_50HMK_2022-10-20_final

Return to ga_s2bm_ard_3 across October 2022 overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

GA Collection 3

USGS Products

Collection 2 NBAR

Collection 2 NBAR Tiled

Pixel Quality

Collection 2 Level1

Tidal

Water Observations

Fractional Cover

Sentinel 2

Ingested Pixel Quality

Geomedians

TMAD

Telemetry data

Summary

Other Products

2022

October

All days