Search ga_s2bm_ard_3 on 31st July 2019

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
2019-07-31 10:14:55	ga_s2bm_ard_3-2-1_54JYP_2019-07-31_final
2019-07-31 10:15:01	ga_s2bm_ard_3-2-1_54JXP_2019-07-31_final
2019-07-31 10:15:05	ga_s2bm_ard_3-2-1_54JWP_2019-07-31_final
2019-07-31 10:15:05	ga_s2bm_ard_3-2-1_54JYN_2019-07-31_final
2019-07-31 10:15:09	ga_s2bm_ard_3-2-1_54JVP_2019-07-31_final
2019-07-31 10:15:16	ga_s2bm_ard_3-2-1_54JUP_2019-07-31_final
2019-07-31 10:15:16	ga_s2bm_ard_3-2-1_54JXN_2019-07-31_final
2019-07-31 10:15:20	ga_s2bm_ard_3-2-1_54JWN_2019-07-31_final
2019-07-31 10:15:23	ga_s2bm_ard_3-2-1_54JVN_2019-07-31_final
2019-07-31 10:15:27	ga_s2bm_ard_3-2-1_54JUN_2019-07-31_final
2019-07-31 10:15:30	ga_s2bm_ard_3-2-1_54JXM_2019-07-31_final
2019-07-31 10:15:34	ga_s2bm_ard_3-2-1_54JWM_2019-07-31_final
2019-07-31 10:15:37	ga_s2bm_ard_3-2-1_54JVM_2019-07-31_final
2019-07-31 10:15:41	ga_s2bm_ard_3-2-1_54JUM_2019-07-31_final
2019-07-31 10:15:45	ga_s2bm_ard_3-2-1_54JXL_2019-07-31_final
2019-07-31 10:15:49	ga_s2bm_ard_3-2-1_54JWL_2019-07-31_final
2019-07-31 10:15:52	ga_s2bm_ard_3-2-1_54JVL_2019-07-31_final
2019-07-31 10:15:55	ga_s2bm_ard_3-2-1_54JUL_2019-07-31_final
2019-07-31 10:15:58	ga_s2bm_ard_3-2-1_54HXK_2019-07-31_final
2019-07-31 10:16:03	ga_s2bm_ard_3-2-1_54HWK_2019-07-31_final
2019-07-31 10:16:07	ga_s2bm_ard_3-2-1_54HVK_2019-07-31_final
2019-07-31 10:16:08	ga_s2bm_ard_3-2-1_54HXJ_2019-07-31_final
2019-07-31 10:16:10	ga_s2bm_ard_3-2-1_54HUK_2019-07-31_final
2019-07-31 10:16:17	ga_s2bm_ard_3-2-1_54HWJ_2019-07-31_final
2019-07-31 10:16:21	ga_s2bm_ard_3-2-1_54HVJ_2019-07-31_final
2019-07-31 10:16:24	ga_s2bm_ard_3-2-1_54HUJ_2019-07-31_final
2019-07-31 10:16:29	ga_s2bm_ard_3-2-1_54HTJ_2019-07-31_final
2019-07-31 10:16:32	ga_s2bm_ard_3-2-1_54HWH_2019-07-31_final
2019-07-31 10:16:36	ga_s2bm_ard_3-2-1_54HVH_2019-07-31_final
2019-07-31 10:16:39	ga_s2bm_ard_3-2-1_54HUH_2019-07-31_final
2019-07-31 10:16:42	ga_s2bm_ard_3-2-1_54HTH_2019-07-31_final
2019-07-31 10:16:47	ga_s2bm_ard_3-2-1_54HWG_2019-07-31_final
2019-07-31 10:16:50	ga_s2bm_ard_3-2-1_54HVG_2019-07-31_final
2019-07-31 10:16:54	ga_s2bm_ard_3-2-1_54HUG_2019-07-31_final
2019-07-31 10:16:57	ga_s2bm_ard_3-2-1_54HTG_2019-07-31_final
2019-07-31 10:17:00	ga_s2bm_ard_3-2-1_53HQB_2019-07-31_final
2019-07-31 10:17:00	ga_s2bm_ard_3-2-1_54HWF_2019-07-31_final
2019-07-31 10:17:05	ga_s2bm_ard_3-2-1_54HVF_2019-07-31_final
2019-07-31 10:17:08	ga_s2bm_ard_3-2-1_54HUF_2019-07-31_final
2019-07-31 10:17:11	ga_s2bm_ard_3-2-1_54HWE_2019-07-31_final
2019-07-31 10:17:11	ga_s2bm_ard_3-2-1_54HTF_2019-07-31_final
2019-07-31 10:17:13	ga_s2bm_ard_3-2-1_53HQA_2019-07-31_final
2019-07-31 10:17:19	ga_s2bm_ard_3-2-1_54HVE_2019-07-31_final
2019-07-31 10:17:23	ga_s2bm_ard_3-2-1_54HUE_2019-07-31_final
2019-07-31 10:17:26	ga_s2bm_ard_3-2-1_54HTE_2019-07-31_final
2019-07-31 10:17:27	ga_s2bm_ard_3-2-1_53HQV_2019-07-31_final
2019-07-31 10:17:34	ga_s2bm_ard_3-2-1_54HVD_2019-07-31_final
2019-07-31 10:17:37	ga_s2bm_ard_3-2-1_54HUD_2019-07-31_final
2019-07-31 10:17:45	ga_s2bm_ard_3-2-1_54HVC_2019-07-31_final
2019-07-31 11:51:20	ga_s2bm_ard_3-2-1_51LUF_2019-07-31_final
2019-07-31 11:51:26	ga_s2bm_ard_3-2-1_51LUF_2019-07-31_final
2019-07-31 11:51:35	ga_s2bm_ard_3-2-1_51LUE_2019-07-31_final
2019-07-31 11:51:46	ga_s2bm_ard_3-2-1_51LUD_2019-07-31_final
2019-07-31 11:52:28	ga_s2bm_ard_3-2-1_50KQG_2019-07-31_final
2019-07-31 11:52:42	ga_s2bm_ard_3-2-1_50KQF_2019-07-31_final
2019-07-31 11:52:45	ga_s2bm_ard_3-2-1_50KPF_2019-07-31_final
2019-07-31 11:52:57	ga_s2bm_ard_3-2-1_50KQE_2019-07-31_final
2019-07-31 11:53:02	ga_s2bm_ard_3-2-1_51KTU_2019-07-31_final
2019-07-31 11:53:07	ga_s2bm_ard_3-2-1_50KRD_2019-07-31_final
2019-07-31 11:53:11	ga_s2bm_ard_3-2-1_50KQD_2019-07-31_final
2019-07-31 11:53:29	ga_s2bm_ard_3-2-1_50KPC_2019-07-31_final
2019-07-31 11:53:32	ga_s2bm_ard_3-2-1_50KNC_2019-07-31_final
2019-07-31 11:53:39	ga_s2bm_ard_3-2-1_50KMC_2019-07-31_final
2019-07-31 11:53:44	ga_s2bm_ard_3-2-1_50KPB_2019-07-31_final
2019-07-31 11:53:47	ga_s2bm_ard_3-2-1_50KNB_2019-07-31_final
2019-07-31 11:53:50	ga_s2bm_ard_3-2-1_50KMB_2019-07-31_final
2019-07-31 11:54:01	ga_s2bm_ard_3-2-1_50KNA_2019-07-31_final
2019-07-31 11:54:04	ga_s2bm_ard_3-2-1_50KMA_2019-07-31_final
2019-07-31 11:54:09	ga_s2bm_ard_3-2-1_50KQV_2019-07-31_final
2019-07-31 11:54:16	ga_s2bm_ard_3-2-1_50KNV_2019-07-31_final
2019-07-31 11:54:19	ga_s2bm_ard_3-2-1_50KMV_2019-07-31_final
2019-07-31 11:54:21	ga_s2bm_ard_3-2-1_50KQU_2019-07-31_final
2019-07-31 11:54:30	ga_s2bm_ard_3-2-1_50KNU_2019-07-31_final
2019-07-31 11:54:31	ga_s2bm_ard_3-2-1_50JQT_2019-07-31_final
2019-07-31 11:54:34	ga_s2bm_ard_3-2-1_50KMU_2019-07-31_final
2019-07-31 11:54:41	ga_s2bm_ard_3-2-1_50JPT_2019-07-31_final
2019-07-31 11:54:41	ga_s2bm_ard_3-2-1_50KLU_2019-07-31_final
2019-07-31 11:54:45	ga_s2bm_ard_3-2-1_50JNT_2019-07-31_final
2019-07-31 11:54:48	ga_s2bm_ard_3-2-1_50JMT_2019-07-31_final
2019-07-31 11:54:52	ga_s2bm_ard_3-2-1_50JLT_2019-07-31_final
2019-07-31 11:54:56	ga_s2bm_ard_3-2-1_50JPS_2019-07-31_final
2019-07-31 11:54:59	ga_s2bm_ard_3-2-1_50JNS_2019-07-31_final
2019-07-31 11:55:03	ga_s2bm_ard_3-2-1_50JMS_2019-07-31_final
2019-07-31 11:55:06	ga_s2bm_ard_3-2-1_50JLS_2019-07-31_final
2019-07-31 11:55:10	ga_s2bm_ard_3-2-1_50JPR_2019-07-31_final
2019-07-31 11:55:14	ga_s2bm_ard_3-2-1_50JNR_2019-07-31_final
2019-07-31 11:55:18	ga_s2bm_ard_3-2-1_50JMR_2019-07-31_final
2019-07-31 11:55:21	ga_s2bm_ard_3-2-1_50JLR_2019-07-31_final
2019-07-31 11:55:24	ga_s2bm_ard_3-2-1_50JPQ_2019-07-31_final
2019-07-31 11:55:28	ga_s2bm_ard_3-2-1_50JNQ_2019-07-31_final
2019-07-31 11:55:32	ga_s2bm_ard_3-2-1_50JMQ_2019-07-31_final
2019-07-31 11:55:34	ga_s2bm_ard_3-2-1_50JPP_2019-07-31_final
2019-07-31 11:55:35	ga_s2bm_ard_3-2-1_50JLQ_2019-07-31_final
2019-07-31 11:55:43	ga_s2bm_ard_3-2-1_50JNP_2019-07-31_final
2019-07-31 11:55:47	ga_s2bm_ard_3-2-1_50JMP_2019-07-31_final
2019-07-31 11:55:50	ga_s2bm_ard_3-2-1_50JLP_2019-07-31_final
2019-07-31 11:55:54	ga_s2bm_ard_3-2-1_50JKP_2019-07-31_final
2019-07-31 11:55:57	ga_s2bm_ard_3-2-1_50JNN_2019-07-31_final
2019-07-31 11:56:01	ga_s2bm_ard_3-2-1_50JMN_2019-07-31_final
2019-07-31 11:56:04	ga_s2bm_ard_3-2-1_50JLN_2019-07-31_final

Return to ga_s2bm_ard_3 on 31st July 2019 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

2019

July

31st