Search ga_s2bm_ard_3 on 9th October 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 s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless 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
2019-10-09 10:10:12	ga_s2bm_ard_3-2-1_54LZN_2019-10-09_final
2019-10-09 10:10:54	ga_s2bm_ard_3-2-1_55LBE_2019-10-09_final
2019-10-09 10:10:56	ga_s2bm_ard_3-2-1_54LZK_2019-10-09_final
2019-10-09 10:11:01	ga_s2bm_ard_3-2-1_54LYK_2019-10-09_final
2019-10-09 10:11:06	ga_s2bm_ard_3-2-1_55LCD_2019-10-09_final
2019-10-09 10:11:09	ga_s2bm_ard_3-2-1_55LBD_2019-10-09_final
2019-10-09 10:11:10	ga_s2bm_ard_3-2-1_54LZJ_2019-10-09_final
2019-10-09 10:11:14	ga_s2bm_ard_3-2-1_54LYJ_2019-10-09_final
2019-10-09 10:11:20	ga_s2bm_ard_3-2-1_55LCC_2019-10-09_final
2019-10-09 10:11:24	ga_s2bm_ard_3-2-1_55LBC_2019-10-09_final
2019-10-09 10:11:25	ga_s2bm_ard_3-2-1_54LZH_2019-10-09_final
2019-10-09 10:11:28	ga_s2bm_ard_3-2-1_54LYH_2019-10-09_final
2019-10-09 10:11:35	ga_s2bm_ard_3-2-1_55KCB_2019-10-09_final
2019-10-09 10:11:49	ga_s2bm_ard_3-2-1_55KCA_2019-10-09_final
2019-10-09 10:11:53	ga_s2bm_ard_3-2-1_55KBA_2019-10-09_final
2019-10-09 10:11:54	ga_s2bm_ard_3-2-1_54KZF_2019-10-09_final
2019-10-09 10:11:57	ga_s2bm_ard_3-2-1_54KYF_2019-10-09_final
2019-10-09 10:12:03	ga_s2bm_ard_3-2-1_54KXF_2019-10-09_final
2019-10-09 10:12:04	ga_s2bm_ard_3-2-1_55KCV_2019-10-09_final
2019-10-09 10:12:08	ga_s2bm_ard_3-2-1_54KZE_2019-10-09_final
2019-10-09 10:12:18	ga_s2bm_ard_3-2-1_55KCU_2019-10-09_final
2019-10-09 10:12:22	ga_s2bm_ard_3-2-1_55KBU_2019-10-09_final
2019-10-09 10:12:26	ga_s2bm_ard_3-2-1_54KYD_2019-10-09_final
2019-10-09 10:12:29	ga_s2bm_ard_3-2-1_55KCT_2019-10-09_final
2019-10-09 10:12:29	ga_s2bm_ard_3-2-1_54KXD_2019-10-09_final
2019-10-09 10:12:36	ga_s2bm_ard_3-2-1_55KBT_2019-10-09_final
2019-10-09 10:12:37	ga_s2bm_ard_3-2-1_54KZC_2019-10-09_final
2019-10-09 10:12:41	ga_s2bm_ard_3-2-1_54KYC_2019-10-09_final
2019-10-09 10:12:44	ga_s2bm_ard_3-2-1_54KXC_2019-10-09_final
2019-10-09 10:13:06	ga_s2bm_ard_3-2-1_54KZA_2019-10-09_final
2019-10-09 10:13:13	ga_s2bm_ard_3-2-1_54KXA_2019-10-09_final
2019-10-09 10:13:17	ga_s2bm_ard_3-2-1_54KWA_2019-10-09_final
2019-10-09 10:13:20	ga_s2bm_ard_3-2-1_55KBQ_2019-10-09_final
2019-10-09 10:13:20	ga_s2bm_ard_3-2-1_54KZV_2019-10-09_final
2019-10-09 10:13:24	ga_s2bm_ard_3-2-1_54KYV_2019-10-09_final
2019-10-09 10:13:31	ga_s2bm_ard_3-2-1_54KWV_2019-10-09_final
2019-10-09 10:13:34	ga_s2bm_ard_3-2-1_55KBP_2019-10-09_final
2019-10-09 10:13:34	ga_s2bm_ard_3-2-1_54KZU_2019-10-09_final
2019-10-09 10:13:42	ga_s2bm_ard_3-2-1_54KXU_2019-10-09_final
2019-10-09 10:13:45	ga_s2bm_ard_3-2-1_54KWU_2019-10-09_final
2019-10-09 10:13:46	ga_s2bm_ard_3-2-1_54JZT_2019-10-09_final
2019-10-09 10:14:14	ga_s2bm_ard_3-2-1_54JWS_2019-10-09_final
2019-10-09 10:14:18	ga_s2bm_ard_3-2-1_54JVS_2019-10-09_final
2019-10-09 10:14:22	ga_s2bm_ard_3-2-1_54JYR_2019-10-09_final
2019-10-09 10:14:25	ga_s2bm_ard_3-2-1_54JXR_2019-10-09_final
2019-10-09 10:14:40	ga_s2bm_ard_3-2-1_54JXQ_2019-10-09_final
2019-10-09 10:14:54	ga_s2bm_ard_3-2-1_54JXP_2019-10-09_final
2019-10-09 10:14:58	ga_s2bm_ard_3-2-1_54JWP_2019-10-09_final
2019-10-09 10:14:58	ga_s2bm_ard_3-2-1_54JYN_2019-10-09_final
2019-10-09 10:15:02	ga_s2bm_ard_3-2-1_54JVP_2019-10-09_final
2019-10-09 10:15:09	ga_s2bm_ard_3-2-1_54JXN_2019-10-09_final
2019-10-09 10:15:20	ga_s2bm_ard_3-2-1_54JUN_2019-10-09_final
2019-10-09 10:15:23	ga_s2bm_ard_3-2-1_54JXM_2019-10-09_final
2019-10-09 10:15:50	ga_s2bm_ard_3-2-1_54HXK_2019-10-09_final
2019-10-09 10:15:57	ga_s2bm_ard_3-2-1_54HUK_2019-10-09_final
2019-10-09 10:15:57	ga_s2bm_ard_3-2-1_54HXK_2019-10-09_final
2019-10-09 10:16:04	ga_s2bm_ard_3-2-1_54HUK_2019-10-09_final
2019-10-09 10:16:10	ga_s2bm_ard_3-2-1_54HWJ_2019-10-09_final
2019-10-09 10:16:14	ga_s2bm_ard_3-2-1_54HVJ_2019-10-09_final
2019-10-09 10:16:32	ga_s2bm_ard_3-2-1_54HUH_2019-10-09_final
2019-10-09 10:16:50	ga_s2bm_ard_3-2-1_54HTG_2019-10-09_final
2019-10-09 10:16:53	ga_s2bm_ard_3-2-1_53HQB_2019-10-09_final
2019-10-09 10:17:19	ga_s2bm_ard_3-2-1_54HTE_2019-10-09_final.stac-item
2019-10-09 10:17:20	ga_s2bm_ard_3-2-1_53HQV_2019-10-09_final.stac-item
2019-10-09 10:17:38	ga_s2bm_ard_3-2-1_54HVC_2019-10-09_final.stac-item
2019-10-09 11:51:40	ga_s2bm_ard_3-2-1_51LUD_2019-10-09_final.stac-item
2019-10-09 11:52:35	ga_s2bm_ard_3-2-1_50KQF_2019-10-09_final.stac-item
2019-10-09 11:52:38	ga_s2bm_ard_3-2-1_50KPF_2019-10-09_final.stac-item
2019-10-09 11:53:00	ga_s2bm_ard_3-2-1_50KRD_2019-10-09_final
2019-10-09 11:53:07	ga_s2bm_ard_3-2-1_50KPD_2019-10-09_final.stac-item
2019-10-09 11:53:12	ga_s2bm_ard_3-2-1_50KRC_2019-10-09_final
2019-10-09 11:53:18	ga_s2bm_ard_3-2-1_50KQC_2019-10-09_final
2019-10-09 11:53:22	ga_s2bm_ard_3-2-1_50KPC_2019-10-09_final
2019-10-09 11:53:37	ga_s2bm_ard_3-2-1_50KPB_2019-10-09_final
2019-10-09 11:53:40	ga_s2bm_ard_3-2-1_50KNB_2019-10-09_final
2019-10-09 11:53:44	ga_s2bm_ard_3-2-1_50KMB_2019-10-09_final
2019-10-09 11:53:51	ga_s2bm_ard_3-2-1_50KPA_2019-10-09_final
2019-10-09 11:53:54	ga_s2bm_ard_3-2-1_50KNA_2019-10-09_final
2019-10-09 11:53:57	ga_s2bm_ard_3-2-1_50KMA_2019-10-09_final
2019-10-09 11:54:02	ga_s2bm_ard_3-2-1_50KQV_2019-10-09_final
2019-10-09 11:54:05	ga_s2bm_ard_3-2-1_50KPV_2019-10-09_final
2019-10-09 11:54:09	ga_s2bm_ard_3-2-1_50KNV_2019-10-09_final
2019-10-09 11:54:12	ga_s2bm_ard_3-2-1_50KMV_2019-10-09_final
2019-10-09 11:54:20	ga_s2bm_ard_3-2-1_50KPU_2019-10-09_final
2019-10-09 11:54:23	ga_s2bm_ard_3-2-1_50KNU_2019-10-09_final
2019-10-09 11:54:27	ga_s2bm_ard_3-2-1_50KMU_2019-10-09_final
2019-10-09 11:54:34	ga_s2bm_ard_3-2-1_50KLU_2019-10-09_final
2019-10-09 11:54:52	ga_s2bm_ard_3-2-1_50JNS_2019-10-09_final
2019-10-09 11:54:56	ga_s2bm_ard_3-2-1_50JMS_2019-10-09_final
2019-10-09 11:55:07	ga_s2bm_ard_3-2-1_50JNR_2019-10-09_final
2019-10-09 11:55:10	ga_s2bm_ard_3-2-1_50JMR_2019-10-09_final
2019-10-09 11:55:17	ga_s2bm_ard_3-2-1_50JPQ_2019-10-09_final
2019-10-09 11:55:28	ga_s2bm_ard_3-2-1_50JLQ_2019-10-09_final
2019-10-09 11:55:36	ga_s2bm_ard_3-2-1_50JNP_2019-10-09_final
2019-10-09 11:55:40	ga_s2bm_ard_3-2-1_50JMP_2019-10-09_final
2019-10-09 11:55:57	ga_s2bm_ard_3-2-1_50JLN_2019-10-09_final
2019-10-09 11:56:00	ga_s2bm_ard_3-2-1_50JKN_2019-10-09_final
2019-10-09 11:56:12	ga_s2bm_ard_3-2-1_50JLM_2019-10-09_final
2019-10-09 11:56:41	ga_s2bm_ard_3-2-1_50HLK_2019-10-09_final
2019-10-09 11:56:52	ga_s2bm_ard_3-2-1_50HMJ_2019-10-09_final

Return to ga_s2bm_ard_3 on 9th October 2019 overview

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

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2019

October

9th