Search ga_s2bm_ard_3 on 30th August 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
2019-08-30 10:10:02	ga_s2bm_ard_3-2-1_54LZP_2019-08-30_final
2019-08-30 10:10:29	ga_s2bm_ard_3-2-1_54LZM_2019-08-30_final
2019-08-30 10:10:54	ga_s2bm_ard_3-2-1_55LCE_2019-08-30_final
2019-08-30 10:10:57	ga_s2bm_ard_3-2-1_55LBE_2019-08-30_final
2019-08-30 10:10:59	ga_s2bm_ard_3-2-1_54LZK_2019-08-30_final
2019-08-30 10:11:04	ga_s2bm_ard_3-2-1_54LYK_2019-08-30_final
2019-08-30 10:11:23	ga_s2bm_ard_3-2-1_55LCC_2019-08-30_final
2019-08-30 10:11:26	ga_s2bm_ard_3-2-1_55LBC_2019-08-30_final
2019-08-30 10:11:28	ga_s2bm_ard_3-2-1_54LZH_2019-08-30_final
2019-08-30 10:11:31	ga_s2bm_ard_3-2-1_54LYH_2019-08-30_final
2019-08-30 10:11:37	ga_s2bm_ard_3-2-1_55KCB_2019-08-30_final
2019-08-30 10:11:50	ga_s2bm_ard_3-2-1_55KCA_2019-08-30_final
2019-08-30 10:11:57	ga_s2bm_ard_3-2-1_55KCA_2019-08-30_final
2019-08-30 10:12:06	ga_s2bm_ard_3-2-1_54KXF_2019-08-30_final
2019-08-30 10:12:07	ga_s2bm_ard_3-2-1_55KCV_2019-08-30_final
2019-08-30 10:12:10	ga_s2bm_ard_3-2-1_55KBV_2019-08-30_final
2019-08-30 10:12:11	ga_s2bm_ard_3-2-1_54KZE_2019-08-30_final
2019-08-30 10:12:14	ga_s2bm_ard_3-2-1_54KYE_2019-08-30_final
2019-08-30 10:12:18	ga_s2bm_ard_3-2-1_54KXE_2019-08-30_final
2019-08-30 10:12:20	ga_s2bm_ard_3-2-1_55KCU_2019-08-30_final
2019-08-30 10:12:32	ga_s2bm_ard_3-2-1_55KCT_2019-08-30_final
2019-08-30 10:12:32	ga_s2bm_ard_3-2-1_54KXD_2019-08-30_final
2019-08-30 10:12:47	ga_s2bm_ard_3-2-1_54KXC_2019-08-30_final
2019-08-30 10:12:53	ga_s2bm_ard_3-2-1_55KBS_2019-08-30_final
2019-08-30 10:12:54	ga_s2bm_ard_3-2-1_54KZB_2019-08-30_final
2019-08-30 10:12:58	ga_s2bm_ard_3-2-1_54KYB_2019-08-30_final
2019-08-30 10:13:08	ga_s2bm_ard_3-2-1_55KBR_2019-08-30_final
2019-08-30 10:13:08	ga_s2bm_ard_3-2-1_54KZA_2019-08-30_final
2019-08-30 10:13:12	ga_s2bm_ard_3-2-1_54KYA_2019-08-30_final
2019-08-30 10:13:23	ga_s2bm_ard_3-2-1_54KZV_2019-08-30_final
2019-08-30 10:13:30	ga_s2bm_ard_3-2-1_54KXV_2019-08-30_final
2019-08-30 10:13:33	ga_s2bm_ard_3-2-1_54KWV_2019-08-30_final
2019-08-30 10:13:36	ga_s2bm_ard_3-2-1_55KBP_2019-08-30_final
2019-08-30 10:13:37	ga_s2bm_ard_3-2-1_54KZU_2019-08-30_final
2019-08-30 10:13:41	ga_s2bm_ard_3-2-1_54KYU_2019-08-30_final
2019-08-30 10:13:45	ga_s2bm_ard_3-2-1_54KXU_2019-08-30_final
2019-08-30 10:13:48	ga_s2bm_ard_3-2-1_54KWU_2019-08-30_final
2019-08-30 10:13:49	ga_s2bm_ard_3-2-1_54JZT_2019-08-30_final
2019-08-30 10:14:10	ga_s2bm_ard_3-2-1_54JYS_2019-08-30_final
2019-08-30 10:14:17	ga_s2bm_ard_3-2-1_54JWS_2019-08-30_final
2019-08-30 10:14:21	ga_s2bm_ard_3-2-1_54JVS_2019-08-30_final
2019-08-30 10:14:28	ga_s2bm_ard_3-2-1_54JXR_2019-08-30_final
2019-08-30 10:14:32	ga_s2bm_ard_3-2-1_54JWR_2019-08-30_final
2019-08-30 10:14:35	ga_s2bm_ard_3-2-1_54JVR_2019-08-30_final
2019-08-30 10:14:39	ga_s2bm_ard_3-2-1_54JYQ_2019-08-30_final
2019-08-30 10:14:50	ga_s2bm_ard_3-2-1_54JVQ_2019-08-30_final
2019-08-30 10:14:51	ga_s2bm_ard_3-2-1_54JYP_2019-08-30_final
2019-08-30 10:14:57	ga_s2bm_ard_3-2-1_54JXP_2019-08-30_final
2019-08-30 10:15:01	ga_s2bm_ard_3-2-1_54JWP_2019-08-30_final
2019-08-30 10:15:01	ga_s2bm_ard_3-2-1_54JYN_2019-08-30_final
2019-08-30 10:15:04	ga_s2bm_ard_3-2-1_54JVP_2019-08-30_final
2019-08-30 10:15:15	ga_s2bm_ard_3-2-1_54JWN_2019-08-30_final
2019-08-30 10:15:19	ga_s2bm_ard_3-2-1_54JVN_2019-08-30_final
2019-08-30 10:15:44	ga_s2bm_ard_3-2-1_54JWL_2019-08-30_final
2019-08-30 10:15:51	ga_s2bm_ard_3-2-1_54JUL_2019-08-30_final
2019-08-30 10:16:49	ga_s2bm_ard_3-2-1_54HUG_2019-08-30_final
2019-08-30 10:16:52	ga_s2bm_ard_3-2-1_54HTG_2019-08-30_final
2019-08-30 10:16:56	ga_s2bm_ard_3-2-1_53HQB_2019-08-30_final
2019-08-30 10:17:29	ga_s2bm_ard_3-2-1_54HVD_2019-08-30_final
2019-08-30 10:17:33	ga_s2bm_ard_3-2-1_54HUD_2019-08-30_final.stac-item
2019-08-30 10:17:41	ga_s2bm_ard_3-2-1_54HVC_2019-08-30_final.stac-item
2019-08-30 11:51:31	ga_s2bm_ard_3-2-1_51LUE_2019-08-30_final
2019-08-30 11:52:41	ga_s2bm_ard_3-2-1_50KPF_2019-08-30_final.stac-item
2019-08-30 11:52:52	ga_s2bm_ard_3-2-1_50KQE_2019-08-30_final.stac-item
2019-08-30 11:53:10	ga_s2bm_ard_3-2-1_50KPD_2019-08-30_final.stac-item
2019-08-30 11:53:25	ga_s2bm_ard_3-2-1_50KPC_2019-08-30_final
2019-08-30 11:53:28	ga_s2bm_ard_3-2-1_50KNC_2019-08-30_final
2019-08-30 11:53:35	ga_s2bm_ard_3-2-1_50KMC_2019-08-30_final
2019-08-30 11:53:35	ga_s2bm_ard_3-2-1_50KQB_2019-08-30_final
2019-08-30 11:53:39	ga_s2bm_ard_3-2-1_50KPB_2019-08-30_final
2019-08-30 11:53:43	ga_s2bm_ard_3-2-1_50KNB_2019-08-30_final
2019-08-30 11:53:46	ga_s2bm_ard_3-2-1_50KMB_2019-08-30_final
2019-08-30 11:53:50	ga_s2bm_ard_3-2-1_50KQA_2019-08-30_final
2019-08-30 11:54:08	ga_s2bm_ard_3-2-1_50KPV_2019-08-30_final
2019-08-30 11:54:12	ga_s2bm_ard_3-2-1_50KNV_2019-08-30_final
2019-08-30 11:54:15	ga_s2bm_ard_3-2-1_50KMV_2019-08-30_final
2019-08-30 11:54:17	ga_s2bm_ard_3-2-1_50KQU_2019-08-30_final
2019-08-30 11:54:23	ga_s2bm_ard_3-2-1_50KPU_2019-08-30_final
2019-08-30 11:54:26	ga_s2bm_ard_3-2-1_50KNU_2019-08-30_final
2019-08-30 11:54:30	ga_s2bm_ard_3-2-1_50KMU_2019-08-30_final
2019-08-30 11:54:37	ga_s2bm_ard_3-2-1_50KLU_2019-08-30_final
2019-08-30 11:54:55	ga_s2bm_ard_3-2-1_50JNS_2019-08-30_final
2019-08-30 11:54:59	ga_s2bm_ard_3-2-1_50JMS_2019-08-30_final
2019-08-30 11:55:06	ga_s2bm_ard_3-2-1_50JPR_2019-08-30_final
2019-08-30 11:55:10	ga_s2bm_ard_3-2-1_50JNR_2019-08-30_final
2019-08-30 11:55:13	ga_s2bm_ard_3-2-1_50JMR_2019-08-30_final
2019-08-30 11:55:16	ga_s2bm_ard_3-2-1_50JLR_2019-08-30_final
2019-08-30 11:55:24	ga_s2bm_ard_3-2-1_50JNQ_2019-08-30_final
2019-08-30 11:55:28	ga_s2bm_ard_3-2-1_50JMQ_2019-08-30_final
2019-08-30 11:55:39	ga_s2bm_ard_3-2-1_50JNP_2019-08-30_final
2019-08-30 11:55:42	ga_s2bm_ard_3-2-1_50JMP_2019-08-30_final
2019-08-30 11:55:50	ga_s2bm_ard_3-2-1_50JKP_2019-08-30_final
2019-08-30 11:55:53	ga_s2bm_ard_3-2-1_50JNN_2019-08-30_final
2019-08-30 11:55:57	ga_s2bm_ard_3-2-1_50JMN_2019-08-30_final
2019-08-30 11:56:03	ga_s2bm_ard_3-2-1_50JKN_2019-08-30_final
2019-08-30 11:56:11	ga_s2bm_ard_3-2-1_50JMM_2019-08-30_final
2019-08-30 11:56:18	ga_s2bm_ard_3-2-1_50JKM_2019-08-30_final
2019-08-30 11:56:22	ga_s2bm_ard_3-2-1_50JNL_2019-08-30_final
2019-08-30 11:56:26	ga_s2bm_ard_3-2-1_50JML_2019-08-30_final
2019-08-30 11:56:29	ga_s2bm_ard_3-2-1_50JLL_2019-08-30_final

Return to ga_s2bm_ard_3 on 30th August 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

August

30th