Search ga_s2bm_ard_3 on 2nd 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
2019-10-02 10:23:05	ga_s2bm_ard_3-2-1_54KWB_2019-10-02_final
2019-10-02 10:23:08	ga_s2bm_ard_3-2-1_54KXA_2019-10-02_final
2019-10-02 10:23:12	ga_s2bm_ard_3-2-1_54KWA_2019-10-02_final
2019-10-02 10:23:15	ga_s2bm_ard_3-2-1_54KVA_2019-10-02_final
2019-10-02 10:23:18	ga_s2bm_ard_3-2-1_54KXV_2019-10-02_final
2019-10-02 10:23:18	ga_s2bm_ard_3-2-1_54KUA_2019-10-02_final
2019-10-02 10:23:33	ga_s2bm_ard_3-2-1_54KUV_2019-10-02_final
2019-10-02 10:23:37	ga_s2bm_ard_3-2-1_54KTV_2019-10-02_final
2019-10-02 10:23:47	ga_s2bm_ard_3-2-1_54KUU_2019-10-02_final
2019-10-02 10:23:50	ga_s2bm_ard_3-2-1_54KTU_2019-10-02_final
2019-10-02 10:23:55	ga_s2bm_ard_3-2-1_54JWT_2019-10-02_final
2019-10-02 10:23:59	ga_s2bm_ard_3-2-1_54JVT_2019-10-02_final
2019-10-02 10:24:02	ga_s2bm_ard_3-2-1_54JUT_2019-10-02_final
2019-10-02 10:24:05	ga_s2bm_ard_3-2-1_54JTT_2019-10-02_final
2019-10-02 10:24:09	ga_s2bm_ard_3-2-1_54JWS_2019-10-02_final
2019-10-02 10:24:13	ga_s2bm_ard_3-2-1_54JVS_2019-10-02_final
2019-10-02 10:24:16	ga_s2bm_ard_3-2-1_54JUS_2019-10-02_final
2019-10-02 10:24:19	ga_s2bm_ard_3-2-1_53JRM_2019-10-02_final
2019-10-02 10:24:20	ga_s2bm_ard_3-2-1_54JTS_2019-10-02_final
2019-10-02 10:24:34	ga_s2bm_ard_3-2-1_54JTR_2019-10-02_final
2019-10-02 10:24:40	ga_s2bm_ard_3-2-1_53JQL_2019-10-02_final
2019-10-02 10:24:42	ga_s2bm_ard_3-2-1_54JVQ_2019-10-02_final
2019-10-02 10:24:49	ga_s2bm_ard_3-2-1_54JTQ_2019-10-02_final
2019-10-02 10:24:57	ga_s2bm_ard_3-2-1_54JVP_2019-10-02_final
2019-10-02 10:25:00	ga_s2bm_ard_3-2-1_54JUP_2019-10-02_final
2019-10-02 10:25:03	ga_s2bm_ard_3-2-1_54JTP_2019-10-02_final
2019-10-02 10:25:06	ga_s2bm_ard_3-2-1_53JQJ_2019-10-02_final
2019-10-02 10:25:11	ga_s2bm_ard_3-2-1_54JVN_2019-10-02_final
2019-10-02 10:25:15	ga_s2bm_ard_3-2-1_54JUN_2019-10-02_final
2019-10-02 10:25:18	ga_s2bm_ard_3-2-1_54JTN_2019-10-02_final
2019-10-02 10:25:21	ga_s2bm_ard_3-2-1_53JQH_2019-10-02_final
2019-10-02 10:25:29	ga_s2bm_ard_3-2-1_54JUM_2019-10-02_final
2019-10-02 10:25:32	ga_s2bm_ard_3-2-1_54JTM_2019-10-02_final
2019-10-02 10:25:35	ga_s2bm_ard_3-2-1_53JQG_2019-10-02_final
2019-10-02 10:25:36	ga_s2bm_ard_3-2-1_54JVL_2019-10-02_final
2019-10-02 10:25:41	ga_s2bm_ard_3-2-1_53JPG_2019-10-02_final
2019-10-02 10:25:43	ga_s2bm_ard_3-2-1_54JUL_2019-10-02_final
2019-10-02 10:25:49	ga_s2bm_ard_3-2-1_53JQF_2019-10-02_final
2019-10-02 10:25:53	ga_s2bm_ard_3-2-1_53JPF_2019-10-02_final
2019-10-02 10:25:58	ga_s2bm_ard_3-2-1_54HUK_2019-10-02_final
2019-10-02 10:26:02	ga_s2bm_ard_3-2-1_54HTK_2019-10-02_final
2019-10-02 10:26:04	ga_s2bm_ard_3-2-1_53HQE_2019-10-02_final
2019-10-02 10:26:07	ga_s2bm_ard_3-2-1_53HPE_2019-10-02_final
2019-10-02 10:26:13	ga_s2bm_ard_3-2-1_54HUJ_2019-10-02_final
2019-10-02 10:26:16	ga_s2bm_ard_3-2-1_54HTJ_2019-10-02_final
2019-10-02 10:26:18	ga_s2bm_ard_3-2-1_53HQD_2019-10-02_final
2019-10-02 10:26:22	ga_s2bm_ard_3-2-1_53HPD_2019-10-02_final
2019-10-02 10:26:27	ga_s2bm_ard_3-2-1_54HUH_2019-10-02_final
2019-10-02 10:26:31	ga_s2bm_ard_3-2-1_54HTH_2019-10-02_final
2019-10-02 10:26:33	ga_s2bm_ard_3-2-1_53HQC_2019-10-02_final
2019-10-02 10:26:36	ga_s2bm_ard_3-2-1_53HPC_2019-10-02_final
2019-10-02 10:26:41	ga_s2bm_ard_3-2-1_53HNC_2019-10-02_final
2019-10-02 10:26:45	ga_s2bm_ard_3-2-1_54HTG_2019-10-02_final
2019-10-02 10:26:47	ga_s2bm_ard_3-2-1_53HQB_2019-10-02_final
2019-10-02 10:26:54	ga_s2bm_ard_3-2-1_53HNB_2019-10-02_final
2019-10-02 10:27:00	ga_s2bm_ard_3-2-1_54HTF_2019-10-02_final
2019-10-02 10:27:02	ga_s2bm_ard_3-2-1_53HQA_2019-10-02_final
2019-10-02 10:27:12	ga_s2bm_ard_3-2-1_54HTE_2019-10-02_final.stac-item
2019-10-02 10:27:13	ga_s2bm_ard_3-2-1_53HQV_2019-10-02_final.stac-item
2019-10-02 10:27:15	ga_s2bm_ard_3-2-1_53HPV_2019-10-02_final.stac-item
2019-10-02 12:03:20	ga_s2bm_ard_3-2-1_50KNC_2019-10-02_final
2019-10-02 12:03:24	ga_s2bm_ard_3-2-1_50KMC_2019-10-02_final
2019-10-02 12:03:27	ga_s2bm_ard_3-2-1_50KLC_2019-10-02_final
2019-10-02 12:03:41	ga_s2bm_ard_3-2-1_50KLB_2019-10-02_final
2019-10-02 12:03:45	ga_s2bm_ard_3-2-1_50KKB_2019-10-02_final
2019-10-02 12:03:45	ga_s2bm_ard_3-2-1_50KNA_2019-10-02_final
2019-10-02 12:03:52	ga_s2bm_ard_3-2-1_50KMA_2019-10-02_final
2019-10-02 12:03:56	ga_s2bm_ard_3-2-1_50KLA_2019-10-02_final
2019-10-02 12:03:59	ga_s2bm_ard_3-2-1_50KKA_2019-10-02_final
2019-10-02 12:04:00	ga_s2bm_ard_3-2-1_49KHR_2019-10-02_final
2019-10-02 12:04:11	ga_s2bm_ard_3-2-1_50KLV_2019-10-02_final
2019-10-02 12:04:14	ga_s2bm_ard_3-2-1_50KKV_2019-10-02_final
2019-10-02 12:04:19	ga_s2bm_ard_3-2-1_49KGQ_2019-10-02_final
2019-10-02 12:04:22	ga_s2bm_ard_3-2-1_50KLU_2019-10-02_final
2019-10-02 12:04:24	ga_s2bm_ard_3-2-1_50KKU_2019-10-02_final
2019-10-02 12:04:25	ga_s2bm_ard_3-2-1_49KGP_2019-10-02_final
2019-10-02 12:04:29	ga_s2bm_ard_3-2-1_50KLU_2019-10-02_final
2019-10-02 12:04:30	ga_s2bm_ard_3-2-1_50KKU_2019-10-02_final
2019-10-02 12:04:32	ga_s2bm_ard_3-2-1_49KGP_2019-10-02_final
2019-10-02 12:04:36	ga_s2bm_ard_3-2-1_50JMT_2019-10-02_final
2019-10-02 12:04:40	ga_s2bm_ard_3-2-1_50JLT_2019-10-02_final
2019-10-02 12:04:43	ga_s2bm_ard_3-2-1_50JKT_2019-10-02_final
2019-10-02 12:04:46	ga_s2bm_ard_3-2-1_49JGN_2019-10-02_final
2019-10-02 12:04:49	ga_s2bm_ard_3-2-1_50JMS_2019-10-02_final
2019-10-02 12:04:54	ga_s2bm_ard_3-2-1_50JLS_2019-10-02_final
2019-10-02 12:04:57	ga_s2bm_ard_3-2-1_49JHM_2019-10-02_final
2019-10-02 12:04:58	ga_s2bm_ard_3-2-1_50JKS_2019-10-02_final
2019-10-02 12:04:59	ga_s2bm_ard_3-2-1_50JMR_2019-10-02_final
2019-10-02 12:05:01	ga_s2bm_ard_3-2-1_49JGM_2019-10-02_final
2019-10-02 12:05:12	ga_s2bm_ard_3-2-1_50JKR_2019-10-02_final
2019-10-02 12:05:15	ga_s2bm_ard_3-2-1_49JGL_2019-10-02_final
2019-10-02 12:05:27	ga_s2bm_ard_3-2-1_50JKQ_2019-10-02_final
2019-10-02 12:05:30	ga_s2bm_ard_3-2-1_49JGK_2019-10-02_final
2019-10-02 12:05:38	ga_s2bm_ard_3-2-1_50JLP_2019-10-02_final
2019-10-02 12:05:41	ga_s2bm_ard_3-2-1_50JKP_2019-10-02_final
2019-10-02 12:05:44	ga_s2bm_ard_3-2-1_49JGJ_2019-10-02_final
2019-10-02 12:05:52	ga_s2bm_ard_3-2-1_50JLN_2019-10-02_final
2019-10-02 12:05:56	ga_s2bm_ard_3-2-1_50JKN_2019-10-02_final
2019-10-02 12:06:05	ga_s2bm_ard_3-2-1_50JLM_2019-10-02_final
2019-10-02 12:06:10	ga_s2bm_ard_3-2-1_50JKM_2019-10-02_final

Return to ga_s2bm_ard_3 on 2nd 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

2nd