Search ga_s2bm_ard_3 on 7th June 2019

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

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

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

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

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

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2019-06-07 10:29:47	ga_s2bm_ard_3-2-1_54LXQ_2019-06-07_final.stac-item
2019-06-07 10:30:02	ga_s2bm_ard_3-2-1_54LXP_2019-06-07_final.stac-item
2019-06-07 10:30:15	ga_s2bm_ard_3-2-1_54LXN_2019-06-07_final.stac-item
2019-06-07 10:30:20	ga_s2bm_ard_3-2-1_54LWN_2019-06-07_final.stac-item
2019-06-07 10:30:26	ga_s2bm_ard_3-2-1_54LXM_2019-06-07_final.stac-item
2019-06-07 10:30:34	ga_s2bm_ard_3-2-1_54LWM_2019-06-07_final.stac-item
2019-06-07 10:30:49	ga_s2bm_ard_3-2-1_54LWL_2019-06-07_final.stac-item
2019-06-07 10:31:03	ga_s2bm_ard_3-2-1_54LWK_2019-06-07_final.stac-item
2019-06-07 10:31:17	ga_s2bm_ard_3-2-1_54LWJ_2019-06-07_final.stac-item
2019-06-07 10:31:27	ga_s2bm_ard_3-2-1_54LWH_2019-06-07_final.stac-item
2019-06-07 10:31:29	ga_s2bm_ard_3-2-1_54LVH_2019-06-07_final.stac-item
2019-06-07 10:31:31	ga_s2bm_ard_3-2-1_54LUH_2019-06-07_final.stac-item
2019-06-07 10:31:32	ga_s2bm_ard_3-2-1_54LWH_2019-06-07_final.stac-item
2019-06-07 10:31:36	ga_s2bm_ard_3-2-1_54LVH_2019-06-07_final.stac-item
2019-06-07 10:31:39	ga_s2bm_ard_3-2-1_54LUH_2019-06-07_final.stac-item
2019-06-07 10:31:40	ga_s2bm_ard_3-2-1_54KWG_2019-06-07_final.stac-item
2019-06-07 10:31:50	ga_s2bm_ard_3-2-1_54KVG_2019-06-07_final.stac-item
2019-06-07 10:31:54	ga_s2bm_ard_3-2-1_54KUG_2019-06-07_final.stac-item
2019-06-07 10:31:57	ga_s2bm_ard_3-2-1_54KTG_2019-06-07_final.stac-item
2019-06-07 10:31:58	ga_s2bm_ard_3-2-1_53KRB_2019-06-07_final
2019-06-07 10:32:05	ga_s2bm_ard_3-2-1_54KVF_2019-06-07_final.stac-item
2019-06-07 10:32:08	ga_s2bm_ard_3-2-1_54KUF_2019-06-07_final.stac-item
2019-06-07 10:32:11	ga_s2bm_ard_3-2-1_54KTF_2019-06-07_final.stac-item
2019-06-07 10:32:12	ga_s2bm_ard_3-2-1_53KRA_2019-06-07_final.stac-item
2019-06-07 10:32:19	ga_s2bm_ard_3-2-1_53KQA_2019-06-07_final.stac-item
2019-06-07 10:32:19	ga_s2bm_ard_3-2-1_54KVE_2019-06-07_final.stac-item
2019-06-07 10:32:23	ga_s2bm_ard_3-2-1_54KUE_2019-06-07_final.stac-item
2019-06-07 10:32:26	ga_s2bm_ard_3-2-1_54KTE_2019-06-07_final.stac-item
2019-06-07 10:32:27	ga_s2bm_ard_3-2-1_53KRV_2019-06-07_final.stac-item
2019-06-07 10:32:30	ga_s2bm_ard_3-2-1_53KQV_2019-06-07_final.stac-item
2019-06-07 10:32:33	ga_s2bm_ard_3-2-1_54KVD_2019-06-07_final.stac-item
2019-06-07 10:32:37	ga_s2bm_ard_3-2-1_54KUD_2019-06-07_final.stac-item
2019-06-07 10:32:40	ga_s2bm_ard_3-2-1_54KTD_2019-06-07_final.stac-item
2019-06-07 10:32:41	ga_s2bm_ard_3-2-1_53KRU_2019-06-07_final.stac-item
2019-06-07 10:34:08	ga_s2bm_ard_3-2-1_54JTT_2019-06-07_final.stac-item
2019-06-07 10:34:15	ga_s2bm_ard_3-2-1_53JPN_2019-06-07_final.stac-item
2019-06-07 10:34:21	ga_s2bm_ard_3-2-1_53JNN_2019-06-07_final.stac-item
2019-06-07 10:34:22	ga_s2bm_ard_3-2-1_54JTS_2019-06-07_final.stac-item
2019-06-07 10:34:29	ga_s2bm_ard_3-2-1_53JPM_2019-06-07_final.stac-item
2019-06-07 10:34:33	ga_s2bm_ard_3-2-1_53JNM_2019-06-07_final.stac-item
2019-06-07 10:34:37	ga_s2bm_ard_3-2-1_54JTR_2019-06-07_final.stac-item
2019-06-07 10:34:40	ga_s2bm_ard_3-2-1_53JQL_2019-06-07_final.stac-item
2019-06-07 10:34:44	ga_s2bm_ard_3-2-1_53JPL_2019-06-07_final.stac-item
2019-06-07 10:34:47	ga_s2bm_ard_3-2-1_53JNL_2019-06-07_final.stac-item
2019-06-07 10:34:52	ga_s2bm_ard_3-2-1_54JTQ_2019-06-07_final.stac-item
2019-06-07 10:34:55	ga_s2bm_ard_3-2-1_53JQK_2019-06-07_final.stac-item
2019-06-07 10:34:58	ga_s2bm_ard_3-2-1_53JPK_2019-06-07_final.stac-item
2019-06-07 10:35:02	ga_s2bm_ard_3-2-1_53JNK_2019-06-07_final.stac-item
2019-06-07 10:35:05	ga_s2bm_ard_3-2-1_54JTP_2019-06-07_final.stac-item
2019-06-07 10:35:09	ga_s2bm_ard_3-2-1_53JQJ_2019-06-07_final.stac-item
2019-06-07 10:35:13	ga_s2bm_ard_3-2-1_53JPJ_2019-06-07_final.stac-item
2019-06-07 10:35:16	ga_s2bm_ard_3-2-1_54JTN_2019-06-07_final.stac-item
2019-06-07 10:35:17	ga_s2bm_ard_3-2-1_53JNJ_2019-06-07_final.stac-item
2019-06-07 10:35:23	ga_s2bm_ard_3-2-1_53JMJ_2019-06-07_final.stac-item
2019-06-07 10:35:23	ga_s2bm_ard_3-2-1_53JQH_2019-06-07_final.stac-item
2019-06-07 10:35:27	ga_s2bm_ard_3-2-1_53JPH_2019-06-07_final.stac-item
2019-06-07 10:35:31	ga_s2bm_ard_3-2-1_53JNH_2019-06-07_final.stac-item
2019-06-07 10:35:35	ga_s2bm_ard_3-2-1_53JMH_2019-06-07_final.stac-item
2019-06-07 10:35:38	ga_s2bm_ard_3-2-1_53JQG_2019-06-07_final.stac-item
2019-06-07 10:35:42	ga_s2bm_ard_3-2-1_53JPG_2019-06-07_final.stac-item
2019-06-07 10:35:45	ga_s2bm_ard_3-2-1_53JNG_2019-06-07_final.stac-item
2019-06-07 10:35:49	ga_s2bm_ard_3-2-1_53JMG_2019-06-07_final.stac-item
2019-06-07 10:35:52	ga_s2bm_ard_3-2-1_53JQF_2019-06-07_final.stac-item
2019-06-07 10:35:56	ga_s2bm_ard_3-2-1_53JPF_2019-06-07_final.stac-item
2019-06-07 10:36:00	ga_s2bm_ard_3-2-1_53JNF_2019-06-07_final.stac-item
2019-06-07 10:36:03	ga_s2bm_ard_3-2-1_53JMF_2019-06-07_final.stac-item
2019-06-07 10:36:04	ga_s2bm_ard_3-2-1_53HQE_2019-06-07_final.stac-item
2019-06-07 10:36:11	ga_s2bm_ard_3-2-1_53HPE_2019-06-07_final.stac-item
2019-06-07 10:36:15	ga_s2bm_ard_3-2-1_53HNE_2019-06-07_final.stac-item
2019-06-07 10:36:18	ga_s2bm_ard_3-2-1_53HME_2019-06-07_final.stac-item
2019-06-07 10:36:24	ga_s2bm_ard_3-2-1_53HLE_2019-06-07_final.stac-item
2019-06-07 10:36:25	ga_s2bm_ard_3-2-1_53HPD_2019-06-07_final.stac-item
2019-06-07 10:36:29	ga_s2bm_ard_3-2-1_53HND_2019-06-07_final.stac-item
2019-06-07 10:36:32	ga_s2bm_ard_3-2-1_53HMD_2019-06-07_final.stac-item
2019-06-07 10:36:36	ga_s2bm_ard_3-2-1_53HLD_2019-06-07_final.stac-item
2019-06-07 10:36:40	ga_s2bm_ard_3-2-1_53HPC_2019-06-07_final.stac-item
2019-06-07 10:36:44	ga_s2bm_ard_3-2-1_53HNC_2019-06-07_final.stac-item
2019-06-07 10:36:54	ga_s2bm_ard_3-2-1_53HPB_2019-06-07_final.stac-item
2019-06-07 10:36:58	ga_s2bm_ard_3-2-1_53HNB_2019-06-07_final.stac-item
2019-06-07 10:37:06	ga_s2bm_ard_3-2-1_53HPA_2019-06-07_final.stac-item
2019-06-07 12:13:47	ga_s2bm_ard_3-2-1_50KKB_2019-06-07_final.stac-item
2019-06-07 12:14:02	ga_s2bm_ard_3-2-1_50KKA_2019-06-07_final.stac-item
2019-06-07 12:14:02	ga_s2bm_ard_3-2-1_49KHR_2019-06-07_final.stac-item
2019-06-07 12:14:06	ga_s2bm_ard_3-2-1_49KGR_2019-06-07_final.stac-item
2019-06-07 12:14:12	ga_s2bm_ard_3-2-1_50KKV_2019-06-07_final.stac-item
2019-06-07 12:14:12	ga_s2bm_ard_3-2-1_49KHQ_2019-06-07_final.stac-item
2019-06-07 12:14:14	ga_s2bm_ard_3-2-1_49KGQ_2019-06-07_final.stac-item
2019-06-07 12:14:14	ga_s2bm_ard_3-2-1_49KGR_2019-06-07_final.stac-item
2019-06-07 12:14:17	ga_s2bm_ard_3-2-1_50KKV_2019-06-07_final.stac-item
2019-06-07 12:14:18	ga_s2bm_ard_3-2-1_49KHQ_2019-06-07_final.stac-item
2019-06-07 12:14:21	ga_s2bm_ard_3-2-1_49KGQ_2019-06-07_final.stac-item
2019-06-07 12:14:27	ga_s2bm_ard_3-2-1_50KKU_2019-06-07_final.stac-item
2019-06-07 12:14:29	ga_s2bm_ard_3-2-1_49KHP_2019-06-07_final.stac-item
2019-06-07 12:14:35	ga_s2bm_ard_3-2-1_49KGP_2019-06-07_final.stac-item
2019-06-07 12:14:39	ga_s2bm_ard_3-2-1_49JHN_2019-06-07_final.stac-item
2019-06-07 12:14:49	ga_s2bm_ard_3-2-1_49JGN_2019-06-07_final.stac-item
2019-06-07 12:14:53	ga_s2bm_ard_3-2-1_49JFN_2019-06-07_final.stac-item
2019-06-07 12:15:04	ga_s2bm_ard_3-2-1_49JGM_2019-06-07_final.stac-item
2019-06-07 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-06-07_final.stac-item
2019-06-07 12:15:18	ga_s2bm_ard_3-2-1_49JGL_2019-06-07_final.stac-item

Return to ga_s2bm_ard_3 on 7th June 2019 overview

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

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2019

June

7th