Search ga_s2bm_ard_3 across 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
2019-08-25 11:03:24	ga_s2bm_ard_3-2-1_52KEB_2019-08-25_final.stac-item
2019-08-25 11:03:39	ga_s2bm_ard_3-2-1_52KEA_2019-08-25_final.stac-item
2019-08-25 11:03:58	ga_s2bm_ard_3-2-1_52KDV_2019-08-25_final.stac-item
2019-08-25 11:04:11	ga_s2bm_ard_3-2-1_52KDU_2019-08-25_final.stac-item
2019-08-25 11:04:16	ga_s2bm_ard_3-2-1_52JGT_2019-08-25_final.stac-item
2019-08-25 11:04:19	ga_s2bm_ard_3-2-1_52JFT_2019-08-25_final.stac-item
2019-08-25 11:04:23	ga_s2bm_ard_3-2-1_52JET_2019-08-25_final.stac-item
2019-08-25 11:04:26	ga_s2bm_ard_3-2-1_52JDT_2019-08-25_final.stac-item
2019-08-25 11:04:29	ga_s2bm_ard_3-2-1_52JGS_2019-08-25_final.stac-item
2019-08-25 11:04:34	ga_s2bm_ard_3-2-1_52JFS_2019-08-25_final.stac-item
2019-08-25 11:04:37	ga_s2bm_ard_3-2-1_52JES_2019-08-25_final.stac-item
2019-08-25 11:04:40	ga_s2bm_ard_3-2-1_52JGR_2019-08-25_final.stac-item
2019-08-25 11:04:41	ga_s2bm_ard_3-2-1_52JDS_2019-08-25_final.stac-item
2019-08-25 11:04:48	ga_s2bm_ard_3-2-1_52JFR_2019-08-25_final.stac-item
2019-08-25 11:04:52	ga_s2bm_ard_3-2-1_52JER_2019-08-25_final.stac-item
2019-08-25 11:04:55	ga_s2bm_ard_3-2-1_52JDR_2019-08-25_final.stac-item
2019-08-25 11:05:00	ga_s2bm_ard_3-2-1_52JCR_2019-08-25_final.stac-item
2019-08-25 11:05:02	ga_s2bm_ard_3-2-1_52JFQ_2019-08-25_final.stac-item
2019-08-25 11:05:06	ga_s2bm_ard_3-2-1_52JEQ_2019-08-25_final.stac-item
2019-08-25 11:05:10	ga_s2bm_ard_3-2-1_52JDQ_2019-08-25_final.stac-item
2019-08-25 11:05:13	ga_s2bm_ard_3-2-1_52JCQ_2019-08-25_final.stac-item
2019-08-25 11:05:17	ga_s2bm_ard_3-2-1_52JFP_2019-08-25_final.stac-item
2019-08-25 11:05:21	ga_s2bm_ard_3-2-1_52JEP_2019-08-25_final.stac-item
2019-08-25 11:05:24	ga_s2bm_ard_3-2-1_52JDP_2019-08-25_final.stac-item
2019-08-25 11:05:27	ga_s2bm_ard_3-2-1_52JCP_2019-08-25_final.stac-item
2019-08-25 11:05:31	ga_s2bm_ard_3-2-1_52JFN_2019-08-25_final.stac-item
2019-08-25 11:05:35	ga_s2bm_ard_3-2-1_52JEN_2019-08-25_final.stac-item
2019-08-25 11:05:39	ga_s2bm_ard_3-2-1_52JDN_2019-08-25_final.stac-item
2019-08-25 11:05:42	ga_s2bm_ard_3-2-1_52JCN_2019-08-25_final.stac-item
2019-08-25 11:05:43	ga_s2bm_ard_3-2-1_52JFM_2019-08-25_final.stac-item
2019-08-25 11:05:49	ga_s2bm_ard_3-2-1_52JEM_2019-08-25_final.stac-item
2019-08-25 11:05:52	ga_s2bm_ard_3-2-1_52JDM_2019-08-25_final.stac-item
2019-08-25 11:05:54	ga_s2bm_ard_3-2-1_52JCM_2019-08-25_final.stac-item
2019-08-25 11:05:57	ga_s2bm_ard_3-2-1_52JEL_2019-08-25_final.stac-item
2019-08-25 11:05:58	ga_s2bm_ard_3-2-1_52JEM_2019-08-25_final.stac-item
2019-08-25 11:05:59	ga_s2bm_ard_3-2-1_52JDM_2019-08-25_final.stac-item
2019-08-25 11:05:59	ga_s2bm_ard_3-2-1_52JDL_2019-08-25_final.stac-item
2019-08-25 11:06:00	ga_s2bm_ard_3-2-1_52JCM_2019-08-25_final.stac-item
2019-08-25 11:06:03	ga_s2bm_ard_3-2-1_52JBM_2019-08-25_final.stac-item
2019-08-25 11:06:04	ga_s2bm_ard_3-2-1_52JEL_2019-08-25_final.stac-item
2019-08-25 11:06:08	ga_s2bm_ard_3-2-1_52JDL_2019-08-25_final.stac-item
2019-08-25 11:06:11	ga_s2bm_ard_3-2-1_52JCL_2019-08-25_final.stac-item
2019-08-25 11:06:15	ga_s2bm_ard_3-2-1_52JBL_2019-08-25_final.stac-item
2019-09-16 10:07:03	ga_s2bm_ard_3-2-1_54HYE_2019-09-16_final.stac-item
2019-09-16 10:07:07	ga_s2bm_ard_3-2-1_54HXE_2019-09-16_final.stac-item
2019-09-16 10:07:11	ga_s2bm_ard_3-2-1_54HWE_2019-09-16_final.stac-item
2019-09-16 10:07:14	ga_s2bm_ard_3-2-1_54HYD_2019-09-16_final.stac-item
2019-09-16 10:07:15	ga_s2bm_ard_3-2-1_54HVE_2019-09-16_final.stac-item
2019-09-16 10:07:22	ga_s2bm_ard_3-2-1_54HXD_2019-09-16_final.stac-item
2019-09-16 10:07:26	ga_s2bm_ard_3-2-1_54HWD_2019-09-16_final.stac-item
2019-09-16 10:07:29	ga_s2bm_ard_3-2-1_54HVD_2019-09-16_final.stac-item
2019-09-16 10:07:36	ga_s2bm_ard_3-2-1_54HXC_2019-09-16_final.stac-item
2019-09-16 10:07:40	ga_s2bm_ard_3-2-1_54HWC_2019-09-16_final.stac-item
2019-09-16 11:41:00	ga_s2bm_ard_3-2-1_51LVG_2019-09-16_final.stac-item
2019-09-16 11:41:15	ga_s2bm_ard_3-2-1_51LVF_2019-09-16_final.stac-item
2019-09-16 11:41:18	ga_s2bm_ard_3-2-1_51LUF_2019-09-16_final.stac-item
2019-09-16 11:41:26	ga_s2bm_ard_3-2-1_51LWE_2019-09-16_final.stac-item
2019-09-16 11:41:29	ga_s2bm_ard_3-2-1_51LVE_2019-09-16_final.stac-item
2019-09-16 11:41:32	ga_s2bm_ard_3-2-1_51LUE_2019-09-16_final.stac-item
2019-09-16 11:41:55	ga_s2bm_ard_3-2-1_51LWC_2019-09-16_final.stac-item
2019-09-16 11:41:58	ga_s2bm_ard_3-2-1_51LVC_2019-09-16_final.stac-item
2019-09-16 11:42:09	ga_s2bm_ard_3-2-1_51KWB_2019-09-16_final.stac-item
2019-09-16 11:42:13	ga_s2bm_ard_3-2-1_51KVB_2019-09-16_final.stac-item
2019-09-16 11:42:20	ga_s2bm_ard_3-2-1_51KWA_2019-09-16_final.stac-item
2019-09-16 11:42:22	ga_s2bm_ard_3-2-1_51KVA_2019-09-16_final.stac-item
2019-09-16 11:42:23	ga_s2bm_ard_3-2-1_51KUA_2019-09-16_final.stac-item
2019-09-16 11:42:24	ga_s2bm_ard_3-2-1_51KWA_2019-09-16_final.stac-item
2019-09-16 11:42:28	ga_s2bm_ard_3-2-1_51KVA_2019-09-16_final.stac-item
2019-09-16 11:42:31	ga_s2bm_ard_3-2-1_51KUA_2019-09-16_final.stac-item
2019-09-16 11:42:42	ga_s2bm_ard_3-2-1_51KVV_2019-09-16_final.stac-item
2019-09-16 11:42:45	ga_s2bm_ard_3-2-1_51KUV_2019-09-16_final.stac-item
2019-09-16 11:42:56	ga_s2bm_ard_3-2-1_51KVU_2019-09-16_final.stac-item
2019-09-16 11:43:00	ga_s2bm_ard_3-2-1_51KUU_2019-09-16_final.stac-item
2019-09-16 11:43:03	ga_s2bm_ard_3-2-1_51KTU_2019-09-16_final.stac-item
2019-09-16 11:43:04	ga_s2bm_ard_3-2-1_50KRD_2019-09-16_final.stac-item
2019-09-16 11:43:11	ga_s2bm_ard_3-2-1_51KVT_2019-09-16_final.stac-item
2019-09-16 11:43:14	ga_s2bm_ard_3-2-1_51KUT_2019-09-16_final.stac-item
2019-09-16 11:43:18	ga_s2bm_ard_3-2-1_51KTT_2019-09-16_final.stac-item
2019-09-16 11:43:18	ga_s2bm_ard_3-2-1_50KRC_2019-09-16_final.stac-item
2019-09-16 11:43:21	ga_s2bm_ard_3-2-1_50KQC_2019-09-16_final.stac-item
2019-09-16 11:43:25	ga_s2bm_ard_3-2-1_51KVS_2019-09-16_final.stac-item
2019-09-16 11:43:29	ga_s2bm_ard_3-2-1_51KUS_2019-09-16_final.stac-item
2019-09-16 11:43:32	ga_s2bm_ard_3-2-1_51KTS_2019-09-16_final.stac-item
2019-09-16 11:43:33	ga_s2bm_ard_3-2-1_50KRB_2019-09-16_final.stac-item
2019-09-16 11:43:36	ga_s2bm_ard_3-2-1_51KVR_2019-09-16_final.stac-item
2019-09-16 11:43:36	ga_s2bm_ard_3-2-1_50KQB_2019-09-16_final.stac-item
2019-09-16 11:43:43	ga_s2bm_ard_3-2-1_51KUR_2019-09-16_final.stac-item
2019-09-16 11:43:47	ga_s2bm_ard_3-2-1_51KTR_2019-09-16_final.stac-item
2019-09-16 11:43:47	ga_s2bm_ard_3-2-1_50KRA_2019-09-16_final.stac-item
2019-09-16 11:43:51	ga_s2bm_ard_3-2-1_50KQA_2019-09-16_final.stac-item
2019-09-16 11:43:58	ga_s2bm_ard_3-2-1_51KUQ_2019-09-16_final.stac-item
2019-09-16 11:44:01	ga_s2bm_ard_3-2-1_51KTQ_2019-09-16_final.stac-item
2019-09-16 11:44:02	ga_s2bm_ard_3-2-1_50KRV_2019-09-16_final.stac-item
2019-09-16 11:44:05	ga_s2bm_ard_3-2-1_50KQV_2019-09-16_final.stac-item
2019-09-16 11:44:10	ga_s2bm_ard_3-2-1_50KPV_2019-09-16_final.stac-item
2019-09-16 11:44:13	ga_s2bm_ard_3-2-1_51KUP_2019-09-16_final.stac-item
2019-09-16 11:44:16	ga_s2bm_ard_3-2-1_50KRU_2019-09-16_final.stac-item
2019-09-16 11:44:16	ga_s2bm_ard_3-2-1_51KTP_2019-09-16_final.stac-item
2019-09-16 11:44:19	ga_s2bm_ard_3-2-1_50KQU_2019-09-16_final.stac-item
2019-09-16 11:44:23	ga_s2bm_ard_3-2-1_50KPU_2019-09-16_final.stac-item

Return to ga_s2bm_ard_3 across 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

All months