Search ga_s2bm_ard_3 whole collection

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
2023-04-16 11:04:04	ga_s2bm_ard_3-2-1_52KEU_2023-04-16_final
2023-04-17 10:32:06	ga_s2bm_ard_3-2-1_53KRA_2023-04-17_final
2023-04-17 10:33:18	ga_s2bm_ard_3-2-1_53KRR_2023-04-17_final
2023-04-17 10:33:32	ga_s2bm_ard_3-2-1_53KRQ_2023-04-17_final
2023-04-17 10:33:36	ga_s2bm_ard_3-2-1_53KQQ_2023-04-17_final
2023-04-17 10:33:51	ga_s2bm_ard_3-2-1_53KQP_2023-04-17_final
2023-04-17 10:34:01	ga_s2bm_ard_3-2-1_53JRN_2023-04-17_final
2023-04-17 10:34:09	ga_s2bm_ard_3-2-1_53JPN_2023-04-17_final
2023-04-17 10:34:23	ga_s2bm_ard_3-2-1_53JPM_2023-04-17_final
2023-04-17 10:35:54	ga_s2bm_ard_3-2-1_53JNF_2023-04-17_final
2023-04-17 10:36:12	ga_s2bm_ard_3-2-1_53HME_2023-04-17_final
2023-04-17 10:36:26	ga_s2bm_ard_3-2-1_53HMD_2023-04-17_final
2023-04-17 10:37:10	ga_s2bm_ard_3-2-1_53HPV_2023-04-17_final
2023-04-17 12:13:41	ga_s2bm_ard_3-2-1_49KHS_2023-04-17_final
2023-04-17 12:13:55	ga_s2bm_ard_3-2-1_50KKA_2023-04-17_final
2023-04-17 12:13:56	ga_s2bm_ard_3-2-1_49KHR_2023-04-17_final
2023-04-17 12:14:00	ga_s2bm_ard_3-2-1_49KGR_2023-04-17_final
2023-04-17 12:14:09	ga_s2bm_ard_3-2-1_50KKV_2023-04-17_final
2023-04-17 12:14:22	ga_s2bm_ard_3-2-1_49KHP_2023-04-17_final
2023-04-17 12:14:47	ga_s2bm_ard_3-2-1_49JFN_2023-04-17_final
2023-04-17 12:15:01	ga_s2bm_ard_3-2-1_49JFM_2023-04-17_final
2023-04-17 12:15:12	ga_s2bm_ard_3-2-1_49JGL_2023-04-17_final
2023-04-17 12:15:21	ga_s2bm_ard_3-2-1_49JGK_2023-04-17_final
2023-04-18 11:40:59	ga_s2bm_ard_3-2-1_51LWG_2023-04-18_final
2023-04-18 11:41:02	ga_s2bm_ard_3-2-1_51LVG_2023-04-18_final
2023-04-18 11:41:17	ga_s2bm_ard_3-2-1_51LVF_2023-04-18_final
2023-04-18 11:41:28	ga_s2bm_ard_3-2-1_51LWE_2023-04-18_final
2023-04-18 11:41:31	ga_s2bm_ard_3-2-1_51LVE_2023-04-18_final
2023-04-18 11:41:34	ga_s2bm_ard_3-2-1_51LUE_2023-04-18_final
2023-04-18 11:41:49	ga_s2bm_ard_3-2-1_51LUD_2023-04-18_final
2023-04-18 11:41:57	ga_s2bm_ard_3-2-1_51LWC_2023-04-18_final
2023-04-18 11:42:04	ga_s2bm_ard_3-2-1_51LUC_2023-04-18_final
2023-04-18 11:42:11	ga_s2bm_ard_3-2-1_51KWB_2023-04-18_final
2023-04-18 11:42:15	ga_s2bm_ard_3-2-1_51KVB_2023-04-18_final
2023-04-18 11:42:18	ga_s2bm_ard_3-2-1_51KUB_2023-04-18_final
2023-04-18 11:42:23	ga_s2bm_ard_3-2-1_51KWA_2023-04-18_final
2023-04-18 11:42:33	ga_s2bm_ard_3-2-1_51KUA_2023-04-18_final
2023-04-18 11:43:06	ga_s2bm_ard_3-2-1_50KRD_2023-04-18_final
2023-04-18 11:43:10	ga_s2bm_ard_3-2-1_50KQD_2023-04-18_final
2023-04-18 11:43:13	ga_s2bm_ard_3-2-1_51KVT_2023-04-18_final
2023-04-18 11:43:16	ga_s2bm_ard_3-2-1_51KUT_2023-04-18_final
2023-04-18 11:43:23	ga_s2bm_ard_3-2-1_50KQC_2023-04-18_final
2023-04-18 11:43:26	ga_s2bm_ard_3-2-1_51KVS_2023-04-18_final
2023-04-18 11:43:31	ga_s2bm_ard_3-2-1_51KUS_2023-04-18_final
2023-04-18 11:43:45	ga_s2bm_ard_3-2-1_51KUR_2023-04-18_final
2023-04-18 11:43:49	ga_s2bm_ard_3-2-1_51KTR_2023-04-18_final
2023-04-18 11:44:00	ga_s2bm_ard_3-2-1_51KUQ_2023-04-18_final
2023-04-18 11:44:03	ga_s2bm_ard_3-2-1_51KTQ_2023-04-18_final
2023-04-18 11:44:03	ga_s2bm_ard_3-2-1_50KRV_2023-04-18_final
2023-04-18 11:44:07	ga_s2bm_ard_3-2-1_50KQV_2023-04-18_final
2023-04-18 11:44:15	ga_s2bm_ard_3-2-1_51KUP_2023-04-18_final
2023-04-18 11:44:18	ga_s2bm_ard_3-2-1_50KRU_2023-04-18_final
2023-04-18 11:44:18	ga_s2bm_ard_3-2-1_51KTP_2023-04-18_final
2023-04-18 11:44:21	ga_s2bm_ard_3-2-1_50KQU_2023-04-18_final
2023-04-18 11:44:32	ga_s2bm_ard_3-2-1_50JRT_2023-04-18_final
2023-04-18 11:44:32	ga_s2bm_ard_3-2-1_51JTN_2023-04-18_final
2023-04-18 11:44:36	ga_s2bm_ard_3-2-1_50JQT_2023-04-18_final
2023-04-18 11:44:46	ga_s2bm_ard_3-2-1_50JRS_2023-04-18_final
2023-04-18 11:44:47	ga_s2bm_ard_3-2-1_51JTM_2023-04-18_final
2023-04-18 11:44:53	ga_s2bm_ard_3-2-1_51JUL_2023-04-18_final
2023-04-18 11:45:01	ga_s2bm_ard_3-2-1_51JTL_2023-04-18_final
2023-04-18 11:45:26	ga_s2bm_ard_3-2-1_50JNQ_2023-04-18_final
2023-04-18 11:45:34	ga_s2bm_ard_3-2-1_50JQP_2023-04-18_final
2023-04-18 11:45:37	ga_s2bm_ard_3-2-1_50JPP_2023-04-18_final
2023-04-18 11:45:41	ga_s2bm_ard_3-2-1_50JNP_2023-04-18_final
2023-04-18 11:45:45	ga_s2bm_ard_3-2-1_51JTH_2023-04-18_final
2023-04-18 11:45:48	ga_s2bm_ard_3-2-1_50JQN_2023-04-18_final
2023-04-18 11:45:52	ga_s2bm_ard_3-2-1_50JPN_2023-04-18_final
2023-04-18 11:45:55	ga_s2bm_ard_3-2-1_50JNN_2023-04-18_final
2023-04-18 11:45:58	ga_s2bm_ard_3-2-1_51JTG_2023-04-18_final
2023-04-18 11:46:02	ga_s2bm_ard_3-2-1_50JQM_2023-04-18_final
2023-04-18 11:46:06	ga_s2bm_ard_3-2-1_50JPM_2023-04-18_final
2023-04-18 11:46:09	ga_s2bm_ard_3-2-1_51JTF_2023-04-18_final
2023-04-18 11:46:10	ga_s2bm_ard_3-2-1_50JNM_2023-04-18_final
2023-04-18 11:46:14	ga_s2bm_ard_3-2-1_50JMM_2023-04-18_final
2023-04-18 11:46:17	ga_s2bm_ard_3-2-1_50JQL_2023-04-18_final
2023-04-18 11:46:28	ga_s2bm_ard_3-2-1_50JML_2023-04-18_final
2023-04-18 11:46:42	ga_s2bm_ard_3-2-1_50HMK_2023-04-18_final
2023-04-18 11:46:45	ga_s2bm_ard_3-2-1_50HQJ_2023-04-18_final
2023-04-18 11:46:55	ga_s2bm_ard_3-2-1_50HQH_2023-04-18_final
2023-04-18 11:47:04	ga_s2bm_ard_3-2-1_50HPH_2023-04-18_final
2023-04-18 11:47:16	ga_s2bm_ard_3-2-1_50HLH_2023-04-18_final
2023-04-18 11:47:18	ga_s2bm_ard_3-2-1_50HPG_2023-04-18_final
2023-04-18 11:47:22	ga_s2bm_ard_3-2-1_50HNG_2023-04-18_final
2023-04-18 11:47:26	ga_s2bm_ard_3-2-1_50HMG_2023-04-18_final
2023-04-28 10:07:51	ga_s2bm_ard_3-2-1_54HWB_2023-04-28_nrt
2023-04-28 11:40:33	ga_s2bm_ard_3-2-1_51LVJ_2023-04-28_nrt
2023-04-28 11:40:47	ga_s2bm_ard_3-2-1_51LVH_2023-04-28_nrt
2023-04-28 11:41:13	ga_s2bm_ard_3-2-1_51LWF_2023-04-28_nrt
2023-04-28 11:41:39	ga_s2bm_ard_3-2-1_51LTE_2023-04-28_nrt
2023-04-28 11:41:46	ga_s2bm_ard_3-2-1_51LVD_2023-04-28_nrt
2023-04-28 11:42:21	ga_s2bm_ard_3-2-1_51KTB_2023-04-28_nrt
2023-04-28 11:42:36	ga_s2bm_ard_3-2-1_51KTA_2023-04-28_nrt
2023-04-28 11:42:50	ga_s2bm_ard_3-2-1_51KTV_2023-04-28_nrt
2023-04-28 11:42:51	ga_s2bm_ard_3-2-1_50KRE_2023-04-28_nrt
2023-04-28 11:47:31	ga_s2bm_ard_3-2-1_50HPF_2023-04-28_nrt
2023-04-28 11:47:35	ga_s2bm_ard_3-2-1_50HMF_2023-04-28_nrt
2023-04-29 11:16:29	ga_s2bm_ard_3-2-1_52HCJ_2023-04-29_nrt
2023-04-29 11:16:36	ga_s2bm_ard_3-2-1_52HBJ_2023-04-29_nrt
2023-04-29 11:16:51	ga_s2bm_ard_3-2-1_52HBH_2023-04-29_nrt

Return to ga_s2bm_ard_3 whole collection 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

All years