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
2019-07-01 11:54:17	ga_s2bm_ard_3-2-1_50KNV_2019-07-01_final.stac-item
2019-07-04 12:05:06	ga_s2bm_ard_3-2-1_50JKS_2019-07-04_final.stac-item
2019-07-04 12:05:22	ga_s2bm_ard_3-2-1_49JGL_2019-07-04_final.stac-item
2019-07-04 12:05:27	ga_s2bm_ard_3-2-1_50JKR_2019-07-04_final.stac-item
2019-07-04 12:05:29	ga_s2bm_ard_3-2-1_49JGK_2019-07-04_final.stac-item
2019-07-04 12:05:35	ga_s2bm_ard_3-2-1_50JKQ_2019-07-04_final.stac-item
2019-07-04 12:05:38	ga_s2bm_ard_3-2-1_49JGK_2019-07-04_final.stac-item
2019-07-04 12:05:49	ga_s2bm_ard_3-2-1_50JKP_2019-07-04_final.stac-item
2019-07-04 12:06:04	ga_s2bm_ard_3-2-1_50JKN_2019-07-04_final.stac-item
2019-07-07 12:15:19	ga_s2bm_ard_3-2-1_49JGL_2019-07-07_final.stac-item
2019-07-11 11:54:35	ga_s2bm_ard_3-2-1_50KMU_2019-07-11_final.stac-item
2019-07-11 11:55:55	ga_s2bm_ard_3-2-1_50JKP_2019-07-11_final.stac-item
2019-07-11 11:56:08	ga_s2bm_ard_3-2-1_50JKN_2019-07-11_final.stac-item
2019-07-14 12:05:06	ga_s2bm_ard_3-2-1_50JKS_2019-07-14_final.stac-item
2019-07-14 12:05:17	ga_s2bm_ard_3-2-1_49JFM_2019-07-14_final.stac-item
2019-07-14 12:05:31	ga_s2bm_ard_3-2-1_49JGL_2019-07-14_final.stac-item
2019-07-14 12:05:38	ga_s2bm_ard_3-2-1_49JGK_2019-07-14_final.stac-item
2019-07-14 12:06:04	ga_s2bm_ard_3-2-1_50JKN_2019-07-14_final.stac-item
2019-07-17 12:15:19	ga_s2bm_ard_3-2-1_49JGL_2019-07-17_final.stac-item
2019-07-17 12:15:28	ga_s2bm_ard_3-2-1_49JGK_2019-07-17_final.stac-item
2019-07-21 11:54:20	ga_s2bm_ard_3-2-1_50KMV_2019-07-21_final.stac-item
2019-07-21 11:56:08	ga_s2bm_ard_3-2-1_50JKN_2019-07-21_final.stac-item
2019-07-24 12:05:05	ga_s2bm_ard_3-2-1_50JKS_2019-07-24_final.stac-item
2019-07-24 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-07-24_final.stac-item
2019-07-24 12:05:30	ga_s2bm_ard_3-2-1_50JKQ_2019-07-24_final.stac-item
2019-07-24 12:05:38	ga_s2bm_ard_3-2-1_49JGK_2019-07-24_final.stac-item
2019-07-24 12:06:04	ga_s2bm_ard_3-2-1_50JKN_2019-07-24_final.stac-item
2019-07-27 12:15:28	ga_s2bm_ard_3-2-1_49JGK_2019-07-27_final.stac-item
2019-07-31 11:53:44	ga_s2bm_ard_3-2-1_50KPB_2019-07-31_final.stac-item
2019-07-31 11:54:27	ga_s2bm_ard_3-2-1_50KPU_2019-07-31_final.stac-item
2019-07-31 11:56:07	ga_s2bm_ard_3-2-1_50JKN_2019-07-31_final.stac-item
2019-08-03 12:04:14	ga_s2bm_ard_3-2-1_50KMV_2019-08-03_final.stac-item
2019-08-03 12:04:29	ga_s2bm_ard_3-2-1_50KMU_2019-08-03_final.stac-item
2019-08-03 12:04:47	ga_s2bm_ard_3-2-1_50JLT_2019-08-03_final.stac-item
2019-08-03 12:05:05	ga_s2bm_ard_3-2-1_50JKS_2019-08-03_final.stac-item
2019-08-03 12:05:34	ga_s2bm_ard_3-2-1_50JKQ_2019-08-03_final.stac-item
2019-08-03 12:05:37	ga_s2bm_ard_3-2-1_49JGK_2019-08-03_final.stac-item
2019-08-06 12:15:18	ga_s2bm_ard_3-2-1_49JGL_2019-08-06_final.stac-item
2019-08-07 11:43:40	ga_s2bm_ard_3-2-1_50KRB_2019-08-07_final.stac-item
2019-08-07 11:43:55	ga_s2bm_ard_3-2-1_50KRA_2019-08-07_final.stac-item
2019-08-07 11:44:17	ga_s2bm_ard_3-2-1_50KPV_2019-08-07_final.stac-item
2019-08-07 11:44:30	ga_s2bm_ard_3-2-1_50KPU_2019-08-07_final.stac-item
2019-08-07 11:44:42	ga_s2bm_ard_3-2-1_50JQT_2019-08-07_final.stac-item
2019-08-07 11:44:45	ga_s2bm_ard_3-2-1_50JPT_2019-08-07_final.stac-item
2019-08-10 11:53:43	ga_s2bm_ard_3-2-1_50KPB_2019-08-10_final.stac-item
2019-08-10 11:53:57	ga_s2bm_ard_3-2-1_50KPA_2019-08-10_final.stac-item
2019-08-10 11:54:11	ga_s2bm_ard_3-2-1_50KPV_2019-08-10_final.stac-item
2019-08-10 11:54:15	ga_s2bm_ard_3-2-1_50KNV_2019-08-10_final.stac-item
2019-08-10 11:54:18	ga_s2bm_ard_3-2-1_50KMV_2019-08-10_final.stac-item
2019-08-10 11:54:26	ga_s2bm_ard_3-2-1_50KPU_2019-08-10_final.stac-item
2019-08-10 11:54:30	ga_s2bm_ard_3-2-1_50JQT_2019-08-10_final.stac-item
2019-08-10 11:54:33	ga_s2bm_ard_3-2-1_50KMU_2019-08-10_final.stac-item
2019-08-10 11:54:44	ga_s2bm_ard_3-2-1_50JNT_2019-08-10_final.stac-item
2019-08-10 11:54:51	ga_s2bm_ard_3-2-1_50JLT_2019-08-10_final.stac-item
2019-08-13 12:04:13	ga_s2bm_ard_3-2-1_50KMV_2019-08-13_final.stac-item
2019-08-13 12:04:28	ga_s2bm_ard_3-2-1_50KMU_2019-08-13_final.stac-item
2019-08-13 12:04:46	ga_s2bm_ard_3-2-1_50JLT_2019-08-13_final.stac-item
2019-08-13 12:05:33	ga_s2bm_ard_3-2-1_50JKQ_2019-08-13_final.stac-item
2019-08-16 12:15:26	ga_s2bm_ard_3-2-1_49JGK_2019-08-16_final.stac-item
2019-08-17 11:43:24	ga_s2bm_ard_3-2-1_50KRC_2019-08-17_final.stac-item
2019-08-17 11:44:16	ga_s2bm_ard_3-2-1_50KPV_2019-08-17_final.stac-item
2019-08-17 11:44:28	ga_s2bm_ard_3-2-1_50KPU_2019-08-17_final.stac-item
2019-08-17 11:44:33	ga_s2bm_ard_3-2-1_50JQT_2019-08-17_final.stac-item
2019-08-17 11:44:34	ga_s2bm_ard_3-2-1_50KPU_2019-08-17_final.stac-item
2019-08-17 11:44:41	ga_s2bm_ard_3-2-1_50JQT_2019-08-17_final.stac-item
2019-08-17 11:44:44	ga_s2bm_ard_3-2-1_50JPT_2019-08-17_final.stac-item
2019-08-20 11:53:16	ga_s2bm_ard_3-2-1_50KRC_2019-08-20_final.stac-item
2019-08-20 11:53:41	ga_s2bm_ard_3-2-1_50KPB_2019-08-20_final.stac-item
2019-08-20 11:53:56	ga_s2bm_ard_3-2-1_50KPA_2019-08-20_final.stac-item
2019-08-20 11:54:10	ga_s2bm_ard_3-2-1_50KPV_2019-08-20_final.stac-item
2019-08-20 11:54:14	ga_s2bm_ard_3-2-1_50KNV_2019-08-20_final.stac-item
2019-08-20 11:54:17	ga_s2bm_ard_3-2-1_50KMV_2019-08-20_final.stac-item
2019-08-20 11:54:24	ga_s2bm_ard_3-2-1_50KPU_2019-08-20_final.stac-item
2019-08-20 11:54:29	ga_s2bm_ard_3-2-1_50JQT_2019-08-20_final.stac-item
2019-08-20 11:54:32	ga_s2bm_ard_3-2-1_50KMU_2019-08-20_final.stac-item
2019-08-20 11:54:43	ga_s2bm_ard_3-2-1_50JNT_2019-08-20_final.stac-item
2019-08-20 11:54:50	ga_s2bm_ard_3-2-1_50JLT_2019-08-20_final.stac-item
2019-08-23 12:04:12	ga_s2bm_ard_3-2-1_50KMV_2019-08-23_final.stac-item
2019-08-23 12:04:26	ga_s2bm_ard_3-2-1_50KMU_2019-08-23_final.stac-item
2019-08-23 12:04:44	ga_s2bm_ard_3-2-1_50JLT_2019-08-23_final.stac-item
2019-08-23 12:05:02	ga_s2bm_ard_3-2-1_50JKS_2019-08-23_final.stac-item
2019-08-23 12:05:34	ga_s2bm_ard_3-2-1_49JGK_2019-08-23_final.stac-item
2019-08-23 12:06:00	ga_s2bm_ard_3-2-1_50JKN_2019-08-23_final.stac-item
2019-08-26 12:15:15	ga_s2bm_ard_3-2-1_49JGL_2019-08-26_final.stac-item
2019-08-27 11:43:23	ga_s2bm_ard_3-2-1_50KRC_2019-08-27_final.stac-item
2019-08-27 11:44:14	ga_s2bm_ard_3-2-1_50KPV_2019-08-27_final.stac-item
2019-08-27 11:44:27	ga_s2bm_ard_3-2-1_50KPU_2019-08-27_final.stac-item
2019-08-27 11:44:39	ga_s2bm_ard_3-2-1_50JQT_2019-08-27_final.stac-item
2019-08-27 11:44:42	ga_s2bm_ard_3-2-1_50JPT_2019-08-27_final.stac-item
2019-08-30 11:53:14	ga_s2bm_ard_3-2-1_50KRC_2019-08-30_final.stac-item
2019-08-30 11:53:39	ga_s2bm_ard_3-2-1_50KPB_2019-08-30_final.stac-item
2019-08-30 11:53:54	ga_s2bm_ard_3-2-1_50KPA_2019-08-30_final.stac-item
2019-08-30 11:54:08	ga_s2bm_ard_3-2-1_50KPV_2019-08-30_final.stac-item
2019-08-30 11:54:12	ga_s2bm_ard_3-2-1_50KNV_2019-08-30_final.stac-item
2019-08-30 11:54:15	ga_s2bm_ard_3-2-1_50KMV_2019-08-30_final.stac-item
2019-08-30 11:54:23	ga_s2bm_ard_3-2-1_50KPU_2019-08-30_final.stac-item
2019-08-30 11:54:27	ga_s2bm_ard_3-2-1_50JQT_2019-08-30_final.stac-item
2019-08-30 11:54:30	ga_s2bm_ard_3-2-1_50KMU_2019-08-30_final.stac-item
2019-08-30 11:54:41	ga_s2bm_ard_3-2-1_50JNT_2019-08-30_final.stac-item
2019-08-30 11:54:48	ga_s2bm_ard_3-2-1_50JLT_2019-08-30_final.stac-item

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