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
2017-10-26 11:41:25	ga_s2bm_ard_3-2-1_51JTM_2017-10-26_final.stac-item
2017-10-26 11:41:25	ga_s2bm_ard_3-2-1_51JTN_2017-10-26_final.stac-item
2017-10-26 11:41:25	ga_s2bm_ard_3-2-1_51JUM_2017-10-26_final.stac-item
2017-10-26 11:41:25	ga_s2bm_ard_3-2-1_51JUN_2017-10-26_final.stac-item
2017-10-26 11:41:25	ga_s2bm_ard_3-2-1_50JPS_2017-10-26_final.stac-item
2017-10-26 11:41:25	ga_s2bm_ard_3-2-1_50JPT_2017-10-26_final.stac-item
2017-10-26 11:41:25	ga_s2bm_ard_3-2-1_50JQS_2017-10-26_final.stac-item
2017-10-26 11:41:25	ga_s2bm_ard_3-2-1_50JQT_2017-10-26_final.stac-item
2017-10-26 11:41:25	ga_s2bm_ard_3-2-1_50JRS_2017-10-26_final.stac-item
2017-10-26 11:41:25	ga_s2bm_ard_3-2-1_50JRT_2017-10-26_final.stac-item
2017-10-29 10:13:28	ga_s2bm_ard_3-2-1_54JVT_2017-10-29_final.stac-item
2017-10-29 10:13:28	ga_s2bm_ard_3-2-1_54JWT_2017-10-29_final.stac-item
2017-10-29 10:13:28	ga_s2bm_ard_3-2-1_54JXS_2017-10-29_final.stac-item
2017-10-29 10:13:28	ga_s2bm_ard_3-2-1_54JXT_2017-10-29_final.stac-item
2017-10-29 10:13:28	ga_s2bm_ard_3-2-1_54JYS_2017-10-29_final.stac-item
2017-10-29 10:13:28	ga_s2bm_ard_3-2-1_54JYT_2017-10-29_final.stac-item
2017-10-31 10:47:11	ga_s2bm_ard_3-2-1_53JKM_2017-10-31_final.stac-item
2017-10-31 10:47:11	ga_s2bm_ard_3-2-1_53JKN_2017-10-31_final.stac-item
2017-10-31 10:47:11	ga_s2bm_ard_3-2-1_53JLM_2017-10-31_final.stac-item
2017-10-31 10:47:11	ga_s2bm_ard_3-2-1_52JFS_2017-10-31_final.stac-item
2017-10-31 10:47:11	ga_s2bm_ard_3-2-1_53JLN_2017-10-31_final.stac-item
2017-10-31 10:47:11	ga_s2bm_ard_3-2-1_52JFT_2017-10-31_final.stac-item
2017-10-31 10:47:11	ga_s2bm_ard_3-2-1_52JGS_2017-10-31_final.stac-item
2017-10-31 10:47:11	ga_s2bm_ard_3-2-1_52JGT_2017-10-31_final.stac-item
2017-10-31 10:47:11	ga_s2bm_ard_3-2-1_52JHS_2017-10-31_final.stac-item
2017-10-31 10:47:11	ga_s2bm_ard_3-2-1_52JHT_2017-10-31_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JTS_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JTT_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JUS_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_53JRM_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JUT_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_53JRN_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JVT_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JWT_2017-11-01_final.stac-item
2017-11-06 09:32:26	ga_s2bm_ard_3-2-1_56JLT_2017-11-06_final.stac-item
2017-11-06 09:32:26	ga_s2bm_ard_3-2-1_56JMT_2017-11-06_final.stac-item
2017-11-08 10:06:51	ga_s2bm_ard_3-2-1_54JVT_2017-11-08_final.stac-item
2017-11-08 10:06:51	ga_s2bm_ard_3-2-1_54JWT_2017-11-08_final.stac-item
2017-11-08 10:06:51	ga_s2bm_ard_3-2-1_54JXS_2017-11-08_final.stac-item
2017-11-08 10:06:51	ga_s2bm_ard_3-2-1_54JXT_2017-11-08_final.stac-item
2017-11-08 10:06:51	ga_s2bm_ard_3-2-1_54JYS_2017-11-08_final.stac-item
2017-11-08 10:06:51	ga_s2bm_ard_3-2-1_54JYT_2017-11-08_final.stac-item
2017-11-10 10:53:01	ga_s2bm_ard_3-2-1_53JKM_2017-11-10_final.stac-item
2017-11-10 10:53:01	ga_s2bm_ard_3-2-1_53JKN_2017-11-10_final.stac-item
2017-11-10 10:53:01	ga_s2bm_ard_3-2-1_53JLM_2017-11-10_final.stac-item
2017-11-10 10:53:01	ga_s2bm_ard_3-2-1_52JFS_2017-11-10_final.stac-item
2017-11-10 10:53:01	ga_s2bm_ard_3-2-1_53JLN_2017-11-10_final.stac-item
2017-11-10 10:53:01	ga_s2bm_ard_3-2-1_52JFT_2017-11-10_final.stac-item
2017-11-10 10:53:01	ga_s2bm_ard_3-2-1_52JGS_2017-11-10_final.stac-item
2017-11-10 10:53:01	ga_s2bm_ard_3-2-1_52JGT_2017-11-10_final.stac-item
2017-11-10 10:53:01	ga_s2bm_ard_3-2-1_52JHS_2017-11-10_final.stac-item
2017-11-10 10:53:01	ga_s2bm_ard_3-2-1_52JHT_2017-11-10_final.stac-item
2017-11-11 10:23:14	ga_s2bm_ard_3-2-1_54JTS_2017-11-11_final.stac-item
2017-11-11 10:23:14	ga_s2bm_ard_3-2-1_54JTT_2017-11-11_final.stac-item
2017-11-11 10:23:14	ga_s2bm_ard_3-2-1_54JUS_2017-11-11_final.stac-item
2017-11-11 10:23:14	ga_s2bm_ard_3-2-1_53JRM_2017-11-11_final.stac-item
2017-11-11 10:23:14	ga_s2bm_ard_3-2-1_54JUT_2017-11-11_final.stac-item
2017-11-11 10:23:14	ga_s2bm_ard_3-2-1_53JRN_2017-11-11_final.stac-item
2017-11-11 10:23:14	ga_s2bm_ard_3-2-1_54JVT_2017-11-11_final.stac-item
2017-11-11 10:23:14	ga_s2bm_ard_3-2-1_54JWT_2017-11-11_final.stac-item
2017-11-12 09:50:41	ga_s2bm_ard_3-2-1_55JCN_2017-11-12_final.stac-item
2017-11-12 09:50:41	ga_s2bm_ard_3-2-1_55JDN_2017-11-12_final.stac-item
2017-11-12 09:50:41	ga_s2bm_ard_3-2-1_55JEN_2017-11-12_final.stac-item
2017-11-12 09:50:41	ga_s2bm_ard_3-2-1_55JFM_2017-11-12_final.stac-item
2017-11-12 09:50:41	ga_s2bm_ard_3-2-1_55JFN_2017-11-12_final.stac-item
2017-11-12 09:50:41	ga_s2bm_ard_3-2-1_55JGM_2017-11-12_final.stac-item
2017-11-12 09:50:41	ga_s2bm_ard_3-2-1_55JGN_2017-11-12_final.stac-item
2019-05-22 11:54:41	ga_s2bm_ard_3-2-1_50JPT_2019-05-22_final.stac-item
2019-05-22 11:54:48	ga_s2bm_ard_3-2-1_50JPT_2019-05-22_final.stac-item
2019-05-22 11:54:50	ga_s2bm_ard_3-2-1_50JNT_2019-05-22_final.stac-item
2019-05-22 11:54:52	ga_s2bm_ard_3-2-1_50JMT_2019-05-22_final.stac-item
2019-05-22 11:54:54	ga_s2bm_ard_3-2-1_50JLT_2019-05-22_final.stac-item
2019-05-30 09:33:44	ga_s2bm_ard_3-2-1_56JNT_2019-05-30_final.stac-item
2019-05-30 09:33:47	ga_s2bm_ard_3-2-1_56JMT_2019-05-30_final.stac-item
2019-05-30 09:33:51	ga_s2bm_ard_3-2-1_56JLT_2019-05-30_final.stac-item
2019-05-30 09:33:58	ga_s2bm_ard_3-2-1_56JKT_2019-05-30_final.stac-item
2019-05-30 09:34:05	ga_s2bm_ard_3-2-1_56JLS_2019-05-30_final.stac-item
2019-05-30 09:34:09	ga_s2bm_ard_3-2-1_55JHM_2019-05-30_final.stac-item
2019-05-30 09:34:09	ga_s2bm_ard_3-2-1_56JKS_2019-05-30_final.stac-item
2019-12-04 12:14:35	ga_s2bm_ard_3-2-1_49JGN_2019-12-04_final.stac-item
2019-12-04 12:14:39	ga_s2bm_ard_3-2-1_49JFN_2019-12-04_final.stac-item
2019-12-04 12:14:50	ga_s2bm_ard_3-2-1_49JGM_2019-12-04_final.stac-item
2019-12-04 12:14:54	ga_s2bm_ard_3-2-1_49JFM_2019-12-04_final.stac-item
2019-12-05 10:03:40	ga_s2bm_ard_3-2-1_55JDN_2019-12-05_final.stac-item
2019-12-05 10:03:44	ga_s2bm_ard_3-2-1_55JCN_2019-12-05_final.stac-item
2019-12-05 10:03:46	ga_s2bm_ard_3-2-1_54JZT_2019-12-05_final.stac-item
2019-12-05 10:03:47	ga_s2bm_ard_3-2-1_55JBN_2019-12-05_final.stac-item
2019-12-05 10:03:50	ga_s2bm_ard_3-2-1_54JYT_2019-12-05_final.stac-item
2019-12-05 10:03:58	ga_s2bm_ard_3-2-1_55JCM_2019-12-05_final.stac-item
2019-12-05 10:04:01	ga_s2bm_ard_3-2-1_54JZS_2019-12-05_final.stac-item
2019-12-05 10:04:01	ga_s2bm_ard_3-2-1_55JBM_2019-12-05_final.stac-item
2019-12-05 10:04:05	ga_s2bm_ard_3-2-1_54JYS_2019-12-05_final.stac-item
2019-12-25 10:03:41	ga_s2bm_ard_3-2-1_55JDN_2019-12-25_final.stac-item
2019-12-25 10:03:45	ga_s2bm_ard_3-2-1_55JCN_2019-12-25_final.stac-item
2019-12-25 10:03:48	ga_s2bm_ard_3-2-1_54JZT_2019-12-25_final.stac-item
2019-12-25 10:03:48	ga_s2bm_ard_3-2-1_55JBN_2019-12-25_final.stac-item
2019-12-25 10:03:51	ga_s2bm_ard_3-2-1_54JYT_2019-12-25_final.stac-item
2019-12-25 10:03:59	ga_s2bm_ard_3-2-1_55JCM_2019-12-25_final.stac-item
2019-12-25 10:04:02	ga_s2bm_ard_3-2-1_54JZS_2019-12-25_final.stac-item
2019-12-25 10:04:02	ga_s2bm_ard_3-2-1_55JBM_2019-12-25_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