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
2018-03-26 11:11:52	ga_s2bm_ard_3-2-1_52JBS_2018-03-26_final.stac-item
2018-03-26 11:11:52	ga_s2bm_ard_3-2-1_52JCS_2018-03-26_final.stac-item
2018-03-26 11:11:52	ga_s2bm_ard_3-2-1_52JDS_2018-03-26_final.stac-item
2018-03-26 11:11:52	ga_s2bm_ard_3-2-1_51JYM_2018-03-26_final.stac-item
2018-03-26 11:11:52	ga_s2bm_ard_3-2-1_51JZM_2018-03-26_final.stac-item
2018-03-26 11:11:52	ga_s2bm_ard_3-2-1_52JBR_2018-03-26_final.stac-item
2018-03-26 11:11:52	ga_s2bm_ard_3-2-1_52JCR_2018-03-26_final.stac-item
2018-03-26 11:11:52	ga_s2bm_ard_3-2-1_51JYL_2018-03-26_final.stac-item
2018-04-02 09:22:41	ga_s2bm_ard_3-2-1_56JNS_2018-04-01_final.stac-item
2018-04-04 11:40:13	ga_s2bm_ard_3-2-1_51JTL_2018-04-04_final.stac-item
2018-04-04 11:40:13	ga_s2bm_ard_3-2-1_51JTM_2018-04-04_final.stac-item
2018-04-04 11:40:13	ga_s2bm_ard_3-2-1_51JUL_2018-04-04_final.stac-item
2018-04-04 11:40:13	ga_s2bm_ard_3-2-1_51JUM_2018-04-04_final.stac-item
2018-04-04 11:40:13	ga_s2bm_ard_3-2-1_50JPR_2018-04-04_final.stac-item
2018-04-04 11:40:13	ga_s2bm_ard_3-2-1_50JPS_2018-04-04_final.stac-item
2018-04-04 11:40:13	ga_s2bm_ard_3-2-1_50JQR_2018-04-04_final.stac-item
2018-04-04 11:40:13	ga_s2bm_ard_3-2-1_50JQS_2018-04-04_final.stac-item
2018-04-04 11:40:13	ga_s2bm_ard_3-2-1_50JRS_2018-04-04_final.stac-item
2018-04-05 11:11:18	ga_s2bm_ard_3-2-1_52JBS_2018-04-05_final.stac-item
2018-04-05 11:11:18	ga_s2bm_ard_3-2-1_52JCS_2018-04-05_final.stac-item
2018-04-05 11:11:18	ga_s2bm_ard_3-2-1_52JDS_2018-04-05_final.stac-item
2018-04-05 11:11:18	ga_s2bm_ard_3-2-1_51JYM_2018-04-05_final.stac-item
2018-04-05 11:11:18	ga_s2bm_ard_3-2-1_51JZM_2018-04-05_final.stac-item
2018-04-07 11:53:07	ga_s2bm_ard_3-2-1_50JLS_2018-04-07_final.stac-item
2018-04-07 11:53:07	ga_s2bm_ard_3-2-1_50JMS_2018-04-07_final.stac-item
2018-04-07 11:53:07	ga_s2bm_ard_3-2-1_50JNS_2018-04-07_final.stac-item
2018-04-07 11:53:07	ga_s2bm_ard_3-2-1_50JPS_2018-04-07_final.stac-item
2018-04-10 12:02:47	ga_s2bm_ard_3-2-1_49JGL_2018-04-10_final.stac-item
2018-04-10 12:02:47	ga_s2bm_ard_3-2-1_49JGM_2018-04-10_final.stac-item
2018-04-10 12:02:47	ga_s2bm_ard_3-2-1_49JHM_2018-04-10_final.stac-item
2018-04-10 12:02:47	ga_s2bm_ard_3-2-1_50JKR_2018-04-10_final.stac-item
2018-04-10 12:02:47	ga_s2bm_ard_3-2-1_50JKS_2018-04-10_final.stac-item
2018-04-10 12:02:47	ga_s2bm_ard_3-2-1_50JLR_2018-04-10_final.stac-item
2018-04-10 12:02:47	ga_s2bm_ard_3-2-1_50JLS_2018-04-10_final.stac-item
2018-04-10 12:02:47	ga_s2bm_ard_3-2-1_50JMS_2018-04-10_final.stac-item
2018-04-12 09:22:42	ga_s2bm_ard_3-2-1_56JNS_2018-04-11_final.stac-item
2018-04-14 11:40:40	ga_s2bm_ard_3-2-1_51JTM_2018-04-14_final.stac-item
2018-04-14 11:40:40	ga_s2bm_ard_3-2-1_51JUM_2018-04-14_final.stac-item
2018-04-14 11:40:40	ga_s2bm_ard_3-2-1_50JPS_2018-04-14_final.stac-item
2018-04-14 11:40:40	ga_s2bm_ard_3-2-1_50JQS_2018-04-14_final.stac-item
2018-04-14 11:40:40	ga_s2bm_ard_3-2-1_50JRS_2018-04-14_final.stac-item
2018-04-14 11:40:40	ga_s2bm_ard_3-2-1_51JTL_2018-04-14_final.stac-item
2018-04-14 11:40:40	ga_s2bm_ard_3-2-1_51JUL_2018-04-14_final.stac-item
2018-04-14 11:40:40	ga_s2bm_ard_3-2-1_50JPR_2018-04-14_final.stac-item
2018-04-14 11:40:40	ga_s2bm_ard_3-2-1_50JQR_2018-04-14_final.stac-item
2018-07-16 10:10:50	ga_s2bm_ard_3-2-1_54JVS_2018-07-16_final.stac-item
2018-07-16 10:10:50	ga_s2bm_ard_3-2-1_54JWS_2018-07-16_final.stac-item
2018-07-16 10:10:50	ga_s2bm_ard_3-2-1_54JXR_2018-07-16_final.stac-item
2018-07-16 10:10:50	ga_s2bm_ard_3-2-1_54JXS_2018-07-16_final.stac-item
2018-07-16 10:10:50	ga_s2bm_ard_3-2-1_54JYR_2018-07-16_final.stac-item
2018-07-16 10:10:50	ga_s2bm_ard_3-2-1_54JYS_2018-07-16_final.stac-item
2018-07-20 09:50:52	ga_s2bm_ard_3-2-1_55JCM_2018-07-20_final.stac-item
2018-07-20 09:50:52	ga_s2bm_ard_3-2-1_55JDM_2018-07-20_final.stac-item
2018-07-20 09:50:52	ga_s2bm_ard_3-2-1_55JEM_2018-07-20_final.stac-item
2018-07-20 09:50:52	ga_s2bm_ard_3-2-1_55JFM_2018-07-20_final.stac-item
2018-07-25 10:41:04	ga_s2bm_ard_3-2-1_53JLM_2018-07-25_final.stac-item
2018-07-25 10:41:04	ga_s2bm_ard_3-2-1_53JMM_2018-07-25_final.stac-item
2018-07-25 10:41:04	ga_s2bm_ard_3-2-1_53JNM_2018-07-25_final.stac-item
2018-07-25 10:41:04	ga_s2bm_ard_3-2-1_53JPM_2018-07-25_final.stac-item
2018-07-26 10:13:42	ga_s2bm_ard_3-2-1_54JVS_2018-07-26_final.stac-item
2018-07-26 10:13:42	ga_s2bm_ard_3-2-1_54JWS_2018-07-26_final.stac-item
2018-07-26 10:13:42	ga_s2bm_ard_3-2-1_54JXR_2018-07-26_final.stac-item
2018-07-26 10:13:42	ga_s2bm_ard_3-2-1_54JXS_2018-07-26_final.stac-item
2018-07-26 10:13:42	ga_s2bm_ard_3-2-1_54JYR_2018-07-26_final.stac-item
2018-07-26 10:13:42	ga_s2bm_ard_3-2-1_54JYS_2018-07-26_final.stac-item
2018-07-27 09:41:06	ga_s2bm_ard_3-2-1_56JKR_2018-07-27_final.stac-item
2019-06-08 11:44:48	ga_s2bm_ard_3-2-1_51JUM_2019-06-08_final.stac-item
2019-06-08 11:44:53	ga_s2bm_ard_3-2-1_50JRS_2019-06-08_final.stac-item
2019-06-08 11:44:53	ga_s2bm_ard_3-2-1_51JTM_2019-06-08_final.stac-item
2019-06-08 11:44:56	ga_s2bm_ard_3-2-1_50JQS_2019-06-08_final.stac-item
2019-06-08 11:44:59	ga_s2bm_ard_3-2-1_51JUL_2019-06-08_final.stac-item
2019-06-08 11:45:00	ga_s2bm_ard_3-2-1_50JPS_2019-06-08_final.stac-item
2019-06-08 11:45:07	ga_s2bm_ard_3-2-1_51JTL_2019-06-08_final.stac-item
2019-06-08 11:45:11	ga_s2bm_ard_3-2-1_50JQR_2019-06-08_final.stac-item
2019-06-08 11:45:15	ga_s2bm_ard_3-2-1_50JPR_2019-06-08_final.stac-item
2019-06-09 11:14:39	ga_s2bm_ard_3-2-1_52JDS_2019-06-09_final.stac-item
2019-06-09 11:14:42	ga_s2bm_ard_3-2-1_52JCS_2019-06-09_final.stac-item
2019-06-09 11:14:45	ga_s2bm_ard_3-2-1_51JZM_2019-06-09_final.stac-item
2019-06-09 11:14:45	ga_s2bm_ard_3-2-1_52JBS_2019-06-09_final.stac-item
2019-06-09 11:14:49	ga_s2bm_ard_3-2-1_51JYM_2019-06-09_final.stac-item
2019-06-09 11:14:57	ga_s2bm_ard_3-2-1_52JCR_2019-06-09_final.stac-item
2019-06-09 11:15:00	ga_s2bm_ard_3-2-1_52JBR_2019-06-09_final.stac-item
2019-06-09 11:15:03	ga_s2bm_ard_3-2-1_51JYL_2019-06-09_final.stac-item
2019-06-18 11:44:48	ga_s2bm_ard_3-2-1_51JUM_2019-06-18_final.stac-item
2019-06-18 11:44:52	ga_s2bm_ard_3-2-1_50JRS_2019-06-18_final.stac-item
2019-06-18 11:44:53	ga_s2bm_ard_3-2-1_51JTM_2019-06-18_final.stac-item
2019-06-18 11:44:56	ga_s2bm_ard_3-2-1_50JQS_2019-06-18_final.stac-item
2019-06-18 11:44:59	ga_s2bm_ard_3-2-1_51JUL_2019-06-18_final.stac-item
2019-06-18 11:45:00	ga_s2bm_ard_3-2-1_50JPS_2019-06-18_final.stac-item
2019-06-18 11:45:07	ga_s2bm_ard_3-2-1_51JTL_2019-06-18_final.stac-item
2019-06-18 11:45:11	ga_s2bm_ard_3-2-1_50JQR_2019-06-18_final.stac-item
2019-06-18 11:45:14	ga_s2bm_ard_3-2-1_50JPR_2019-06-18_final.stac-item
2019-06-28 11:44:49	ga_s2bm_ard_3-2-1_51JUM_2019-06-28_final.stac-item
2019-06-28 11:44:53	ga_s2bm_ard_3-2-1_50JRS_2019-06-28_final.stac-item
2019-06-28 11:44:54	ga_s2bm_ard_3-2-1_51JTM_2019-06-28_final.stac-item
2019-06-28 11:44:57	ga_s2bm_ard_3-2-1_50JQS_2019-06-28_final.stac-item
2019-06-28 11:44:59	ga_s2bm_ard_3-2-1_51JUL_2019-06-28_final.stac-item
2019-06-28 11:45:01	ga_s2bm_ard_3-2-1_50JPS_2019-06-28_final.stac-item
2019-06-28 11:45:08	ga_s2bm_ard_3-2-1_51JTL_2019-06-28_final.stac-item
2019-06-28 11:45:12	ga_s2bm_ard_3-2-1_50JQR_2019-06-28_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