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
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JKF_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JKG_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JLF_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JLG_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JMF_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_52JGL_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JMG_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_52JGM_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JNG_2017-11-17_final.stac-item
2017-11-18 10:13:29	ga_s2bm_ard_3-2-1_54JUM_2017-11-18_final.stac-item
2017-11-18 10:13:29	ga_s2bm_ard_3-2-1_54JVM_2017-11-18_final.stac-item
2017-11-18 10:13:29	ga_s2bm_ard_3-2-1_54JWM_2017-11-18_final.stac-item
2017-11-18 10:13:29	ga_s2bm_ard_3-2-1_54JXM_2017-11-18_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JBF_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JBG_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JCF_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JCG_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JDF_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JDG_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JEF_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JEG_2017-11-22_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JBF_2017-12-02_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JBG_2017-12-02_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JCF_2017-12-02_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JCG_2017-12-02_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JDF_2017-12-02_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JDG_2017-12-02_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JEF_2017-12-02_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JEG_2017-12-02_final.stac-item
2019-07-29 11:15:56	ga_s2bm_ard_3-2-1_52JCM_2019-07-29_final.stac-item
2019-07-29 11:15:59	ga_s2bm_ard_3-2-1_52JBM_2019-07-29_final.stac-item
2019-07-29 11:16:02	ga_s2bm_ard_3-2-1_51JYG_2019-07-29_final.stac-item
2019-08-13 12:06:11	ga_s2bm_ard_3-2-1_50JLM_2019-08-13_final.stac-item
2019-08-13 12:06:16	ga_s2bm_ard_3-2-1_50JKM_2019-08-13_final.stac-item
2019-08-20 11:56:10	ga_s2bm_ard_3-2-1_50JNM_2019-08-20_final.stac-item
2019-08-20 11:56:13	ga_s2bm_ard_3-2-1_50JMM_2019-08-20_final.stac-item
2019-08-20 11:56:17	ga_s2bm_ard_3-2-1_50JLM_2019-08-20_final.stac-item
2019-08-20 11:56:19	ga_s2bm_ard_3-2-1_50JKM_2019-08-20_final.stac-item
2019-08-20 11:56:24	ga_s2bm_ard_3-2-1_50JNL_2019-08-20_final.stac-item
2019-08-20 11:56:28	ga_s2bm_ard_3-2-1_50JML_2019-08-20_final.stac-item
2019-08-20 11:56:31	ga_s2bm_ard_3-2-1_50JLL_2019-08-20_final.stac-item
2019-08-24 11:36:01	ga_s2bm_ard_3-2-1_51JVG_2019-08-24_final.stac-item
2019-08-24 11:36:04	ga_s2bm_ard_3-2-1_51JUG_2019-08-24_final.stac-item
2019-08-24 11:36:07	ga_s2bm_ard_3-2-1_51JTG_2019-08-24_final.stac-item
2019-08-24 11:36:10	ga_s2bm_ard_3-2-1_50JQM_2019-08-24_final.stac-item
2019-08-24 11:36:15	ga_s2bm_ard_3-2-1_51JVF_2019-08-24_final.stac-item
2019-08-24 11:36:19	ga_s2bm_ard_3-2-1_51JUF_2019-08-24_final.stac-item
2019-08-24 11:36:22	ga_s2bm_ard_3-2-1_51JTF_2019-08-24_final.stac-item
2019-08-24 11:36:25	ga_s2bm_ard_3-2-1_50JQL_2019-08-24_final.stac-item
2019-08-28 09:35:17	ga_s2bm_ard_3-2-1_56JKM_2019-08-28_final.stac-item
2019-08-28 09:35:32	ga_s2bm_ard_3-2-1_56JKL_2019-08-28_final.stac-item
2019-09-06 11:46:11	ga_s2bm_ard_3-2-1_50JNM_2019-09-06_final.stac-item
2019-09-06 11:46:15	ga_s2bm_ard_3-2-1_50JMM_2019-09-06_final.stac-item
2019-09-06 11:46:17	ga_s2bm_ard_3-2-1_50JQL_2019-09-06_final.stac-item
2019-09-06 11:46:21	ga_s2bm_ard_3-2-1_50JPL_2019-09-06_final.stac-item
2019-09-06 11:46:25	ga_s2bm_ard_3-2-1_50JNL_2019-09-06_final.stac-item
2019-09-07 09:35:08	ga_s2bm_ard_3-2-1_56JMM_2019-09-07_final.stac-item
2019-09-07 09:35:12	ga_s2bm_ard_3-2-1_56JLM_2019-09-07_final.stac-item
2019-09-07 09:35:15	ga_s2bm_ard_3-2-1_56JKM_2019-09-07_final.stac-item
2019-09-07 09:35:17	ga_s2bm_ard_3-2-1_55JGG_2019-09-07_final.stac-item
2019-09-07 09:35:23	ga_s2bm_ard_3-2-1_56JML_2019-09-07_final.stac-item
2019-09-07 09:35:26	ga_s2bm_ard_3-2-1_56JLL_2019-09-07_final.stac-item
2019-09-07 09:35:29	ga_s2bm_ard_3-2-1_56JKL_2019-09-07_final.stac-item
2019-09-07 09:35:32	ga_s2bm_ard_3-2-1_55JGF_2019-09-07_final.stac-item
2019-09-07 11:15:50	ga_s2bm_ard_3-2-1_52JCM_2019-09-07_final.stac-item
2019-09-07 11:15:53	ga_s2bm_ard_3-2-1_52JBM_2019-09-07_final.stac-item
2019-09-07 11:15:56	ga_s2bm_ard_3-2-1_51JYG_2019-09-07_final.stac-item
2019-09-07 11:15:59	ga_s2bm_ard_3-2-1_51JXG_2019-09-07_final.stac-item
2019-09-07 11:16:04	ga_s2bm_ard_3-2-1_52JCL_2019-09-07_final.stac-item
2019-09-07 11:16:08	ga_s2bm_ard_3-2-1_52JBL_2019-09-07_final.stac-item
2019-09-07 11:16:10	ga_s2bm_ard_3-2-1_51JYF_2019-09-07_final.stac-item
2019-09-07 11:16:14	ga_s2bm_ard_3-2-1_51JXF_2019-09-07_final.stac-item
2019-09-09 11:56:06	ga_s2bm_ard_3-2-1_50JNM_2019-09-09_final.stac-item
2019-09-09 11:56:09	ga_s2bm_ard_3-2-1_50JMM_2019-09-09_final.stac-item
2019-09-09 11:56:12	ga_s2bm_ard_3-2-1_50JLM_2019-09-09_final.stac-item
2019-09-09 11:56:15	ga_s2bm_ard_3-2-1_50JKM_2019-09-09_final.stac-item
2019-09-09 11:56:20	ga_s2bm_ard_3-2-1_50JNL_2019-09-09_final.stac-item
2019-09-09 11:56:24	ga_s2bm_ard_3-2-1_50JML_2019-09-09_final.stac-item
2019-09-09 11:56:27	ga_s2bm_ard_3-2-1_50JLL_2019-09-09_final.stac-item
2019-09-13 11:35:56	ga_s2bm_ard_3-2-1_51JVG_2019-09-13_final.stac-item
2019-09-13 11:36:00	ga_s2bm_ard_3-2-1_51JUG_2019-09-13_final.stac-item
2019-09-13 11:36:03	ga_s2bm_ard_3-2-1_51JTG_2019-09-13_final.stac-item
2019-09-13 11:36:06	ga_s2bm_ard_3-2-1_50JQM_2019-09-13_final.stac-item
2019-09-13 11:36:11	ga_s2bm_ard_3-2-1_51JVF_2019-09-13_final.stac-item
2019-09-13 11:36:14	ga_s2bm_ard_3-2-1_51JUF_2019-09-13_final.stac-item
2019-09-13 11:36:18	ga_s2bm_ard_3-2-1_51JTF_2019-09-13_final.stac-item
2019-09-13 11:36:20	ga_s2bm_ard_3-2-1_50JQL_2019-09-13_final.stac-item
2019-09-14 09:25:07	ga_s2bm_ard_3-2-1_56JNM_2019-09-13_final.stac-item
2019-09-14 09:25:11	ga_s2bm_ard_3-2-1_56JMM_2019-09-13_final.stac-item
2019-09-14 09:25:22	ga_s2bm_ard_3-2-1_56JNL_2019-09-13_final.stac-item
2019-09-14 09:25:25	ga_s2bm_ard_3-2-1_56JML_2019-09-13_final.stac-item
2019-09-14 09:25:30	ga_s2bm_ard_3-2-1_56JLL_2019-09-13_final.stac-item
2019-09-16 11:45:57	ga_s2bm_ard_3-2-1_51JTG_2019-09-16_final.stac-item
2019-09-16 11:46:00	ga_s2bm_ard_3-2-1_50JQM_2019-09-16_final.stac-item
2019-09-16 11:46:05	ga_s2bm_ard_3-2-1_50JPM_2019-09-16_final.stac-item
2019-09-16 11:46:08	ga_s2bm_ard_3-2-1_51JTF_2019-09-16_final.stac-item
2019-09-16 11:46:08	ga_s2bm_ard_3-2-1_50JNM_2019-09-16_final.stac-item
2019-09-16 11:46:13	ga_s2bm_ard_3-2-1_50JMM_2019-09-16_final.stac-item
2019-09-16 11:46:15	ga_s2bm_ard_3-2-1_50JQL_2019-09-16_final.stac-item
2019-09-16 11:46:19	ga_s2bm_ard_3-2-1_50JPL_2019-09-16_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

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