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
2019-10-02 12:04:14	ga_s2bm_ard_3-2-1_49KHQ_2019-10-02_final.stac-item
2019-10-02 12:04:25	ga_s2bm_ard_3-2-1_49KGP_2019-10-02_final.stac-item
2019-10-02 12:04:32	ga_s2bm_ard_3-2-1_49KGP_2019-10-02_final.stac-item
2019-10-02 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2019-10-02_final.stac-item
2019-10-05 12:14:05	ga_s2bm_ard_3-2-1_49KHQ_2019-10-05_final.stac-item
2019-10-05 12:14:11	ga_s2bm_ard_3-2-1_49KHQ_2019-10-05_final.stac-item
2019-10-05 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2019-10-05_final.stac-item
2019-10-05 12:14:32	ga_s2bm_ard_3-2-1_49JHN_2019-10-05_final.stac-item
2019-10-05 12:14:46	ga_s2bm_ard_3-2-1_49JFN_2019-10-05_final.stac-item
2019-10-12 12:04:15	ga_s2bm_ard_3-2-1_49KHQ_2019-10-12_final.stac-item
2019-10-12 12:04:32	ga_s2bm_ard_3-2-1_49KGP_2019-10-12_final.stac-item
2019-10-12 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2019-10-12_final.stac-item
2019-10-15 12:14:10	ga_s2bm_ard_3-2-1_49KHQ_2019-10-15_final.stac-item
2019-10-15 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2019-10-15_final.stac-item
2019-10-15 12:14:32	ga_s2bm_ard_3-2-1_49JHN_2019-10-15_final.stac-item
2019-10-15 12:14:43	ga_s2bm_ard_3-2-1_49JFN_2019-10-15_final.stac-item
2019-10-22 12:04:15	ga_s2bm_ard_3-2-1_49KHQ_2019-10-22_final.stac-item
2019-10-22 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2019-10-22_final.stac-item
2019-10-25 12:14:10	ga_s2bm_ard_3-2-1_49KHQ_2019-10-25_final.stac-item
2019-10-25 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2019-10-25_final.stac-item
2019-10-25 12:14:32	ga_s2bm_ard_3-2-1_49JHN_2019-10-25_final.stac-item
2019-10-25 12:14:46	ga_s2bm_ard_3-2-1_49JFN_2019-10-25_final.stac-item
2019-11-01 12:04:49	ga_s2bm_ard_3-2-1_50JMS_2019-11-01_final.stac-item
2019-11-01 12:05:23	ga_s2bm_ard_3-2-1_50JLQ_2019-11-01_final.stac-item
2019-11-01 12:05:38	ga_s2bm_ard_3-2-1_50JLP_2019-11-01_final.stac-item
2019-11-05 11:44:52	ga_s2bm_ard_3-2-1_50JPS_2019-11-05_final.stac-item
2019-11-05 11:45:54	ga_s2bm_ard_3-2-1_50JNN_2019-11-05_final.stac-item
2019-11-08 11:54:48	ga_s2bm_ard_3-2-1_50JPS_2019-11-08_final.stac-item
2019-11-08 11:54:55	ga_s2bm_ard_3-2-1_50JMS_2019-11-08_final.stac-item
2019-11-08 11:55:27	ga_s2bm_ard_3-2-1_50JLQ_2019-11-08_final.stac-item
2019-11-08 11:55:42	ga_s2bm_ard_3-2-1_50JLP_2019-11-08_final.stac-item
2019-11-08 11:55:49	ga_s2bm_ard_3-2-1_50JNN_2019-11-08_final.stac-item
2019-11-08 11:55:53	ga_s2bm_ard_3-2-1_50JMN_2019-11-08_final.stac-item
2019-11-11 12:04:48	ga_s2bm_ard_3-2-1_50JMS_2019-11-11_final.stac-item
2019-11-11 12:05:22	ga_s2bm_ard_3-2-1_50JLQ_2019-11-11_final.stac-item
2019-11-11 12:05:37	ga_s2bm_ard_3-2-1_50JLP_2019-11-11_final.stac-item
2019-11-15 11:45:53	ga_s2bm_ard_3-2-1_50JNN_2019-11-15_final.stac-item
2019-11-18 11:54:53	ga_s2bm_ard_3-2-1_50JMS_2019-11-18_final.stac-item
2019-11-18 11:55:25	ga_s2bm_ard_3-2-1_50JLQ_2019-11-18_final.stac-item
2019-11-18 11:55:40	ga_s2bm_ard_3-2-1_50JLP_2019-11-18_final.stac-item
2019-11-18 11:55:47	ga_s2bm_ard_3-2-1_50JNN_2019-11-18_final.stac-item
2019-11-18 11:55:51	ga_s2bm_ard_3-2-1_50JMN_2019-11-18_final.stac-item
2019-11-21 12:04:46	ga_s2bm_ard_3-2-1_50JMS_2019-11-21_final.stac-item
2019-11-21 12:05:20	ga_s2bm_ard_3-2-1_50JLQ_2019-11-21_final.stac-item
2019-11-21 12:05:35	ga_s2bm_ard_3-2-1_50JLP_2019-11-21_final.stac-item
2019-11-25 11:44:49	ga_s2bm_ard_3-2-1_50JPS_2019-11-25_final.stac-item
2019-11-25 11:45:50	ga_s2bm_ard_3-2-1_50JNN_2019-11-25_final.stac-item
2019-11-28 11:55:23	ga_s2bm_ard_3-2-1_50JLQ_2019-11-28_final.stac-item
2019-11-28 11:55:38	ga_s2bm_ard_3-2-1_50JLP_2019-11-28_final.stac-item
2019-11-28 11:55:45	ga_s2bm_ard_3-2-1_50JNN_2019-11-28_final.stac-item
2019-11-28 11:55:49	ga_s2bm_ard_3-2-1_50JMN_2019-11-28_final.stac-item
2019-12-02 11:36:21	ga_s2bm_ard_3-2-1_50JPL_2019-12-02_final.stac-item
2019-12-02 11:36:33	ga_s2bm_ard_3-2-1_50HPK_2019-12-02_final.stac-item
2019-12-02 11:36:46	ga_s2bm_ard_3-2-1_50HPJ_2019-12-02_final.stac-item
2019-12-05 11:45:57	ga_s2bm_ard_3-2-1_50JNM_2019-12-05_final.stac-item
2019-12-05 11:46:04	ga_s2bm_ard_3-2-1_50JNM_2019-12-05_final.stac-item
2019-12-05 11:46:07	ga_s2bm_ard_3-2-1_50JMM_2019-12-05_final.stac-item
2019-12-05 11:46:13	ga_s2bm_ard_3-2-1_50JPL_2019-12-05_final.stac-item
2019-12-05 11:46:28	ga_s2bm_ard_3-2-1_50HPK_2019-12-05_final.stac-item
2019-12-05 11:46:35	ga_s2bm_ard_3-2-1_50HMK_2019-12-05_final.stac-item
2019-12-05 11:47:08	ga_s2bm_ard_3-2-1_50HLH_2019-12-05_final.stac-item
2019-12-08 11:55:58	ga_s2bm_ard_3-2-1_50JNM_2019-12-08_final.stac-item
2019-12-08 11:56:02	ga_s2bm_ard_3-2-1_50JMM_2019-12-08_final.stac-item
2019-12-08 11:56:31	ga_s2bm_ard_3-2-1_50HMK_2019-12-08_final.stac-item
2019-12-08 11:56:49	ga_s2bm_ard_3-2-1_50HLJ_2019-12-08_final.stac-item
2019-12-08 11:57:03	ga_s2bm_ard_3-2-1_50HLH_2019-12-08_final.stac-item
2019-12-12 11:36:21	ga_s2bm_ard_3-2-1_50JPL_2019-12-12_final.stac-item
2019-12-12 11:36:32	ga_s2bm_ard_3-2-1_50HPK_2019-12-12_final.stac-item
2019-12-12 11:36:38	ga_s2bm_ard_3-2-1_50HPK_2019-12-12_final.stac-item
2019-12-12 11:36:38	ga_s2bm_ard_3-2-1_50HPJ_2019-12-12_final.stac-item
2019-12-12 11:36:46	ga_s2bm_ard_3-2-1_50HPJ_2019-12-12_final.stac-item
2019-12-15 11:46:03	ga_s2bm_ard_3-2-1_50JNM_2019-12-15_final.stac-item
2019-12-15 11:46:07	ga_s2bm_ard_3-2-1_50JMM_2019-12-15_final.stac-item
2019-12-15 11:46:12	ga_s2bm_ard_3-2-1_50JPL_2019-12-15_final.stac-item
2019-12-15 11:46:18	ga_s2bm_ard_3-2-1_50HPK_2019-12-15_final.stac-item
2019-12-15 11:46:19	ga_s2bm_ard_3-2-1_50JPL_2019-12-15_final.stac-item
2019-12-15 11:46:28	ga_s2bm_ard_3-2-1_50HPK_2019-12-15_final.stac-item
2019-12-15 11:46:35	ga_s2bm_ard_3-2-1_50HMK_2019-12-15_final.stac-item
2019-12-15 11:46:43	ga_s2bm_ard_3-2-1_50HPJ_2019-12-15_final.stac-item
2019-12-15 11:47:09	ga_s2bm_ard_3-2-1_50HLH_2019-12-15_final.stac-item
2019-12-18 11:55:59	ga_s2bm_ard_3-2-1_50JNM_2019-12-18_final.stac-item
2019-12-18 11:56:02	ga_s2bm_ard_3-2-1_50JMM_2019-12-18_final.stac-item
2019-12-18 11:56:31	ga_s2bm_ard_3-2-1_50HMK_2019-12-18_final.stac-item
2019-12-18 11:56:49	ga_s2bm_ard_3-2-1_50HLJ_2019-12-18_final.stac-item
2019-12-18 11:57:04	ga_s2bm_ard_3-2-1_50HLH_2019-12-18_final.stac-item
2019-12-22 11:36:21	ga_s2bm_ard_3-2-1_50JPL_2019-12-22_final.stac-item
2019-12-22 11:36:33	ga_s2bm_ard_3-2-1_50HPK_2019-12-22_final.stac-item
2019-12-22 11:36:42	ga_s2bm_ard_3-2-1_50HPJ_2019-12-22_final.stac-item
2019-12-22 11:36:49	ga_s2bm_ard_3-2-1_50HPJ_2019-12-22_final.stac-item
2019-12-25 11:46:03	ga_s2bm_ard_3-2-1_50JNM_2019-12-25_final.stac-item
2019-12-25 11:46:08	ga_s2bm_ard_3-2-1_50JMM_2019-12-25_final.stac-item
2019-12-25 11:46:14	ga_s2bm_ard_3-2-1_50JPL_2019-12-25_final.stac-item
2019-12-25 11:46:29	ga_s2bm_ard_3-2-1_50HPK_2019-12-25_final.stac-item
2019-12-25 11:46:36	ga_s2bm_ard_3-2-1_50HMK_2019-12-25_final.stac-item
2019-12-25 11:46:43	ga_s2bm_ard_3-2-1_50HPJ_2019-12-25_final.stac-item
2019-12-25 11:47:09	ga_s2bm_ard_3-2-1_50HLH_2019-12-25_final.stac-item
2019-12-28 11:55:59	ga_s2bm_ard_3-2-1_50JNM_2019-12-28_final.stac-item
2019-12-28 11:56:03	ga_s2bm_ard_3-2-1_50JMM_2019-12-28_final.stac-item
2019-12-28 11:56:31	ga_s2bm_ard_3-2-1_50HMK_2019-12-28_final.stac-item
2019-12-28 11:56:50	ga_s2bm_ard_3-2-1_50HLJ_2019-12-28_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