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
2022-04-02 12:14:05	ga_s2bm_ard_3-2-1_49KHQ_2022-04-02_final.stac-item
2022-04-02 12:14:28	ga_s2bm_ard_3-2-1_49JHN_2022-04-02_final.stac-item
2022-04-06 11:54:52	ga_s2bm_ard_3-2-1_50JMS_2022-04-06_final.stac-item
2022-04-06 11:54:55	ga_s2bm_ard_3-2-1_50JLS_2022-04-06_final.stac-item
2022-04-06 11:55:09	ga_s2bm_ard_3-2-1_50JLR_2022-04-06_final.stac-item
2022-04-06 11:55:43	ga_s2bm_ard_3-2-1_50JKP_2022-04-06_final.stac-item
2022-04-06 11:55:46	ga_s2bm_ard_3-2-1_50JNN_2022-04-06_final.stac-item
2022-04-06 11:55:56	ga_s2bm_ard_3-2-1_50JKN_2022-04-06_final.stac-item
2022-04-09 12:04:36	ga_s2bm_ard_3-2-1_50JKT_2022-04-09_final.stac-item
2022-04-09 12:04:40	ga_s2bm_ard_3-2-1_50JMS_2022-04-09_final.stac-item
2022-04-09 12:04:40	ga_s2bm_ard_3-2-1_50JLS_2022-04-09_final.stac-item
2022-04-09 12:04:43	ga_s2bm_ard_3-2-1_50JKT_2022-04-09_final.stac-item
2022-04-09 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2022-04-09_final.stac-item
2022-04-09 12:04:45	ga_s2bm_ard_3-2-1_50JMS_2022-04-09_final.stac-item
2022-04-09 12:04:50	ga_s2bm_ard_3-2-1_50JLS_2022-04-09_final.stac-item
2022-04-09 12:05:05	ga_s2bm_ard_3-2-1_50JLR_2022-04-09_final.stac-item
2022-04-09 12:05:38	ga_s2bm_ard_3-2-1_50JKP_2022-04-09_final.stac-item
2022-04-09 12:05:52	ga_s2bm_ard_3-2-1_50JKN_2022-04-09_final.stac-item
2022-04-12 12:14:05	ga_s2bm_ard_3-2-1_49KHQ_2022-04-12_final.stac-item
2022-04-13 11:45:43	ga_s2bm_ard_3-2-1_50JNN_2022-04-13_final.stac-item
2022-04-13 11:45:50	ga_s2bm_ard_3-2-1_50JNN_2022-04-13_final.stac-item
2022-04-16 11:54:51	ga_s2bm_ard_3-2-1_50JMS_2022-04-16_final.stac-item
2022-04-16 11:54:54	ga_s2bm_ard_3-2-1_50JLS_2022-04-16_final.stac-item
2022-04-16 11:55:09	ga_s2bm_ard_3-2-1_50JLR_2022-04-16_final.stac-item
2022-04-16 11:55:42	ga_s2bm_ard_3-2-1_50JKP_2022-04-16_final.stac-item
2022-04-16 11:55:45	ga_s2bm_ard_3-2-1_50JNN_2022-04-16_final.stac-item
2022-04-16 11:55:55	ga_s2bm_ard_3-2-1_50JKN_2022-04-16_final.stac-item
2022-04-19 12:04:09	ga_s2bm_ard_3-2-1_49KHQ_2022-04-19_final.stac-item
2022-04-19 12:04:35	ga_s2bm_ard_3-2-1_49JHN_2022-04-19_final.stac-item
2022-04-19 12:04:39	ga_s2bm_ard_3-2-1_50JMS_2022-04-19_final.stac-item
2022-04-19 12:04:39	ga_s2bm_ard_3-2-1_50JLS_2022-04-19_final.stac-item
2022-04-19 12:04:42	ga_s2bm_ard_3-2-1_50JKT_2022-04-19_final.stac-item
2022-04-19 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2022-04-19_final.stac-item
2022-04-19 12:04:44	ga_s2bm_ard_3-2-1_50JMS_2022-04-19_final.stac-item
2022-04-19 12:05:04	ga_s2bm_ard_3-2-1_50JLR_2022-04-19_final.stac-item
2022-04-19 12:05:36	ga_s2bm_ard_3-2-1_50JKP_2022-04-19_final.stac-item
2022-04-19 12:05:51	ga_s2bm_ard_3-2-1_50JKN_2022-04-19_final.stac-item
2022-04-22 12:14:03	ga_s2bm_ard_3-2-1_49KHQ_2022-04-22_final.stac-item
2022-04-22 12:14:26	ga_s2bm_ard_3-2-1_49JHN_2022-04-22_final.stac-item
2022-04-23 11:45:41	ga_s2bm_ard_3-2-1_50JNN_2022-04-23_final.stac-item
2022-04-26 11:54:48	ga_s2bm_ard_3-2-1_50JMS_2022-04-26_final.stac-item
2022-04-26 11:54:51	ga_s2bm_ard_3-2-1_50JLS_2022-04-26_final.stac-item
2022-04-26 11:55:06	ga_s2bm_ard_3-2-1_50JLR_2022-04-26_final.stac-item
2022-04-26 11:55:40	ga_s2bm_ard_3-2-1_50JKP_2022-04-26_final.stac-item
2022-04-26 11:55:43	ga_s2bm_ard_3-2-1_50JNN_2022-04-26_final.stac-item
2022-04-26 11:55:53	ga_s2bm_ard_3-2-1_50JKN_2022-04-26_final.stac-item
2022-04-29 12:04:06	ga_s2bm_ard_3-2-1_49KHQ_2022-04-29_final.stac-item
2022-04-29 12:04:32	ga_s2bm_ard_3-2-1_50JKT_2022-04-29_final.stac-item
2022-04-29 12:04:36	ga_s2bm_ard_3-2-1_50JMS_2022-04-29_final.stac-item
2022-04-29 12:04:36	ga_s2bm_ard_3-2-1_50JLS_2022-04-29_final.stac-item
2022-04-29 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2022-04-29_final.stac-item
2022-04-29 12:04:39	ga_s2bm_ard_3-2-1_50JKT_2022-04-29_final.stac-item
2022-04-29 12:04:42	ga_s2bm_ard_3-2-1_50JMS_2022-04-29_final.stac-item
2022-04-29 12:04:47	ga_s2bm_ard_3-2-1_50JLS_2022-04-29_final.stac-item
2022-04-29 12:05:01	ga_s2bm_ard_3-2-1_50JLR_2022-04-29_final.stac-item
2022-04-29 12:05:34	ga_s2bm_ard_3-2-1_50JKP_2022-04-29_final.stac-item
2022-04-29 12:05:48	ga_s2bm_ard_3-2-1_50JKN_2022-04-29_final.stac-item
2022-05-02 12:14:25	ga_s2bm_ard_3-2-1_49JHN_2022-05-02_final.stac-item
2022-05-03 11:46:03	ga_s2bm_ard_3-2-1_50JNM_2022-05-03_final.stac-item
2022-05-03 11:46:28	ga_s2bm_ard_3-2-1_50HPK_2022-05-03_final.stac-item
2022-05-03 11:46:43	ga_s2bm_ard_3-2-1_50HPJ_2022-05-03_final.stac-item
2022-05-03 11:46:50	ga_s2bm_ard_3-2-1_50HMJ_2022-05-03_final.stac-item
2022-05-03 11:47:04	ga_s2bm_ard_3-2-1_50HMH_2022-05-03_final.stac-item
2022-05-03 11:47:09	ga_s2bm_ard_3-2-1_50HLH_2022-05-03_final.stac-item
2022-05-06 11:56:00	ga_s2bm_ard_3-2-1_50JNM_2022-05-06_final.stac-item
2022-05-06 11:56:21	ga_s2bm_ard_3-2-1_50JLL_2022-05-06_final.stac-item
2022-05-06 11:56:47	ga_s2bm_ard_3-2-1_50HMJ_2022-05-06_final.stac-item
2022-05-06 11:56:50	ga_s2bm_ard_3-2-1_50HLJ_2022-05-06_final.stac-item
2022-05-06 11:57:02	ga_s2bm_ard_3-2-1_50HMH_2022-05-06_final.stac-item
2022-05-06 11:57:05	ga_s2bm_ard_3-2-1_50HLH_2022-05-06_final.stac-item
2022-05-09 12:06:11	ga_s2bm_ard_3-2-1_50JLL_2022-05-09_final.stac-item
2022-05-10 11:36:35	ga_s2bm_ard_3-2-1_50HPK_2022-05-10_final.stac-item
2022-05-10 11:36:49	ga_s2bm_ard_3-2-1_50HPJ_2022-05-10_final.stac-item
2022-05-13 11:46:07	ga_s2bm_ard_3-2-1_50JNM_2022-05-13_final.stac-item
2022-05-13 11:46:32	ga_s2bm_ard_3-2-1_50HPK_2022-05-13_final.stac-item
2022-05-13 11:46:46	ga_s2bm_ard_3-2-1_50HPJ_2022-05-13_final.stac-item
2022-05-13 11:46:54	ga_s2bm_ard_3-2-1_50HMJ_2022-05-13_final.stac-item
2022-05-13 11:47:08	ga_s2bm_ard_3-2-1_50HMH_2022-05-13_final.stac-item
2022-05-13 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2022-05-13_final.stac-item
2022-05-16 11:56:03	ga_s2bm_ard_3-2-1_50JNM_2022-05-16_final.stac-item
2022-05-16 11:56:50	ga_s2bm_ard_3-2-1_50HMJ_2022-05-16_final.stac-item
2022-05-16 11:56:54	ga_s2bm_ard_3-2-1_50HLJ_2022-05-16_final.stac-item
2022-05-16 11:57:05	ga_s2bm_ard_3-2-1_50HMH_2022-05-16_final.stac-item
2022-05-16 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2022-05-16_final.stac-item
2022-05-20 11:36:38	ga_s2bm_ard_3-2-1_50HPK_2022-05-20_final.stac-item
2022-05-20 11:36:52	ga_s2bm_ard_3-2-1_50HPJ_2022-05-20_final.stac-item
2022-05-23 11:46:08	ga_s2bm_ard_3-2-1_50JNM_2022-05-23_final.stac-item
2022-05-23 11:46:34	ga_s2bm_ard_3-2-1_50HPK_2022-05-23_final.stac-item
2022-05-23 11:46:48	ga_s2bm_ard_3-2-1_50HPJ_2022-05-23_final.stac-item
2022-05-23 11:46:55	ga_s2bm_ard_3-2-1_50HMJ_2022-05-23_final.stac-item
2022-05-23 11:47:10	ga_s2bm_ard_3-2-1_50HMH_2022-05-23_final.stac-item
2022-05-23 11:47:14	ga_s2bm_ard_3-2-1_50HLH_2022-05-23_final.stac-item
2022-05-26 11:56:04	ga_s2bm_ard_3-2-1_50JNM_2022-05-26_final.stac-item
2022-05-26 11:56:26	ga_s2bm_ard_3-2-1_50JLL_2022-05-26_final.stac-item
2022-05-26 11:56:51	ga_s2bm_ard_3-2-1_50HMJ_2022-05-26_final.stac-item
2022-05-26 11:56:55	ga_s2bm_ard_3-2-1_50HLJ_2022-05-26_final.stac-item
2022-05-26 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2022-05-26_final.stac-item
2022-05-26 11:57:09	ga_s2bm_ard_3-2-1_50HLH_2022-05-26_final.stac-item
2022-05-29 12:06:14	ga_s2bm_ard_3-2-1_50JLL_2022-05-29_final.stac-item
2022-05-30 11:36:38	ga_s2bm_ard_3-2-1_50HPK_2022-05-30_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

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