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
2019-04-02 11:56:28	ga_s2bm_ard_3-2-1_50JLL_2019-04-02_final.stac-item
2019-04-02 11:56:54	ga_s2bm_ard_3-2-1_50HMJ_2019-04-02_final.stac-item
2019-04-02 11:57:08	ga_s2bm_ard_3-2-1_50HMH_2019-04-02_final.stac-item
2019-04-05 12:06:17	ga_s2bm_ard_3-2-1_50JLL_2019-04-05_final.stac-item
2019-04-06 11:36:52	ga_s2bm_ard_3-2-1_50HQJ_2019-04-06_final.stac-item
2019-04-06 11:37:10	ga_s2bm_ard_3-2-1_50HPH_2019-04-06_final.stac-item
2019-04-09 11:46:47	ga_s2bm_ard_3-2-1_50HQJ_2019-04-09_final.stac-item
2019-04-09 11:46:59	ga_s2bm_ard_3-2-1_50HMJ_2019-04-09_final.stac-item
2019-04-09 11:47:06	ga_s2bm_ard_3-2-1_50HPH_2019-04-09_final.stac-item
2019-04-09 11:47:14	ga_s2bm_ard_3-2-1_50HMH_2019-04-09_final.stac-item
2019-04-12 11:56:30	ga_s2bm_ard_3-2-1_50JLL_2019-04-12_final.stac-item
2019-04-12 11:56:56	ga_s2bm_ard_3-2-1_50HMJ_2019-04-12_final.stac-item
2019-04-12 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2019-04-12_final.stac-item
2019-04-12 11:57:13	ga_s2bm_ard_3-2-1_50HMH_2019-04-12_final.stac-item
2019-04-15 12:06:19	ga_s2bm_ard_3-2-1_50JLL_2019-04-15_final.stac-item
2019-04-16 11:36:54	ga_s2bm_ard_3-2-1_50HQJ_2019-04-16_final.stac-item
2019-04-16 11:37:12	ga_s2bm_ard_3-2-1_50HPH_2019-04-16_final.stac-item
2019-04-19 11:46:49	ga_s2bm_ard_3-2-1_50HQJ_2019-04-19_final.stac-item
2019-04-19 11:47:01	ga_s2bm_ard_3-2-1_50HMJ_2019-04-19_final.stac-item
2019-04-19 11:47:08	ga_s2bm_ard_3-2-1_50HPH_2019-04-19_final.stac-item
2019-04-19 11:47:16	ga_s2bm_ard_3-2-1_50HMH_2019-04-19_final.stac-item
2019-04-22 11:56:32	ga_s2bm_ard_3-2-1_50JLL_2019-04-22_final.stac-item
2019-04-22 11:56:57	ga_s2bm_ard_3-2-1_50HMJ_2019-04-22_final.stac-item
2019-04-22 11:57:12	ga_s2bm_ard_3-2-1_50HMH_2019-04-22_final.stac-item
2019-04-25 12:06:21	ga_s2bm_ard_3-2-1_50JLL_2019-04-25_final.stac-item
2019-04-26 11:36:55	ga_s2bm_ard_3-2-1_50HQJ_2019-04-26_final.stac-item
2019-04-26 11:37:14	ga_s2bm_ard_3-2-1_50HPH_2019-04-26_final.stac-item
2019-04-29 11:46:49	ga_s2bm_ard_3-2-1_50HQJ_2019-04-29_final.stac-item
2019-04-29 11:46:55	ga_s2bm_ard_3-2-1_50HMJ_2019-04-29_final.stac-item
2019-04-29 11:46:56	ga_s2bm_ard_3-2-1_50HQJ_2019-04-29_final.stac-item
2019-04-29 11:47:03	ga_s2bm_ard_3-2-1_50HMJ_2019-04-29_final.stac-item
2019-04-29 11:47:10	ga_s2bm_ard_3-2-1_50HPH_2019-04-29_final.stac-item
2019-04-29 11:47:17	ga_s2bm_ard_3-2-1_50HMH_2019-04-29_final.stac-item
2019-05-02 11:54:56	ga_s2bm_ard_3-2-1_50JMT_2019-05-02_final.stac-item
2019-05-02 11:54:58	ga_s2bm_ard_3-2-1_50JLS_2019-05-02_final.stac-item
2019-05-02 11:55:06	ga_s2bm_ard_3-2-1_50JLS_2019-05-02_final.stac-item
2019-05-02 11:55:20	ga_s2bm_ard_3-2-1_50JLR_2019-05-02_final.stac-item
2019-05-05 12:04:44	ga_s2bm_ard_3-2-1_50JMT_2019-05-05_final.stac-item
2019-05-05 12:05:02	ga_s2bm_ard_3-2-1_50JLS_2019-05-05_final.stac-item
2019-05-05 12:05:05	ga_s2bm_ard_3-2-1_50JKS_2019-05-05_final.stac-item
2019-05-05 12:05:16	ga_s2bm_ard_3-2-1_50JLR_2019-05-05_final.stac-item
2019-05-05 12:05:16	ga_s2bm_ard_3-2-1_49JFM_2019-05-05_final.stac-item
2019-05-05 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-05-05_final.stac-item
2019-05-05 12:05:23	ga_s2bm_ard_3-2-1_49JGL_2019-05-05_final.stac-item
2019-05-05 12:05:34	ga_s2bm_ard_3-2-1_50JKQ_2019-05-05_final.stac-item
2019-05-05 12:05:37	ga_s2bm_ard_3-2-1_49JGK_2019-05-05_final.stac-item
2019-05-08 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-05-08_final.stac-item
2019-05-08 12:15:28	ga_s2bm_ard_3-2-1_49JGK_2019-05-08_final.stac-item
2019-05-12 11:54:49	ga_s2bm_ard_3-2-1_50JMT_2019-05-12_final.stac-item
2019-05-12 11:55:06	ga_s2bm_ard_3-2-1_50JLS_2019-05-12_final.stac-item
2019-05-12 11:55:21	ga_s2bm_ard_3-2-1_50JLR_2019-05-12_final.stac-item
2019-05-15 12:04:44	ga_s2bm_ard_3-2-1_50JMT_2019-05-15_final.stac-item
2019-05-15 12:05:02	ga_s2bm_ard_3-2-1_50JLS_2019-05-15_final.stac-item
2019-05-15 12:05:06	ga_s2bm_ard_3-2-1_50JKS_2019-05-15_final.stac-item
2019-05-15 12:05:17	ga_s2bm_ard_3-2-1_50JLR_2019-05-15_final.stac-item
2019-05-15 12:05:17	ga_s2bm_ard_3-2-1_49JFM_2019-05-15_final.stac-item
2019-05-15 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-05-15_final.stac-item
2019-05-15 12:05:30	ga_s2bm_ard_3-2-1_50JKQ_2019-05-15_final.stac-item
2019-05-15 12:05:31	ga_s2bm_ard_3-2-1_49JGK_2019-05-15_final.stac-item
2019-05-15 12:05:36	ga_s2bm_ard_3-2-1_50JKQ_2019-05-15_final.stac-item
2019-05-15 12:05:38	ga_s2bm_ard_3-2-1_49JGK_2019-05-15_final.stac-item
2019-05-18 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-05-18_final.stac-item
2019-05-18 12:15:19	ga_s2bm_ard_3-2-1_49JGL_2019-05-18_final.stac-item
2019-05-18 12:15:28	ga_s2bm_ard_3-2-1_49JGK_2019-05-18_final.stac-item
2019-05-22 11:55:06	ga_s2bm_ard_3-2-1_50JLS_2019-05-22_final.stac-item
2019-05-22 11:55:21	ga_s2bm_ard_3-2-1_50JLR_2019-05-22_final.stac-item
2019-05-25 12:04:44	ga_s2bm_ard_3-2-1_50JMT_2019-05-25_final.stac-item
2019-05-25 12:05:02	ga_s2bm_ard_3-2-1_50JLS_2019-05-25_final.stac-item
2019-05-25 12:05:06	ga_s2bm_ard_3-2-1_50JKS_2019-05-25_final.stac-item
2019-05-25 12:05:17	ga_s2bm_ard_3-2-1_50JLR_2019-05-25_final.stac-item
2019-05-25 12:05:17	ga_s2bm_ard_3-2-1_49JFM_2019-05-25_final.stac-item
2019-05-25 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-05-25_final.stac-item
2019-05-25 12:05:30	ga_s2bm_ard_3-2-1_50JKQ_2019-05-25_final.stac-item
2019-05-25 12:05:31	ga_s2bm_ard_3-2-1_49JGK_2019-05-25_final.stac-item
2019-05-25 12:05:36	ga_s2bm_ard_3-2-1_50JKQ_2019-05-25_final.stac-item
2019-05-25 12:05:38	ga_s2bm_ard_3-2-1_49JGK_2019-05-25_final.stac-item
2019-05-28 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-05-28_final.stac-item
2019-05-28 12:15:28	ga_s2bm_ard_3-2-1_49JGK_2019-05-28_final.stac-item
2019-06-04 12:05:05	ga_s2bm_ard_3-2-1_50JKS_2019-06-04_final.stac-item
2019-06-04 12:05:17	ga_s2bm_ard_3-2-1_49JFM_2019-06-04_final.stac-item
2019-06-04 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-06-04_final.stac-item
2019-06-04 12:05:34	ga_s2bm_ard_3-2-1_50JKQ_2019-06-04_final.stac-item
2019-06-04 12:05:37	ga_s2bm_ard_3-2-1_49JGK_2019-06-04_final.stac-item
2019-06-07 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-06-07_final.stac-item
2019-06-07 12:15:28	ga_s2bm_ard_3-2-1_49JGK_2019-06-07_final.stac-item
2019-06-14 12:05:19	ga_s2bm_ard_3-2-1_50JKR_2019-06-14_final.stac-item
2019-06-14 12:05:21	ga_s2bm_ard_3-2-1_49JGL_2019-06-14_final.stac-item
2019-06-14 12:05:26	ga_s2bm_ard_3-2-1_50JKR_2019-06-14_final.stac-item
2019-06-14 12:05:27	ga_s2bm_ard_3-2-1_49JGK_2019-06-14_final.stac-item
2019-06-14 12:05:33	ga_s2bm_ard_3-2-1_50JKQ_2019-06-14_final.stac-item
2019-06-14 12:05:36	ga_s2bm_ard_3-2-1_49JGK_2019-06-14_final.stac-item
2019-06-17 12:15:07	ga_s2bm_ard_3-2-1_49JFM_2019-06-17_final.stac-item
2019-06-17 12:15:27	ga_s2bm_ard_3-2-1_49JGK_2019-06-17_final.stac-item
2019-06-21 11:54:48	ga_s2bm_ard_3-2-1_50JMT_2019-06-21_final.stac-item
2019-06-24 12:05:05	ga_s2bm_ard_3-2-1_50JKS_2019-06-24_final.stac-item
2019-06-24 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-06-24_final.stac-item
2019-06-24 12:05:34	ga_s2bm_ard_3-2-1_50JKQ_2019-06-24_final.stac-item
2019-06-24 12:05:37	ga_s2bm_ard_3-2-1_49JGK_2019-06-24_final.stac-item
2019-06-27 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-06-27_final.stac-item
2019-06-27 12:15:19	ga_s2bm_ard_3-2-1_49JGL_2019-06-27_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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