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
2018-04-28 11:24:29	ga_s2bm_ard_3-2-1_51HXE_2018-04-28_final.stac-item
2018-05-02 11:00:12	ga_s2bm_ard_3-2-1_51HYD_2018-05-02_final.stac-item
2018-05-10 12:05:05	ga_s2bm_ard_3-2-1_50JLL_2018-05-10_final.stac-item
2018-05-10 12:05:05	ga_s2bm_ard_3-2-1_50JLM_2018-05-10_final.stac-item
2018-05-15 11:13:12	ga_s2bm_ard_3-2-1_51HYD_2018-05-15_final.stac-item
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_50JLL_2018-05-20_final.stac-item
2018-05-30 12:04:45	ga_s2bm_ard_3-2-1_50JLL_2018-05-30_final.stac-item
2022-06-02 11:43:21	ga_s2bm_ard_3-2-1_50KQC_2022-06-02_final.stac-item
2022-06-02 11:44:05	ga_s2bm_ard_3-2-1_50KQV_2022-06-02_final.stac-item
2022-06-02 11:44:19	ga_s2bm_ard_3-2-1_50KQU_2022-06-02_final.stac-item
2022-06-02 11:44:30	ga_s2bm_ard_3-2-1_50JRT_2022-06-02_final.stac-item
2022-06-02 11:44:34	ga_s2bm_ard_3-2-1_50JQT_2022-06-02_final.stac-item
2022-06-03 11:14:23	ga_s2bm_ard_3-2-1_51JZN_2022-06-03_final.stac-item
2022-06-05 11:53:18	ga_s2bm_ard_3-2-1_50KQC_2022-06-05_final.stac-item
2022-06-05 11:53:22	ga_s2bm_ard_3-2-1_50KPC_2022-06-05_final.stac-item
2022-06-05 11:53:39	ga_s2bm_ard_3-2-1_50KNB_2022-06-05_final.stac-item
2022-06-05 11:53:54	ga_s2bm_ard_3-2-1_50KNA_2022-06-05_final.stac-item
2022-06-05 11:53:57	ga_s2bm_ard_3-2-1_50KMA_2022-06-05_final.stac-item
2022-06-05 11:53:59	ga_s2bm_ard_3-2-1_50KQV_2022-06-05_final.stac-item
2022-06-05 11:54:04	ga_s2bm_ard_3-2-1_50KMA_2022-06-05_final.stac-item
2022-06-05 11:54:05	ga_s2bm_ard_3-2-1_50KQV_2022-06-05_final.stac-item
2022-06-05 11:54:14	ga_s2bm_ard_3-2-1_50KQU_2022-06-05_final.stac-item
2022-06-05 11:54:24	ga_s2bm_ard_3-2-1_50JQT_2022-06-05_final.stac-item
2022-06-05 11:54:26	ga_s2bm_ard_3-2-1_50KMU_2022-06-05_final.stac-item
2022-06-05 11:54:34	ga_s2bm_ard_3-2-1_50KLU_2022-06-05_final.stac-item
2022-06-05 11:54:41	ga_s2bm_ard_3-2-1_50JMT_2022-06-05_final.stac-item
2022-06-05 11:54:45	ga_s2bm_ard_3-2-1_50JLT_2022-06-05_final.stac-item
2022-06-05 11:55:47	ga_s2bm_ard_3-2-1_50JKP_2022-06-05_final.stac-item
2022-06-06 11:24:20	ga_s2bm_ard_3-2-1_51JZN_2022-06-06_final.stac-item
2022-06-08 12:03:35	ga_s2bm_ard_3-2-1_50KNB_2022-06-08_final.stac-item
2022-06-08 12:03:45	ga_s2bm_ard_3-2-1_50KNA_2022-06-08_final.stac-item
2022-06-08 12:03:53	ga_s2bm_ard_3-2-1_50KMA_2022-06-08_final.stac-item
2022-06-08 12:04:12	ga_s2bm_ard_3-2-1_50KLV_2022-06-08_final.stac-item
2022-06-08 12:04:23	ga_s2bm_ard_3-2-1_50KMU_2022-06-08_final.stac-item
2022-06-08 12:04:26	ga_s2bm_ard_3-2-1_50KLU_2022-06-08_final.stac-item
2022-06-08 12:04:37	ga_s2bm_ard_3-2-1_50JMT_2022-06-08_final.stac-item
2022-06-08 12:04:39	ga_s2bm_ard_3-2-1_50JLT_2022-06-08_final.stac-item
2022-06-08 12:04:48	ga_s2bm_ard_3-2-1_50JKT_2022-06-08_final.stac-item
2022-06-09 11:34:19	ga_s2bm_ard_3-2-1_51KUP_2022-06-09_final.stac-item
2022-06-12 11:43:24	ga_s2bm_ard_3-2-1_50KQC_2022-06-12_final.stac-item
2022-06-12 11:44:08	ga_s2bm_ard_3-2-1_50KQV_2022-06-12_final.stac-item
2022-06-12 11:44:22	ga_s2bm_ard_3-2-1_50KQU_2022-06-12_final.stac-item
2022-06-12 11:44:33	ga_s2bm_ard_3-2-1_50JRT_2022-06-12_final.stac-item
2022-06-12 11:44:37	ga_s2bm_ard_3-2-1_50JQT_2022-06-12_final.stac-item
2022-06-13 11:14:26	ga_s2bm_ard_3-2-1_51JZN_2022-06-13_final.stac-item
2022-06-15 11:53:21	ga_s2bm_ard_3-2-1_50KQC_2022-06-15_final.stac-item
2022-06-15 11:53:24	ga_s2bm_ard_3-2-1_50KPC_2022-06-15_final.stac-item
2022-06-15 11:53:42	ga_s2bm_ard_3-2-1_50KNB_2022-06-15_final.stac-item
2022-06-15 11:53:57	ga_s2bm_ard_3-2-1_50KNA_2022-06-15_final.stac-item
2022-06-15 11:54:00	ga_s2bm_ard_3-2-1_50KMA_2022-06-15_final.stac-item
2022-06-15 11:54:02	ga_s2bm_ard_3-2-1_50KQV_2022-06-15_final.stac-item
2022-06-15 11:54:07	ga_s2bm_ard_3-2-1_50KMA_2022-06-15_final.stac-item
2022-06-15 11:54:08	ga_s2bm_ard_3-2-1_50KQV_2022-06-15_final.stac-item
2022-06-15 11:54:15	ga_s2bm_ard_3-2-1_50KMV_2022-06-15_final.stac-item
2022-06-15 11:54:16	ga_s2bm_ard_3-2-1_50KQU_2022-06-15_final.stac-item
2022-06-15 11:54:26	ga_s2bm_ard_3-2-1_50JQT_2022-06-15_final.stac-item
2022-06-15 11:54:29	ga_s2bm_ard_3-2-1_50KMU_2022-06-15_final.stac-item
2022-06-15 11:54:36	ga_s2bm_ard_3-2-1_50KLU_2022-06-15_final.stac-item
2022-06-15 11:54:44	ga_s2bm_ard_3-2-1_50JMT_2022-06-15_final.stac-item
2022-06-15 11:54:48	ga_s2bm_ard_3-2-1_50JLT_2022-06-15_final.stac-item
2022-06-16 11:24:22	ga_s2bm_ard_3-2-1_51JZN_2022-06-16_final.stac-item
2022-06-18 12:03:37	ga_s2bm_ard_3-2-1_50KNB_2022-06-18_final.stac-item
2022-06-18 12:03:48	ga_s2bm_ard_3-2-1_50KNA_2022-06-18_final.stac-item
2022-06-18 12:03:56	ga_s2bm_ard_3-2-1_50KMA_2022-06-18_final.stac-item
2022-06-18 12:04:14	ga_s2bm_ard_3-2-1_50KLV_2022-06-18_final.stac-item
2022-06-18 12:04:25	ga_s2bm_ard_3-2-1_50KMU_2022-06-18_final.stac-item
2022-06-18 12:04:29	ga_s2bm_ard_3-2-1_50KLU_2022-06-18_final.stac-item
2022-06-18 12:04:39	ga_s2bm_ard_3-2-1_50JMT_2022-06-18_final.stac-item
2022-06-18 12:04:42	ga_s2bm_ard_3-2-1_50JLT_2022-06-18_final.stac-item
2022-06-18 12:04:50	ga_s2bm_ard_3-2-1_50JKT_2022-06-18_final.stac-item
2022-06-22 11:43:26	ga_s2bm_ard_3-2-1_50KQC_2022-06-22_final.stac-item
2022-06-22 11:44:10	ga_s2bm_ard_3-2-1_50KQV_2022-06-22_final.stac-item
2022-06-22 11:44:24	ga_s2bm_ard_3-2-1_50KQU_2022-06-22_final.stac-item
2022-06-22 11:44:35	ga_s2bm_ard_3-2-1_50JRT_2022-06-22_final.stac-item
2022-06-22 11:44:39	ga_s2bm_ard_3-2-1_50JQT_2022-06-22_final.stac-item
2022-06-25 11:53:22	ga_s2bm_ard_3-2-1_50KQC_2022-06-25_final.stac-item
2022-06-25 11:53:26	ga_s2bm_ard_3-2-1_50KPC_2022-06-25_final.stac-item
2022-06-25 11:53:44	ga_s2bm_ard_3-2-1_50KNB_2022-06-25_final.stac-item
2022-06-25 11:53:58	ga_s2bm_ard_3-2-1_50KNA_2022-06-25_final.stac-item
2022-06-25 11:54:01	ga_s2bm_ard_3-2-1_50KMA_2022-06-25_final.stac-item
2022-06-25 11:54:03	ga_s2bm_ard_3-2-1_50KQV_2022-06-25_final.stac-item
2022-06-25 11:54:07	ga_s2bm_ard_3-2-1_50KNA_2022-06-25_final.stac-item
2022-06-25 11:54:08	ga_s2bm_ard_3-2-1_50KMA_2022-06-25_final.stac-item
2022-06-25 11:54:10	ga_s2bm_ard_3-2-1_50KQV_2022-06-25_final.stac-item
2022-06-25 11:54:16	ga_s2bm_ard_3-2-1_50KMV_2022-06-25_final.stac-item
2022-06-25 11:54:18	ga_s2bm_ard_3-2-1_50KQU_2022-06-25_final.stac-item
2022-06-25 11:54:28	ga_s2bm_ard_3-2-1_50JQT_2022-06-25_final.stac-item
2022-06-25 11:54:31	ga_s2bm_ard_3-2-1_50KMU_2022-06-25_final.stac-item
2022-06-25 11:54:38	ga_s2bm_ard_3-2-1_50KLU_2022-06-25_final.stac-item
2022-06-25 11:54:45	ga_s2bm_ard_3-2-1_50JMT_2022-06-25_final.stac-item
2022-06-25 11:54:49	ga_s2bm_ard_3-2-1_50JLT_2022-06-25_final.stac-item
2022-06-26 11:24:24	ga_s2bm_ard_3-2-1_51JZN_2022-06-26_final.stac-item
2022-06-28 12:03:38	ga_s2bm_ard_3-2-1_50KNB_2022-06-28_final.stac-item
2022-06-28 12:03:49	ga_s2bm_ard_3-2-1_50KNA_2022-06-28_final.stac-item
2022-06-28 12:03:57	ga_s2bm_ard_3-2-1_50KMA_2022-06-28_final.stac-item
2022-06-28 12:04:12	ga_s2bm_ard_3-2-1_50KMV_2022-06-28_final.stac-item
2022-06-28 12:04:15	ga_s2bm_ard_3-2-1_50KLV_2022-06-28_final.stac-item
2022-06-28 12:04:26	ga_s2bm_ard_3-2-1_50KMU_2022-06-28_final.stac-item
2022-06-28 12:04:30	ga_s2bm_ard_3-2-1_50KLU_2022-06-28_final.stac-item
2022-06-28 12:04:40	ga_s2bm_ard_3-2-1_50JMT_2022-06-28_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

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