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
2022-06-01 12:14:08	ga_s2bm_ard_3-2-1_49KHQ_2022-06-01_final.stac-item
2022-06-01 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2022-06-01_final.stac-item
2022-06-01 12:14:31	ga_s2bm_ard_3-2-1_49JHN_2022-06-01_final.stac-item
2022-06-05 11:54:55	ga_s2bm_ard_3-2-1_50JMS_2022-06-05_final.stac-item
2022-06-05 11:55:35	ga_s2bm_ard_3-2-1_50JNP_2022-06-05_final.stac-item
2022-06-05 11:55:54	ga_s2bm_ard_3-2-1_50JMN_2022-06-05_final.stac-item
2022-06-05 11:55:57	ga_s2bm_ard_3-2-1_50JLN_2022-06-05_final.stac-item
2022-06-05 11:56:08	ga_s2bm_ard_3-2-1_50JMM_2022-06-05_final.stac-item
2022-06-05 11:56:37	ga_s2bm_ard_3-2-1_50HMK_2022-06-05_final.stac-item
2022-06-08 12:04:45	ga_s2bm_ard_3-2-1_50JMS_2022-06-08_final.stac-item
2022-06-08 12:04:50	ga_s2bm_ard_3-2-1_50JMS_2022-06-08_final.stac-item
2022-06-08 12:05:53	ga_s2bm_ard_3-2-1_50JLN_2022-06-08_final.stac-item
2022-06-08 12:06:05	ga_s2bm_ard_3-2-1_50JLM_2022-06-08_final.stac-item
2022-06-11 12:14:11	ga_s2bm_ard_3-2-1_49KHQ_2022-06-11_final.stac-item
2022-06-11 12:14:29	ga_s2bm_ard_3-2-1_49KGP_2022-06-11_final.stac-item
2022-06-15 11:54:58	ga_s2bm_ard_3-2-1_50JMS_2022-06-15_final.stac-item
2022-06-15 11:55:56	ga_s2bm_ard_3-2-1_50JMN_2022-06-15_final.stac-item
2022-06-15 11:56:00	ga_s2bm_ard_3-2-1_50JLN_2022-06-15_final.stac-item
2022-06-15 11:57:13	ga_s2bm_ard_3-2-1_50HLH_2022-06-15_final.stac-item
2022-06-18 12:04:47	ga_s2bm_ard_3-2-1_50JMS_2022-06-18_final.stac-item
2022-06-18 12:04:52	ga_s2bm_ard_3-2-1_50JMS_2022-06-18_final.stac-item
2022-06-18 12:05:55	ga_s2bm_ard_3-2-1_50JLN_2022-06-18_final.stac-item
2022-06-18 12:06:08	ga_s2bm_ard_3-2-1_50JLM_2022-06-18_final.stac-item
2022-06-21 12:13:59	ga_s2bm_ard_3-2-1_49KHR_2022-06-21_final.stac-item
2022-06-22 11:46:53	ga_s2bm_ard_3-2-1_50HPJ_2022-06-22_final.stac-item
2022-06-25 11:55:00	ga_s2bm_ard_3-2-1_50JMS_2022-06-25_final.stac-item
2022-06-25 11:55:58	ga_s2bm_ard_3-2-1_50JMN_2022-06-25_final.stac-item
2022-06-25 11:56:01	ga_s2bm_ard_3-2-1_50JLN_2022-06-25_final.stac-item
2022-06-28 12:04:04	ga_s2bm_ard_3-2-1_49KHR_2022-06-28_final.stac-item
2022-06-28 12:04:48	ga_s2bm_ard_3-2-1_50JMS_2022-06-28_final.stac-item
2022-06-28 12:04:53	ga_s2bm_ard_3-2-1_50JMS_2022-06-28_final.stac-item
2022-06-28 12:05:56	ga_s2bm_ard_3-2-1_50JLN_2022-06-28_final.stac-item
2022-06-28 12:06:09	ga_s2bm_ard_3-2-1_50JLM_2022-06-28_final.stac-item
2022-07-02 11:46:18	ga_s2bm_ard_3-2-1_50JMM_2022-07-02_final.stac-item
2022-07-02 11:46:42	ga_s2bm_ard_3-2-1_50HNK_2022-07-02_final.stac-item
2022-07-02 11:46:46	ga_s2bm_ard_3-2-1_50HMK_2022-07-02_final.stac-item
2022-07-02 11:46:53	ga_s2bm_ard_3-2-1_50HPJ_2022-07-02_final.stac-item
2022-07-02 11:46:57	ga_s2bm_ard_3-2-1_50HNJ_2022-07-02_final.stac-item
2022-07-02 11:46:58	ga_s2bm_ard_3-2-1_50HQH_2022-07-02_final.stac-item
2022-07-02 11:47:11	ga_s2bm_ard_3-2-1_50HNH_2022-07-02_final.stac-item
2022-07-02 11:47:19	ga_s2bm_ard_3-2-1_50HLH_2022-07-02_final.stac-item
2022-07-05 11:55:00	ga_s2bm_ard_3-2-1_50JMS_2022-07-05_final.stac-item
2022-07-05 11:55:58	ga_s2bm_ard_3-2-1_50JMN_2022-07-05_final.stac-item
2022-07-05 11:56:01	ga_s2bm_ard_3-2-1_50JLN_2022-07-05_final.stac-item
2022-07-05 11:56:13	ga_s2bm_ard_3-2-1_50JMM_2022-07-05_final.stac-item
2022-07-05 11:56:16	ga_s2bm_ard_3-2-1_50JLM_2022-07-05_final.stac-item
2022-07-05 11:56:34	ga_s2bm_ard_3-2-1_50HNK_2022-07-05_final.stac-item
2022-07-05 11:56:41	ga_s2bm_ard_3-2-1_50HMK_2022-07-05_final.stac-item
2022-07-05 11:56:45	ga_s2bm_ard_3-2-1_50HLK_2022-07-05_final.stac-item
2022-07-05 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2022-07-05_final.stac-item
2022-07-05 11:57:14	ga_s2bm_ard_3-2-1_50HLH_2022-07-05_final.stac-item
2022-07-08 12:04:48	ga_s2bm_ard_3-2-1_50JMS_2022-07-08_final.stac-item
2022-07-08 12:04:53	ga_s2bm_ard_3-2-1_50JMS_2022-07-08_final.stac-item
2022-07-08 12:05:56	ga_s2bm_ard_3-2-1_50JLN_2022-07-08_final.stac-item
2022-07-08 12:06:09	ga_s2bm_ard_3-2-1_50JLM_2022-07-08_final.stac-item
2022-07-09 11:36:57	ga_s2bm_ard_3-2-1_50HPJ_2022-07-09_final.stac-item
2022-07-09 11:37:07	ga_s2bm_ard_3-2-1_50HQH_2022-07-09_final.stac-item
2022-07-12 11:46:17	ga_s2bm_ard_3-2-1_50JMM_2022-07-12_final.stac-item
2022-07-12 11:46:42	ga_s2bm_ard_3-2-1_50HNK_2022-07-12_final.stac-item
2022-07-12 11:46:45	ga_s2bm_ard_3-2-1_50HMK_2022-07-12_final.stac-item
2022-07-12 11:46:52	ga_s2bm_ard_3-2-1_50HPJ_2022-07-12_final.stac-item
2022-07-12 11:46:56	ga_s2bm_ard_3-2-1_50HNJ_2022-07-12_final.stac-item
2022-07-12 11:46:58	ga_s2bm_ard_3-2-1_50HQH_2022-07-12_final.stac-item
2022-07-12 11:47:11	ga_s2bm_ard_3-2-1_50HNH_2022-07-12_final.stac-item
2022-07-12 11:47:18	ga_s2bm_ard_3-2-1_50HLH_2022-07-12_final.stac-item
2022-07-15 11:54:59	ga_s2bm_ard_3-2-1_50JMS_2022-07-15_final.stac-item
2022-07-15 11:55:57	ga_s2bm_ard_3-2-1_50JMN_2022-07-15_final.stac-item
2022-07-15 11:56:01	ga_s2bm_ard_3-2-1_50JLN_2022-07-15_final.stac-item
2022-07-15 11:56:12	ga_s2bm_ard_3-2-1_50JMM_2022-07-15_final.stac-item
2022-07-15 11:56:15	ga_s2bm_ard_3-2-1_50JLM_2022-07-15_final.stac-item
2022-07-15 11:56:34	ga_s2bm_ard_3-2-1_50HNK_2022-07-15_final.stac-item
2022-07-15 11:56:41	ga_s2bm_ard_3-2-1_50HMK_2022-07-15_final.stac-item
2022-07-15 11:56:44	ga_s2bm_ard_3-2-1_50HLK_2022-07-15_final.stac-item
2022-07-15 11:56:59	ga_s2bm_ard_3-2-1_50HLJ_2022-07-15_final.stac-item
2022-07-15 11:57:13	ga_s2bm_ard_3-2-1_50HLH_2022-07-15_final.stac-item
2022-07-18 12:04:53	ga_s2bm_ard_3-2-1_50JMS_2022-07-18_final.stac-item
2022-07-18 12:05:56	ga_s2bm_ard_3-2-1_50JLN_2022-07-18_final.stac-item
2022-07-18 12:06:09	ga_s2bm_ard_3-2-1_50JLM_2022-07-18_final.stac-item
2022-07-19 11:37:07	ga_s2bm_ard_3-2-1_50HQH_2022-07-19_final.stac-item
2022-07-22 11:46:18	ga_s2bm_ard_3-2-1_50JMM_2022-07-22_final.stac-item
2022-07-22 11:46:42	ga_s2bm_ard_3-2-1_50HNK_2022-07-22_final.stac-item
2022-07-22 11:46:46	ga_s2bm_ard_3-2-1_50HMK_2022-07-22_final.stac-item
2022-07-22 11:46:57	ga_s2bm_ard_3-2-1_50HNJ_2022-07-22_final.stac-item
2022-07-22 11:46:58	ga_s2bm_ard_3-2-1_50HQH_2022-07-22_final.stac-item
2022-07-22 11:47:11	ga_s2bm_ard_3-2-1_50HNH_2022-07-22_final.stac-item
2022-07-22 11:47:19	ga_s2bm_ard_3-2-1_50HLH_2022-07-22_final.stac-item
2022-07-25 11:55:00	ga_s2bm_ard_3-2-1_50JMS_2022-07-25_final.stac-item
2022-07-25 11:55:58	ga_s2bm_ard_3-2-1_50JMN_2022-07-25_final.stac-item
2022-07-25 11:56:01	ga_s2bm_ard_3-2-1_50JLN_2022-07-25_final.stac-item
2022-07-25 11:56:13	ga_s2bm_ard_3-2-1_50JMM_2022-07-25_final.stac-item
2022-07-25 11:56:16	ga_s2bm_ard_3-2-1_50JLM_2022-07-25_final.stac-item
2022-07-25 11:56:35	ga_s2bm_ard_3-2-1_50HNK_2022-07-25_final.stac-item
2022-07-25 11:56:41	ga_s2bm_ard_3-2-1_50HMK_2022-07-25_final.stac-item
2022-07-25 11:56:45	ga_s2bm_ard_3-2-1_50HLK_2022-07-25_final.stac-item
2022-07-25 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2022-07-25_final.stac-item
2022-07-25 11:57:14	ga_s2bm_ard_3-2-1_50HLH_2022-07-25_final.stac-item
2022-07-28 12:04:53	ga_s2bm_ard_3-2-1_50JMS_2022-07-28_final.stac-item
2022-07-28 12:05:56	ga_s2bm_ard_3-2-1_50JLN_2022-07-28_final.stac-item
2022-07-28 12:06:09	ga_s2bm_ard_3-2-1_50JLM_2022-07-28_final.stac-item
2022-07-29 11:36:57	ga_s2bm_ard_3-2-1_50HPJ_2022-07-29_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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