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 12:13:45	ga_s2bm_ard_3-2-1_49KHR_2022-04-02_final.stac-item
2022-04-02 12:13:46	ga_s2bm_ard_3-2-1_49KGR_2022-04-02_final.stac-item
2022-04-02 12:13:51	ga_s2bm_ard_3-2-1_49KHR_2022-04-02_final.stac-item
2022-04-02 12:13:55	ga_s2bm_ard_3-2-1_49KGR_2022-04-02_final.stac-item
2022-04-02 12:14:23	ga_s2bm_ard_3-2-1_49KGP_2022-04-02_final.stac-item
2022-04-02 12:14:38	ga_s2bm_ard_3-2-1_49JGN_2022-04-02_final.stac-item
2022-04-02 12:14:56	ga_s2bm_ard_3-2-1_49JFM_2022-04-02_final.stac-item
2022-04-02 12:15:07	ga_s2bm_ard_3-2-1_49JGL_2022-04-02_final.stac-item
2022-04-02 12:15:16	ga_s2bm_ard_3-2-1_49JGK_2022-04-02_final.stac-item
2022-04-06 11:54:41	ga_s2bm_ard_3-2-1_50JLT_2022-04-06_final.stac-item
2022-04-09 12:03:56	ga_s2bm_ard_3-2-1_49KHR_2022-04-09_final.stac-item
2022-04-09 12:04:15	ga_s2bm_ard_3-2-1_49KGQ_2022-04-09_final.stac-item
2022-04-09 12:04:25	ga_s2bm_ard_3-2-1_49KHP_2022-04-09_final.stac-item
2022-04-09 12:04:38	ga_s2bm_ard_3-2-1_49JGN_2022-04-09_final.stac-item
2022-04-09 12:04:41	ga_s2bm_ard_3-2-1_50JLT_2022-04-09_final.stac-item
2022-04-09 12:04:45	ga_s2bm_ard_3-2-1_49JGN_2022-04-09_final.stac-item
2022-04-09 12:04:53	ga_s2bm_ard_3-2-1_49JHM_2022-04-09_final.stac-item
2022-04-09 12:05:12	ga_s2bm_ard_3-2-1_49JGL_2022-04-09_final.stac-item
2022-04-09 12:05:26	ga_s2bm_ard_3-2-1_49JGK_2022-04-09_final.stac-item
2022-04-12 12:13:45	ga_s2bm_ard_3-2-1_49KHR_2022-04-12_final.stac-item
2022-04-12 12:14:09	ga_s2bm_ard_3-2-1_49KGQ_2022-04-12_final.stac-item
2022-04-12 12:14:18	ga_s2bm_ard_3-2-1_49KHP_2022-04-12_final.stac-item
2022-04-12 12:14:23	ga_s2bm_ard_3-2-1_49KGP_2022-04-12_final.stac-item
2022-04-12 12:14:38	ga_s2bm_ard_3-2-1_49JGN_2022-04-12_final.stac-item
2022-04-12 12:14:42	ga_s2bm_ard_3-2-1_49JFN_2022-04-12_final.stac-item
2022-04-12 12:14:56	ga_s2bm_ard_3-2-1_49JFM_2022-04-12_final.stac-item
2022-04-12 12:15:07	ga_s2bm_ard_3-2-1_49JGL_2022-04-12_final.stac-item
2022-04-12 12:15:16	ga_s2bm_ard_3-2-1_49JGK_2022-04-12_final.stac-item
2022-04-16 11:54:40	ga_s2bm_ard_3-2-1_50JLT_2022-04-16_final.stac-item
2022-04-19 12:03:55	ga_s2bm_ard_3-2-1_49KHR_2022-04-19_final.stac-item
2022-04-19 12:04:27	ga_s2bm_ard_3-2-1_49KGP_2022-04-19_final.stac-item
2022-04-19 12:04:33	ga_s2bm_ard_3-2-1_50JLT_2022-04-19_final.stac-item
2022-04-19 12:04:40	ga_s2bm_ard_3-2-1_50JLT_2022-04-19_final.stac-item
2022-04-19 12:04:44	ga_s2bm_ard_3-2-1_49JGN_2022-04-19_final.stac-item
2022-04-19 12:04:52	ga_s2bm_ard_3-2-1_49JHM_2022-04-19_final.stac-item
2022-04-19 12:05:10	ga_s2bm_ard_3-2-1_49JGL_2022-04-19_final.stac-item
2022-04-19 12:05:25	ga_s2bm_ard_3-2-1_49JGK_2022-04-19_final.stac-item
2022-04-22 12:13:44	ga_s2bm_ard_3-2-1_49KGR_2022-04-22_final.stac-item
2022-04-22 12:13:49	ga_s2bm_ard_3-2-1_49KHR_2022-04-22_final.stac-item
2022-04-22 12:13:53	ga_s2bm_ard_3-2-1_49KGR_2022-04-22_final.stac-item
2022-04-22 12:14:40	ga_s2bm_ard_3-2-1_49JFN_2022-04-22_final.stac-item
2022-04-22 12:14:54	ga_s2bm_ard_3-2-1_49JFM_2022-04-22_final.stac-item
2022-04-22 12:15:05	ga_s2bm_ard_3-2-1_49JGL_2022-04-22_final.stac-item
2022-04-22 12:15:15	ga_s2bm_ard_3-2-1_49JGK_2022-04-22_final.stac-item
2022-04-29 12:04:11	ga_s2bm_ard_3-2-1_49KGQ_2022-04-29_final.stac-item
2022-04-29 12:04:21	ga_s2bm_ard_3-2-1_49KHP_2022-04-29_final.stac-item
2022-04-29 12:04:24	ga_s2bm_ard_3-2-1_49KGP_2022-04-29_final.stac-item
2022-04-29 12:04:31	ga_s2bm_ard_3-2-1_50JLT_2022-04-29_final.stac-item
2022-04-29 12:04:34	ga_s2bm_ard_3-2-1_49JGN_2022-04-29_final.stac-item
2022-04-29 12:04:37	ga_s2bm_ard_3-2-1_50JLT_2022-04-29_final.stac-item
2022-04-29 12:04:41	ga_s2bm_ard_3-2-1_49JGN_2022-04-29_final.stac-item
2022-04-29 12:04:50	ga_s2bm_ard_3-2-1_49JHM_2022-04-29_final.stac-item
2022-04-29 12:05:08	ga_s2bm_ard_3-2-1_49JGL_2022-04-29_final.stac-item
2022-04-29 12:05:22	ga_s2bm_ard_3-2-1_49JGK_2022-04-29_final.stac-item
2022-05-03 11:46:21	ga_s2bm_ard_3-2-1_50JML_2022-05-03_final.stac-item
2022-05-03 11:46:25	ga_s2bm_ard_3-2-1_50HQK_2022-05-03_final.stac-item
2022-05-03 11:46:48	ga_s2bm_ard_3-2-1_50HQH_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 11:56:10	ga_s2bm_ard_3-2-1_50JKM_2022-05-06_final.stac-item
2022-05-06 11:56:18	ga_s2bm_ard_3-2-1_50JML_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 12:06:07	ga_s2bm_ard_3-2-1_50JKM_2022-05-09_final.stac-item
2022-05-10 11:36:31	ga_s2bm_ard_3-2-1_50HQK_2022-05-10_final.stac-item
2022-05-10 11:37:00	ga_s2bm_ard_3-2-1_50HQH_2022-05-10_final.stac-item
2022-05-13 11:46:24	ga_s2bm_ard_3-2-1_50JML_2022-05-13_final.stac-item
2022-05-13 11:46:28	ga_s2bm_ard_3-2-1_50HQK_2022-05-13_final.stac-item
2022-05-13 11:46:51	ga_s2bm_ard_3-2-1_50HQH_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 11:56:13	ga_s2bm_ard_3-2-1_50JKM_2022-05-16_final.stac-item
2022-05-16 11:56:21	ga_s2bm_ard_3-2-1_50JML_2022-05-16_final.stac-item
2022-05-16 11:56:39	ga_s2bm_ard_3-2-1_50HLK_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
2022-05-19 12:06:09	ga_s2bm_ard_3-2-1_50JKM_2022-05-19_final.stac-item
2022-05-20 11:36:34	ga_s2bm_ard_3-2-1_50HQK_2022-05-20_final.stac-item
2022-05-20 11:37:03	ga_s2bm_ard_3-2-1_50HQH_2022-05-20_final.stac-item
2022-05-23 11:46:26	ga_s2bm_ard_3-2-1_50JML_2022-05-23_final.stac-item
2022-05-23 11:46:30	ga_s2bm_ard_3-2-1_50HQK_2022-05-23_final.stac-item
2022-05-23 11:46:53	ga_s2bm_ard_3-2-1_50HQH_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 11:56:14	ga_s2bm_ard_3-2-1_50JKM_2022-05-26_final.stac-item
2022-05-26 11:56:22	ga_s2bm_ard_3-2-1_50JML_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 12:06:10	ga_s2bm_ard_3-2-1_50JKM_2022-05-29_final.stac-item
2022-05-30 11:36:34	ga_s2bm_ard_3-2-1_50HQK_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

All years