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

43 results

Time (local)	Label
2017-10-27 09:32:47	ga_s2bm_ard_3-2-1_55GDR_2017-10-27_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50JNL_2017-11-28_final.stac-item
2017-12-01 10:16:54	ga_s2bm_ard_3-2-1_54KUV_2017-12-01_final.stac-item
2018-03-21 10:17:00	ga_s2bm_ard_3-2-1_54LWH_2018-03-21_final.stac-item
2018-07-12 10:29:34	ga_s2bm_ard_3-2-1_53KRQ_2018-07-12_final.stac-item
2018-10-15 09:46:40	ga_s2bm_ard_3-2-1_54GYA_2018-10-15_final.stac-item
2018-10-24 11:43:41	ga_s2bm_ard_3-2-1_50KPC_2018-10-24_final.stac-item
2018-11-24 11:26:46	ga_s2bm_ard_3-2-1_51HVC_2018-11-24_final.stac-item
2019-01-03 11:27:05	ga_s2bm_ard_3-2-1_51HTC_2019-01-03_final.stac-item
2019-02-16 09:28:30	ga_s2bm_ard_3-2-1_55GFP_2019-02-15_final.stac-item
2019-02-25 11:33:33	ga_s2bm_ard_3-2-1_51KUS_2019-02-25_final.stac-item
2019-05-16 09:57:59	ga_s2bm_ard_3-2-1_55HBS_2019-05-16_final.stac-item
2019-06-22 09:43:35	ga_s2bm_ard_3-2-1_56KKU_2019-06-22_final.stac-item
2019-08-16 10:34:20	ga_s2bm_ard_3-2-1_53JNN_2019-08-16_final.stac-item
2019-10-22 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2019-10-22_final.stac-item
2019-10-31 10:55:43	ga_s2bm_ard_3-2-1_52JGM_2019-10-31_final.stac-item
2020-01-13 10:34:24	ga_s2bm_ard_3-2-1_54JTR_2020-01-13_final.stac-item
2020-08-25 11:21:35	ga_s2bm_ard_3-2-1_52LDJ_2020-08-25_final.stac-item
2020-12-03 11:23:38	ga_s2bm_ard_3-2-1_51KYR_2020-12-03_final.stac-item
2020-12-23 11:22:09	ga_s2bm_ard_3-2-1_52KDF_2020-12-23_final.stac-item
2021-01-08 10:04:21	ga_s2bm_ard_3-2-1_55JBL_2021-01-08_final.stac-item
2021-04-04 10:20:04	ga_s2bm_ard_3-2-1_54LZN_2021-04-04_final.stac-item
2021-04-07 10:30:23	ga_s2bm_ard_3-2-1_54LWM_2021-04-07_final.stac-item
2021-04-11 10:16:24	ga_s2bm_ard_3-2-1_54HVH_2021-04-11_final.stac-item
2021-07-10 10:16:40	ga_s2bm_ard_3-2-1_54HWG_2021-07-10_final.stac-item
2021-09-26 11:13:28	ga_s2bm_ard_3-2-1_52KEA_2021-09-26_final.stac-item
2022-02-25 11:56:13	ga_s2bm_ard_3-2-1_50JNL_2022-02-25_final.stac-item
2022-04-12 10:31:28	ga_s2bm_ard_3-2-1_54LUH_2022-04-12_final.stac-item
2022-06-03 11:12:10	ga_s2bm_ard_3-2-1_52KCG_2022-06-03_final.stac-item
2022-06-23 11:14:21	ga_s2bm_ard_3-2-1_52JDT_2022-06-23_final.stac-item
2022-07-03 11:16:17	ga_s2bm_ard_3-2-1_51JXF_2022-07-03_final.stac-item
2022-08-08 11:34:07	ga_s2bm_ard_3-2-1_51KUQ_2022-08-08_final.stac-item
2022-08-31 10:02:02	ga_s2bm_ard_3-2-1_55KEV_2022-08-31_final.stac-item
2022-09-20 11:42:47	ga_s2bm_ard_3-2-1_51KUV_2022-09-20_final.stac-item
2023-02-06 10:31:38	ga_s2bm_ard_3-2-1_53LRC_2023-02-06_nrt.stac-item
2023-02-22 09:15:22	ga_s2bm_ard_3-2-1_56JPL_2023-02-21_nrt.stac-item
2023-02-25 09:28:29	ga_s2bm_ard_3-2-1_55GFP_2023-02-24_final
2023-02-26 10:32:11	ga_s2bm_ard_3-2-1_53KQA_2023-02-26_final
2023-03-28 10:30:59	ga_s2bm_ard_3-2-1_54LWK_2023-03-28_final
2023-05-03 10:56:02	ga_s2bm_ard_3-2-1_52JFL_2023-05-03_final
2023-05-22 11:21:37	ga_s2bm_ard_3-2-1_52LDJ_2023-05-22_final
2024-02-16 09:47:45	ga_s2bm_ard_3-2-1_55HES_2024-02-16_final
2024-04-11 10:34:18	ga_s2bm_ard_3-2-1_53JQM_2024-04-11_final

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