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
2019-01-07 11:03:00	ga_s2bm_ard_3-2-1_52KFC_2019-01-07_final.stac-item
2019-01-09 11:42:55	ga_s2bm_ard_3-2-1_51KVU_2019-01-09_final.stac-item
2019-01-09 11:42:59	ga_s2bm_ard_3-2-1_51KUU_2019-01-09_final.stac-item
2019-01-09 11:43:02	ga_s2bm_ard_3-2-1_51KTU_2019-01-09_final.stac-item
2019-01-09 11:43:03	ga_s2bm_ard_3-2-1_50KRD_2019-01-09_final.stac-item
2019-01-09 11:43:13	ga_s2bm_ard_3-2-1_51KUT_2019-01-09_final.stac-item
2019-01-09 11:43:17	ga_s2bm_ard_3-2-1_51KTT_2019-01-09_final.stac-item
2019-01-09 11:43:17	ga_s2bm_ard_3-2-1_50KRC_2019-01-09_final.stac-item
2019-01-09 11:43:20	ga_s2bm_ard_3-2-1_50KQC_2019-01-09_final.stac-item
2019-01-25 12:03:27	ga_s2bm_ard_3-2-1_50KLC_2019-01-25_final.stac-item
2019-01-26 09:52:14	ga_s2bm_ard_3-2-1_55KGU_2019-01-26_final.stac-item
2019-01-26 09:52:17	ga_s2bm_ard_3-2-1_55KFU_2019-01-26_final.stac-item
2019-01-26 09:52:20	ga_s2bm_ard_3-2-1_55KEU_2019-01-26_final.stac-item
2019-01-26 09:52:28	ga_s2bm_ard_3-2-1_55KGT_2019-01-26_final.stac-item
2019-01-26 09:52:31	ga_s2bm_ard_3-2-1_55KFT_2019-01-26_final.stac-item
2019-02-01 11:52:59	ga_s2bm_ard_3-2-1_50KRD_2019-02-01_final.stac-item
2019-02-01 11:53:11	ga_s2bm_ard_3-2-1_50KRC_2019-02-01_final.stac-item
2019-02-01 11:53:17	ga_s2bm_ard_3-2-1_50KQC_2019-02-01_final.stac-item
2019-02-01 11:53:21	ga_s2bm_ard_3-2-1_50KPC_2019-02-01_final.stac-item
2019-02-03 10:52:38	ga_s2bm_ard_3-2-1_53KMU_2019-02-03_final.stac-item
2019-02-03 10:52:41	ga_s2bm_ard_3-2-1_53KLU_2019-02-03_final.stac-item
2019-02-03 10:52:45	ga_s2bm_ard_3-2-1_53KKU_2019-02-03_final.stac-item
2019-02-03 10:52:45	ga_s2bm_ard_3-2-1_52KHD_2019-02-03_final.stac-item
2019-02-03 10:52:56	ga_s2bm_ard_3-2-1_53KLT_2019-02-03_final.stac-item
2019-02-03 10:52:59	ga_s2bm_ard_3-2-1_53KKT_2019-02-03_final.stac-item
2019-02-03 10:53:00	ga_s2bm_ard_3-2-1_52KHC_2019-02-03_final.stac-item
2019-02-09 11:12:42	ga_s2bm_ard_3-2-1_52KFD_2019-02-09_final.stac-item
2019-02-09 11:12:46	ga_s2bm_ard_3-2-1_52KED_2019-02-09_final.stac-item
2019-02-09 11:12:50	ga_s2bm_ard_3-2-1_52KDD_2019-02-09_final.stac-item
2019-02-09 11:12:53	ga_s2bm_ard_3-2-1_52KCD_2019-02-09_final.stac-item
2019-03-01 11:12:48	ga_s2bm_ard_3-2-1_52KDD_2019-03-01_final.stac-item
2019-03-01 11:12:51	ga_s2bm_ard_3-2-1_52KCD_2019-03-01_final.stac-item
2019-03-02 10:42:30	ga_s2bm_ard_3-2-1_53KQU_2019-03-02_final.stac-item
2019-03-02 10:42:34	ga_s2bm_ard_3-2-1_53KPU_2019-03-02_final.stac-item
2019-03-02 10:42:37	ga_s2bm_ard_3-2-1_53KNU_2019-03-02_final.stac-item
2019-03-02 10:42:42	ga_s2bm_ard_3-2-1_53KMU_2019-03-02_final.stac-item
2019-03-02 10:42:45	ga_s2bm_ard_3-2-1_53KQT_2019-03-02_final.stac-item
2019-03-02 10:42:48	ga_s2bm_ard_3-2-1_53KPT_2019-03-02_final.stac-item
2019-03-04 09:42:08	ga_s2bm_ard_3-2-1_56KLD_2019-03-04_final.stac-item
2019-03-04 09:42:31	ga_s2bm_ard_3-2-1_55KGT_2019-03-04_final.stac-item
2019-03-08 11:02:37	ga_s2bm_ard_3-2-1_53KKU_2019-03-08_final.stac-item
2019-03-08 11:02:37	ga_s2bm_ard_3-2-1_52KHD_2019-03-08_final.stac-item
2019-03-08 11:02:42	ga_s2bm_ard_3-2-1_52KGD_2019-03-08_final.stac-item
2019-03-08 11:02:45	ga_s2bm_ard_3-2-1_52KFD_2019-03-08_final.stac-item
2019-03-08 11:02:49	ga_s2bm_ard_3-2-1_52KED_2019-03-08_final.stac-item
2019-03-08 11:02:52	ga_s2bm_ard_3-2-1_53KKT_2019-03-08_final.stac-item
2019-03-08 11:02:52	ga_s2bm_ard_3-2-1_52KHC_2019-03-08_final.stac-item
2019-03-08 11:02:56	ga_s2bm_ard_3-2-1_52KGC_2019-03-08_final.stac-item
2019-03-08 11:02:59	ga_s2bm_ard_3-2-1_52KFC_2019-03-08_final.stac-item
2019-03-09 10:32:23	ga_s2bm_ard_3-2-1_54KVD_2019-03-09_final.stac-item
2019-03-09 10:32:27	ga_s2bm_ard_3-2-1_54KUD_2019-03-09_final.stac-item
2019-03-09 10:32:30	ga_s2bm_ard_3-2-1_54KTD_2019-03-09_final.stac-item
2019-03-09 10:32:31	ga_s2bm_ard_3-2-1_53KRU_2019-03-09_final.stac-item
2019-03-09 10:32:34	ga_s2bm_ard_3-2-1_53KQU_2019-03-09_final.stac-item
2019-03-09 10:32:41	ga_s2bm_ard_3-2-1_54KUC_2019-03-09_final.stac-item
2019-03-09 10:32:45	ga_s2bm_ard_3-2-1_54KTC_2019-03-09_final.stac-item
2019-03-09 10:32:45	ga_s2bm_ard_3-2-1_53KRT_2019-03-09_final.stac-item
2019-03-09 10:32:49	ga_s2bm_ard_3-2-1_53KQT_2019-03-09_final.stac-item
2019-03-10 10:02:13	ga_s2bm_ard_3-2-1_55KEU_2019-03-10_final.stac-item
2019-03-10 10:02:16	ga_s2bm_ard_3-2-1_55KDU_2019-03-10_final.stac-item
2019-03-10 10:02:20	ga_s2bm_ard_3-2-1_55KCU_2019-03-10_final.stac-item
2019-03-10 10:02:23	ga_s2bm_ard_3-2-1_55KBU_2019-03-10_final.stac-item
2019-03-10 10:02:34	ga_s2bm_ard_3-2-1_55KCT_2019-03-10_final.stac-item
2019-03-10 10:02:37	ga_s2bm_ard_3-2-1_55KBT_2019-03-10_final.stac-item
2019-03-10 10:02:39	ga_s2bm_ard_3-2-1_54KZC_2019-03-10_final.stac-item
2019-03-16 10:22:22	ga_s2bm_ard_3-2-1_54KXD_2019-03-16_final.stac-item
2019-03-16 10:22:25	ga_s2bm_ard_3-2-1_54KWD_2019-03-16_final.stac-item
2019-03-16 10:22:29	ga_s2bm_ard_3-2-1_54KVD_2019-03-16_final.stac-item
2019-03-16 10:22:33	ga_s2bm_ard_3-2-1_54KUD_2019-03-16_final.stac-item
2019-03-16 12:03:24	ga_s2bm_ard_3-2-1_50KLC_2019-03-16_final.stac-item
2019-03-17 09:52:12	ga_s2bm_ard_3-2-1_55KGU_2019-03-17_final.stac-item
2019-03-17 09:52:15	ga_s2bm_ard_3-2-1_55KFU_2019-03-17_final.stac-item
2019-03-17 09:52:18	ga_s2bm_ard_3-2-1_55KEU_2019-03-17_final.stac-item
2019-03-17 09:52:26	ga_s2bm_ard_3-2-1_55KGT_2019-03-17_final.stac-item
2019-03-17 09:52:30	ga_s2bm_ard_3-2-1_55KFT_2019-03-17_final.stac-item
2019-03-17 11:32:49	ga_s2bm_ard_3-2-1_51KYU_2019-03-17_final.stac-item
2019-03-17 11:32:53	ga_s2bm_ard_3-2-1_51KXU_2019-03-17_final.stac-item
2019-03-17 11:32:56	ga_s2bm_ard_3-2-1_51KWU_2019-03-17_final.stac-item
2019-03-17 11:33:00	ga_s2bm_ard_3-2-1_51KVU_2019-03-17_final.stac-item
2019-03-17 11:33:00	ga_s2bm_ard_3-2-1_51KYT_2019-03-17_final.stac-item
2019-03-17 11:33:07	ga_s2bm_ard_3-2-1_51KXT_2019-03-17_final.stac-item
2019-03-18 11:02:39	ga_s2bm_ard_3-2-1_52KHD_2019-03-18_final.stac-item
2019-03-18 11:02:43	ga_s2bm_ard_3-2-1_52KGD_2019-03-18_final.stac-item
2019-03-18 11:02:46	ga_s2bm_ard_3-2-1_52KFD_2019-03-18_final.stac-item
2019-03-18 11:02:50	ga_s2bm_ard_3-2-1_52KED_2019-03-18_final.stac-item
2019-03-18 11:02:53	ga_s2bm_ard_3-2-1_53KKT_2019-03-18_final.stac-item
2019-03-18 11:02:53	ga_s2bm_ard_3-2-1_52KHC_2019-03-18_final.stac-item
2019-03-18 11:02:57	ga_s2bm_ard_3-2-1_52KGC_2019-03-18_final.stac-item
2019-03-18 11:03:00	ga_s2bm_ard_3-2-1_52KFC_2019-03-18_final.stac-item
2019-11-11 12:03:26	ga_s2bm_ard_3-2-1_50KLC_2019-11-11_final.stac-item
2019-11-21 12:03:24	ga_s2bm_ard_3-2-1_50KLC_2019-11-21_final.stac-item
2019-11-25 11:42:53	ga_s2bm_ard_3-2-1_51KVU_2019-11-25_final.stac-item
2019-11-25 11:42:57	ga_s2bm_ard_3-2-1_51KUU_2019-11-25_final.stac-item
2019-11-25 11:43:00	ga_s2bm_ard_3-2-1_51KTU_2019-11-25_final.stac-item
2019-11-25 11:43:00	ga_s2bm_ard_3-2-1_50KRD_2019-11-25_final.stac-item
2019-11-25 11:43:11	ga_s2bm_ard_3-2-1_51KUT_2019-11-25_final.stac-item
2019-11-25 11:43:14	ga_s2bm_ard_3-2-1_51KTT_2019-11-25_final.stac-item
2019-11-25 11:43:15	ga_s2bm_ard_3-2-1_50KRC_2019-11-25_final.stac-item
2019-11-25 11:43:18	ga_s2bm_ard_3-2-1_50KQC_2019-11-25_final.stac-item
2019-11-29 09:42:06	ga_s2bm_ard_3-2-1_56KLD_2019-11-29_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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