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
2019-09-09 11:56:38	ga_s2bm_ard_3-2-1_50HMK_2019-09-09_final.stac-item
2019-09-09 11:56:42	ga_s2bm_ard_3-2-1_50HLK_2019-09-09_final.stac-item
2019-09-09 11:56:52	ga_s2bm_ard_3-2-1_50HMJ_2019-09-09_final.stac-item
2019-09-09 11:56:56	ga_s2bm_ard_3-2-1_50HLJ_2019-09-09_final.stac-item
2019-09-09 11:57:07	ga_s2bm_ard_3-2-1_50HMH_2019-09-09_final.stac-item
2019-09-09 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2019-09-09_final.stac-item
2019-09-10 09:41:43	ga_s2bm_ard_3-2-1_56KLF_2019-09-10_final.stac-item
2019-09-10 09:41:46	ga_s2bm_ard_3-2-1_56KKF_2019-09-10_final.stac-item
2019-09-10 09:41:57	ga_s2bm_ard_3-2-1_56KLE_2019-09-10_final.stac-item
2019-09-10 09:42:12	ga_s2bm_ard_3-2-1_56KLD_2019-09-10_final.stac-item
2019-09-10 09:42:35	ga_s2bm_ard_3-2-1_55KGT_2019-09-10_final.stac-item
2019-09-10 09:42:41	ga_s2bm_ard_3-2-1_56KLB_2019-09-10_final.stac-item
2019-09-10 09:42:44	ga_s2bm_ard_3-2-1_56KKB_2019-09-10_final.stac-item
2019-09-10 09:42:44	ga_s2bm_ard_3-2-1_55KHS_2019-09-10_final.stac-item
2019-09-10 09:42:48	ga_s2bm_ard_3-2-1_55KGS_2019-09-10_final.stac-item
2019-09-10 09:42:51	ga_s2bm_ard_3-2-1_56KMA_2019-09-10_final.stac-item
2019-09-10 09:42:55	ga_s2bm_ard_3-2-1_56KLA_2019-09-10_final.stac-item
2019-09-10 09:42:59	ga_s2bm_ard_3-2-1_56KKA_2019-09-10_final.stac-item
2019-09-10 09:42:59	ga_s2bm_ard_3-2-1_55KHR_2019-09-10_final.stac-item
2019-09-10 09:43:02	ga_s2bm_ard_3-2-1_55KGR_2019-09-10_final.stac-item
2019-09-10 09:43:10	ga_s2bm_ard_3-2-1_56KLV_2019-09-10_final.stac-item
2019-09-10 09:43:13	ga_s2bm_ard_3-2-1_56KKV_2019-09-10_final.stac-item
2019-09-10 09:43:13	ga_s2bm_ard_3-2-1_55KHQ_2019-09-10_final.stac-item
2019-09-10 09:43:17	ga_s2bm_ard_3-2-1_55KGQ_2019-09-10_final.stac-item
2019-09-10 09:43:24	ga_s2bm_ard_3-2-1_56KLU_2019-09-10_final.stac-item
2019-09-10 09:43:28	ga_s2bm_ard_3-2-1_56KKU_2019-09-10_final.stac-item
2019-09-10 09:43:28	ga_s2bm_ard_3-2-1_55KHP_2019-09-10_final.stac-item
2019-09-10 09:43:31	ga_s2bm_ard_3-2-1_55KGP_2019-09-10_final.stac-item
2019-09-10 09:43:36	ga_s2bm_ard_3-2-1_55KFP_2019-09-10_final.stac-item
2019-09-10 09:43:39	ga_s2bm_ard_3-2-1_56JLT_2019-09-10_final.stac-item
2019-09-10 09:43:42	ga_s2bm_ard_3-2-1_55JHN_2019-09-10_final.stac-item
2019-09-10 09:43:42	ga_s2bm_ard_3-2-1_56JKT_2019-09-10_final.stac-item
2019-09-10 09:43:57	ga_s2bm_ard_3-2-1_56JKS_2019-09-10_final.stac-item
2019-09-10 09:44:11	ga_s2bm_ard_3-2-1_56JKR_2019-09-10_final.stac-item
2019-09-10 09:44:26	ga_s2bm_ard_3-2-1_56JKQ_2019-09-10_final.stac-item
2019-09-10 09:44:40	ga_s2bm_ard_3-2-1_56JKP_2019-09-10_final.stac-item
2019-09-10 09:44:55	ga_s2bm_ard_3-2-1_56JKN_2019-09-10_final.stac-item
2019-09-10 09:45:10	ga_s2bm_ard_3-2-1_56JKM_2019-09-10_final.stac-item
2019-09-10 09:45:23	ga_s2bm_ard_3-2-1_56JKL_2019-09-10_final.stac-item
2019-09-10 09:45:34	ga_s2bm_ard_3-2-1_56HKK_2019-09-10_final.stac-item
2019-09-10 11:21:25	ga_s2bm_ard_3-2-1_52LBK_2019-09-10_final.stac-item
2019-09-10 11:21:27	ga_s2bm_ard_3-2-1_51LZE_2019-09-10_final.stac-item
2019-09-10 11:21:33	ga_s2bm_ard_3-2-1_52LDJ_2019-09-10_final.stac-item
2019-09-10 11:21:37	ga_s2bm_ard_3-2-1_52LCJ_2019-09-10_final.stac-item
2019-09-10 11:21:40	ga_s2bm_ard_3-2-1_52LBJ_2019-09-10_final.stac-item
2019-09-10 11:21:41	ga_s2bm_ard_3-2-1_51LZD_2019-09-10_final.stac-item
2019-09-10 11:21:48	ga_s2bm_ard_3-2-1_52LDH_2019-09-10_final.stac-item
2019-09-10 11:21:51	ga_s2bm_ard_3-2-1_52LCH_2019-09-10_final.stac-item
2019-09-10 11:21:55	ga_s2bm_ard_3-2-1_52LBH_2019-09-10_final.stac-item
2019-09-10 11:21:56	ga_s2bm_ard_3-2-1_51LZC_2019-09-10_final.stac-item
2019-09-10 11:22:00	ga_s2bm_ard_3-2-1_51LYC_2019-09-10_final.stac-item
2019-09-10 11:22:02	ga_s2bm_ard_3-2-1_52KDG_2019-09-10_final.stac-item
2019-09-10 11:22:06	ga_s2bm_ard_3-2-1_52KCG_2019-09-10_final.stac-item
2019-09-10 11:22:09	ga_s2bm_ard_3-2-1_52KBG_2019-09-10_final.stac-item
2019-09-10 11:22:10	ga_s2bm_ard_3-2-1_51KZB_2019-09-10_final.stac-item
2019-09-10 11:22:13	ga_s2bm_ard_3-2-1_51KYB_2019-09-10_final.stac-item
2019-09-10 11:22:14	ga_s2bm_ard_3-2-1_52KDF_2019-09-10_final.stac-item
2019-09-10 11:22:20	ga_s2bm_ard_3-2-1_52KCF_2019-09-10_final.stac-item
2019-09-10 11:22:24	ga_s2bm_ard_3-2-1_52KBF_2019-09-10_final.stac-item
2019-09-10 11:22:25	ga_s2bm_ard_3-2-1_51KZA_2019-09-10_final.stac-item
2019-09-10 11:22:28	ga_s2bm_ard_3-2-1_51KYA_2019-09-10_final.stac-item
2019-09-10 11:22:35	ga_s2bm_ard_3-2-1_52KCE_2019-09-10_final.stac-item
2019-09-10 11:22:38	ga_s2bm_ard_3-2-1_52KBE_2019-09-10_final.stac-item
2019-09-10 11:22:39	ga_s2bm_ard_3-2-1_51KZV_2019-09-10_final.stac-item
2019-09-10 11:22:43	ga_s2bm_ard_3-2-1_51KYV_2019-09-10_final.stac-item
2019-09-10 11:22:49	ga_s2bm_ard_3-2-1_52KCD_2019-09-10_final.stac-item
2019-09-10 11:22:53	ga_s2bm_ard_3-2-1_52KBD_2019-09-10_final.stac-item
2019-09-10 11:22:54	ga_s2bm_ard_3-2-1_51KZU_2019-09-10_final.stac-item
2019-09-10 11:22:57	ga_s2bm_ard_3-2-1_51KYU_2019-09-10_final.stac-item
2019-09-10 11:23:02	ga_s2bm_ard_3-2-1_51KXU_2019-09-10_final.stac-item
2019-09-10 11:23:04	ga_s2bm_ard_3-2-1_52KCC_2019-09-10_final.stac-item
2019-09-10 11:23:07	ga_s2bm_ard_3-2-1_52KBC_2019-09-10_final.stac-item
2019-09-10 11:23:08	ga_s2bm_ard_3-2-1_51KZT_2019-09-10_final.stac-item
2019-09-10 11:23:11	ga_s2bm_ard_3-2-1_51KYT_2019-09-10_final.stac-item
2019-09-10 11:23:15	ga_s2bm_ard_3-2-1_51KXT_2019-09-10_final.stac-item
2019-09-10 11:23:16	ga_s2bm_ard_3-2-1_52KCB_2019-09-10_final.stac-item
2019-09-10 11:23:19	ga_s2bm_ard_3-2-1_52KBB_2019-09-10_final.stac-item
2019-09-10 11:23:19	ga_s2bm_ard_3-2-1_51KZS_2019-09-10_final.stac-item
2019-09-10 11:23:21	ga_s2bm_ard_3-2-1_51KYS_2019-09-10_final.stac-item
2019-09-10 11:23:22	ga_s2bm_ard_3-2-1_51KXT_2019-09-10_final.stac-item
2019-09-10 11:23:22	ga_s2bm_ard_3-2-1_51KXS_2019-09-10_final.stac-item
2019-09-10 11:23:23	ga_s2bm_ard_3-2-1_52KCB_2019-09-10_final.stac-item
2019-09-10 11:23:25	ga_s2bm_ard_3-2-1_52KBB_2019-09-10_final.stac-item
2019-09-10 11:23:26	ga_s2bm_ard_3-2-1_51KZS_2019-09-10_final.stac-item
2019-09-10 11:23:28	ga_s2bm_ard_3-2-1_51KYS_2019-09-10_final.stac-item
2019-09-10 11:23:29	ga_s2bm_ard_3-2-1_52KCA_2019-09-10_final.stac-item
2019-09-10 11:23:30	ga_s2bm_ard_3-2-1_51KXS_2019-09-10_final.stac-item
2019-09-10 11:23:36	ga_s2bm_ard_3-2-1_52KBA_2019-09-10_final.stac-item
2019-09-10 11:23:37	ga_s2bm_ard_3-2-1_51KZR_2019-09-10_final.stac-item
2019-09-10 11:23:40	ga_s2bm_ard_3-2-1_51KYR_2019-09-10_final.stac-item
2019-09-10 11:23:44	ga_s2bm_ard_3-2-1_51KXR_2019-09-10_final.stac-item
2019-09-10 11:23:51	ga_s2bm_ard_3-2-1_52KBV_2019-09-10_final.stac-item
2019-09-10 11:23:51	ga_s2bm_ard_3-2-1_51KZQ_2019-09-10_final.stac-item
2019-09-10 11:23:55	ga_s2bm_ard_3-2-1_51KYQ_2019-09-10_final.stac-item
2019-09-10 11:23:58	ga_s2bm_ard_3-2-1_51KXQ_2019-09-10_final.stac-item
2019-09-10 11:24:03	ga_s2bm_ard_3-2-1_51KWQ_2019-09-10_final.stac-item
2019-09-10 11:24:05	ga_s2bm_ard_3-2-1_51KZP_2019-09-10_final.stac-item
2019-09-10 11:24:06	ga_s2bm_ard_3-2-1_52KBU_2019-09-10_final.stac-item
2019-09-10 11:24:09	ga_s2bm_ard_3-2-1_51KYP_2019-09-10_final.stac-item
2019-09-10 11:27:03	ga_s2bm_ard_3-2-1_51HUC_2019-09-10_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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