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
2023-05-22 09:41:32	ga_s2bm_ard_3-2-1_56KLG_2023-05-22_final
2023-05-22 09:41:37	ga_s2bm_ard_3-2-1_55KHB_2023-05-22_final
2023-05-22 09:41:46	ga_s2bm_ard_3-2-1_56KLF_2023-05-22_final
2023-05-22 09:42:01	ga_s2bm_ard_3-2-1_56KLE_2023-05-22_final
2023-05-22 09:42:12	ga_s2bm_ard_3-2-1_56KMD_2023-05-22_final
2023-05-22 09:42:41	ga_s2bm_ard_3-2-1_56KMB_2023-05-22_final
2023-05-22 09:43:35	ga_s2bm_ard_3-2-1_55KGP_2023-05-22_final
2023-05-22 09:43:39	ga_s2bm_ard_3-2-1_55KFP_2023-05-22_final
2023-05-22 09:43:53	ga_s2bm_ard_3-2-1_55JFN_2023-05-22_final
2023-05-22 09:43:57	ga_s2bm_ard_3-2-1_56JLS_2023-05-22_final
2023-05-22 09:44:04	ga_s2bm_ard_3-2-1_55JGM_2023-05-22_final
2023-05-22 09:44:08	ga_s2bm_ard_3-2-1_55JFM_2023-05-22_final
2023-05-22 09:44:10	ga_s2bm_ard_3-2-1_56JLR_2023-05-22_final
2023-05-22 09:44:15	ga_s2bm_ard_3-2-1_56JKR_2023-05-22_final
2023-05-22 09:44:18	ga_s2bm_ard_3-2-1_55JGL_2023-05-22_final
2023-05-22 09:44:29	ga_s2bm_ard_3-2-1_56JKQ_2023-05-22_final
2023-05-22 09:44:33	ga_s2bm_ard_3-2-1_55JGK_2023-05-22_final
2023-05-22 09:45:09	ga_s2bm_ard_3-2-1_55JEH_2023-05-22_final
2023-05-22 09:45:20	ga_s2bm_ard_3-2-1_55JFG_2023-05-22_final
2023-05-22 09:45:24	ga_s2bm_ard_3-2-1_55JEG_2023-05-22_final
2023-05-22 09:45:27	ga_s2bm_ard_3-2-1_56JKL_2023-05-22_final
2023-05-22 09:45:35	ga_s2bm_ard_3-2-1_55JFF_2023-05-22_final
2023-05-22 09:45:49	ga_s2bm_ard_3-2-1_55HFE_2023-05-22_final
2023-05-22 09:46:03	ga_s2bm_ard_3-2-1_55HFD_2023-05-22_final
2023-05-22 09:46:11	ga_s2bm_ard_3-2-1_55HDD_2023-05-22_final
2023-05-22 09:46:22	ga_s2bm_ard_3-2-1_55HGB_2023-05-22_final
2023-05-22 09:46:25	ga_s2bm_ard_3-2-1_55HDC_2023-05-22_final
2023-05-22 09:46:32	ga_s2bm_ard_3-2-1_55HCC_2023-05-22_final
2023-05-22 09:46:43	ga_s2bm_ard_3-2-1_55HCB_2023-05-22_final
2023-05-22 09:46:50	ga_s2bm_ard_3-2-1_55HEA_2023-05-22_final
2023-05-22 09:47:09	ga_s2bm_ard_3-2-1_55HDV_2023-05-22_final
2023-05-22 09:47:19	ga_s2bm_ard_3-2-1_55HEU_2023-05-22_final
2023-05-22 09:47:27	ga_s2bm_ard_3-2-1_55HCU_2023-05-22_final
2023-05-22 09:47:34	ga_s2bm_ard_3-2-1_55HET_2023-05-22_final
2023-05-22 09:47:59	ga_s2bm_ard_3-2-1_55HBS_2023-05-22_final
2023-05-22 09:48:07	ga_s2bm_ard_3-2-1_55GDR_2023-05-22_final
2023-05-22 09:48:10	ga_s2bm_ard_3-2-1_55GCR_2023-05-22_final
2023-05-22 09:48:21	ga_s2bm_ard_3-2-1_55GDQ_2023-05-22_final
2023-05-22 09:48:25	ga_s2bm_ard_3-2-1_55GCQ_2023-05-22_final
2023-05-22 09:48:28	ga_s2bm_ard_3-2-1_54GYV_2023-05-22_final
2023-05-22 09:48:47	ga_s2bm_ard_3-2-1_55GCN_2023-05-22_final
2023-05-22 09:48:54	ga_s2bm_ard_3-2-1_55GCN_2023-05-22_final
2023-05-22 11:21:29	ga_s2bm_ard_3-2-1_52LBK_2023-05-22_final
2023-05-22 11:21:30	ga_s2bm_ard_3-2-1_51LZE_2023-05-22_final
2023-05-22 11:21:45	ga_s2bm_ard_3-2-1_51LZD_2023-05-22_final
2023-05-22 11:21:55	ga_s2bm_ard_3-2-1_52LCH_2023-05-22_final
2023-05-22 11:22:04	ga_s2bm_ard_3-2-1_51LYC_2023-05-22_final
2023-05-22 11:22:13	ga_s2bm_ard_3-2-1_52KBG_2023-05-22_final
2023-05-22 11:22:14	ga_s2bm_ard_3-2-1_51KZB_2023-05-22_final
2023-05-22 11:22:17	ga_s2bm_ard_3-2-1_52KDF_2023-05-22_final
2023-05-22 11:22:43	ga_s2bm_ard_3-2-1_51KZV_2023-05-22_final
2023-05-22 11:22:57	ga_s2bm_ard_3-2-1_51KZU_2023-05-22_final
2023-05-22 11:23:05	ga_s2bm_ard_3-2-1_51KXU_2023-05-22_final
2023-05-22 11:23:08	ga_s2bm_ard_3-2-1_52KCC_2023-05-22_final
2023-05-22 11:23:18	ga_s2bm_ard_3-2-1_51KXT_2023-05-22_final
2023-05-22 11:23:21	ga_s2bm_ard_3-2-1_52KCB_2023-05-22_final
2023-05-22 11:23:30	ga_s2bm_ard_3-2-1_51KYS_2023-05-22_final
2023-05-22 11:23:44	ga_s2bm_ard_3-2-1_51KYR_2023-05-22_final
2023-05-22 11:23:59	ga_s2bm_ard_3-2-1_51KYQ_2023-05-22_final
2023-05-22 11:24:09	ga_s2bm_ard_3-2-1_51KZP_2023-05-22_final
2023-05-22 11:24:09	ga_s2bm_ard_3-2-1_52KBU_2023-05-22_final
2023-05-22 11:24:28	ga_s2bm_ard_3-2-1_51JYN_2023-05-22_final
2023-05-22 11:24:34	ga_s2bm_ard_3-2-1_51JWN_2023-05-22_final
2023-05-22 11:24:42	ga_s2bm_ard_3-2-1_51JYM_2023-05-22_final
2023-05-22 11:24:46	ga_s2bm_ard_3-2-1_51JXM_2023-05-22_final
2023-05-22 11:25:00	ga_s2bm_ard_3-2-1_51JXL_2023-05-22_final
2023-05-22 11:25:08	ga_s2bm_ard_3-2-1_51JVL_2023-05-22_final
2023-05-22 11:25:36	ga_s2bm_ard_3-2-1_51JVJ_2023-05-22_final
2023-05-22 11:25:47	ga_s2bm_ard_3-2-1_51JWH_2023-05-22_final
2023-05-22 11:25:51	ga_s2bm_ard_3-2-1_51JVH_2023-05-22_final
2023-05-22 11:26:02	ga_s2bm_ard_3-2-1_51JWG_2023-05-22_final
2023-05-22 11:26:05	ga_s2bm_ard_3-2-1_51JVG_2023-05-22_final
2023-05-22 11:26:12	ga_s2bm_ard_3-2-1_51JXF_2023-05-22_final
2023-05-22 11:26:16	ga_s2bm_ard_3-2-1_51JWF_2023-05-22_final
2023-05-22 11:26:19	ga_s2bm_ard_3-2-1_51JVF_2023-05-22_final
2023-05-22 11:26:23	ga_s2bm_ard_3-2-1_51JUF_2023-05-22_final
2023-05-22 11:26:31	ga_s2bm_ard_3-2-1_51HWE_2023-05-22_final
2023-05-22 11:26:41	ga_s2bm_ard_3-2-1_51HXD_2023-05-22_final
2023-05-22 11:26:45	ga_s2bm_ard_3-2-1_51HWD_2023-05-22_final
2023-05-22 11:26:49	ga_s2bm_ard_3-2-1_51HVD_2023-05-22_final
2023-05-22 11:26:52	ga_s2bm_ard_3-2-1_51HUD_2023-05-22_final
2023-05-22 11:26:52	ga_s2bm_ard_3-2-1_51HXC_2023-05-22_final
2023-05-22 11:26:59	ga_s2bm_ard_3-2-1_51HWC_2023-05-22_final
2023-05-22 11:27:03	ga_s2bm_ard_3-2-1_51HVC_2023-05-22_final
2023-05-22 11:27:07	ga_s2bm_ard_3-2-1_51HUC_2023-05-22_final
2023-05-22 11:27:16	ga_s2bm_ard_3-2-1_51HUB_2023-05-22_final
2023-05-31 11:52:34	ga_s2bm_ard_3-2-1_50KRF_2023-05-31_nrt
2023-05-31 11:53:14	ga_s2bm_ard_3-2-1_50KND_2023-05-31_nrt
2023-05-31 11:57:29	ga_s2bm_ard_3-2-1_49HGB_2023-05-31_nrt
2023-05-31 11:57:31	ga_s2bm_ard_3-2-1_49HFB_2023-05-31_nrt
2023-06-01 09:39:46	ga_s2bm_ard_3-2-1_56LMP_2023-06-01_nrt
2023-06-01 09:39:52	ga_s2bm_ard_3-2-1_56LLP_2023-06-01_nrt
2023-06-01 09:40:00	ga_s2bm_ard_3-2-1_56LMN_2023-06-01_nrt
2023-06-01 09:40:04	ga_s2bm_ard_3-2-1_56LLN_2023-06-01_nrt
2023-06-01 09:40:10	ga_s2bm_ard_3-2-1_56LMM_2023-06-01_nrt
2023-06-01 09:41:19	ga_s2bm_ard_3-2-1_56LMH_2023-06-01_nrt
2023-06-01 09:41:20	ga_s2bm_ard_3-2-1_56LLH_2023-06-01_nrt
2023-06-01 09:41:49	ga_s2bm_ard_3-2-1_55KHA_2023-06-01_nrt
2023-06-01 09:42:25	ga_s2bm_ard_3-2-1_56KMC_2023-06-01_nrt
2023-06-01 09:48:51	ga_s2bm_ard_3-2-1_54GYT_2023-06-01_nrt

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