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
2023-02-01 11:22:24	ga_s2bm_ard_3-2-1_51KYA_2023-02-01_final
2023-02-02 10:51:28	ga_s2bm_ard_3-2-1_53LPC_2023-02-02_final
2023-02-02 10:51:38	ga_s2bm_ard_3-2-1_53KPB_2023-02-02_final
2023-02-02 10:51:54	ga_s2bm_ard_3-2-1_53KLB_2023-02-02_final
2023-02-02 10:51:59	ga_s2bm_ard_3-2-1_53KKB_2023-02-02_final
2023-02-02 10:52:02	ga_s2bm_ard_3-2-1_53KNA_2023-02-02_final
2023-02-02 10:52:06	ga_s2bm_ard_3-2-1_53KMA_2023-02-02_final
2023-02-02 10:52:17	ga_s2bm_ard_3-2-1_53KNV_2023-02-02_final
2023-02-02 10:52:20	ga_s2bm_ard_3-2-1_53KMV_2023-02-02_final
2023-02-02 10:52:26	ga_s2bm_ard_3-2-1_53KKV_2023-02-02_final
2023-02-02 10:52:28	ga_s2bm_ard_3-2-1_52KHE_2023-02-02_final
2023-02-02 10:52:50	ga_s2bm_ard_3-2-1_53KNT_2023-02-02_final
2023-02-06 10:33:00	ga_s2bm_ard_3-2-1_54KTB_2023-02-06_final
2023-02-06 10:33:00	ga_s2bm_ard_3-2-1_53KRS_2023-02-06_final
2023-02-06 10:33:07	ga_s2bm_ard_3-2-1_54KTB_2023-02-06_final
2023-02-06 10:33:07	ga_s2bm_ard_3-2-1_54KTA_2023-02-06_final
2023-02-06 10:33:07	ga_s2bm_ard_3-2-1_53KRS_2023-02-06_final
2023-02-06 10:33:08	ga_s2bm_ard_3-2-1_53KRR_2023-02-06_final
2023-02-06 10:33:09	ga_s2bm_ard_3-2-1_53KQR_2023-02-06_final
2023-02-06 10:33:12	ga_s2bm_ard_3-2-1_54KUA_2023-02-06_final
2023-02-06 10:33:25	ga_s2bm_ard_3-2-1_54KUV_2023-02-06_final
2023-02-07 10:03:07	ga_s2bm_ard_3-2-1_55KEQ_2023-02-07_final
2023-02-07 10:03:54	ga_s2bm_ard_3-2-1_54JYT_2023-02-07_final
2023-02-07 10:03:58	ga_s2bm_ard_3-2-1_55JDM_2023-02-07_final
2023-02-07 10:04:02	ga_s2bm_ard_3-2-1_55JCM_2023-02-07_final
2023-02-07 10:04:05	ga_s2bm_ard_3-2-1_54JZS_2023-02-07_final
2023-02-07 10:04:05	ga_s2bm_ard_3-2-1_55JBM_2023-02-07_final
2023-02-07 10:04:09	ga_s2bm_ard_3-2-1_54JYS_2023-02-07_final
2023-02-07 10:04:12	ga_s2bm_ard_3-2-1_55JDL_2023-02-07_final
2023-02-07 10:04:20	ga_s2bm_ard_3-2-1_55JBL_2023-02-07_final
2023-02-07 10:04:22	ga_s2bm_ard_3-2-1_55JDK_2023-02-07_final
2023-02-07 10:04:31	ga_s2bm_ard_3-2-1_54JXR_2023-02-07_final
2023-02-08 09:36:39	ga_s2bm_ard_3-2-1_56HKF_2023-02-08_final
2023-02-08 09:38:25	ga_s2bm_ard_3-2-1_55GFP_2023-02-08_final
2023-02-08 11:10:23	ga_s2bm_ard_3-2-1_52LHN_2023-02-08_final
2023-02-08 11:10:35	ga_s2bm_ard_3-2-1_52LHM_2023-02-08_final
2023-02-08 11:10:41	ga_s2bm_ard_3-2-1_52LGM_2023-02-08_final
2023-02-08 11:10:45	ga_s2bm_ard_3-2-1_52LHL_2023-02-08_final
2023-02-24 09:49:37	ga_s2bm_ard_3-2-1_56LMP_2023-02-24_nrt
2023-02-24 09:49:49	ga_s2bm_ard_3-2-1_56LMN_2023-02-24_nrt
2023-02-24 09:49:59	ga_s2bm_ard_3-2-1_56LMM_2023-02-24_nrt
2023-02-24 09:50:05	ga_s2bm_ard_3-2-1_56LKM_2023-02-24_nrt
2023-02-24 09:50:06	ga_s2bm_ard_3-2-1_55LHG_2023-02-24_nrt
2023-02-24 09:50:59	ga_s2bm_ard_3-2-1_56LLJ_2023-02-24_nrt
2023-02-24 09:51:01	ga_s2bm_ard_3-2-1_56LKJ_2023-02-24_nrt
2023-02-24 11:30:36	ga_s2bm_ard_3-2-1_52LBN_2023-02-24_nrt
2023-02-24 11:30:50	ga_s2bm_ard_3-2-1_52LBM_2023-02-24_nrt
2023-02-24 11:30:52	ga_s2bm_ard_3-2-1_51LZG_2023-02-24_nrt
2023-02-24 11:31:05	ga_s2bm_ard_3-2-1_52LBL_2023-02-24_nrt
2023-02-24 11:31:06	ga_s2bm_ard_3-2-1_51LZF_2023-02-24_nrt
2023-02-24 11:31:10	ga_s2bm_ard_3-2-1_51LYF_2023-02-24_nrt
2023-02-24 11:31:28	ga_s2bm_ard_3-2-1_51LXE_2023-02-24_nrt
2023-02-24 11:37:34	ga_s2bm_ard_3-2-1_51HUV_2023-02-24_nrt
2023-02-24 11:37:34	ga_s2bm_ard_3-2-1_51HTV_2023-02-24_nrt
2023-02-26 10:30:16	ga_s2bm_ard_3-2-1_54LVN_2023-02-26_nrt
2023-02-26 10:31:03	ga_s2bm_ard_3-2-1_54LUK_2023-02-26_nrt
2023-02-26 10:31:14	ga_s2bm_ard_3-2-1_54LTJ_2023-02-26_nrt
2023-02-26 10:31:15	ga_s2bm_ard_3-2-1_53LRD_2023-02-26_nrt
2023-02-26 10:37:09	ga_s2bm_ard_3-2-1_53HNV_2023-02-26_nrt
2023-02-27 09:59:39	ga_s2bm_ard_3-2-1_55LHJ_2023-02-27_nrt
2023-02-27 10:00:10	ga_s2bm_ard_3-2-1_55LDH_2023-02-27_nrt
2023-02-27 10:00:13	ga_s2bm_ard_3-2-1_55LGG_2023-02-27_nrt
2023-02-27 10:00:17	ga_s2bm_ard_3-2-1_55LFG_2023-02-27_nrt
2023-02-27 10:00:28	ga_s2bm_ard_3-2-1_55LGF_2023-02-27_nrt
2023-02-27 10:07:47	ga_s2bm_ard_3-2-1_54HUC_2023-02-27_nrt
2023-02-27 10:07:52	ga_s2bm_ard_3-2-1_54HVB_2023-02-27_nrt
2023-02-27 10:07:52	ga_s2bm_ard_3-2-1_54HUB_2023-02-27_nrt
2023-02-27 11:40:40	ga_s2bm_ard_3-2-1_51LXH_2023-02-27_nrt
2023-02-27 11:40:43	ga_s2bm_ard_3-2-1_51LWH_2023-02-27_nrt
2023-02-27 11:40:47	ga_s2bm_ard_3-2-1_51LVH_2023-02-27_nrt
2023-02-27 11:40:49	ga_s2bm_ard_3-2-1_51LUH_2023-02-27_nrt
2023-02-27 11:40:54	ga_s2bm_ard_3-2-1_51LXG_2023-02-27_nrt
2023-02-27 11:41:04	ga_s2bm_ard_3-2-1_51LUG_2023-02-27_nrt
2023-02-27 11:41:07	ga_s2bm_ard_3-2-1_51LXF_2023-02-27_nrt
2023-02-27 11:41:12	ga_s2bm_ard_3-2-1_51LWF_2023-02-27_nrt
2023-02-27 11:41:38	ga_s2bm_ard_3-2-1_51LTE_2023-02-27_nrt
2023-02-27 11:41:41	ga_s2bm_ard_3-2-1_51LWD_2023-02-27_nrt
2023-02-27 11:41:45	ga_s2bm_ard_3-2-1_51LVD_2023-02-27_nrt
2023-02-27 11:41:51	ga_s2bm_ard_3-2-1_51LTD_2023-02-27_nrt
2023-02-27 11:42:05	ga_s2bm_ard_3-2-1_51LTC_2023-02-27_nrt
2023-02-27 11:42:08	ga_s2bm_ard_3-2-1_50LRH_2023-02-27_nrt
2023-02-27 11:42:21	ga_s2bm_ard_3-2-1_50KRG_2023-02-27_nrt
2023-02-28 09:29:55	ga_s2bm_ard_3-2-1_56LPN_2023-02-27_nrt
2023-02-28 09:30:07	ga_s2bm_ard_3-2-1_56LPM_2023-02-28_nrt
2023-02-28 09:35:59	ga_s2bm_ard_3-2-1_56HMH_2023-02-28_nrt
2023-02-28 09:38:20	ga_s2bm_ard_3-2-1_55GGP_2023-02-28_nrt
2023-02-28 09:38:21	ga_s2bm_ard_3-2-1_56GKU_2023-02-28_nrt
2023-02-28 11:10:21	ga_s2bm_ard_3-2-1_52LEP_2023-02-28_nrt
2023-02-28 11:11:09	ga_s2bm_ard_3-2-1_52LDL_2023-02-28_nrt
2023-02-28 11:11:23	ga_s2bm_ard_3-2-1_52LDK_2023-02-28_nrt
2023-02-28 11:11:30	ga_s2bm_ard_3-2-1_52LDK_2023-02-28_nrt
2023-03-01 10:46:28	ga_s2bm_ard_3-2-1_53HKD_2023-03-01_nrt
2023-03-03 09:40:14	ga_s2bm_ard_3-2-1_56LNL_2023-03-03_nrt
2023-03-05 10:20:31	ga_s2bm_ard_3-2-1_55LBF_2023-03-05_nrt
2023-08-02 12:06:03	ga_s2bm_ard_3-2-1_49JGH_2023-08-02_final
2023-08-02 12:06:09	ga_s2bm_ard_3-2-1_50JLM_2023-08-02_final
2023-08-02 12:06:15	ga_s2bm_ard_3-2-1_50JKM_2023-08-02_final
2023-08-02 12:06:19	ga_s2bm_ard_3-2-1_50JLL_2023-08-02_final
2023-08-04 11:05:27	ga_s2bm_ard_3-2-1_52JCP_2023-08-04_final
2023-08-12 10:27:24	ga_s2bm_ard_3-2-1_53HQU_2023-08-12_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