Search ga_s2bm_ard_3 on 9th February 2023

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
2023-02-09 09:05:08	ga_s2bm_ard_3-2-1_57JWF_2023-02-08_final
2023-02-09 09:05:12	ga_s2bm_ard_3-2-1_57JVF_2023-02-08_final
2023-02-09 10:39:57	ga_s2bm_ard_3-2-1_54LUP_2023-02-09_nrt.stac-item
2023-02-09 10:40:01	ga_s2bm_ard_3-2-1_54LTP_2023-02-09_nrt.stac-item
2023-02-09 10:40:02	ga_s2bm_ard_3-2-1_53LRJ_2023-02-09_nrt.stac-item
2023-02-09 10:40:06	ga_s2bm_ard_3-2-1_53LQJ_2023-02-09_nrt.stac-item
2023-02-09 10:40:12	ga_s2bm_ard_3-2-1_54LUN_2023-02-09_nrt.stac-item
2023-02-09 10:40:17	ga_s2bm_ard_3-2-1_53LRH_2023-02-09_nrt.stac-item
2023-02-09 10:40:20	ga_s2bm_ard_3-2-1_53LQH_2023-02-09_nrt.stac-item
2023-02-09 10:40:26	ga_s2bm_ard_3-2-1_54LUM_2023-02-09_nrt.stac-item
2023-02-09 10:40:30	ga_s2bm_ard_3-2-1_54LTM_2023-02-09_nrt.stac-item
2023-02-09 10:40:31	ga_s2bm_ard_3-2-1_53LRG_2023-02-09_nrt.stac-item
2023-02-09 10:40:35	ga_s2bm_ard_3-2-1_53LQG_2023-02-09_final
2023-02-09 10:40:37	ga_s2bm_ard_3-2-1_54LUL_2023-02-09_nrt.stac-item
2023-02-09 10:40:38	ga_s2bm_ard_3-2-1_53LPG_2023-02-09_final.stac-item
2023-02-09 10:40:44	ga_s2bm_ard_3-2-1_54LTL_2023-02-09_nrt.stac-item
2023-02-09 10:40:46	ga_s2bm_ard_3-2-1_53LRF_2023-02-09_nrt.stac-item
2023-02-09 10:40:52	ga_s2bm_ard_3-2-1_53LPF_2023-02-09_final.stac-item
2023-02-09 10:40:59	ga_s2bm_ard_3-2-1_54LTK_2023-02-09_nrt.stac-item
2023-02-09 10:41:00	ga_s2bm_ard_3-2-1_53LRE_2023-02-09_nrt.stac-item
2023-02-09 10:41:04	ga_s2bm_ard_3-2-1_53LPE_2023-02-09_final.stac-item
2023-02-09 10:41:06	ga_s2bm_ard_3-2-1_54LTK_2023-02-09_nrt.stac-item
2023-02-09 10:41:07	ga_s2bm_ard_3-2-1_54LTJ_2023-02-09_nrt.stac-item
2023-02-09 10:41:07	ga_s2bm_ard_3-2-1_53LRE_2023-02-09_nrt.stac-item
2023-02-09 10:41:07	ga_s2bm_ard_3-2-1_53LRD_2023-02-09_nrt.stac-item
2023-02-09 10:41:10	ga_s2bm_ard_3-2-1_53LPE_2023-02-09_final.stac-item
2023-02-09 10:41:13	ga_s2bm_ard_3-2-1_54LTJ_2023-02-09_nrt.stac-item
2023-02-09 10:41:14	ga_s2bm_ard_3-2-1_53LRD_2023-02-09_nrt.stac-item
2023-02-09 10:41:18	ga_s2bm_ard_3-2-1_53LQD_2023-02-09_final.stac-item
2023-02-09 10:41:22	ga_s2bm_ard_3-2-1_53LPD_2023-02-09_final.stac-item
2023-02-09 10:41:28	ga_s2bm_ard_3-2-1_54LTH_2023-02-09_nrt.stac-item
2023-02-09 10:41:29	ga_s2bm_ard_3-2-1_53LND_2023-02-09_final.stac-item
2023-02-09 10:41:29	ga_s2bm_ard_3-2-1_53LRC_2023-02-09_nrt.stac-item
2023-02-09 10:41:33	ga_s2bm_ard_3-2-1_53LQC_2023-02-09_final.stac-item
2023-02-09 10:41:36	ga_s2bm_ard_3-2-1_53LPC_2023-02-09_final.stac-item
2023-02-09 10:41:40	ga_s2bm_ard_3-2-1_53LNC_2023-02-09_final.stac-item
2023-02-09 10:41:41	ga_s2bm_ard_3-2-1_54KTG_2023-02-09_final.stac-item
2023-02-09 10:41:44	ga_s2bm_ard_3-2-1_53KRB_2023-02-09_final.stac-item
2023-02-09 10:41:47	ga_s2bm_ard_3-2-1_53KQB_2023-02-09_final.stac-item
2023-02-09 10:41:51	ga_s2bm_ard_3-2-1_53KPB_2023-02-09_final.stac-item
2023-02-09 10:41:53	ga_s2bm_ard_3-2-1_54KTF_2023-02-09_final.stac-item
2023-02-09 10:41:54	ga_s2bm_ard_3-2-1_53KNB_2023-02-09_final.stac-item
2023-02-09 10:41:58	ga_s2bm_ard_3-2-1_53KRA_2023-02-09_final.stac-item
2023-02-09 10:42:02	ga_s2bm_ard_3-2-1_53KQA_2023-02-09_final.stac-item
2023-02-09 10:42:05	ga_s2bm_ard_3-2-1_53KPA_2023-02-09_final.stac-item
2023-02-09 10:42:08	ga_s2bm_ard_3-2-1_53KNA_2023-02-09_final.stac-item
2023-02-09 10:42:11	ga_s2bm_ard_3-2-1_53KRV_2023-02-09_final.stac-item
2023-02-09 10:42:16	ga_s2bm_ard_3-2-1_53KQV_2023-02-09_final.stac-item
2023-02-09 10:43:44	ga_s2bm_ard_3-2-1_53KLQ_2023-02-09_final.stac-item
2023-02-09 10:43:53	ga_s2bm_ard_3-2-1_53KMP_2023-02-09_final.stac-item
2023-02-09 10:43:57	ga_s2bm_ard_3-2-1_53KLP_2023-02-09_final.stac-item
2023-02-09 10:44:01	ga_s2bm_ard_3-2-1_53JPN_2023-02-09_final.stac-item
2023-02-09 10:44:05	ga_s2bm_ard_3-2-1_53JNN_2023-02-09_final.stac-item
2023-02-09 10:44:08	ga_s2bm_ard_3-2-1_53JMN_2023-02-09_final.stac-item
2023-02-09 10:44:11	ga_s2bm_ard_3-2-1_53JLN_2023-02-09_final.stac-item
2023-02-09 10:44:15	ga_s2bm_ard_3-2-1_53JPM_2023-02-09_final.stac-item
2023-02-09 10:44:19	ga_s2bm_ard_3-2-1_53JNM_2023-02-09_final.stac-item
2023-02-09 10:44:23	ga_s2bm_ard_3-2-1_53JMM_2023-02-09_final.stac-item
2023-02-09 10:44:26	ga_s2bm_ard_3-2-1_53JLM_2023-02-09_final.stac-item
2023-02-09 10:44:27	ga_s2bm_ard_3-2-1_53JPL_2023-02-09_final.stac-item
2023-02-09 10:44:33	ga_s2bm_ard_3-2-1_53JNL_2023-02-09_final.stac-item
2023-02-09 10:44:37	ga_s2bm_ard_3-2-1_53JML_2023-02-09_final.stac-item
2023-02-09 10:44:40	ga_s2bm_ard_3-2-1_53JLL_2023-02-09_final.stac-item
2023-02-09 10:44:46	ga_s2bm_ard_3-2-1_53JKL_2023-02-09_final.stac-item
2023-02-09 10:44:48	ga_s2bm_ard_3-2-1_53JNK_2023-02-09_final.stac-item
2023-02-09 10:44:52	ga_s2bm_ard_3-2-1_53JMK_2023-02-09_final.stac-item
2023-02-09 10:44:55	ga_s2bm_ard_3-2-1_53JLK_2023-02-09_final.stac-item
2023-02-09 10:44:58	ga_s2bm_ard_3-2-1_53JKK_2023-02-09_final.stac-item
2023-02-09 10:45:03	ga_s2bm_ard_3-2-1_53JNJ_2023-02-09_final.stac-item
2023-02-09 10:45:06	ga_s2bm_ard_3-2-1_53JMJ_2023-02-09_final.stac-item
2023-02-09 10:45:09	ga_s2bm_ard_3-2-1_53JLJ_2023-02-09_final.stac-item
2023-02-09 10:45:12	ga_s2bm_ard_3-2-1_53JKJ_2023-02-09_final.stac-item
2023-02-09 10:45:17	ga_s2bm_ard_3-2-1_53JNH_2023-02-09_final.stac-item
2023-02-09 10:45:21	ga_s2bm_ard_3-2-1_53JMH_2023-02-09_final.stac-item
2023-02-09 10:45:24	ga_s2bm_ard_3-2-1_53JLH_2023-02-09_final.stac-item
2023-02-09 10:45:27	ga_s2bm_ard_3-2-1_53JKH_2023-02-09_final.stac-item
2023-02-09 10:45:30	ga_s2bm_ard_3-2-1_53JNG_2023-02-09_final.stac-item
2023-02-09 10:45:35	ga_s2bm_ard_3-2-1_53JMG_2023-02-09_final.stac-item
2023-02-09 10:45:39	ga_s2bm_ard_3-2-1_53JLG_2023-02-09_final.stac-item
2023-02-09 10:45:40	ga_s2bm_ard_3-2-1_53JNF_2023-02-09_final.stac-item
2023-02-09 10:45:42	ga_s2bm_ard_3-2-1_53JKG_2023-02-09_final.stac-item
2023-02-09 10:45:45	ga_s2bm_ard_3-2-1_52JGM_2023-02-09_final.stac-item
2023-02-09 10:45:50	ga_s2bm_ard_3-2-1_53JMF_2023-02-09_final.stac-item
2023-02-09 10:45:53	ga_s2bm_ard_3-2-1_53JLF_2023-02-09_final.stac-item
2023-02-09 10:45:56	ga_s2bm_ard_3-2-1_53JKF_2023-02-09_final.stac-item
2023-02-09 10:45:58	ga_s2bm_ard_3-2-1_52JGL_2023-02-09_final.stac-item
2023-02-09 10:46:04	ga_s2bm_ard_3-2-1_53HME_2023-02-09_final.stac-item
2023-02-09 10:46:08	ga_s2bm_ard_3-2-1_53HLE_2023-02-09_final.stac-item
2023-02-09 10:46:11	ga_s2bm_ard_3-2-1_53HKE_2023-02-09_final
2023-02-09 10:46:13	ga_s2bm_ard_3-2-1_52HGK_2023-02-09_final
2023-02-09 10:46:19	ga_s2bm_ard_3-2-1_53HMD_2023-02-09_final.stac-item
2023-02-09 10:46:22	ga_s2bm_ard_3-2-1_53HLD_2023-02-09_final.stac-item
2023-02-09 10:46:25	ga_s2bm_ard_3-2-1_53HKD_2023-02-09_nrt.stac-item
2023-02-09 10:46:26	ga_s2bm_ard_3-2-1_52HGJ_2023-02-09_nrt.stac-item
2023-02-09 10:46:29	ga_s2bm_ard_3-2-1_53HMC_2023-02-09_final
2023-02-09 10:46:31	ga_s2bm_ard_3-2-1_53HLC_2023-02-09_nrt.stac-item
2023-02-09 10:46:32	ga_s2bm_ard_3-2-1_52HFJ_2023-02-09_nrt.stac-item
2023-02-09 10:46:32	ga_s2bm_ard_3-2-1_53HKC_2023-02-09_nrt.stac-item
2023-02-09 10:46:33	ga_s2bm_ard_3-2-1_52HGH_2023-02-09_nrt.stac-item
2023-02-09 14:13:36	ga_s2bm_ard_3-2-1_43FDB_2023-02-09_final

Return to ga_s2bm_ard_3 on 9th February 2023 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

2023

February

9th