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
2019-08-17 11:46:47	ga_s2bm_ard_3-2-1_50HMK_2019-08-17_final.stac-item
2019-08-17 11:46:49	ga_s2bm_ard_3-2-1_50HQJ_2019-08-17_final.stac-item
2019-08-17 11:46:54	ga_s2bm_ard_3-2-1_50HPJ_2019-08-17_final.stac-item
2019-08-17 11:46:58	ga_s2bm_ard_3-2-1_50HNJ_2019-08-17_final.stac-item
2019-08-17 11:46:59	ga_s2bm_ard_3-2-1_50HQH_2019-08-17_final.stac-item
2019-08-17 11:47:01	ga_s2bm_ard_3-2-1_50HMJ_2019-08-17_final.stac-item
2019-08-17 11:47:08	ga_s2bm_ard_3-2-1_50HPH_2019-08-17_final.stac-item
2019-08-17 11:47:12	ga_s2bm_ard_3-2-1_50HNH_2019-08-17_final.stac-item
2019-08-17 11:47:16	ga_s2bm_ard_3-2-1_50HMH_2019-08-17_final.stac-item
2019-08-17 11:47:19	ga_s2bm_ard_3-2-1_50HLH_2019-08-17_final.stac-item
2019-08-17 11:47:23	ga_s2bm_ard_3-2-1_50HMH_2019-08-17_final.stac-item
2019-08-17 11:47:24	ga_s2bm_ard_3-2-1_50HLH_2019-08-17_final.stac-item
2019-08-18 09:32:54	ga_s2bm_ard_3-2-1_56KLB_2019-08-18_final.stac-item
2019-08-18 09:33:01	ga_s2bm_ard_3-2-1_56KMA_2019-08-18_final.stac-item
2019-08-18 09:33:05	ga_s2bm_ard_3-2-1_56KLA_2019-08-18_final.stac-item
2019-08-18 09:33:19	ga_s2bm_ard_3-2-1_56KLV_2019-08-18_final.stac-item
2019-08-18 09:33:31	ga_s2bm_ard_3-2-1_56KMU_2019-08-18_final.stac-item
2019-08-18 09:33:34	ga_s2bm_ard_3-2-1_56KLU_2019-08-18_final.stac-item
2019-08-18 09:33:41	ga_s2bm_ard_3-2-1_56JNT_2019-08-18_final.stac-item
2019-08-18 09:33:45	ga_s2bm_ard_3-2-1_56JMT_2019-08-18_final.stac-item
2019-08-18 09:33:48	ga_s2bm_ard_3-2-1_56JLT_2019-08-18_final.stac-item
2019-08-18 09:33:56	ga_s2bm_ard_3-2-1_56JKT_2019-08-18_final.stac-item
2019-08-18 09:33:56	ga_s2bm_ard_3-2-1_56JNS_2019-08-18_final.stac-item
2019-08-18 09:34:00	ga_s2bm_ard_3-2-1_56JMS_2019-08-18_final.stac-item
2019-08-18 09:34:03	ga_s2bm_ard_3-2-1_56JLS_2019-08-18_final.stac-item
2019-08-18 09:34:07	ga_s2bm_ard_3-2-1_55JHM_2019-08-18_final.stac-item
2019-08-18 09:34:07	ga_s2bm_ard_3-2-1_56JKS_2019-08-18_final.stac-item
2019-08-18 09:34:14	ga_s2bm_ard_3-2-1_56JMR_2019-08-18_final.stac-item
2019-08-18 09:34:17	ga_s2bm_ard_3-2-1_56JLR_2019-08-18_final.stac-item
2019-08-18 09:34:20	ga_s2bm_ard_3-2-1_56JKR_2019-08-18_final.stac-item
2019-08-18 09:34:29	ga_s2bm_ard_3-2-1_56JMQ_2019-08-18_final.stac-item
2019-08-18 09:34:32	ga_s2bm_ard_3-2-1_56JLQ_2019-08-18_final.stac-item
2019-08-18 09:34:35	ga_s2bm_ard_3-2-1_56JKQ_2019-08-18_final.stac-item
2019-08-18 09:34:43	ga_s2bm_ard_3-2-1_56JMP_2019-08-18_final.stac-item
2019-08-18 09:34:46	ga_s2bm_ard_3-2-1_56JLP_2019-08-18_final.stac-item
2019-08-18 09:34:50	ga_s2bm_ard_3-2-1_56JKP_2019-08-18_final.stac-item
2019-08-18 09:34:50	ga_s2bm_ard_3-2-1_56JNN_2019-08-18_final.stac-item
2019-08-18 09:34:56	ga_s2bm_ard_3-2-1_55JGJ_2019-08-18_final.stac-item
2019-08-18 09:34:57	ga_s2bm_ard_3-2-1_56JMN_2019-08-18_final.stac-item
2019-08-18 09:35:01	ga_s2bm_ard_3-2-1_56JLN_2019-08-18_final.stac-item
2019-08-18 09:35:04	ga_s2bm_ard_3-2-1_56JKN_2019-08-18_final.stac-item
2019-08-18 09:35:07	ga_s2bm_ard_3-2-1_55JGH_2019-08-18_final.stac-item
2019-08-18 09:35:12	ga_s2bm_ard_3-2-1_56JMM_2019-08-18_final.stac-item
2019-08-18 09:35:16	ga_s2bm_ard_3-2-1_56JLM_2019-08-18_final.stac-item
2019-08-18 09:35:19	ga_s2bm_ard_3-2-1_56JKM_2019-08-18_final.stac-item
2019-08-18 09:35:21	ga_s2bm_ard_3-2-1_55JGG_2019-08-18_final.stac-item
2019-08-18 09:35:27	ga_s2bm_ard_3-2-1_56JML_2019-08-18_final.stac-item
2019-08-18 09:35:30	ga_s2bm_ard_3-2-1_56JLL_2019-08-18_final.stac-item
2019-08-18 09:35:33	ga_s2bm_ard_3-2-1_56JKL_2019-08-18_final.stac-item
2019-08-18 09:35:36	ga_s2bm_ard_3-2-1_55JGF_2019-08-18_final.stac-item
2019-08-18 09:35:41	ga_s2bm_ard_3-2-1_56HMK_2019-08-18_final.stac-item
2019-08-18 09:35:45	ga_s2bm_ard_3-2-1_56HLK_2019-08-18_final.stac-item
2019-08-18 09:35:48	ga_s2bm_ard_3-2-1_56HKK_2019-08-18_final.stac-item
2019-08-18 09:35:50	ga_s2bm_ard_3-2-1_55HGE_2019-08-18_final.stac-item
2019-08-18 09:35:54	ga_s2bm_ard_3-2-1_56HMJ_2019-08-18_final.stac-item
2019-08-18 09:35:56	ga_s2bm_ard_3-2-1_55HFE_2019-08-18_final.stac-item
2019-08-18 09:35:59	ga_s2bm_ard_3-2-1_56HLJ_2019-08-18_final.stac-item
2019-08-18 09:36:03	ga_s2bm_ard_3-2-1_56HKJ_2019-08-18_final.stac-item
2019-08-18 09:36:05	ga_s2bm_ard_3-2-1_55HGD_2019-08-18_final.stac-item
2019-08-18 09:36:08	ga_s2bm_ard_3-2-1_55HFD_2019-08-18_final.stac-item
2019-08-18 09:36:17	ga_s2bm_ard_3-2-1_56HKH_2019-08-18_final.stac-item
2019-08-18 09:36:19	ga_s2bm_ard_3-2-1_55HGC_2019-08-18_final.stac-item
2019-08-18 09:36:23	ga_s2bm_ard_3-2-1_55HFC_2019-08-18_final.stac-item
2019-08-18 09:36:32	ga_s2bm_ard_3-2-1_56HKG_2019-08-18_final.stac-item
2019-08-18 09:36:33	ga_s2bm_ard_3-2-1_55HGB_2019-08-18_final.stac-item
2019-08-18 09:36:37	ga_s2bm_ard_3-2-1_55HFB_2019-08-18_final.stac-item
2019-08-18 09:36:46	ga_s2bm_ard_3-2-1_56HKF_2019-08-18_final.stac-item
2019-08-18 09:36:48	ga_s2bm_ard_3-2-1_55HGA_2019-08-18_final.stac-item
2019-08-18 09:36:52	ga_s2bm_ard_3-2-1_55HFA_2019-08-18_final.stac-item
2019-08-18 09:36:56	ga_s2bm_ard_3-2-1_55HEA_2019-08-18_final.stac-item
2019-08-18 09:37:02	ga_s2bm_ard_3-2-1_55HGV_2019-08-18_final.stac-item
2019-08-18 09:37:06	ga_s2bm_ard_3-2-1_55HFV_2019-08-18_final.stac-item
2019-08-18 09:37:10	ga_s2bm_ard_3-2-1_55HEV_2019-08-18_final.stac-item
2019-08-18 11:14:13	ga_s2bm_ard_3-2-1_52JET_2019-08-18_final.stac-item
2019-08-18 11:14:23	ga_s2bm_ard_3-2-1_52JDT_2019-08-18_final.stac-item
2019-08-18 11:14:26	ga_s2bm_ard_3-2-1_52JCT_2019-08-18_final.stac-item
2019-08-18 11:14:29	ga_s2bm_ard_3-2-1_52JBT_2019-08-18_final.stac-item
2019-08-18 11:14:37	ga_s2bm_ard_3-2-1_52JDS_2019-08-18_final.stac-item
2019-08-18 11:14:41	ga_s2bm_ard_3-2-1_52JCS_2019-08-18_final.stac-item
2019-08-18 11:14:44	ga_s2bm_ard_3-2-1_52JBS_2019-08-18_final.stac-item
2019-08-18 11:14:52	ga_s2bm_ard_3-2-1_52JDR_2019-08-18_final.stac-item
2019-08-18 11:14:55	ga_s2bm_ard_3-2-1_52JCR_2019-08-18_final.stac-item
2019-08-18 11:14:58	ga_s2bm_ard_3-2-1_52JBR_2019-08-18_final.stac-item
2019-08-18 11:15:06	ga_s2bm_ard_3-2-1_52JDQ_2019-08-18_final.stac-item
2019-08-18 11:15:10	ga_s2bm_ard_3-2-1_52JCQ_2019-08-18_final.stac-item
2019-08-18 11:15:13	ga_s2bm_ard_3-2-1_52JBQ_2019-08-18_final.stac-item
2019-08-18 11:15:18	ga_s2bm_ard_3-2-1_52JDP_2019-08-18_final.stac-item
2019-08-18 11:15:24	ga_s2bm_ard_3-2-1_52JCP_2019-08-18_final.stac-item
2019-08-18 11:15:28	ga_s2bm_ard_3-2-1_52JBP_2019-08-18_final.stac-item
2019-08-18 11:15:39	ga_s2bm_ard_3-2-1_52JCN_2019-08-18_final.stac-item
2019-08-18 11:15:42	ga_s2bm_ard_3-2-1_52JBN_2019-08-18_final.stac-item
2019-08-18 11:15:53	ga_s2bm_ard_3-2-1_52JCM_2019-08-18_final.stac-item
2019-08-18 11:15:57	ga_s2bm_ard_3-2-1_52JBM_2019-08-18_final.stac-item
2019-08-18 11:16:05	ga_s2bm_ard_3-2-1_52JCL_2019-08-18_final.stac-item
2019-08-18 11:16:06	ga_s2bm_ard_3-2-1_52JBL_2019-08-18_final.stac-item
2019-08-18 11:16:11	ga_s2bm_ard_3-2-1_52JCL_2019-08-18_final.stac-item
2019-08-18 11:16:13	ga_s2bm_ard_3-2-1_52JBL_2019-08-18_final.stac-item
2019-08-18 11:16:26	ga_s2bm_ard_3-2-1_52HBK_2019-08-18_final.stac-item
2019-08-18 11:16:28	ga_s2bm_ard_3-2-1_51HYE_2019-08-18_final.stac-item
2019-08-18 11:16:32	ga_s2bm_ard_3-2-1_51HXE_2019-08-18_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

All years