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
2019-09-16 11:46:08	ga_s2bm_ard_3-2-1_50JNM_2019-09-16_final.stac-item
2019-09-16 11:46:13	ga_s2bm_ard_3-2-1_50JMM_2019-09-16_final.stac-item
2019-09-16 11:46:15	ga_s2bm_ard_3-2-1_50JQL_2019-09-16_final.stac-item
2019-09-16 11:46:19	ga_s2bm_ard_3-2-1_50JPL_2019-09-16_final.stac-item
2019-09-16 11:46:22	ga_s2bm_ard_3-2-1_50JNL_2019-09-16_final.stac-item
2019-09-16 11:46:26	ga_s2bm_ard_3-2-1_50JML_2019-09-16_final.stac-item
2019-09-16 11:46:30	ga_s2bm_ard_3-2-1_50HQK_2019-09-16_final.stac-item
2019-09-16 11:46:33	ga_s2bm_ard_3-2-1_50HPK_2019-09-16_final.stac-item
2019-09-16 11:46:37	ga_s2bm_ard_3-2-1_50HNK_2019-09-16_final.stac-item
2019-09-16 11:46:40	ga_s2bm_ard_3-2-1_50HMK_2019-09-16_final.stac-item
2019-09-16 11:46:43	ga_s2bm_ard_3-2-1_50HQJ_2019-09-16_final.stac-item
2019-09-16 11:46:48	ga_s2bm_ard_3-2-1_50HPJ_2019-09-16_final.stac-item
2019-09-16 11:46:51	ga_s2bm_ard_3-2-1_50HNJ_2019-09-16_final.stac-item
2019-09-16 11:46:53	ga_s2bm_ard_3-2-1_50HQH_2019-09-16_final.stac-item
2019-09-16 11:46:55	ga_s2bm_ard_3-2-1_50HMJ_2019-09-16_final.stac-item
2019-09-16 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2019-09-16_final.stac-item
2019-09-16 11:47:06	ga_s2bm_ard_3-2-1_50HNH_2019-09-16_final.stac-item
2019-09-16 11:47:09	ga_s2bm_ard_3-2-1_50HMH_2019-09-16_final.stac-item
2019-09-16 11:47:14	ga_s2bm_ard_3-2-1_50HLH_2019-09-16_final.stac-item
2019-09-17 09:32:48	ga_s2bm_ard_3-2-1_56KLB_2019-09-17_final.stac-item
2019-09-17 09:32:55	ga_s2bm_ard_3-2-1_56KMA_2019-09-17_final.stac-item
2019-09-17 09:32:58	ga_s2bm_ard_3-2-1_56KLA_2019-09-17_final.stac-item
2019-09-17 09:33:12	ga_s2bm_ard_3-2-1_56KLV_2019-09-17_final.stac-item
2019-09-17 09:33:24	ga_s2bm_ard_3-2-1_56KMU_2019-09-17_final.stac-item
2019-09-17 09:33:27	ga_s2bm_ard_3-2-1_56KLU_2019-09-17_final.stac-item
2019-09-17 09:33:35	ga_s2bm_ard_3-2-1_56JNT_2019-09-17_final.stac-item
2019-09-17 09:33:38	ga_s2bm_ard_3-2-1_56JMT_2019-09-17_final.stac-item
2019-09-17 09:33:42	ga_s2bm_ard_3-2-1_56JLT_2019-09-17_final.stac-item
2019-09-17 09:33:49	ga_s2bm_ard_3-2-1_56JNS_2019-09-17_final.stac-item
2019-09-17 09:33:53	ga_s2bm_ard_3-2-1_56JMS_2019-09-17_final.stac-item
2019-09-17 09:33:56	ga_s2bm_ard_3-2-1_56JLS_2019-09-17_final.stac-item
2019-09-17 09:34:00	ga_s2bm_ard_3-2-1_55JHM_2019-09-17_final.stac-item
2019-09-17 09:34:00	ga_s2bm_ard_3-2-1_56JKS_2019-09-17_final.stac-item
2019-09-17 09:34:08	ga_s2bm_ard_3-2-1_56JMR_2019-09-17_final.stac-item
2019-09-17 09:34:11	ga_s2bm_ard_3-2-1_56JLR_2019-09-17_final.stac-item
2019-09-17 09:34:14	ga_s2bm_ard_3-2-1_56JKR_2019-09-17_final.stac-item
2019-09-17 09:34:22	ga_s2bm_ard_3-2-1_56JMQ_2019-09-17_final.stac-item
2019-09-17 09:34:25	ga_s2bm_ard_3-2-1_56JLQ_2019-09-17_final.stac-item
2019-09-17 09:34:28	ga_s2bm_ard_3-2-1_56JKQ_2019-09-17_final.stac-item
2019-09-17 09:34:37	ga_s2bm_ard_3-2-1_56JMP_2019-09-17_final.stac-item
2019-09-17 09:34:40	ga_s2bm_ard_3-2-1_56JLP_2019-09-17_final.stac-item
2019-09-17 09:34:43	ga_s2bm_ard_3-2-1_56JKP_2019-09-17_final.stac-item
2019-09-17 09:34:43	ga_s2bm_ard_3-2-1_56JNN_2019-09-17_final.stac-item
2019-09-17 09:34:50	ga_s2bm_ard_3-2-1_55JGJ_2019-09-17_final.stac-item
2019-09-17 09:34:51	ga_s2bm_ard_3-2-1_56JMN_2019-09-17_final.stac-item
2019-09-17 09:34:55	ga_s2bm_ard_3-2-1_56JLN_2019-09-17_final.stac-item
2019-09-17 09:34:58	ga_s2bm_ard_3-2-1_56JKN_2019-09-17_final.stac-item
2019-09-17 09:35:01	ga_s2bm_ard_3-2-1_55JGH_2019-09-17_final.stac-item
2019-09-17 09:35:05	ga_s2bm_ard_3-2-1_56JMM_2019-09-17_final.stac-item
2019-09-17 09:35:09	ga_s2bm_ard_3-2-1_56JLM_2019-09-17_final.stac-item
2019-09-17 09:35:12	ga_s2bm_ard_3-2-1_56JKM_2019-09-17_final.stac-item
2019-09-17 09:35:15	ga_s2bm_ard_3-2-1_55JGG_2019-09-17_final.stac-item
2019-09-17 09:35:20	ga_s2bm_ard_3-2-1_56JML_2019-09-17_final.stac-item
2019-09-17 09:35:24	ga_s2bm_ard_3-2-1_56JLL_2019-09-17_final.stac-item
2019-09-17 09:35:27	ga_s2bm_ard_3-2-1_56JKL_2019-09-17_final.stac-item
2019-09-17 09:35:29	ga_s2bm_ard_3-2-1_55JGF_2019-09-17_final.stac-item
2019-09-17 09:35:35	ga_s2bm_ard_3-2-1_56HMK_2019-09-17_final.stac-item
2019-09-17 09:35:38	ga_s2bm_ard_3-2-1_56HLK_2019-09-17_final.stac-item
2019-09-17 09:35:42	ga_s2bm_ard_3-2-1_56HKK_2019-09-17_final.stac-item
2019-09-17 09:35:44	ga_s2bm_ard_3-2-1_55HGE_2019-09-17_final.stac-item
2019-09-17 09:35:48	ga_s2bm_ard_3-2-1_56HMJ_2019-09-17_final.stac-item
2019-09-17 09:35:50	ga_s2bm_ard_3-2-1_55HFE_2019-09-17_final.stac-item
2019-09-17 09:35:53	ga_s2bm_ard_3-2-1_56HLJ_2019-09-17_final.stac-item
2019-09-17 09:35:56	ga_s2bm_ard_3-2-1_56HKJ_2019-09-17_final.stac-item
2019-09-17 09:35:58	ga_s2bm_ard_3-2-1_55HGD_2019-09-17_final.stac-item
2019-09-17 09:36:02	ga_s2bm_ard_3-2-1_55HFD_2019-09-17_final.stac-item
2019-09-17 09:36:11	ga_s2bm_ard_3-2-1_56HKH_2019-09-17_final.stac-item
2019-09-17 09:36:13	ga_s2bm_ard_3-2-1_55HGC_2019-09-17_final.stac-item
2019-09-17 09:36:16	ga_s2bm_ard_3-2-1_55HFC_2019-09-17_final.stac-item
2019-09-17 09:36:25	ga_s2bm_ard_3-2-1_56HKG_2019-09-17_final.stac-item
2019-09-17 09:36:27	ga_s2bm_ard_3-2-1_55HGB_2019-09-17_final.stac-item
2019-09-17 09:36:31	ga_s2bm_ard_3-2-1_55HFB_2019-09-17_final.stac-item
2019-09-17 09:36:40	ga_s2bm_ard_3-2-1_56HKF_2019-09-17_final.stac-item
2019-09-17 09:36:41	ga_s2bm_ard_3-2-1_55HGA_2019-09-17_final.stac-item
2019-09-17 09:36:45	ga_s2bm_ard_3-2-1_55HFA_2019-09-17_final.stac-item
2019-09-17 09:36:50	ga_s2bm_ard_3-2-1_55HEA_2019-09-17_final.stac-item
2019-09-17 09:36:56	ga_s2bm_ard_3-2-1_55HGV_2019-09-17_final.stac-item
2019-09-17 09:37:00	ga_s2bm_ard_3-2-1_55HFV_2019-09-17_final.stac-item
2019-09-17 09:37:03	ga_s2bm_ard_3-2-1_55HEV_2019-09-17_final.stac-item
2019-09-17 09:37:18	ga_s2bm_ard_3-2-1_55HEU_2019-09-17_final.stac-item
2019-09-17 09:37:32	ga_s2bm_ard_3-2-1_55HET_2019-09-17_final.stac-item
2019-09-17 09:37:40	ga_s2bm_ard_3-2-1_55HDT_2019-09-17_final.stac-item
2019-09-17 09:37:46	ga_s2bm_ard_3-2-1_55HES_2019-09-17_final.stac-item
2019-09-17 09:37:48	ga_s2bm_ard_3-2-1_55HDS_2019-09-17_final.stac-item
2019-09-17 09:37:51	ga_s2bm_ard_3-2-1_55GFR_2019-09-17_final.stac-item
2019-09-17 09:37:52	ga_s2bm_ard_3-2-1_55GER_2019-09-17_final.stac-item
2019-09-17 09:37:52	ga_s2bm_ard_3-2-1_55HES_2019-09-17_final.stac-item
2019-09-17 09:37:54	ga_s2bm_ard_3-2-1_55HDS_2019-09-17_final.stac-item
2019-09-17 09:37:58	ga_s2bm_ard_3-2-1_55GFR_2019-09-17_final.stac-item
2019-09-17 11:15:47	ga_s2bm_ard_3-2-1_52JCM_2019-09-17_final.stac-item
2019-09-17 11:15:50	ga_s2bm_ard_3-2-1_52JBM_2019-09-17_final.stac-item
2019-09-17 11:15:58	ga_s2bm_ard_3-2-1_52JCL_2019-09-17_final.stac-item
2019-09-17 11:16:00	ga_s2bm_ard_3-2-1_52JBL_2019-09-17_final.stac-item
2019-09-17 11:16:05	ga_s2bm_ard_3-2-1_52JCL_2019-09-17_final.stac-item
2019-09-17 11:16:06	ga_s2bm_ard_3-2-1_52JBL_2019-09-17_final.stac-item
2019-09-17 11:16:19	ga_s2bm_ard_3-2-1_52HBK_2019-09-17_final.stac-item
2019-09-17 11:16:26	ga_s2bm_ard_3-2-1_51HXE_2019-09-17_final.stac-item
2019-09-17 11:16:30	ga_s2bm_ard_3-2-1_51HWE_2019-09-17_final.stac-item
2019-09-17 11:16:36	ga_s2bm_ard_3-2-1_51HYD_2019-09-17_final.stac-item
2019-09-17 11:16:40	ga_s2bm_ard_3-2-1_51HXD_2019-09-17_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