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
2023-01-18 11:42:10	ga_s2bm_ard_3-2-1_51KVB_2023-01-18_final.stac-item
2023-01-18 11:42:17	ga_s2bm_ard_3-2-1_51KTB_2023-01-18_nrt.stac-item
2023-01-18 11:42:19	ga_s2bm_ard_3-2-1_51KWA_2023-01-18_final.stac-item
2023-01-18 11:42:25	ga_s2bm_ard_3-2-1_51KVA_2023-01-18_final.stac-item
2023-01-18 11:42:28	ga_s2bm_ard_3-2-1_51KUA_2023-01-18_final.stac-item
2023-01-18 11:44:28	ga_s2bm_ard_3-2-1_50JRT_2023-01-18_final.stac-item
2023-01-18 11:44:28	ga_s2bm_ard_3-2-1_51JTN_2023-01-18_final.stac-item
2023-01-18 11:44:32	ga_s2bm_ard_3-2-1_50JQT_2023-01-18_final.stac-item
2023-01-18 11:44:35	ga_s2bm_ard_3-2-1_50JPT_2023-01-18_final.stac-item
2023-01-18 11:44:38	ga_s2bm_ard_3-2-1_51JUM_2023-01-18_final.stac-item
2023-01-18 11:44:42	ga_s2bm_ard_3-2-1_50JRS_2023-01-18_final.stac-item
2023-01-18 11:44:42	ga_s2bm_ard_3-2-1_51JTM_2023-01-18_final.stac-item
2023-01-18 11:44:46	ga_s2bm_ard_3-2-1_50JQS_2023-01-18_final.stac-item
2023-01-18 11:44:49	ga_s2bm_ard_3-2-1_51JUL_2023-01-18_final.stac-item
2023-01-18 11:44:50	ga_s2bm_ard_3-2-1_50JPS_2023-01-18_final.stac-item
2023-01-18 11:44:57	ga_s2bm_ard_3-2-1_51JTL_2023-01-18_final.stac-item
2023-01-18 11:45:01	ga_s2bm_ard_3-2-1_50JQR_2023-01-18_final.stac-item
2023-01-18 11:45:04	ga_s2bm_ard_3-2-1_50JPR_2023-01-18_final.stac-item
2023-01-18 11:45:09	ga_s2bm_ard_3-2-1_50JNR_2023-01-18_final.stac-item
2023-01-18 11:45:11	ga_s2bm_ard_3-2-1_51JTK_2023-01-18_final.stac-item
2023-01-18 11:45:15	ga_s2bm_ard_3-2-1_50JQQ_2023-01-18_final.stac-item
2023-01-18 11:45:18	ga_s2bm_ard_3-2-1_50JPQ_2023-01-18_final.stac-item
2023-01-18 11:45:22	ga_s2bm_ard_3-2-1_50JNQ_2023-01-18_final.stac-item
2023-01-18 11:45:26	ga_s2bm_ard_3-2-1_51JTJ_2023-01-18_final.stac-item
2023-01-18 11:45:29	ga_s2bm_ard_3-2-1_50JQP_2023-01-18_final.stac-item
2023-01-18 11:45:33	ga_s2bm_ard_3-2-1_50JPP_2023-01-18_final.stac-item
2023-01-18 11:45:36	ga_s2bm_ard_3-2-1_50JNP_2023-01-18_final.stac-item
2023-01-18 11:45:41	ga_s2bm_ard_3-2-1_51JTH_2023-01-18_final.stac-item
2023-01-18 11:45:44	ga_s2bm_ard_3-2-1_50JQN_2023-01-18_final.stac-item
2023-01-18 11:45:47	ga_s2bm_ard_3-2-1_50JPN_2023-01-18_final.stac-item
2023-01-18 11:45:51	ga_s2bm_ard_3-2-1_50JNN_2023-01-18_final.stac-item
2023-01-18 11:45:54	ga_s2bm_ard_3-2-1_51JTG_2023-01-18_final.stac-item
2023-01-18 11:45:58	ga_s2bm_ard_3-2-1_50JQM_2023-01-18_final.stac-item
2023-01-18 11:46:02	ga_s2bm_ard_3-2-1_50JPM_2023-01-18_final.stac-item
2023-01-18 11:46:05	ga_s2bm_ard_3-2-1_51JTF_2023-01-18_final.stac-item
2023-01-18 11:46:05	ga_s2bm_ard_3-2-1_50JNM_2023-01-18_final.stac-item
2023-01-18 11:46:10	ga_s2bm_ard_3-2-1_50JMM_2023-01-18_final.stac-item
2023-01-18 11:46:12	ga_s2bm_ard_3-2-1_50JQL_2023-01-18_final.stac-item
2023-01-18 11:46:16	ga_s2bm_ard_3-2-1_50JPL_2023-01-18_final.stac-item
2023-01-18 11:46:20	ga_s2bm_ard_3-2-1_50JNL_2023-01-18_final.stac-item
2023-01-18 11:46:23	ga_s2bm_ard_3-2-1_50JML_2023-01-18_final.stac-item
2023-01-18 11:46:27	ga_s2bm_ard_3-2-1_50HQK_2023-01-18_final.stac-item
2023-01-18 11:46:31	ga_s2bm_ard_3-2-1_50HPK_2023-01-18_final.stac-item
2023-01-18 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2023-01-18_final.stac-item
2023-01-18 11:46:38	ga_s2bm_ard_3-2-1_50HMK_2023-01-18_final.stac-item
2023-01-18 11:46:40	ga_s2bm_ard_3-2-1_50HQJ_2023-01-18_final.stac-item
2023-01-18 11:46:45	ga_s2bm_ard_3-2-1_50HPJ_2023-01-18_final.stac-item
2023-01-18 11:46:49	ga_s2bm_ard_3-2-1_50HNJ_2023-01-18_final.stac-item
2023-01-18 11:46:51	ga_s2bm_ard_3-2-1_50HQH_2023-01-18_final.stac-item
2023-01-18 11:46:53	ga_s2bm_ard_3-2-1_50HMJ_2023-01-18_final.stac-item
2023-01-18 11:46:59	ga_s2bm_ard_3-2-1_50HPH_2023-01-18_final.stac-item
2023-01-18 11:47:04	ga_s2bm_ard_3-2-1_50HNH_2023-01-18_final.stac-item
2023-01-18 11:47:07	ga_s2bm_ard_3-2-1_50HMH_2023-01-18_final.stac-item
2023-01-18 11:47:11	ga_s2bm_ard_3-2-1_50HLH_2023-01-18_final.stac-item
2023-01-18 11:47:14	ga_s2bm_ard_3-2-1_50HPG_2023-01-18_final
2023-01-18 11:47:18	ga_s2bm_ard_3-2-1_50HNG_2023-01-18_final
2023-01-18 11:47:21	ga_s2bm_ard_3-2-1_50HMG_2023-01-18_final
2023-01-18 11:47:25	ga_s2bm_ard_3-2-1_50HLG_2023-01-18_final
2023-01-18 11:47:27	ga_s2bm_ard_3-2-1_50HPF_2023-01-18_nrt.stac-item
2023-01-18 11:47:29	ga_s2bm_ard_3-2-1_50HNF_2023-01-18_nrt.stac-item
2023-01-18 11:47:31	ga_s2bm_ard_3-2-1_50HMF_2023-01-18_nrt.stac-item
2023-01-18 11:47:32	ga_s2bm_ard_3-2-1_50HLF_2023-01-18_nrt.stac-item
2023-01-18 13:21:35	ga_s2bm_ard_3-2-1_47LKH_2023-01-18_interim
2023-01-18 13:21:35	ga_s2bm_ard_3-2-1_46LHN_2023-01-18_interim
2023-01-18 13:21:41	ga_s2bm_ard_3-2-1_47LKG_2023-01-18_interim
2023-01-18 13:21:42	ga_s2bm_ard_3-2-1_46LHM_2023-01-18_interim
2023-01-19 09:29:38	ga_s2bm_ard_3-2-1_56LPP_2023-01-18_nrt.stac-item
2023-01-19 09:29:52	ga_s2bm_ard_3-2-1_56LPN_2023-01-18_nrt.stac-item
2023-01-19 09:30:03	ga_s2bm_ard_3-2-1_56LPM_2023-01-19_nrt.stac-item
2023-01-19 09:31:23	ga_s2bm_ard_3-2-1_56KPG_2023-01-19_nrt.stac-item
2023-01-19 09:31:25	ga_s2bm_ard_3-2-1_56KNG_2023-01-19_nrt.stac-item
2023-01-19 09:31:30	ga_s2bm_ard_3-2-1_56KPF_2023-01-19_nrt.stac-item
2023-01-19 09:31:31	ga_s2bm_ard_3-2-1_56KNF_2023-01-19_nrt.stac-item
2023-01-19 09:32:26	ga_s2bm_ard_3-2-1_56KQB_2023-01-19_interim
2023-01-19 09:32:26	ga_s2bm_ard_3-2-1_56KNC_2023-01-19_nrt.stac-item
2023-01-19 09:32:27	ga_s2bm_ard_3-2-1_56KMC_2023-01-19_nrt.stac-item
2023-01-19 09:32:44	ga_s2bm_ard_3-2-1_56KLB_2023-01-19_final.stac-item
2023-01-19 09:32:46	ga_s2bm_ard_3-2-1_56KPA_2023-01-19_nrt.stac-item
2023-01-19 09:32:53	ga_s2bm_ard_3-2-1_56KMA_2023-01-19_final.stac-item
2023-01-19 09:32:56	ga_s2bm_ard_3-2-1_56KLA_2023-01-19_final.stac-item
2023-01-19 09:33:01	ga_s2bm_ard_3-2-1_56KPV_2023-01-19_nrt.stac-item
2023-01-19 09:33:04	ga_s2bm_ard_3-2-1_56KNV_2023-01-19_nrt.stac-item
2023-01-19 09:33:07	ga_s2bm_ard_3-2-1_56KMV_2023-01-19_nrt.stac-item
2023-01-19 09:33:10	ga_s2bm_ard_3-2-1_56KLV_2023-01-19_final.stac-item
2023-01-19 09:33:15	ga_s2bm_ard_3-2-1_56KPU_2023-01-19_nrt.stac-item
2023-01-19 09:33:19	ga_s2bm_ard_3-2-1_56KNU_2023-01-19_nrt.stac-item
2023-01-19 09:33:22	ga_s2bm_ard_3-2-1_56KMU_2023-01-19_final.stac-item
2023-01-19 09:33:25	ga_s2bm_ard_3-2-1_56KLU_2023-01-19_final.stac-item
2023-01-19 09:33:28	ga_s2bm_ard_3-2-1_56JPT_2023-01-19_nrt.stac-item
2023-01-19 09:33:33	ga_s2bm_ard_3-2-1_56JNT_2023-01-19_final.stac-item
2023-01-19 09:33:36	ga_s2bm_ard_3-2-1_56JMT_2023-01-19_final.stac-item
2023-01-19 09:33:38	ga_s2bm_ard_3-2-1_56JPS_2023-01-19_nrt.stac-item
2023-01-19 09:33:40	ga_s2bm_ard_3-2-1_56JLT_2023-01-19_final.stac-item
2023-01-19 09:33:47	ga_s2bm_ard_3-2-1_56JNS_2023-01-19_final.stac-item
2023-01-19 09:33:51	ga_s2bm_ard_3-2-1_56JMS_2023-01-19_final.stac-item
2023-01-19 09:33:54	ga_s2bm_ard_3-2-1_56JLS_2023-01-19_final.stac-item
2023-01-19 09:33:58	ga_s2bm_ard_3-2-1_55JHM_2023-01-19_final.stac-item
2023-01-19 09:33:58	ga_s2bm_ard_3-2-1_56JKS_2023-01-19_final.stac-item
2023-01-19 09:34:02	ga_s2bm_ard_3-2-1_56JNR_2023-01-19_final
2023-01-19 09:34:06	ga_s2bm_ard_3-2-1_56JMR_2023-01-19_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

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