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
2023-08-09 11:53:46	ga_s2bm_ard_3-2-1_50KPB_2023-08-09_final
2023-08-09 11:53:48	ga_s2bm_ard_3-2-1_50KNB_2023-08-09_final
2023-08-09 11:53:55	ga_s2bm_ard_3-2-1_50KPA_2023-08-09_final
2023-08-09 11:53:59	ga_s2bm_ard_3-2-1_50KNA_2023-08-09_final
2023-08-09 11:54:02	ga_s2bm_ard_3-2-1_50KMA_2023-08-09_final
2023-08-09 11:54:13	ga_s2bm_ard_3-2-1_50KNV_2023-08-09_final
2023-08-09 11:54:17	ga_s2bm_ard_3-2-1_50KMV_2023-08-09_final
2023-08-09 11:54:24	ga_s2bm_ard_3-2-1_50KPU_2023-08-09_final
2023-08-09 11:54:31	ga_s2bm_ard_3-2-1_50KMU_2023-08-09_final
2023-08-09 11:54:39	ga_s2bm_ard_3-2-1_50JPT_2023-08-09_final
2023-08-09 11:54:42	ga_s2bm_ard_3-2-1_50JNT_2023-08-09_final
2023-08-09 11:54:46	ga_s2bm_ard_3-2-1_50JMT_2023-08-09_final
2023-08-09 11:54:53	ga_s2bm_ard_3-2-1_50JPS_2023-08-09_final
2023-08-09 11:54:57	ga_s2bm_ard_3-2-1_50JNS_2023-08-09_final
2023-08-09 11:55:00	ga_s2bm_ard_3-2-1_50JMS_2023-08-09_final
2023-08-09 11:55:03	ga_s2bm_ard_3-2-1_50JLS_2023-08-09_final
2023-08-09 11:55:08	ga_s2bm_ard_3-2-1_50JPR_2023-08-09_final
2023-08-09 11:55:11	ga_s2bm_ard_3-2-1_50JNR_2023-08-09_final
2023-08-09 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-08-09_final
2023-08-09 11:55:21	ga_s2bm_ard_3-2-1_50JPQ_2023-08-09_final
2023-08-09 11:55:33	ga_s2bm_ard_3-2-1_50JLQ_2023-08-09_final
2023-08-09 11:55:47	ga_s2bm_ard_3-2-1_50JLP_2023-08-09_final
2023-08-09 11:55:52	ga_s2bm_ard_3-2-1_50JKP_2023-08-09_final
2023-08-09 11:55:55	ga_s2bm_ard_3-2-1_50JNN_2023-08-09_final
2023-08-09 11:55:58	ga_s2bm_ard_3-2-1_50JMN_2023-08-09_final
2023-08-09 11:56:05	ga_s2bm_ard_3-2-1_50JKN_2023-08-09_final
2023-08-09 11:56:10	ga_s2bm_ard_3-2-1_50JNM_2023-08-09_final
2023-08-09 11:56:13	ga_s2bm_ard_3-2-1_50JMM_2023-08-09_final
2023-08-09 11:56:23	ga_s2bm_ard_3-2-1_50JNL_2023-08-09_final
2023-08-09 11:56:31	ga_s2bm_ard_3-2-1_50JLL_2023-08-09_final
2023-08-09 11:56:42	ga_s2bm_ard_3-2-1_50HMK_2023-08-09_final
2023-08-09 11:56:45	ga_s2bm_ard_3-2-1_50HLK_2023-08-09_final
2023-08-09 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2023-08-09_final
2023-08-09 11:57:15	ga_s2bm_ard_3-2-1_50HLH_2023-08-09_final
2023-08-09 11:57:25	ga_s2bm_ard_3-2-1_50HMG_2023-08-09_final
2023-09-05 10:03:36	ga_s2bm_ard_3-2-1_54KYV_2023-09-05_final
2023-09-05 10:03:47	ga_s2bm_ard_3-2-1_54KYU_2023-09-05_final
2023-09-05 10:04:44	ga_s2bm_ard_3-2-1_54JYQ_2023-09-05_final
2023-09-05 10:04:59	ga_s2bm_ard_3-2-1_54JYP_2023-09-05_final
2023-09-05 10:05:31	ga_s2bm_ard_3-2-1_54JXM_2023-09-05_final
2023-09-05 10:05:46	ga_s2bm_ard_3-2-1_54JXL_2023-09-05_final
2023-09-05 10:05:54	ga_s2bm_ard_3-2-1_55HBE_2023-09-05_final
2023-09-05 10:06:03	ga_s2bm_ard_3-2-1_54HWK_2023-09-05_final
2023-09-05 10:06:29	ga_s2bm_ard_3-2-1_54HXH_2023-09-05_final
2023-09-05 10:06:39	ga_s2bm_ard_3-2-1_54HYG_2023-09-05_final
2023-09-05 10:06:43	ga_s2bm_ard_3-2-1_54HXG_2023-09-05_final
2023-09-05 10:07:05	ga_s2bm_ard_3-2-1_54HVF_2023-09-05_final
2023-09-05 10:07:20	ga_s2bm_ard_3-2-1_54HVE_2023-09-05_final
2023-09-05 11:41:23	ga_s2bm_ard_3-2-1_51LUF_2023-09-05_final
2023-09-05 11:42:03	ga_s2bm_ard_3-2-1_51LVC_2023-09-05_final
2023-09-05 11:42:18	ga_s2bm_ard_3-2-1_51KVB_2023-09-05_final
2023-09-05 11:43:10	ga_s2bm_ard_3-2-1_50KQD_2023-09-05_final
2023-09-05 11:43:11	ga_s2bm_ard_3-2-1_51KVT_2023-09-05_final
2023-09-05 11:43:14	ga_s2bm_ard_3-2-1_50KRC_2023-09-05_final
2023-09-05 11:43:16	ga_s2bm_ard_3-2-1_50KQD_2023-09-05_final
2023-09-05 11:43:17	ga_s2bm_ard_3-2-1_51KVT_2023-09-05_final
2023-09-05 11:43:23	ga_s2bm_ard_3-2-1_50KRC_2023-09-05_final
2023-09-05 11:43:26	ga_s2bm_ard_3-2-1_50KQC_2023-09-05_final
2023-09-05 11:43:29	ga_s2bm_ard_3-2-1_51KVS_2023-09-05_final
2023-09-05 11:43:38	ga_s2bm_ard_3-2-1_50KRB_2023-09-05_final
2023-09-05 11:43:48	ga_s2bm_ard_3-2-1_51KUR_2023-09-05_final
2023-09-05 11:43:52	ga_s2bm_ard_3-2-1_50KRA_2023-09-05_final
2023-09-05 11:44:03	ga_s2bm_ard_3-2-1_51KUQ_2023-09-05_final
2023-09-05 11:44:35	ga_s2bm_ard_3-2-1_50JRT_2023-09-05_final
2023-09-05 11:44:42	ga_s2bm_ard_3-2-1_50JPT_2023-09-05_final
2023-09-05 11:44:50	ga_s2bm_ard_3-2-1_51JTM_2023-09-05_final
2023-09-05 11:44:53	ga_s2bm_ard_3-2-1_50JQS_2023-09-05_final
2023-09-05 11:44:55	ga_s2bm_ard_3-2-1_51JUL_2023-09-05_final
2023-09-05 11:44:57	ga_s2bm_ard_3-2-1_50JPS_2023-09-05_final
2023-09-05 11:45:04	ga_s2bm_ard_3-2-1_51JTL_2023-09-05_final
2023-09-05 11:45:08	ga_s2bm_ard_3-2-1_50JQR_2023-09-05_final
2023-09-05 11:45:11	ga_s2bm_ard_3-2-1_50JPR_2023-09-05_final
2023-09-05 11:45:16	ga_s2bm_ard_3-2-1_50JNR_2023-09-05_final
2023-09-05 11:45:22	ga_s2bm_ard_3-2-1_50JQQ_2023-09-05_final
2023-09-05 11:45:26	ga_s2bm_ard_3-2-1_50JPQ_2023-09-05_final
2023-09-05 11:45:37	ga_s2bm_ard_3-2-1_50JQP_2023-09-05_final
2023-09-05 11:45:51	ga_s2bm_ard_3-2-1_50JQN_2023-09-05_final
2023-09-05 11:45:58	ga_s2bm_ard_3-2-1_50JNN_2023-09-05_final
2023-09-05 11:46:12	ga_s2bm_ard_3-2-1_51JTF_2023-09-05_final
2023-09-05 11:46:13	ga_s2bm_ard_3-2-1_50JNM_2023-09-05_final
2023-09-05 11:46:17	ga_s2bm_ard_3-2-1_50JMM_2023-09-05_final
2023-09-05 11:46:24	ga_s2bm_ard_3-2-1_50JPL_2023-09-05_final
2023-09-05 11:46:27	ga_s2bm_ard_3-2-1_50JNL_2023-09-05_final
2023-09-05 11:46:38	ga_s2bm_ard_3-2-1_50HPK_2023-09-05_final
2023-09-05 11:46:45	ga_s2bm_ard_3-2-1_50HMK_2023-09-05_final
2023-09-05 11:46:48	ga_s2bm_ard_3-2-1_50HQJ_2023-09-05_final
2023-09-05 11:46:53	ga_s2bm_ard_3-2-1_50HPJ_2023-09-05_final
2023-09-05 11:47:07	ga_s2bm_ard_3-2-1_50HPH_2023-09-05_final
2023-09-05 11:47:19	ga_s2bm_ard_3-2-1_50HLH_2023-09-05_final
2023-09-05 11:47:21	ga_s2bm_ard_3-2-1_50HPG_2023-09-05_final
2023-09-05 11:47:25	ga_s2bm_ard_3-2-1_50HNG_2023-09-05_final
2023-09-05 11:47:29	ga_s2bm_ard_3-2-1_50HMG_2023-09-05_final
2023-09-15 10:07:50	ga_s2bm_ard_3-2-1_54HXB_2023-09-15_nrt
2023-09-15 11:40:38	ga_s2bm_ard_3-2-1_51LUJ_2023-09-15_nrt
2023-09-15 11:40:52	ga_s2bm_ard_3-2-1_51LUH_2023-09-15_nrt
2023-09-15 11:41:06	ga_s2bm_ard_3-2-1_51LUG_2023-09-15_nrt
2023-09-15 11:41:53	ga_s2bm_ard_3-2-1_51LTD_2023-09-15_nrt
2023-09-15 11:42:08	ga_s2bm_ard_3-2-1_51LTC_2023-09-15_nrt
2023-09-15 11:47:31	ga_s2bm_ard_3-2-1_50HPF_2023-09-15_nrt
2023-09-15 11:47:32	ga_s2bm_ard_3-2-1_50HNF_2023-09-15_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