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
2018-07-08 10:51:28	ga_s2bm_ard_3-2-1_52JGN_2018-07-08_final.stac-item
2018-07-08 10:51:28	ga_s2bm_ard_3-2-1_52JGP_2018-07-08_final.stac-item
2018-07-09 12:03:10	ga_s2bm_ard_3-2-1_49KHP_2018-07-09_final.stac-item
2018-07-11 11:03:18	ga_s2bm_ard_3-2-1_52JFQ_2018-07-11_final.stac-item
2018-07-11 11:03:18	ga_s2bm_ard_3-2-1_52JFR_2018-07-11_final.stac-item
2018-07-12 12:13:20	ga_s2bm_ard_3-2-1_49JGN_2018-07-12_final.stac-item
2018-07-12 12:13:20	ga_s2bm_ard_3-2-1_49KGR_2018-07-12_final.stac-item
2018-07-18 10:51:28	ga_s2bm_ard_3-2-1_52JFR_2018-07-18_final.stac-item
2018-07-18 10:51:28	ga_s2bm_ard_3-2-1_52JGQ_2018-07-18_final.stac-item
2018-07-18 10:51:28	ga_s2bm_ard_3-2-1_52JHS_2018-07-18_final.stac-item
2018-07-21 11:01:52	ga_s2bm_ard_3-2-1_52JFQ_2018-07-21_final.stac-item
2018-07-28 10:49:53	ga_s2bm_ard_3-2-1_52JGN_2018-07-28_final.stac-item
2018-07-28 10:49:53	ga_s2bm_ard_3-2-1_52JGQ_2018-07-28_final.stac-item
2018-07-28 10:49:53	ga_s2bm_ard_3-2-1_52JHS_2018-07-28_final.stac-item
2018-07-29 12:02:46	ga_s2bm_ard_3-2-1_49KGQ_2018-07-29_final.stac-item
2018-07-31 11:00:38	ga_s2bm_ard_3-2-1_52JFR_2018-07-31_final.stac-item
2018-08-01 10:31:02	ga_s2bm_ard_3-2-1_53HNE_2018-08-01_final.stac-item
2018-08-11 10:36:08	ga_s2bm_ard_3-2-1_53HND_2018-08-11_final.stac-item
2018-08-28 10:21:53	ga_s2bm_ard_3-2-1_53HQD_2018-08-28_final.stac-item
2018-08-31 10:30:56	ga_s2bm_ard_3-2-1_53HND_2018-08-31_final.stac-item
2018-09-01 11:35:18	ga_s2bm_ard_3-2-1_50JPS_2018-09-01_final.stac-item
2018-09-01 11:35:18	ga_s2bm_ard_3-2-1_50JQQ_2018-09-01_final.stac-item
2018-09-01 11:35:18	ga_s2bm_ard_3-2-1_50JQR_2018-09-01_final.stac-item
2018-09-01 11:35:18	ga_s2bm_ard_3-2-1_50JQS_2018-09-01_final.stac-item
2018-09-04 11:52:51	ga_s2bm_ard_3-2-1_50JLP_2018-09-04_final.stac-item
2018-09-04 11:52:51	ga_s2bm_ard_3-2-1_50JLQ_2018-09-04_final.stac-item
2018-09-04 11:52:51	ga_s2bm_ard_3-2-1_50JMN_2018-09-04_final.stac-item
2018-09-04 11:52:51	ga_s2bm_ard_3-2-1_50JNN_2018-09-04_final.stac-item
2018-09-04 11:52:51	ga_s2bm_ard_3-2-1_50JPS_2018-09-04_final.stac-item
2018-09-04 11:52:51	ga_s2bm_ard_3-2-1_50JLR_2018-09-04_final.stac-item
2018-09-04 11:52:51	ga_s2bm_ard_3-2-1_50JLS_2018-09-04_final.stac-item
2018-09-04 11:52:51	ga_s2bm_ard_3-2-1_50JMP_2018-09-04_final.stac-item
2018-09-04 11:52:51	ga_s2bm_ard_3-2-1_50JMQ_2018-09-04_final.stac-item
2018-09-05 11:21:46	ga_s2bm_ard_3-2-1_51JWM_2018-09-05_final.stac-item
2018-09-05 11:21:46	ga_s2bm_ard_3-2-1_51JXK_2018-09-05_final.stac-item
2018-09-07 12:02:58	ga_s2bm_ard_3-2-1_49JGN_2018-09-07_final.stac-item
2018-09-07 12:02:58	ga_s2bm_ard_3-2-1_49KHP_2018-09-07_final.stac-item
2018-09-07 12:02:58	ga_s2bm_ard_3-2-1_50JLP_2018-09-07_final.stac-item
2018-09-07 12:02:58	ga_s2bm_ard_3-2-1_50JLQ_2018-09-07_final.stac-item
2018-09-07 12:02:58	ga_s2bm_ard_3-2-1_50JKT_2018-09-07_final.stac-item
2018-09-07 12:02:58	ga_s2bm_ard_3-2-1_50JLR_2018-09-07_final.stac-item
2018-09-07 12:02:58	ga_s2bm_ard_3-2-1_50JLS_2018-09-07_final.stac-item
2018-09-07 12:02:58	ga_s2bm_ard_3-2-1_50JMR_2018-09-07_final.stac-item
2018-09-08 11:30:45	ga_s2bm_ard_3-2-1_51JTL_2018-09-08_final.stac-item
2018-09-08 11:30:45	ga_s2bm_ard_3-2-1_51JUH_2018-09-08_final.stac-item
2018-09-08 11:30:45	ga_s2bm_ard_3-2-1_51JVM_2018-09-08_final.stac-item
2018-09-08 11:30:45	ga_s2bm_ard_3-2-1_51JWM_2018-09-08_final.stac-item
2018-09-09 11:01:38	ga_s2bm_ard_3-2-1_52JFR_2018-09-09_final.stac-item
2018-09-10 12:13:12	ga_s2bm_ard_3-2-1_49JFN_2018-09-10_final.stac-item
2018-09-11 11:41:45	ga_s2bm_ard_3-2-1_50JPS_2018-09-11_final.stac-item
2018-09-11 11:41:45	ga_s2bm_ard_3-2-1_50JQQ_2018-09-11_final.stac-item
2018-09-11 11:41:45	ga_s2bm_ard_3-2-1_50JQR_2018-09-11_final.stac-item
2018-09-11 11:41:45	ga_s2bm_ard_3-2-1_50JQS_2018-09-11_final.stac-item
2018-09-11 11:41:45	ga_s2bm_ard_3-2-1_51JTM_2018-09-11_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50JLP_2018-09-14_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50JLQ_2018-09-14_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50JMN_2018-09-14_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50JMS_2018-09-14_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50JNN_2018-09-14_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50JPS_2018-09-14_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50JLR_2018-09-14_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50JLS_2018-09-14_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50JMQ_2018-09-14_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50JMR_2018-09-14_final.stac-item
2018-09-15 11:21:46	ga_s2bm_ard_3-2-1_51JVL_2018-09-15_final.stac-item
2018-09-17 12:03:21	ga_s2bm_ard_3-2-1_50JLP_2018-09-17_final.stac-item
2018-09-17 12:03:21	ga_s2bm_ard_3-2-1_50JLQ_2018-09-17_final.stac-item
2018-09-17 12:03:21	ga_s2bm_ard_3-2-1_50JMS_2018-09-17_final.stac-item
2018-09-17 12:03:21	ga_s2bm_ard_3-2-1_49KHR_2018-09-17_final.stac-item
2018-09-17 12:03:21	ga_s2bm_ard_3-2-1_50JLR_2018-09-17_final.stac-item
2018-09-17 12:03:21	ga_s2bm_ard_3-2-1_50JMR_2018-09-17_final.stac-item
2018-09-18 11:33:03	ga_s2bm_ard_3-2-1_51JUH_2018-09-18_final.stac-item
2018-09-18 11:33:03	ga_s2bm_ard_3-2-1_51JVM_2018-09-18_final.stac-item
2018-09-18 11:33:03	ga_s2bm_ard_3-2-1_51JWM_2018-09-18_final.stac-item
2018-09-20 12:13:14	ga_s2bm_ard_3-2-1_50KKB_2018-09-20_final.stac-item
2018-09-20 12:13:54	ga_s2bm_ard_3-2-1_49KGP_2018-09-20_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_50JQQ_2018-09-21_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_50JQR_2018-09-21_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_51JTL_2018-09-21_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50JLP_2018-09-24_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50JMN_2018-09-24_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50JMS_2018-09-24_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50JNN_2018-09-24_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50JPS_2018-09-24_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50JLR_2018-09-24_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50JLS_2018-09-24_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50JMP_2018-09-24_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50JMR_2018-09-24_final.stac-item
2018-09-25 11:23:23	ga_s2bm_ard_3-2-1_51JXK_2018-09-25_final.stac-item
2018-09-27 12:02:43	ga_s2bm_ard_3-2-1_49JGN_2018-09-27_final.stac-item
2018-09-27 12:02:43	ga_s2bm_ard_3-2-1_50JMS_2018-09-27_final.stac-item
2018-09-27 12:02:43	ga_s2bm_ard_3-2-1_49KGQ_2018-09-27_final.stac-item
2018-09-27 12:02:43	ga_s2bm_ard_3-2-1_50JLS_2018-09-27_final.stac-item
2018-09-27 12:04:56	ga_s2bm_ard_3-2-1_50JLP_2018-09-27_final.stac-item
2018-09-27 12:04:56	ga_s2bm_ard_3-2-1_50JLQ_2018-09-27_final.stac-item
2018-09-27 12:04:56	ga_s2bm_ard_3-2-1_50JLR_2018-09-27_final.stac-item
2018-09-28 11:30:45	ga_s2bm_ard_3-2-1_51JTM_2018-09-28_final.stac-item
2018-09-28 11:30:45	ga_s2bm_ard_3-2-1_51JVL_2018-09-28_final.stac-item
2018-09-28 11:30:45	ga_s2bm_ard_3-2-1_51JWL_2018-09-28_final.stac-item
2018-09-30 12:13:16	ga_s2bm_ard_3-2-1_50KKB_2018-09-30_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