Search ga_s2bm_ard_3 on 1st November 2017

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
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JTS_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JTT_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JUS_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_53JRM_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JUT_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_53JRN_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JVS_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JVT_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JWS_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54JWT_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KTU_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KTV_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KUA_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KUB_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KUC_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KUD_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KUU_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KUV_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KVA_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KVB_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KVC_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KVD_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_53KRP_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KVE_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KVF_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KVG_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KVU_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KVV_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KWA_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KWB_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KWC_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KWD_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KWE_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KWF_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KWG_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KWU_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KWV_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KXA_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KXB_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KXC_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KXD_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KXE_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KXF_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KXG_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KXV_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KYD_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KYE_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KYF_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54KYG_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54LVH_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54LWH_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54LWJ_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54LWK_2017-11-01_final.stac-item
2017-11-01 10:16:52	ga_s2bm_ard_3-2-1_54LWL_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49JGJ_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49JGK_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49JGL_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49JGM_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49JGN_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49JHM_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49JHN_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49KGP_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JKM_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49KGQ_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JKN_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JKP_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49KHP_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JKQ_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JKR_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49KHQ_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JKS_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JKT_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49KHR_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLL_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLM_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLN_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLP_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLQ_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLR_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLS_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLT_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JMR_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JMS_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JMT_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KKA_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KKB_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KKU_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KKV_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KLA_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KLB_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KLC_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KLU_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KLV_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KMA_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KMB_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KMC_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KMU_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KMV_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KNA_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KNB_2017-11-01_final.stac-item

Return to ga_s2bm_ard_3 on 1st November 2017 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

2017

November

1st