Search ga_s2am_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
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JKM_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JKN_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JKP_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JKQ_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JKR_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JKS_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JKT_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JLL_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JLM_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JLN_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JLP_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JLQ_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JLR_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JLS_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JLT_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JMR_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JMS_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JMT_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KKA_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KKB_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KKU_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KKV_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KLA_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KLB_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KLC_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KLU_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KLV_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KMA_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KMB_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KMC_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KMU_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KMV_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KNA_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KNB_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KNC_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGJ_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGK_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGL_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGM_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGN_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JHM_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JHN_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49KGP_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49KGQ_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49KHP_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49KHQ_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49KHR_2018-07-14_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_56KKF_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JCK_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JCL_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JCM_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JCN_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JDK_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JDL_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JDM_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JDN_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JEK_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JEL_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JEM_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JEN_2018-07-15_final.stac-item
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JFK_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50HPH_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50HPJ_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50HPK_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50HQH_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50HQJ_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50HQK_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50JPL_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50JQL_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50JQM_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50JQN_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50JQP_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51HTC_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51HTD_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51HTE_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51HUC_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51HUD_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51HUE_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51HVD_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51HVE_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JTF_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JTG_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JTH_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JTJ_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JTK_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JTL_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JUF_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JUG_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JUH_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JUJ_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JUK_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JUL_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JVF_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JVG_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JVH_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JVJ_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JVK_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JVL_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JWJ_2018-07-15_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JWK_2018-07-15_final.stac-item

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

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