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
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKM_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKN_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKP_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKQ_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKR_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKS_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKT_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLL_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLM_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLN_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLP_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLQ_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLR_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLS_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLT_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JMR_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JMS_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JMT_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KKA_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KKB_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KKU_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KKV_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KLA_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KLB_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KLC_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KLU_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KLV_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KMA_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KMB_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KMC_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KMU_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KMV_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KNA_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KNB_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KNC_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGH_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGJ_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGK_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGL_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGM_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGN_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JHM_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JHN_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KGP_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KGQ_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHP_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHQ_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHR_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHS_2016-11-11_final
2016-11-12 11:26:19	ga_s2am_ard_3-2-1_51KUT_2016-11-12_final.stac-item
2016-11-12 11:26:19	ga_s2am_ard_3-2-1_51KVA_2016-11-12_final.stac-item
2016-11-12 11:26:19	ga_s2am_ard_3-2-1_51KVB_2016-11-12_final.stac-item
2016-11-12 11:26:19	ga_s2am_ard_3-2-1_51KVS_2016-11-12_final.stac-item
2016-11-12 11:26:19	ga_s2am_ard_3-2-1_51KVT_2016-11-12_final.stac-item
2016-11-12 11:26:19	ga_s2am_ard_3-2-1_51KVU_2016-11-12_final.stac-item
2016-11-12 11:26:19	ga_s2am_ard_3-2-1_51KVV_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HPH_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HPJ_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HPK_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HQH_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HQJ_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HQK_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50JPL_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50JQL_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50JQM_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50JQN_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50JQP_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HTB_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HTC_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HTD_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HTE_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HUB_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HUC_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HUD_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HUE_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HVD_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HVE_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JTF_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JTG_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JTH_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JTJ_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JTK_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JTL_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JUF_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JUG_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JUH_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JUJ_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JUK_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JUL_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JVF_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JVG_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JVH_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JVJ_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JVK_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JVL_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JWJ_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JWK_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51JWL_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HPG_2016-11-12_final
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HNG_2016-11-12_final

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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