Search ga_s2am_ard_3 across June 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
2017-06-26 11:56:32	ga_s2am_ard_3-2-1_50HLH_2017-06-26_final.stac-item
2017-06-26 11:56:32	ga_s2am_ard_3-2-1_50HLJ_2017-06-26_final.stac-item
2017-06-26 11:56:32	ga_s2am_ard_3-2-1_50HLK_2017-06-26_final.stac-item
2017-06-26 11:56:32	ga_s2am_ard_3-2-1_50HMH_2017-06-26_final.stac-item
2017-06-26 11:56:32	ga_s2am_ard_3-2-1_50HMJ_2017-06-26_final.stac-item
2017-06-26 11:56:32	ga_s2am_ard_3-2-1_50HMK_2017-06-26_final.stac-item
2017-06-26 11:56:32	ga_s2am_ard_3-2-1_50HNK_2017-06-26_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KKA_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KKB_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KKU_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KKV_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KLA_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KLB_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KLD_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KLU_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KLV_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KMA_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KFP_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KGP_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KGQ_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KGR_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KGS_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KGT_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KHP_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KHQ_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KHR_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KHS_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_56JKS_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_56JKT_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_56JLS_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_56JLT_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_56KKU_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_56KLU_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_55JFN_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_55JGN_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_55JHM_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_55JHN_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_55KFP_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_55KGP_2017-06-27_final.stac-item
2017-06-27 09:43:20	ga_s2am_ard_3-2-1_55KHP_2017-06-27_final.stac-item
2017-06-27 09:46:24	ga_s2am_ard_3-2-1_55HCA_2017-06-27_final.stac-item
2017-06-27 09:46:24	ga_s2am_ard_3-2-1_55HCB_2017-06-27_final.stac-item
2017-06-27 09:46:24	ga_s2am_ard_3-2-1_55HDA_2017-06-27_final.stac-item
2017-06-27 09:46:24	ga_s2am_ard_3-2-1_55HDB_2017-06-27_final.stac-item
2017-06-27 09:46:24	ga_s2am_ard_3-2-1_55HEA_2017-06-27_final.stac-item
2017-06-27 09:46:24	ga_s2am_ard_3-2-1_55HEB_2017-06-27_final.stac-item
2017-06-27 09:46:24	ga_s2am_ard_3-2-1_55HFA_2017-06-27_final.stac-item
2017-06-27 09:46:24	ga_s2am_ard_3-2-1_55HFB_2017-06-27_final.stac-item
2017-06-27 09:48:37	ga_s2am_ard_3-2-1_55GCN_2017-06-27_final.stac-item
2017-06-27 09:48:37	ga_s2am_ard_3-2-1_55GDN_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51HTC_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51HUC_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51HUD_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51HUE_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51HVC_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51HVD_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51HVE_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51HWD_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51HWE_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JUF_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JUG_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JVF_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JVG_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JVH_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JVJ_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JVK_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JVL_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JWF_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JWG_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JWH_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JWJ_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JWK_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JWL_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JWM_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JWN_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51KWP_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51KWQ_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52JBS_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52KBA_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52KBB_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52KBC_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52KBV_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52KCA_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52KCB_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52KCC_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51HXD_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51HXE_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JXF_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JXG_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JXH_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JXJ_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JXK_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JXL_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JXM_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JXN_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JYG_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JYH_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JYJ_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JYK_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JYL_2017-06-27_final.stac-item

Return to ga_s2am_ard_3 across June 2017 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

Other products

2017

June

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