Search ga_s2am_ard_3 on 22nd December 2016

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
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_56KKF_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_56KKG_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55JFN_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KDP_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KER_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KES_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KET_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KFA_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KFR_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KGB_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KGP_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KGR_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KGS_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KGT_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KGU_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KHB_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55LFC_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55LGC_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55LHC_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55JGN_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KDQ_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KDR_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KDS_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KEP_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KEQ_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KEU_2016-12-22_final.stac-item
2016-12-22 09:50:59	ga_s2am_ard_3-2-1_55KEV_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50JRS_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50JRT_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JTM_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JTN_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JUM_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JUN_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JVM_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JVN_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JWM_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JWN_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JXN_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KUP_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KUQ_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KUR_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KUS_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KUT_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KVA_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KVB_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KVP_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KVQ_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KVR_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KVS_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KVT_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KVU_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KVV_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KWA_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KWB_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KWP_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KWQ_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KWR_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KWS_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KWT_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KWU_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KWV_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KXA_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KXB_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KXP_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KXQ_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KXR_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KXS_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KXT_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KXU_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KXV_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KYA_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KYB_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KYT_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KYU_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KYV_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KZB_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LWC_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LWE_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LXC_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LXD_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LYC_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LYD_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LYE_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LZC_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LZD_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LZE_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_52LBJ_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_52LBK_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50JQP_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JTJ_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JTK_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JTL_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JUJ_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JUK_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JUL_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JVJ_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JVK_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JVL_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JWJ_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JWK_2016-12-22_final.stac-item

Return to ga_s2am_ard_3 on 22nd December 2016 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

2016

December

22nd