Search ga_s2am_ard_3 across January 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
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HLH_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HMH_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HMJ_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HMK_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HNH_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HNJ_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HNK_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HPH_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HPJ_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HPK_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HQH_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HQJ_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HQK_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JML_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JMM_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JNL_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JNM_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JNN_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JNP_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JNQ_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JNR_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JPL_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JPM_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JPN_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JPP_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JPQ_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JPR_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JQL_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JQM_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JQN_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JQP_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JQQ_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JQR_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51JTF_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51JTG_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51JTH_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51JTJ_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51JTK_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51JTL_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51JUL_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HLG_2016-01-20_final
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HPG_2016-01-20_final
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HNG_2016-01-20_final
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HMG_2016-01-20_final
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JUG_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JVG_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JVH_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JVJ_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JVK_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JVL_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JWG_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JWH_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JWJ_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JWK_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JWL_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JWM_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JWN_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JXG_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JXH_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JXJ_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JXK_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JXL_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JXM_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JXN_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JYG_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JYH_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JYJ_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JYK_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JYL_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JYM_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JYN_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JZM_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JZN_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KWP_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KWQ_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KXP_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KXQ_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KXR_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KXS_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KXT_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KXU_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KYP_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KYQ_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KYR_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KYS_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KYT_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KYU_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KZP_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KZQ_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KZR_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KZS_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KZT_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KZU_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51LYC_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51LZC_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51LZD_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51LZE_2016-01-24_final.stac-item
2016-01-24 11:27:30	ga_s2am_ard_3-2-1_51JUG_2016-01-24_final.stac-item
2016-01-24 11:27:30	ga_s2am_ard_3-2-1_51JVG_2016-01-24_final.stac-item
2016-01-24 11:27:30	ga_s2am_ard_3-2-1_51JWG_2016-01-24_final.stac-item

Return to ga_s2am_ard_3 across January 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

January

All days