Search ga_s2am_ard_3 on 7th September 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
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56KPC_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56KPB_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56KNB_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56KNA_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56KMU_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JKN_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JKP_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JKQ_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JKR_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JKS_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JLN_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JLP_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JLQ_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JLR_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JLS_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JLT_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JMN_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JMP_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JMQ_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JMR_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JMS_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JMT_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JNN_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JNS_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JNT_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56KLA_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56KLB_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56KLU_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56KLV_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56KMA_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56KMB_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_55JGH_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_55JGJ_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_55JHM_2016-09-07_final.stac-item
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JNP_2016-09-07_final
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JNR_2016-09-07_final
2016-09-07 09:32:16	ga_s2am_ard_3-2-1_56JNQ_2016-09-07_final.stac-item
2016-09-07 09:36:27	ga_s2am_ard_3-2-1_56HKF_2016-09-07_final.stac-item
2016-09-07 09:36:27	ga_s2am_ard_3-2-1_55HEA_2016-09-07_final.stac-item
2016-09-07 09:36:27	ga_s2am_ard_3-2-1_55HFA_2016-09-07_final.stac-item
2016-09-07 09:36:27	ga_s2am_ard_3-2-1_55HGA_2016-09-07_final.stac-item
2016-09-07 09:38:34	ga_s2am_ard_3-2-1_55GCN_2016-09-07_final.stac-item
2016-09-07 09:38:34	ga_s2am_ard_3-2-1_55GCP_2016-09-07_final.stac-item
2016-09-07 09:38:34	ga_s2am_ard_3-2-1_55GDN_2016-09-07_final.stac-item
2016-09-07 09:38:34	ga_s2am_ard_3-2-1_55GDP_2016-09-07_final.stac-item
2016-09-07 09:38:34	ga_s2am_ard_3-2-1_55GEN_2016-09-07_final.stac-item
2016-09-07 09:38:34	ga_s2am_ard_3-2-1_55GFN_2016-09-07_final.stac-item
2016-09-07 09:38:34	ga_s2am_ard_3-2-1_55GEM_2016-09-07_final
2016-09-07 09:38:34	ga_s2am_ard_3-2-1_55GDM_2016-09-07_final
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LDJ_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LEJ_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LFH_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LFJ_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LFK_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LFL_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LFN_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LGH_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LGJ_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LGK_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LGL_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LGM_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_53LKJ_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LGN_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LHL_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LHM_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LHN_2016-09-07_final.stac-item
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LEL_2016-09-07_final
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LEK_2016-09-07_final
2016-09-07 11:07:11	ga_s2am_ard_3-2-1_52LFM_2016-09-07_final
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KBC_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KCC_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KCD_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KCE_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KCF_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KCG_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KDC_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KDD_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KDE_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KDF_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KDG_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KEC_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KED_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KEE_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KEF_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KEG_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KFC_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KFD_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KFE_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KFF_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52KFG_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52LDH_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52LDJ_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52LEH_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52LEJ_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52LFH_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52LFJ_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52LGH_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_52LGJ_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_51HWB_2016-09-07_final.stac-item
2016-09-07 11:11:27	ga_s2am_ard_3-2-1_51HWD_2016-09-07_final.stac-item

Return to ga_s2am_ard_3 on 7th September 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

September

7th