Search ga_s2am_ard_3 on 9th 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
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_54LZN_2016-09-09_final.stac-item
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_54LZM_2016-09-09_final.stac-item
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_54LZL_2016-09-09_final.stac-item
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_54LYJ_2016-09-09_final.stac-item
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_54LYK_2016-09-09_final.stac-item
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_54LZJ_2016-09-09_final.stac-item
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_54LZK_2016-09-09_final.stac-item
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_55LBD_2016-09-09_final.stac-item
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_55LBE_2016-09-09_final.stac-item
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_55LCC_2016-09-09_final.stac-item
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_55LCD_2016-09-09_final.stac-item
2016-09-09 10:07:02	ga_s2am_ard_3-2-1_55LCE_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HTF_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HTG_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HTH_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HTJ_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HUF_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HUG_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HUH_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HUJ_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HUK_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HVE_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HVF_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HVG_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HVH_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HVJ_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HVK_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HWE_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HWF_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HWG_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HWH_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HWJ_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HWK_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54HXK_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JUL_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JUM_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JVL_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JVM_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JWL_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JWM_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JXL_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JXM_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_53HQA_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_53HQB_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JUN_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JUP_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JVN_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JVP_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JVQ_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JVR_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JVS_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JVT_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JWN_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JWP_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JWQ_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JWR_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JWS_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JWT_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JXN_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JXP_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JXQ_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JXR_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JXS_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JXT_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JYN_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JYP_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JYQ_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JYR_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JYS_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JYT_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54JZT_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54KWA_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54KWB_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54KWU_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54KWV_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54KXA_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54KXB_2016-09-09_final.stac-item
2016-09-09 10:11:04	ga_s2am_ard_3-2-1_54KXC_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HTE_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HTF_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HUF_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HVD_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HVE_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HVF_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HWE_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HWF_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_53HQA_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_53HQV_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HUE_2016-09-09_final
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HVC_2016-09-09_final
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HUD_2016-09-09_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50HLK_2016-09-09_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50HMK_2016-09-09_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50HNK_2016-09-09_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50JKM_2016-09-09_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50JLL_2016-09-09_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50JLM_2016-09-09_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50JML_2016-09-09_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50JMM_2016-09-09_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50JNL_2016-09-09_final.stac-item

Return to ga_s2am_ard_3 on 9th 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

9th