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The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56KMU_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JMR_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JNR_2018-10-17_final.stac-item
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55HEA_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56HKK_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55HEU_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55HFB_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JLQ_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55JGF_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JKL_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56HLK_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55GCM_2018-10-17_final.stac-item
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55JHM_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JMT_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JNT_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56HKJ_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55HGD_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JKM_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55JGG_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JNQ_2018-10-17_final.stac-item
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JNP_2018-10-17_final.stac-item
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JLM_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JMQ_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JKN_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JLS_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JKT_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JMS_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JML_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56KLV_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56KLU_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55HGC_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55HFS_2018-10-17_final.stac-item
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55HDS_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55HES_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56KNA_2018-10-17_final.stac-item
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56KMA_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JNS_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55GDM_2018-10-17_final.stac-item
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55GEM_2018-10-17_final.stac-item
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_53LKJ_2018-10-17_final.stac-item
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LGH_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LEK_2018-10-17_final.stac-item
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LFK_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KCD_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KFD_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LFL_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KCC_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LGM_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LHM_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LGL_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KEC_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KDC_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LFM_2018-10-17_final.stac-item
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LFN_2018-10-17_final.stac-item
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KFC_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KDD_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KED_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LEL_2018-10-17_final.stac-item
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KGG_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KDE_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LGJ_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52LFH_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KEE_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KFF_2018-10-17_final
2018-10-17 11:07:09	ga_s2am_ard_3-2-1_52KCF_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KCD_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KCC_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KDU_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KEC_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KDC_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KEU_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KBC_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JDR_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JCQ_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51JYF_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51JXG_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JBL_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51JYK_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51HWC_2018-10-17_final.stac-item
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51JYN_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51JXH_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KFC_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51KZP_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JET_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JDT_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51KZR_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JBT_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51HYD_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JCS_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JBM_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51JYG_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JDP_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JCR_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JBN_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JCM_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51JZM_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KCV_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KBV_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KBU_2018-10-17_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KCU_2018-10-17_final

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years