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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
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HES_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HEA_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HDA_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55JEF_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HDD_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HED_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HEC_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55JFF_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HCA_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_54GYA_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55GDR_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HDE_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HEE_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55GER_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HFA_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55GBR_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55GCR_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HFB_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55JFH_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HGB_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HCC_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HFD_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HGC_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HBS_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HCS_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_54HYB_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HDS_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HCB_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HDC_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HBT_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HCT_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HDT_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HEB_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55GCM_2018-10-10_final.stac-item
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55GDN_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55GCN_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HET_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HFT_2018-10-10_final.stac-item
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HDB_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55GDM_2018-10-10_final.stac-item
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HFC_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HGE_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HDU_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HEU_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55JGF_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_56JKL_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HBU_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HFU_2018-10-10_final.stac-item
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_52LBH_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51LYC_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51LZC_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KWP_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KZP_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KZQ_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KZR_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KZV_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KZA_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KYV_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_52KCB_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KXR_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_52JBS_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KWQ_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KXS_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51JYN_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_52KBE_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_52KBV_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_52LCJ_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KYQ_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_52KCA_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KYA_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_52KBU_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KYP_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KXP_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51LZE_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_52LBK_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51LZD_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_52KDF_2018-10-10_final
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_52LBJ_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51JVF_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51JWF_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51JVL_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HXC_2018-10-10_final.stac-item
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HWD_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HVD_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HVC_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HWC_2018-10-10_final.stac-item
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HTC_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51JXF_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HWE_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HVB_2018-10-10_final.stac-item
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HUD_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HXD_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51JXH_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HUC_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HUB_2018-10-10_final.stac-item
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_52JBS_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51JUG_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HTB_2018-10-10_final.stac-item
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51JXK_2018-10-10_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HWB_2018-10-10_final.stac-item

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