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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
2017-10-30 12:14:41	ga_s2am_ard_3-2-1_49JGK_2017-10-30_final
2017-10-30 12:14:41	ga_s2am_ard_3-2-1_49JFN_2017-10-30_final
2017-10-30 12:14:41	ga_s2am_ard_3-2-1_49JGL_2017-10-30_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55KBT_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55KFA_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55KDT_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55KCA_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55KDQ_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55KEQ_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55KBR_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_54KZC_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55LCC_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55LFC_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55KEV_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55LEC_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55KDA_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55KDV_2017-10-31_final
2017-10-31 10:00:32	ga_s2am_ard_3-2-1_55KER_2017-10-31_final
2017-10-31 10:03:03	ga_s2am_ard_3-2-1_55KDP_2017-10-31_final
2017-10-31 10:03:03	ga_s2am_ard_3-2-1_55KDQ_2017-10-31_final
2017-10-31 10:03:03	ga_s2am_ard_3-2-1_55KEQ_2017-10-31_final
2017-10-31 10:03:03	ga_s2am_ard_3-2-1_54KZA_2017-10-31_final
2017-10-31 10:03:03	ga_s2am_ard_3-2-1_54KYV_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_55HBD_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_54HXG_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_54HVH_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_55HBE_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_54HXJ_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_54HXH_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_54HYJ_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_54HYK_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_54HYG_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_54HWJ_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_54HWH_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_54HXK_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_54HWK_2017-10-31_final
2017-10-31 10:05:51	ga_s2am_ard_3-2-1_55HBB_2017-10-31_final
2017-10-31 11:37:51	ga_s2am_ard_3-2-1_51LUF_2017-10-31_final
2017-10-31 11:37:51	ga_s2am_ard_3-2-1_51LVE_2017-10-31_final
2017-10-31 11:37:51	ga_s2am_ard_3-2-1_51LWE_2017-10-31_final
2017-10-31 11:37:51	ga_s2am_ard_3-2-1_51LUE_2017-10-31_final
2017-10-31 11:37:51	ga_s2am_ard_3-2-1_51KUB_2017-10-31_final.stac-item
2017-10-31 11:37:51	ga_s2am_ard_3-2-1_51LUC_2017-10-31_final.stac-item
2017-10-31 11:37:51	ga_s2am_ard_3-2-1_51LWC_2017-10-31_final
2017-10-31 11:37:51	ga_s2am_ard_3-2-1_51LVC_2017-10-31_final
2017-10-31 11:37:51	ga_s2am_ard_3-2-1_51LWG_2017-10-31_final.stac-item
2017-10-31 11:37:51	ga_s2am_ard_3-2-1_51LVG_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51JTH_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JNP_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51JTG_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JNR_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JMM_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JNM_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JNL_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JML_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JQM_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JPR_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51KTT_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50KQC_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51KUA_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51KTR_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50KRC_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50KRD_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51JTF_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JQQ_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JPN_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HLG_2017-10-31_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HMK_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HNK_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51JUL_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HMJ_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JQL_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51LUC_2017-10-31_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HLH_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51KVV_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HNH_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HQJ_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HPH_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HQK_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HMG_2017-10-31_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HNG_2017-10-31_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51JTK_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HMH_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HNJ_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HPK_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JPQ_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51JTJ_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JPM_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JPL_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HPJ_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JPP_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HPG_2017-10-31_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51KVA_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51LVC_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JRS_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JPT_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JNQ_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JNN_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50KQV_2017-10-31_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JQR_2017-10-31_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

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