Search ga_s2am_ard_3 whole collection

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
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50KMU_2018-10-12_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JLN_2018-10-12_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JKQ_2018-10-12_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JGN_2018-10-12_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JMS_2018-10-12_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50KLV_2018-10-12_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JGK_2018-10-12_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49KHQ_2018-10-12_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49KHP_2018-10-12_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55LHC_2018-10-13_final.stac-item
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55LGC_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55KGT_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55KEP_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55KFT_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55KFU_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55KDP_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55KET_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HDA_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55KGU_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55KEU_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JDL_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JEL_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_54HXG_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HCB_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HCD_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_54HWC_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HBB_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HDB_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HBE_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HBT_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HCT_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_54HYC_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_54HXC_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_54HYK_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HDD_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HED_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JFK_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JCH_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HCC_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JGN_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JDM_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JEM_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_56KKF_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55KFP_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JFH_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_54HYG_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55KFQ_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_54HYJ_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55KEV_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HBD_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55LFC_2018-10-13_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_54HXD_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51LYC_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51LZC_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51KYU_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51KYT_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51KXT_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51LWE_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51KXU_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51KYA_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51KVV_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51LZE_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51LYE_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_52LBK_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51LXC_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51KWV_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51KVA_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51KWA_2018-10-13_final
2018-10-13 11:26:17	ga_s2am_ard_3-2-1_51LYD_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51KYT_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51KVP_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51KUT_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51KWP_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51KXT_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51KVT_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51KWT_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JVF_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51KXU_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51HUC_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_50HNG_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_50HPH_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JTK_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51HUD_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51HTE_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_50HPJ_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51HVD_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_50HQK_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51HTB_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JUH_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_50HQG_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51HUB_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JVM_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JWM_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51KXP_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51KXQ_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51KUQ_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_50JQL_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51HUE_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_50HPK_2018-10-13_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51HTD_2018-10-13_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