Search ga_s2am_ard_3 whole collection

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
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HTC_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HUC_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HUD_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HUE_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HVC_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HVD_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HVE_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HWD_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HWE_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HXD_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HXE_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JUF_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JUG_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JVF_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JVG_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JVH_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JVJ_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JVK_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JVL_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JWF_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JWG_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JWH_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JWJ_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JWK_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JWL_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JWM_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JWN_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JXF_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JXG_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JXH_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JXJ_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JXK_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JXL_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JXM_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JXN_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JYG_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JYH_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JYJ_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JYK_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JYL_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JYM_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JYN_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JZM_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JZN_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51KWP_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51KXP_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51KYP_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51KZP_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_52JBR_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_52JBS_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_52JBT_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_52KBU_2018-09-30_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53LPC_2018-10-01_final
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53LPD_2018-10-01_final
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KKA_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KKB_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KKQ_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KKR_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KKS_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KKT_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KKU_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KKV_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KLA_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KLB_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KLQ_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KLR_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KLS_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KLT_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KLU_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KLV_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KMA_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KMB_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KMQ_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KMR_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KMS_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KMT_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KMU_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52KGA_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KMV_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52KGB_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KNA_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KNB_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KNT_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52KGV_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KNU_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52KHA_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KNV_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52KHB_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53KPB_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52KHC_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52KHD_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52KHE_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52KHF_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52KHV_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53LLC_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53LLD_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53LLE_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53LLF_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53LLG_2018-10-01_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_53LMC_2018-10-01_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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