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
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_50KKV_2018-06-17_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_50KKU_2018-06-17_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49KGP_2018-06-17_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49JGN_2018-06-17_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49KGQ_2018-06-17_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49JGK_2018-06-17_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49JGM_2018-06-17_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_50KKA_2018-06-17_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_50KKB_2018-06-17_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49KGR_2018-06-17_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KCT_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KCA_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55JDM_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54HWF_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KDT_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KBS_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KEU_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KDU_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54JWM_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KDP_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KFA_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54HVF_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KDS_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KES_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KBQ_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KCQ_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KCP_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KBV_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KCR_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KEQ_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KDQ_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KDR_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KER_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55JBN_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54JYT_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KBP_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54KYU_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55LCD_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KCS_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KBR_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54HXK_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55JCK_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54HXH_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54JXM_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54HXG_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54JXN_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55JBF_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54HWD_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54JYQ_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54HXC_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54JYL_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54HWC_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54HVC_2018-06-18_final.stac-item
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KCU_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KBU_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55KFU_2018-06-18_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55JCH_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KUT_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KUA_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KTU_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KVU_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KTS_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51LUF_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KVS_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KTQ_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KUP_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KUQ_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KVR_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51LUD_2018-06-18_final.stac-item
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_50KQU_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KTP_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KTR_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KUS_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_50KQV_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51LVF_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KUR_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KUU_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_50KQB_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_50KQA_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_50KPV_2018-06-18_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_50KPU_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JMM_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JNM_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JNP_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JQS_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50KPU_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_51KUP_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_51JTN_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JQT_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50KQU_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_51KTP_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50KQV_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50HPH_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50HPK_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50HPG_2018-06-18_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JPM_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50HLG_2018-06-18_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JQQ_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JPN_2018-06-18_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_51JTF_2018-06-18_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