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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
2019-11-29 12:15:10	ga_s2am_ard_3-2-1_49JGL_2019-11-29_final
2019-11-29 12:15:19	ga_s2am_ard_3-2-1_49JGK_2019-11-29_final
2019-11-30 10:01:17	ga_s2am_ard_3-2-1_55LEC_2019-11-30_final
2019-11-30 10:01:31	ga_s2am_ard_3-2-1_55KEB_2019-11-30_final
2019-11-30 10:01:35	ga_s2am_ard_3-2-1_55KDB_2019-11-30_final
2019-11-30 10:01:49	ga_s2am_ard_3-2-1_55KDA_2019-11-30_final
2019-11-30 10:02:00	ga_s2am_ard_3-2-1_55KEV_2019-11-30_final
2019-11-30 10:02:04	ga_s2am_ard_3-2-1_55KDV_2019-11-30_final
2019-11-30 10:02:04	ga_s2am_ard_3-2-1_55KFU_2019-11-30_final
2019-11-30 10:02:07	ga_s2am_ard_3-2-1_55KCV_2019-11-30_final
2019-11-30 10:04:13	ga_s2am_ard_3-2-1_55JDL_2019-11-30_final
2019-11-30 10:04:18	ga_s2am_ard_3-2-1_55JCL_2019-11-30_final
2019-11-30 10:04:21	ga_s2am_ard_3-2-1_55JBL_2019-11-30_final
2019-11-30 10:04:23	ga_s2am_ard_3-2-1_55JDK_2019-11-30_final
2019-11-30 10:04:24	ga_s2am_ard_3-2-1_54JYR_2019-11-30_final
2019-11-30 10:04:32	ga_s2am_ard_3-2-1_54JXR_2019-11-30_final
2019-11-30 10:04:32	ga_s2am_ard_3-2-1_55JCK_2019-11-30_final
2019-11-30 10:04:36	ga_s2am_ard_3-2-1_55JBK_2019-11-30_final
2019-11-30 10:04:39	ga_s2am_ard_3-2-1_54JYQ_2019-11-30_final
2019-11-30 10:04:43	ga_s2am_ard_3-2-1_54JXQ_2019-11-30_final
2019-11-30 10:04:50	ga_s2am_ard_3-2-1_55JBJ_2019-11-30_final
2019-11-30 10:04:53	ga_s2am_ard_3-2-1_54JYP_2019-11-30_final
2019-11-30 10:05:02	ga_s2am_ard_3-2-1_55JCH_2019-11-30_final
2019-11-30 10:05:05	ga_s2am_ard_3-2-1_55JBH_2019-11-30_final
2019-11-30 10:05:08	ga_s2am_ard_3-2-1_54JYN_2019-11-30_final
2019-11-30 10:05:11	ga_s2am_ard_3-2-1_54JXN_2019-11-30_final
2019-11-30 10:05:19	ga_s2am_ard_3-2-1_55JBG_2019-11-30_final
2019-11-30 10:05:22	ga_s2am_ard_3-2-1_54JYM_2019-11-30_final
2019-11-30 10:05:26	ga_s2am_ard_3-2-1_54JXM_2019-11-30_final
2019-11-30 10:05:32	ga_s2am_ard_3-2-1_54JWM_2019-11-30_final
2019-11-30 10:05:34	ga_s2am_ard_3-2-1_55JBF_2019-11-30_final
2019-11-30 10:05:37	ga_s2am_ard_3-2-1_54JYL_2019-11-30_final
2019-11-30 10:05:40	ga_s2am_ard_3-2-1_54JXL_2019-11-30_final
2019-11-30 10:05:44	ga_s2am_ard_3-2-1_54JWL_2019-11-30_final
2019-11-30 10:05:48	ga_s2am_ard_3-2-1_55HBE_2019-11-30_final
2019-11-30 10:05:51	ga_s2am_ard_3-2-1_54HYK_2019-11-30_final
2019-11-30 10:05:55	ga_s2am_ard_3-2-1_54HXK_2019-11-30_final
2019-11-30 10:06:03	ga_s2am_ard_3-2-1_55HBD_2019-11-30_final
2019-11-30 10:06:05	ga_s2am_ard_3-2-1_54HYJ_2019-11-30_final
2019-11-30 10:06:09	ga_s2am_ard_3-2-1_54HXJ_2019-11-30_final
2019-11-30 10:06:19	ga_s2am_ard_3-2-1_54HYH_2019-11-30_final
2019-11-30 10:06:24	ga_s2am_ard_3-2-1_54HXH_2019-11-30_final
2019-11-30 10:06:32	ga_s2am_ard_3-2-1_55HBB_2019-11-30_final
2019-11-30 10:06:34	ga_s2am_ard_3-2-1_54HYG_2019-11-30_final
2019-11-30 10:06:38	ga_s2am_ard_3-2-1_54HXG_2019-11-30_final
2019-11-30 10:06:42	ga_s2am_ard_3-2-1_54HWG_2019-11-30_final
2019-11-30 10:06:45	ga_s2am_ard_3-2-1_54HVG_2019-11-30_final
2019-11-30 10:06:53	ga_s2am_ard_3-2-1_54HXF_2019-11-30_final
2019-11-30 10:06:55	ga_s2am_ard_3-2-1_55HBV_2019-11-30_final
2019-11-30 10:07:02	ga_s2am_ard_3-2-1_54HYE_2019-11-30_final
2019-11-30 10:07:07	ga_s2am_ard_3-2-1_54HXE_2019-11-30_final
2019-11-30 10:07:11	ga_s2am_ard_3-2-1_54HWE_2019-11-30_final
2019-11-30 10:07:13	ga_s2am_ard_3-2-1_54HYD_2019-11-30_final
2019-11-30 10:07:14	ga_s2am_ard_3-2-1_54HVE_2019-11-30_final
2019-11-30 10:07:21	ga_s2am_ard_3-2-1_54HXD_2019-11-30_final
2019-11-30 10:07:25	ga_s2am_ard_3-2-1_54HWD_2019-11-30_final
2019-11-30 10:07:29	ga_s2am_ard_3-2-1_54HVD_2019-11-30_final
2019-11-30 10:07:34	ga_s2am_ard_3-2-1_54HUD_2019-11-30_final.stac-item
2019-11-30 10:07:36	ga_s2am_ard_3-2-1_54HXC_2019-11-30_final
2019-11-30 10:07:40	ga_s2am_ard_3-2-1_54HWC_2019-11-30_final
2019-11-30 10:07:43	ga_s2am_ard_3-2-1_54HVC_2019-11-30_final.stac-item
2019-11-30 11:41:58	ga_s2am_ard_3-2-1_51LVC_2019-11-30_final
2019-11-30 11:42:08	ga_s2am_ard_3-2-1_51KWB_2019-11-30_final
2019-11-30 11:42:12	ga_s2am_ard_3-2-1_51KVB_2019-11-30_final
2019-11-30 11:42:20	ga_s2am_ard_3-2-1_51KWA_2019-11-30_final
2019-11-30 11:42:27	ga_s2am_ard_3-2-1_51KVA_2019-11-30_final
2019-11-30 11:42:41	ga_s2am_ard_3-2-1_51KVV_2019-11-30_final
2019-11-30 11:42:45	ga_s2am_ard_3-2-1_51KUV_2019-11-30_final
2019-11-30 11:44:50	ga_s2am_ard_3-2-1_51JUL_2019-11-30_final
2019-11-30 11:44:59	ga_s2am_ard_3-2-1_51JTL_2019-11-30_final
2019-11-30 11:45:02	ga_s2am_ard_3-2-1_50JQR_2019-11-30_final
2019-11-30 11:45:06	ga_s2am_ard_3-2-1_50JPR_2019-11-30_final
2019-11-30 11:45:13	ga_s2am_ard_3-2-1_51JTK_2019-11-30_final
2019-11-30 11:45:17	ga_s2am_ard_3-2-1_50JQQ_2019-11-30_final
2019-11-30 11:45:20	ga_s2am_ard_3-2-1_50JPQ_2019-11-30_final
2019-11-30 11:45:24	ga_s2am_ard_3-2-1_50JNQ_2019-11-30_final
2019-11-30 11:45:28	ga_s2am_ard_3-2-1_51JTJ_2019-11-30_final
2019-11-30 11:45:31	ga_s2am_ard_3-2-1_50JQP_2019-11-30_final
2019-11-30 11:45:38	ga_s2am_ard_3-2-1_50JNP_2019-11-30_final
2019-11-30 11:45:43	ga_s2am_ard_3-2-1_51JTH_2019-11-30_final
2019-11-30 11:45:46	ga_s2am_ard_3-2-1_50JQN_2019-11-30_final
2019-11-30 11:45:49	ga_s2am_ard_3-2-1_50JPN_2019-11-30_final
2019-11-30 11:45:56	ga_s2am_ard_3-2-1_51JTG_2019-11-30_final
2019-11-30 11:46:00	ga_s2am_ard_3-2-1_50JQM_2019-11-30_final
2019-11-30 11:46:04	ga_s2am_ard_3-2-1_50JPM_2019-11-30_final
2019-11-30 11:46:07	ga_s2am_ard_3-2-1_51JTF_2019-11-30_final
2019-11-30 11:46:07	ga_s2am_ard_3-2-1_50JNM_2019-11-30_final
2019-11-30 11:46:12	ga_s2am_ard_3-2-1_50JMM_2019-11-30_final
2019-11-30 11:46:14	ga_s2am_ard_3-2-1_50JQL_2019-11-30_final
2019-11-30 11:46:18	ga_s2am_ard_3-2-1_50JPL_2019-11-30_final
2019-11-30 11:46:22	ga_s2am_ard_3-2-1_50JNL_2019-11-30_final
2019-11-30 11:46:25	ga_s2am_ard_3-2-1_50JML_2019-11-30_final
2019-11-30 11:46:29	ga_s2am_ard_3-2-1_50HQK_2019-11-30_final
2019-11-30 11:46:33	ga_s2am_ard_3-2-1_50HPK_2019-11-30_final
2019-11-30 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2019-11-30_final
2019-11-30 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2019-11-30_final
2019-11-30 11:47:01	ga_s2am_ard_3-2-1_50HPH_2019-11-30_final
2019-11-30 11:47:16	ga_s2am_ard_3-2-1_50HPG_2019-11-30_final.stac-item
2019-11-30 11:47:20	ga_s2am_ard_3-2-1_50HNG_2019-11-30_final.stac-item
2019-11-30 11:47:23	ga_s2am_ard_3-2-1_50HMG_2019-11-30_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

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