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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
2019-11-18 11:03:21	ga_s2am_ard_3-2-1_52KEB_2019-11-18_final
2019-11-18 11:03:28	ga_s2am_ard_3-2-1_52KGA_2019-11-18_final
2019-11-18 11:03:32	ga_s2am_ard_3-2-1_52KEA_2019-11-18_final
2019-11-18 11:03:33	ga_s2am_ard_3-2-1_52KHV_2019-11-18_final
2019-11-18 11:03:34	ga_s2am_ard_3-2-1_52KHV_2019-11-18_final
2019-11-18 11:03:35	ga_s2am_ard_3-2-1_52KGA_2019-11-18_final
2019-11-18 11:03:38	ga_s2am_ard_3-2-1_52KEA_2019-11-18_final
2019-11-18 11:03:58	ga_s2am_ard_3-2-1_52KGU_2019-11-18_final
2019-11-18 11:04:16	ga_s2am_ard_3-2-1_52JFT_2019-11-18_final
2019-11-18 11:04:19	ga_s2am_ard_3-2-1_52JET_2019-11-18_final
2019-11-18 11:04:23	ga_s2am_ard_3-2-1_52JDT_2019-11-18_final
2019-11-18 11:04:30	ga_s2am_ard_3-2-1_52JFS_2019-11-18_final
2019-11-18 11:04:37	ga_s2am_ard_3-2-1_52JGR_2019-11-18_final
2019-11-18 11:04:37	ga_s2am_ard_3-2-1_52JDS_2019-11-18_final
2019-11-18 11:04:45	ga_s2am_ard_3-2-1_52JFR_2019-11-18_final
2019-11-18 11:04:48	ga_s2am_ard_3-2-1_52JER_2019-11-18_final
2019-11-18 11:04:52	ga_s2am_ard_3-2-1_52JDR_2019-11-18_final
2019-11-18 11:04:57	ga_s2am_ard_3-2-1_52JCR_2019-11-18_final
2019-11-18 11:04:59	ga_s2am_ard_3-2-1_52JFQ_2019-11-18_final
2019-11-18 11:05:10	ga_s2am_ard_3-2-1_52JCQ_2019-11-18_final
2019-11-18 11:05:14	ga_s2am_ard_3-2-1_52JFP_2019-11-18_final
2019-11-18 11:05:17	ga_s2am_ard_3-2-1_52JEP_2019-11-18_final
2019-11-18 11:05:21	ga_s2am_ard_3-2-1_52JDP_2019-11-18_final
2019-11-18 11:05:24	ga_s2am_ard_3-2-1_52JCP_2019-11-18_final
2019-11-18 11:05:28	ga_s2am_ard_3-2-1_52JFN_2019-11-18_final
2019-11-18 11:05:39	ga_s2am_ard_3-2-1_52JCN_2019-11-18_final
2019-11-18 11:05:40	ga_s2am_ard_3-2-1_52JFM_2019-11-18_final
2019-11-18 11:05:46	ga_s2am_ard_3-2-1_52JEM_2019-11-18_final
2019-11-18 11:05:50	ga_s2am_ard_3-2-1_52JDM_2019-11-18_final
2019-11-18 11:05:53	ga_s2am_ard_3-2-1_52JCM_2019-11-18_final
2019-11-18 11:06:05	ga_s2am_ard_3-2-1_52JDL_2019-11-18_final
2019-11-18 11:06:08	ga_s2am_ard_3-2-1_52JCL_2019-11-18_final
2019-11-18 11:06:11	ga_s2am_ard_3-2-1_52JBL_2019-11-18_final
2019-11-18 11:06:19	ga_s2am_ard_3-2-1_52HDK_2019-11-18_final.stac-item
2019-11-18 11:06:22	ga_s2am_ard_3-2-1_52HCK_2019-11-18_final.stac-item
2019-11-19 10:30:13	ga_s2am_ard_3-2-1_54LWN_2019-11-19_final
2019-11-19 10:30:19	ga_s2am_ard_3-2-1_54LXM_2019-11-19_final
2019-11-19 10:30:31	ga_s2am_ard_3-2-1_54LVM_2019-11-19_final.stac-item
2019-11-19 10:30:57	ga_s2am_ard_3-2-1_54LWK_2019-11-19_final
2019-11-19 10:31:00	ga_s2am_ard_3-2-1_54LVK_2019-11-19_final.stac-item
2019-11-19 10:31:11	ga_s2am_ard_3-2-1_54LWJ_2019-11-19_final
2019-11-19 10:31:15	ga_s2am_ard_3-2-1_54LVJ_2019-11-19_final.stac-item
2019-11-19 10:31:18	ga_s2am_ard_3-2-1_54LUJ_2019-11-19_final.stac-item
2019-11-19 10:31:23	ga_s2am_ard_3-2-1_54LWH_2019-11-19_final
2019-11-19 10:31:29	ga_s2am_ard_3-2-1_54LVH_2019-11-19_final
2019-11-19 10:31:32	ga_s2am_ard_3-2-1_54LUH_2019-11-19_final
2019-11-19 10:31:33	ga_s2am_ard_3-2-1_54KWG_2019-11-19_final
2019-11-19 10:31:43	ga_s2am_ard_3-2-1_54KVG_2019-11-19_final
2019-11-19 10:31:47	ga_s2am_ard_3-2-1_54KUG_2019-11-19_final
2019-11-19 10:31:50	ga_s2am_ard_3-2-1_54KTG_2019-11-19_final
2019-11-19 10:31:51	ga_s2am_ard_3-2-1_53KRB_2019-11-19_final
2019-11-19 10:32:06	ga_s2am_ard_3-2-1_53KRA_2019-11-19_final
2019-11-19 10:32:12	ga_s2am_ard_3-2-1_53KQA_2019-11-19_final
2019-11-19 10:32:13	ga_s2am_ard_3-2-1_54KVE_2019-11-19_final
2019-11-19 10:32:16	ga_s2am_ard_3-2-1_54KUE_2019-11-19_final
2019-11-19 10:32:48	ga_s2am_ard_3-2-1_54KTC_2019-11-19_final
2019-11-19 10:32:53	ga_s2am_ard_3-2-1_53KQT_2019-11-19_final
2019-11-19 10:33:18	ga_s2am_ard_3-2-1_54KTA_2019-11-19_final
2019-11-19 10:33:21	ga_s2am_ard_3-2-1_53KQR_2019-11-19_final
2019-11-19 10:33:32	ga_s2am_ard_3-2-1_53KRQ_2019-11-19_final
2019-11-19 10:33:47	ga_s2am_ard_3-2-1_54KTU_2019-11-19_final
2019-11-19 10:33:47	ga_s2am_ard_3-2-1_53KRP_2019-11-19_final
2019-11-19 10:33:50	ga_s2am_ard_3-2-1_53KQP_2019-11-19_final
2019-11-19 10:34:01	ga_s2am_ard_3-2-1_53JRN_2019-11-19_final
2019-11-19 10:34:09	ga_s2am_ard_3-2-1_53JPN_2019-11-19_final
2019-11-19 10:34:15	ga_s2am_ard_3-2-1_53JNN_2019-11-19_final
2019-11-19 10:34:23	ga_s2am_ard_3-2-1_53JPM_2019-11-19_final
2019-11-19 10:34:27	ga_s2am_ard_3-2-1_53JNM_2019-11-19_final
2019-11-19 10:34:30	ga_s2am_ard_3-2-1_54JTR_2019-11-19_final
2019-11-19 10:34:34	ga_s2am_ard_3-2-1_53JQL_2019-11-19_final
2019-11-19 10:34:37	ga_s2am_ard_3-2-1_53JPL_2019-11-19_final
2019-11-19 10:34:41	ga_s2am_ard_3-2-1_53JNL_2019-11-19_final
2019-11-19 10:34:45	ga_s2am_ard_3-2-1_54JTQ_2019-11-19_final
2019-11-19 10:34:52	ga_s2am_ard_3-2-1_53JPK_2019-11-19_final
2019-11-19 10:34:58	ga_s2am_ard_3-2-1_54JTP_2019-11-19_final
2019-11-19 10:35:02	ga_s2am_ard_3-2-1_53JQJ_2019-11-19_final
2019-11-19 10:35:06	ga_s2am_ard_3-2-1_53JPJ_2019-11-19_final
2019-11-19 10:35:09	ga_s2am_ard_3-2-1_54JTN_2019-11-19_final
2019-11-19 10:35:10	ga_s2am_ard_3-2-1_53JNJ_2019-11-19_final
2019-11-19 10:35:16	ga_s2am_ard_3-2-1_53JMJ_2019-11-19_final
2019-11-19 10:35:17	ga_s2am_ard_3-2-1_53JQH_2019-11-19_final
2019-11-19 10:35:24	ga_s2am_ard_3-2-1_53JNH_2019-11-19_final
2019-11-19 10:35:28	ga_s2am_ard_3-2-1_53JMH_2019-11-19_final
2019-11-19 10:35:35	ga_s2am_ard_3-2-1_53JPG_2019-11-19_final
2019-11-19 10:35:39	ga_s2am_ard_3-2-1_53JNG_2019-11-19_final
2019-11-19 10:35:42	ga_s2am_ard_3-2-1_53JMG_2019-11-19_final
2019-11-19 10:35:46	ga_s2am_ard_3-2-1_53JQF_2019-11-19_final
2019-11-19 10:35:50	ga_s2am_ard_3-2-1_53JPF_2019-11-19_final
2019-11-19 10:35:57	ga_s2am_ard_3-2-1_53JMF_2019-11-19_final
2019-11-19 10:36:04	ga_s2am_ard_3-2-1_53HPE_2019-11-19_final
2019-11-19 10:36:08	ga_s2am_ard_3-2-1_53HNE_2019-11-19_final
2019-11-19 10:36:11	ga_s2am_ard_3-2-1_53HME_2019-11-19_final
2019-11-19 10:36:18	ga_s2am_ard_3-2-1_53HLE_2019-11-19_final
2019-11-19 10:36:18	ga_s2am_ard_3-2-1_53HPD_2019-11-19_final
2019-11-19 10:36:22	ga_s2am_ard_3-2-1_53HND_2019-11-19_final
2019-11-19 10:36:26	ga_s2am_ard_3-2-1_53HMD_2019-11-19_final
2019-11-19 10:36:30	ga_s2am_ard_3-2-1_53HLD_2019-11-19_final
2019-11-19 10:36:33	ga_s2am_ard_3-2-1_53HPC_2019-11-19_final
2019-11-19 10:36:37	ga_s2am_ard_3-2-1_53HNC_2019-11-19_final
2019-11-19 10:36:40	ga_s2am_ard_3-2-1_53HMC_2019-11-19_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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