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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 11:00:50	ga_s2am_ard_3-2-1_53LMF_2019-11-18_final
2019-11-18 11:01:18	ga_s2am_ard_3-2-1_52LGK_2019-11-18_final
2019-11-18 11:01:25	ga_s2am_ard_3-2-1_53LLD_2019-11-18_final
2019-11-18 11:01:41	ga_s2am_ard_3-2-1_52LFJ_2019-11-18_final
2019-11-18 11:01:53	ga_s2am_ard_3-2-1_53KLB_2019-11-18_final
2019-11-18 11:02:05	ga_s2am_ard_3-2-1_52KFG_2019-11-18_final
2019-11-18 11:02:12	ga_s2am_ard_3-2-1_53KKA_2019-11-18_final
2019-11-18 11:02:13	ga_s2am_ard_3-2-1_52KHF_2019-11-18_final
2019-11-18 11:02:17	ga_s2am_ard_3-2-1_52KGF_2019-11-18_final
2019-11-18 11:02:27	ga_s2am_ard_3-2-1_52KHE_2019-11-18_final
2019-11-18 11:02:34	ga_s2am_ard_3-2-1_52KFE_2019-11-18_final
2019-11-18 11:02:42	ga_s2am_ard_3-2-1_52KHD_2019-11-18_final
2019-11-18 11:02:49	ga_s2am_ard_3-2-1_52KFD_2019-11-18_final
2019-11-18 11:02:56	ga_s2am_ard_3-2-1_52KHC_2019-11-18_final
2019-11-18 11:03:06	ga_s2am_ard_3-2-1_52KEC_2019-11-18_final
2019-11-18 11:03:09	ga_s2am_ard_3-2-1_53KKS_2019-11-18_final
2019-11-18 11:03:11	ga_s2am_ard_3-2-1_52KHB_2019-11-18_final
2019-11-18 11:03:14	ga_s2am_ard_3-2-1_52KGB_2019-11-18_final
2019-11-18 11:03:21	ga_s2am_ard_3-2-1_52KEB_2019-11-18_final
2019-11-18 11:03:24	ga_s2am_ard_3-2-1_52KHA_2019-11-18_final
2019-11-18 11:03:28	ga_s2am_ard_3-2-1_52KGA_2019-11-18_final
2019-11-18 11:03:33	ga_s2am_ard_3-2-1_52KHA_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 11:03:47	ga_s2am_ard_3-2-1_52KFV_2019-11-18_final
2019-11-18 11:03:58	ga_s2am_ard_3-2-1_52KGU_2019-11-18_final
2019-11-18 11:04:01	ga_s2am_ard_3-2-1_52KFU_2019-11-18_final
2019-11-18 11:04:16	ga_s2am_ard_3-2-1_52JFT_2019-11-18_final
2019-11-18 11:04:34	ga_s2am_ard_3-2-1_52JES_2019-11-18_final
2019-11-18 11:04:37	ga_s2am_ard_3-2-1_52JDS_2019-11-18_final
2019-11-18 11:04:59	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 11:05:24	ga_s2am_ard_3-2-1_52JCP_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 11:05:53	ga_s2am_ard_3-2-1_52JCM_2019-11-18_final
2019-11-18 11:06:00	ga_s2am_ard_3-2-1_52JBM_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 11:06:22	ga_s2am_ard_3-2-1_52HCK_2019-11-18_final.stac-item
2019-11-19 10:29:41	ga_s2am_ard_3-2-1_54LXQ_2019-11-19_final
2019-11-19 10:29:44	ga_s2am_ard_3-2-1_54LWQ_2019-11-19_final.stac-item
2019-11-19 10:30:19	ga_s2am_ard_3-2-1_54LXM_2019-11-19_final
2019-11-19 10:30:27	ga_s2am_ard_3-2-1_54LWM_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 10:30:42	ga_s2am_ard_3-2-1_54LWL_2019-11-19_final
2019-11-19 10:30:46	ga_s2am_ard_3-2-1_54LVL_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 10:31:18	ga_s2am_ard_3-2-1_54LUJ_2019-11-19_final.stac-item
2019-11-19 10:31:47	ga_s2am_ard_3-2-1_54KUG_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 10:32:16	ga_s2am_ard_3-2-1_54KUE_2019-11-19_final
2019-11-19 10:32:19	ga_s2am_ard_3-2-1_54KTE_2019-11-19_final
2019-11-19 10:32:20	ga_s2am_ard_3-2-1_53KRV_2019-11-19_final
2019-11-19 10:32:24	ga_s2am_ard_3-2-1_53KQV_2019-11-19_final
2019-11-19 10:32:26	ga_s2am_ard_3-2-1_54KVD_2019-11-19_final
2019-11-19 10:32:31	ga_s2am_ard_3-2-1_54KUD_2019-11-19_final
2019-11-19 10:32:35	ga_s2am_ard_3-2-1_53KRU_2019-11-19_final
2019-11-19 10:32:38	ga_s2am_ard_3-2-1_54KVC_2019-11-19_final
2019-11-19 10:32:49	ga_s2am_ard_3-2-1_53KRT_2019-11-19_final
2019-11-19 10:33:03	ga_s2am_ard_3-2-1_54KTB_2019-11-19_final
2019-11-19 10:33:04	ga_s2am_ard_3-2-1_53KRS_2019-11-19_final
2019-11-19 10:33:07	ga_s2am_ard_3-2-1_53KQS_2019-11-19_final
2019-11-19 10:33:14	ga_s2am_ard_3-2-1_54KUA_2019-11-19_final
2019-11-19 10:33:18	ga_s2am_ard_3-2-1_54KTA_2019-11-19_final
2019-11-19 10:33:18	ga_s2am_ard_3-2-1_53KRR_2019-11-19_final
2019-11-19 10:33:21	ga_s2am_ard_3-2-1_53KQR_2019-11-19_final
2019-11-19 10:33:29	ga_s2am_ard_3-2-1_54KUV_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_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 10:33:53	ga_s2am_ard_3-2-1_54JUT_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_53JRM_2019-11-19_final
2019-11-19 10:34:16	ga_s2am_ard_3-2-1_54JTS_2019-11-19_final
2019-11-19 10:34:19	ga_s2am_ard_3-2-1_53JQM_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 10:34:45	ga_s2am_ard_3-2-1_54JTQ_2019-11-19_final
2019-11-19 10:34:48	ga_s2am_ard_3-2-1_53JQK_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 10:35:35	ga_s2am_ard_3-2-1_53JPG_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 10:35:58	ga_s2am_ard_3-2-1_53HQE_2019-11-19_final
2019-11-19 10:36:08	ga_s2am_ard_3-2-1_53HNE_2019-11-19_final
2019-11-19 10:36:18	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 10:36:30	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 10:36:47	ga_s2am_ard_3-2-1_53HPB_2019-11-19_final
2019-11-19 10:36:51	ga_s2am_ard_3-2-1_53HNB_2019-11-19_final
2019-11-19 10:36:55	ga_s2am_ard_3-2-1_53HMB_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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