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
2022-07-13 12:05:10	ga_s2am_ard_3-2-1_50JKS_2022-07-13_final
2022-07-13 12:05:13	ga_s2am_ard_3-2-1_49JGM_2022-07-13_final
2022-07-13 12:05:35	ga_s2am_ard_3-2-1_50JLQ_2022-07-13_final
2022-07-13 12:05:39	ga_s2am_ard_3-2-1_50JKQ_2022-07-13_final
2022-07-13 12:05:42	ga_s2am_ard_3-2-1_49JGK_2022-07-13_final
2022-07-13 12:06:04	ga_s2am_ard_3-2-1_50JLN_2022-07-13_final
2022-07-13 12:06:11	ga_s2am_ard_3-2-1_49JGH_2022-07-13_final.stac-item
2022-07-13 12:06:16	ga_s2am_ard_3-2-1_50JLM_2022-07-13_final
2022-07-14 09:51:52	ga_s2am_ard_3-2-1_56KKF_2022-07-14_final
2022-07-14 09:52:58	ga_s2am_ard_3-2-1_55KFS_2022-07-14_final
2022-07-14 09:53:02	ga_s2am_ard_3-2-1_55KES_2022-07-14_final
2022-07-14 09:53:08	ga_s2am_ard_3-2-1_55KDS_2022-07-14_final
2022-07-14 09:53:09	ga_s2am_ard_3-2-1_55KGR_2022-07-14_final
2022-07-14 09:53:13	ga_s2am_ard_3-2-1_55KFR_2022-07-14_final
2022-07-14 09:53:16	ga_s2am_ard_3-2-1_55KER_2022-07-14_final
2022-07-14 09:53:20	ga_s2am_ard_3-2-1_55KDR_2022-07-14_final
2022-07-14 09:53:24	ga_s2am_ard_3-2-1_55KGQ_2022-07-14_final
2022-07-14 09:53:27	ga_s2am_ard_3-2-1_55KFQ_2022-07-14_final
2022-07-14 09:53:31	ga_s2am_ard_3-2-1_55KEQ_2022-07-14_final
2022-07-14 09:53:34	ga_s2am_ard_3-2-1_55KDQ_2022-07-14_final
2022-07-14 09:54:15	ga_s2am_ard_3-2-1_55JEM_2022-07-14_final
2022-07-14 09:54:18	ga_s2am_ard_3-2-1_55JDM_2022-07-14_final
2022-07-14 09:54:58	ga_s2am_ard_3-2-1_55JEJ_2022-07-14_final
2022-07-14 09:55:01	ga_s2am_ard_3-2-1_55JDJ_2022-07-14_final
2022-07-14 09:55:03	ga_s2am_ard_3-2-1_55JFH_2022-07-14_final
2022-07-14 09:55:19	ga_s2am_ard_3-2-1_55JCH_2022-07-14_final
2022-07-14 09:55:34	ga_s2am_ard_3-2-1_55JCG_2022-07-14_final
2022-07-14 09:55:51	ga_s2am_ard_3-2-1_55JBF_2022-07-14_final
2022-07-14 09:55:55	ga_s2am_ard_3-2-1_55HEE_2022-07-14_final
2022-07-14 09:55:59	ga_s2am_ard_3-2-1_55HDE_2022-07-14_final
2022-07-14 09:56:03	ga_s2am_ard_3-2-1_55HCE_2022-07-14_final
2022-07-14 09:56:06	ga_s2am_ard_3-2-1_55HBE_2022-07-14_final
2022-07-14 09:56:06	ga_s2am_ard_3-2-1_55HED_2022-07-14_final
2022-07-14 09:56:09	ga_s2am_ard_3-2-1_54HYK_2022-07-14_final
2022-07-14 09:56:14	ga_s2am_ard_3-2-1_55HDD_2022-07-14_final
2022-07-14 09:56:18	ga_s2am_ard_3-2-1_55HCD_2022-07-14_final
2022-07-14 09:56:32	ga_s2am_ard_3-2-1_55HCC_2022-07-14_final
2022-07-14 09:56:35	ga_s2am_ard_3-2-1_55HBC_2022-07-14_final
2022-07-14 09:56:37	ga_s2am_ard_3-2-1_54HYH_2022-07-14_final
2022-07-14 09:56:43	ga_s2am_ard_3-2-1_55HDB_2022-07-14_final
2022-07-14 09:56:47	ga_s2am_ard_3-2-1_55HCB_2022-07-14_final
2022-07-14 09:56:50	ga_s2am_ard_3-2-1_55HBB_2022-07-14_final
2022-07-14 09:56:52	ga_s2am_ard_3-2-1_54HYG_2022-07-14_final
2022-07-14 09:56:58	ga_s2am_ard_3-2-1_55HDA_2022-07-14_final
2022-07-14 09:56:58	ga_s2am_ard_3-2-1_54HXG_2022-07-14_final
2022-07-14 09:57:21	ga_s2am_ard_3-2-1_55HDU_2022-07-14_final
2022-07-14 09:57:25	ga_s2am_ard_3-2-1_55HCU_2022-07-14_final
2022-07-14 09:57:27	ga_s2am_ard_3-2-1_55HBU_2022-07-14_final
2022-07-14 09:57:28	ga_s2am_ard_3-2-1_54HYD_2022-07-14_final
2022-07-14 09:57:32	ga_s2am_ard_3-2-1_55HCU_2022-07-14_final
2022-07-14 09:57:34	ga_s2am_ard_3-2-1_55HBU_2022-07-14_final
2022-07-14 09:57:35	ga_s2am_ard_3-2-1_54HYD_2022-07-14_final
2022-07-14 09:57:39	ga_s2am_ard_3-2-1_54HXD_2022-07-14_final
2022-07-14 09:57:45	ga_s2am_ard_3-2-1_55HCT_2022-07-14_final
2022-07-14 09:57:48	ga_s2am_ard_3-2-1_55HBT_2022-07-14_final
2022-07-14 09:57:49	ga_s2am_ard_3-2-1_54HYC_2022-07-14_final
2022-07-14 09:57:53	ga_s2am_ard_3-2-1_54HXC_2022-07-14_final
2022-07-14 09:57:58	ga_s2am_ard_3-2-1_54HWC_2022-07-14_final
2022-07-14 09:58:13	ga_s2am_ard_3-2-1_55GCR_2022-07-14_final
2022-07-14 11:31:55	ga_s2am_ard_3-2-1_51LXD_2022-07-14_final
2022-07-14 11:32:35	ga_s2am_ard_3-2-1_51KYA_2022-07-14_final
2022-07-14 11:32:49	ga_s2am_ard_3-2-1_51KYV_2022-07-14_final
2022-07-14 11:33:36	ga_s2am_ard_3-2-1_51KXS_2022-07-14_final
2022-07-14 11:33:44	ga_s2am_ard_3-2-1_51KUS_2022-07-14_final
2022-07-14 11:33:46	ga_s2am_ard_3-2-1_51KXR_2022-07-14_final
2022-07-14 11:33:47	ga_s2am_ard_3-2-1_51KWR_2022-07-14_final
2022-07-14 11:33:50	ga_s2am_ard_3-2-1_51KUS_2022-07-14_final
2022-07-14 11:33:52	ga_s2am_ard_3-2-1_51KXR_2022-07-14_final
2022-07-14 11:33:55	ga_s2am_ard_3-2-1_51KWR_2022-07-14_final
2022-07-14 11:33:58	ga_s2am_ard_3-2-1_51KVR_2022-07-14_final
2022-07-14 11:34:00	ga_s2am_ard_3-2-1_51KUR_2022-07-14_final
2022-07-14 11:34:05	ga_s2am_ard_3-2-1_51KXQ_2022-07-14_final
2022-07-14 11:34:09	ga_s2am_ard_3-2-1_51KWQ_2022-07-14_final
2022-07-14 11:34:12	ga_s2am_ard_3-2-1_51KVQ_2022-07-14_final
2022-07-14 11:34:15	ga_s2am_ard_3-2-1_51KUQ_2022-07-14_final
2022-07-14 11:34:18	ga_s2am_ard_3-2-1_51KXP_2022-07-14_final
2022-07-14 11:34:30	ga_s2am_ard_3-2-1_51KUP_2022-07-14_final
2022-07-14 11:35:02	ga_s2am_ard_3-2-1_51JTM_2022-07-14_final
2022-07-14 11:35:10	ga_s2am_ard_3-2-1_51JVL_2022-07-14_final
2022-07-14 11:35:31	ga_s2am_ard_3-2-1_51JTK_2022-07-14_final
2022-07-14 11:35:31	ga_s2am_ard_3-2-1_51JWJ_2022-07-14_final
2022-07-14 11:35:39	ga_s2am_ard_3-2-1_51JVJ_2022-07-14_final
2022-07-14 11:35:57	ga_s2am_ard_3-2-1_51JUH_2022-07-14_final
2022-07-14 11:36:23	ga_s2am_ard_3-2-1_51JVF_2022-07-14_final
2022-07-14 11:36:30	ga_s2am_ard_3-2-1_51JTF_2022-07-14_final
2022-07-14 11:36:32	ga_s2am_ard_3-2-1_50JQL_2022-07-14_final
2022-07-14 11:36:44	ga_s2am_ard_3-2-1_51HTE_2022-07-14_final
2022-07-14 11:36:46	ga_s2am_ard_3-2-1_51HVD_2022-07-14_final
2022-07-14 11:36:46	ga_s2am_ard_3-2-1_50HQK_2022-07-14_final
2022-07-14 11:36:50	ga_s2am_ard_3-2-1_50HPK_2022-07-14_final
2022-07-14 11:36:55	ga_s2am_ard_3-2-1_51HUD_2022-07-14_final
2022-07-14 11:37:04	ga_s2am_ard_3-2-1_50HPJ_2022-07-14_final
2022-07-14 11:37:10	ga_s2am_ard_3-2-1_51HUC_2022-07-14_final
2022-07-14 11:37:13	ga_s2am_ard_3-2-1_51HTC_2022-07-14_final
2022-07-14 11:37:15	ga_s2am_ard_3-2-1_50HQH_2022-07-14_final
2022-07-14 11:37:19	ga_s2am_ard_3-2-1_50HPH_2022-07-14_final
2022-07-14 11:37:25	ga_s2am_ard_3-2-1_51HUB_2022-07-14_final.stac-item
2022-07-14 11:37:28	ga_s2am_ard_3-2-1_51HTB_2022-07-14_final.stac-item
2022-07-14 11:37:30	ga_s2am_ard_3-2-1_50HQG_2022-07-14_final.stac-item
2022-07-14 11:37:34	ga_s2am_ard_3-2-1_50HPG_2022-07-14_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

All years