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
2022-03-15 12:05:16	ga_s2am_ard_3-2-1_50JKR_2022-03-15_final
2022-03-15 12:05:19	ga_s2am_ard_3-2-1_49JGL_2022-03-15_final
2022-03-15 12:05:39	ga_s2am_ard_3-2-1_50JKP_2022-03-15_final
2022-03-15 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2022-03-15_final
2022-03-15 12:05:46	ga_s2am_ard_3-2-1_50JKP_2022-03-15_final
2022-03-15 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2022-03-15_final
2022-03-15 12:05:59	ga_s2am_ard_3-2-1_50JKN_2022-03-15_final
2022-03-15 12:06:02	ga_s2am_ard_3-2-1_49JGH_2022-03-15_final.stac-item
2022-03-15 12:06:14	ga_s2am_ard_3-2-1_50JKM_2022-03-15_final
2022-03-16 09:51:16	ga_s2am_ard_3-2-1_55LHC_2022-03-16_final.stac-item
2022-03-16 09:51:19	ga_s2am_ard_3-2-1_55LGC_2022-03-16_final
2022-03-16 09:51:29	ga_s2am_ard_3-2-1_56KKG_2022-03-16_final.stac-item
2022-03-16 09:51:30	ga_s2am_ard_3-2-1_55KHB_2022-03-16_final.stac-item
2022-03-16 09:51:34	ga_s2am_ard_3-2-1_55KGB_2022-03-16_final
2022-03-16 09:52:17	ga_s2am_ard_3-2-1_55KGU_2022-03-16_final
2022-03-16 09:52:24	ga_s2am_ard_3-2-1_55KEU_2022-03-16_final
2022-03-16 09:52:32	ga_s2am_ard_3-2-1_55KGT_2022-03-16_final
2022-03-16 09:53:08	ga_s2am_ard_3-2-1_55KER_2022-03-16_final
2022-03-16 09:53:11	ga_s2am_ard_3-2-1_55KDR_2022-03-16_final
2022-03-16 09:53:19	ga_s2am_ard_3-2-1_55KFQ_2022-03-16_final
2022-03-16 09:53:33	ga_s2am_ard_3-2-1_55KFP_2022-03-16_final
2022-03-16 09:53:47	ga_s2am_ard_3-2-1_55JFN_2022-03-16_final
2022-03-16 09:53:51	ga_s2am_ard_3-2-1_55JEN_2022-03-16_final
2022-03-16 09:53:55	ga_s2am_ard_3-2-1_55JDN_2022-03-16_final
2022-03-16 09:54:02	ga_s2am_ard_3-2-1_55JFM_2022-03-16_final
2022-03-16 09:54:13	ga_s2am_ard_3-2-1_55JCM_2022-03-16_final
2022-03-16 09:54:17	ga_s2am_ard_3-2-1_55JFL_2022-03-16_final
2022-03-16 09:54:20	ga_s2am_ard_3-2-1_55JEL_2022-03-16_final
2022-03-16 09:54:24	ga_s2am_ard_3-2-1_55JDL_2022-03-16_final
2022-03-16 09:54:27	ga_s2am_ard_3-2-1_55JCL_2022-03-16_final
2022-03-16 09:54:35	ga_s2am_ard_3-2-1_55JEK_2022-03-16_final
2022-03-16 09:54:38	ga_s2am_ard_3-2-1_55JDK_2022-03-16_final
2022-03-16 09:54:49	ga_s2am_ard_3-2-1_55JEJ_2022-03-16_final
2022-03-16 09:54:53	ga_s2am_ard_3-2-1_55JDJ_2022-03-16_final
2022-03-16 09:54:56	ga_s2am_ard_3-2-1_55JCJ_2022-03-16_final
2022-03-16 09:55:03	ga_s2am_ard_3-2-1_55JEH_2022-03-16_final
2022-03-16 09:55:07	ga_s2am_ard_3-2-1_55JDH_2022-03-16_final
2022-03-16 09:55:18	ga_s2am_ard_3-2-1_55JEG_2022-03-16_final
2022-03-16 09:55:22	ga_s2am_ard_3-2-1_55JDG_2022-03-16_final
2022-03-16 09:55:28	ga_s2am_ard_3-2-1_55JBG_2022-03-16_final
2022-03-16 09:55:33	ga_s2am_ard_3-2-1_55JEF_2022-03-16_final
2022-03-16 09:55:36	ga_s2am_ard_3-2-1_55JDF_2022-03-16_final
2022-03-16 09:56:12	ga_s2am_ard_3-2-1_55HBD_2022-03-16_final
2022-03-16 09:56:14	ga_s2am_ard_3-2-1_54HYJ_2022-03-16_final
2022-03-16 09:56:23	ga_s2am_ard_3-2-1_55HCC_2022-03-16_final
2022-03-16 09:56:26	ga_s2am_ard_3-2-1_55HBC_2022-03-16_final
2022-03-16 09:56:28	ga_s2am_ard_3-2-1_54HYH_2022-03-16_final
2022-03-16 09:56:43	ga_s2am_ard_3-2-1_54HYG_2022-03-16_final
2022-03-16 09:56:49	ga_s2am_ard_3-2-1_55HDA_2022-03-16_final
2022-03-16 09:57:02	ga_s2am_ard_3-2-1_55HDV_2022-03-16_final
2022-03-16 09:57:07	ga_s2am_ard_3-2-1_55HCV_2022-03-16_final
2022-03-16 09:57:10	ga_s2am_ard_3-2-1_55HBV_2022-03-16_final
2022-03-16 09:57:12	ga_s2am_ard_3-2-1_54HYE_2022-03-16_final
2022-03-16 09:57:15	ga_s2am_ard_3-2-1_54HXE_2022-03-16_final
2022-03-16 09:57:51	ga_s2am_ard_3-2-1_55HCS_2022-03-16_final
2022-03-16 09:57:54	ga_s2am_ard_3-2-1_55HBS_2022-03-16_final
2022-03-16 09:57:55	ga_s2am_ard_3-2-1_54HYB_2022-03-16_final
2022-03-16 09:58:27	ga_s2am_ard_3-2-1_55GCP_2022-03-16_final
2022-03-16 11:31:52	ga_s2am_ard_3-2-1_51LZC_2022-03-16_final
2022-03-16 11:31:57	ga_s2am_ard_3-2-1_51LYC_2022-03-16_final
2022-03-16 11:32:11	ga_s2am_ard_3-2-1_51KYB_2022-03-16_final
2022-03-16 11:32:15	ga_s2am_ard_3-2-1_51KXB_2022-03-16_final
2022-03-16 11:32:18	ga_s2am_ard_3-2-1_51KWB_2022-03-16_final
2022-03-16 11:32:23	ga_s2am_ard_3-2-1_51KVB_2022-03-16_final
2022-03-16 11:32:29	ga_s2am_ard_3-2-1_51KXA_2022-03-16_final
2022-03-16 11:32:41	ga_s2am_ard_3-2-1_51KYV_2022-03-16_final
2022-03-16 11:32:44	ga_s2am_ard_3-2-1_51KXV_2022-03-16_final
2022-03-16 11:32:54	ga_s2am_ard_3-2-1_51KYU_2022-03-16_final
2022-03-16 11:33:04	ga_s2am_ard_3-2-1_51KYT_2022-03-16_final
2022-03-16 11:33:07	ga_s2am_ard_3-2-1_51KYT_2022-03-16_final
2022-03-16 11:33:56	ga_s2am_ard_3-2-1_51KXQ_2022-03-16_final
2022-03-16 11:34:07	ga_s2am_ard_3-2-1_51KUQ_2022-03-16_final
2022-03-16 11:34:09	ga_s2am_ard_3-2-1_51KXP_2022-03-16_final
2022-03-16 11:34:19	ga_s2am_ard_3-2-1_51JXN_2022-03-16_final
2022-03-16 11:34:21	ga_s2am_ard_3-2-1_51KUP_2022-03-16_final
2022-03-16 11:34:29	ga_s2am_ard_3-2-1_51JWN_2022-03-16_final
2022-03-16 11:34:33	ga_s2am_ard_3-2-1_51JVN_2022-03-16_final
2022-03-16 11:34:50	ga_s2am_ard_3-2-1_51JUM_2022-03-16_final
2022-03-16 11:34:58	ga_s2am_ard_3-2-1_51JWL_2022-03-16_final
2022-03-16 11:35:02	ga_s2am_ard_3-2-1_51JVL_2022-03-16_final
2022-03-16 11:35:05	ga_s2am_ard_3-2-1_51JUL_2022-03-16_final
2022-03-16 11:35:08	ga_s2am_ard_3-2-1_51JTL_2022-03-16_final
2022-03-16 11:35:12	ga_s2am_ard_3-2-1_51JWK_2022-03-16_final
2022-03-16 11:35:16	ga_s2am_ard_3-2-1_51JVK_2022-03-16_final
2022-03-16 11:35:23	ga_s2am_ard_3-2-1_51JWJ_2022-03-16_final
2022-03-16 11:35:30	ga_s2am_ard_3-2-1_51JVJ_2022-03-16_final
2022-03-16 11:35:34	ga_s2am_ard_3-2-1_51JUJ_2022-03-16_final
2022-03-16 11:35:37	ga_s2am_ard_3-2-1_51JTJ_2022-03-16_final
2022-03-16 11:35:41	ga_s2am_ard_3-2-1_50JQP_2022-03-16_final
2022-03-16 11:35:45	ga_s2am_ard_3-2-1_51JVH_2022-03-16_final
2022-03-16 11:35:52	ga_s2am_ard_3-2-1_51JTH_2022-03-16_final
2022-03-16 11:35:54	ga_s2am_ard_3-2-1_50JQN_2022-03-16_final
2022-03-16 11:36:00	ga_s2am_ard_3-2-1_51JVG_2022-03-16_final
2022-03-16 11:36:06	ga_s2am_ard_3-2-1_51JTG_2022-03-16_final
2022-03-16 11:36:14	ga_s2am_ard_3-2-1_51JVF_2022-03-16_final
2022-03-16 11:36:50	ga_s2am_ard_3-2-1_51HTD_2022-03-16_final
2022-03-16 11:36:52	ga_s2am_ard_3-2-1_50HQJ_2022-03-16_final
2022-03-16 11:37:05	ga_s2am_ard_3-2-1_51HTC_2022-03-16_final
2022-03-16 11:37:07	ga_s2am_ard_3-2-1_50HQH_2022-03-16_final
2022-03-16 11:37:10	ga_s2am_ard_3-2-1_50HPH_2022-03-16_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