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
2019-10-03 10:44:26	ga_s2am_ard_3-2-1_53JMM_2019-10-03_final
2019-10-03 10:45:13	ga_s2am_ard_3-2-1_53JLJ_2019-10-03_final
2019-10-06 10:54:35	ga_s2am_ard_3-2-1_52JFS_2019-10-06_final
2019-10-06 10:54:50	ga_s2am_ard_3-2-1_53JKL_2019-10-06_final
2019-10-06 10:55:01	ga_s2am_ard_3-2-1_52JGQ_2019-10-06_final
2019-10-09 11:05:15	ga_s2am_ard_3-2-1_52JFP_2019-10-09_final
2019-10-10 12:13:57	ga_s2am_ard_3-2-1_49KHR_2019-10-10_final
2019-10-10 12:14:10	ga_s2am_ard_3-2-1_50KKV_2019-10-10_final
2019-10-10 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-10-10_final
2019-10-13 10:44:42	ga_s2am_ard_3-2-1_53JML_2019-10-13_final
2019-10-13 10:44:51	ga_s2am_ard_3-2-1_53JKL_2019-10-13_final
2019-10-13 10:45:14	ga_s2am_ard_3-2-1_53JLJ_2019-10-13_final
2019-10-16 10:55:20	ga_s2am_ard_3-2-1_52JFP_2019-10-16_final
2019-10-17 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-10-17_final
2019-10-19 11:05:16	ga_s2am_ard_3-2-1_52JFP_2019-10-19_final
2019-10-20 12:14:22	ga_s2am_ard_3-2-1_50KKU_2019-10-20_final
2019-10-20 12:14:44	ga_s2am_ard_3-2-1_49JGN_2019-10-20_final
2019-10-23 10:44:27	ga_s2am_ard_3-2-1_53JMM_2019-10-23_final
2019-10-23 10:44:57	ga_s2am_ard_3-2-1_53JMK_2019-10-23_final
2019-10-26 10:54:29	ga_s2am_ard_3-2-1_52JHS_2019-10-26_final
2019-10-26 10:54:30	ga_s2am_ard_3-2-1_53JKM_2019-10-26_final
2019-10-26 10:54:44	ga_s2am_ard_3-2-1_53JKL_2019-10-26_final
2019-10-26 10:55:02	ga_s2am_ard_3-2-1_52JGQ_2019-10-26_final
2019-10-27 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-10-27_final
2019-10-29 11:04:32	ga_s2am_ard_3-2-1_52JFS_2019-10-29_final
2019-10-30 12:13:57	ga_s2am_ard_3-2-1_50KKA_2019-10-30_final
2019-10-30 12:14:11	ga_s2am_ard_3-2-1_50KKV_2019-10-30_final
2019-11-03 11:55:05	ga_s2am_ard_3-2-1_50JPR_2019-11-03_final
2019-11-03 11:55:38	ga_s2am_ard_3-2-1_50JNP_2019-11-03_final
2019-11-10 10:05:54	ga_s2am_ard_3-2-1_54HYK_2019-11-10_final
2019-11-10 10:06:41	ga_s2am_ard_3-2-1_54HXG_2019-11-10_final
2019-11-13 10:16:41	ga_s2am_ard_3-2-1_54HWG_2019-11-13_final
2019-11-20 11:45:47	ga_s2am_ard_3-2-1_50JQN_2019-11-20_final
2019-11-23 10:15:37	ga_s2am_ard_3-2-1_54JXL_2019-11-23_final
2019-11-23 10:16:39	ga_s2am_ard_3-2-1_54HWG_2019-11-23_final
2019-11-30 10:06:42	ga_s2am_ard_3-2-1_54HWG_2019-11-30_final
2019-12-03 10:14:04	ga_s2am_ard_3-2-1_54JVT_2019-12-03_final
2019-12-03 10:14:41	ga_s2am_ard_3-2-1_54JWQ_2019-12-03_final
2019-12-03 10:14:59	ga_s2am_ard_3-2-1_54JVP_2019-12-03_final
2019-12-03 11:56:06	ga_s2am_ard_3-2-1_50JMM_2019-12-03_final
2019-12-03 11:56:16	ga_s2am_ard_3-2-1_50JNL_2019-12-03_final
2019-12-03 11:56:20	ga_s2am_ard_3-2-1_50JML_2019-12-03_final
2019-12-03 11:56:24	ga_s2am_ard_3-2-1_50JLL_2019-12-03_final
2019-12-03 11:56:38	ga_s2am_ard_3-2-1_50HLK_2019-12-03_final
2019-12-06 10:24:29	ga_s2am_ard_3-2-1_54JWQ_2019-12-06_final
2019-12-06 10:24:54	ga_s2am_ard_3-2-1_54JVP_2019-12-06_final
2019-12-07 11:32:44	ga_s2am_ard_3-2-1_51KVV_2019-12-07_final
2019-12-07 11:36:02	ga_s2am_ard_3-2-1_50JQM_2019-12-07_final
2019-12-10 10:04:51	ga_s2am_ard_3-2-1_54JYP_2019-12-10_final
2019-12-10 11:42:39	ga_s2am_ard_3-2-1_51KVV_2019-12-10_final
2019-12-10 11:46:09	ga_s2am_ard_3-2-1_50JMM_2019-12-10_final
2019-12-10 11:46:16	ga_s2am_ard_3-2-1_50JPL_2019-12-10_final
2019-12-10 11:46:26	ga_s2am_ard_3-2-1_50HQK_2019-12-10_final
2019-12-10 11:46:40	ga_s2am_ard_3-2-1_50HQJ_2019-12-10_final
2019-12-10 11:47:03	ga_s2am_ard_3-2-1_50HNH_2019-12-10_final
2019-12-10 11:47:11	ga_s2am_ard_3-2-1_50HLH_2019-12-10_final
2019-12-11 11:10:39	ga_s2am_ard_3-2-1_52LGM_2019-12-11_final
2019-12-13 10:14:43	ga_s2am_ard_3-2-1_54JYP_2019-12-13_final
2019-12-13 10:14:53	ga_s2am_ard_3-2-1_54JWP_2019-12-13_final
2019-12-13 10:15:07	ga_s2am_ard_3-2-1_54JWN_2019-12-13_final
2019-12-13 11:56:07	ga_s2am_ard_3-2-1_50JLM_2019-12-13_final
2019-12-13 11:56:21	ga_s2am_ard_3-2-1_50JLL_2019-12-13_final
2019-12-13 11:56:36	ga_s2am_ard_3-2-1_50HLK_2019-12-13_final
2019-12-13 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2019-12-13_final
2019-12-17 11:32:57	ga_s2am_ard_3-2-1_51KVU_2019-12-17_final
2019-12-17 11:36:05	ga_s2am_ard_3-2-1_51JVF_2019-12-17_final
2019-12-17 11:36:28	ga_s2am_ard_3-2-1_50HQK_2019-12-17_final
2019-12-17 11:37:01	ga_s2am_ard_3-2-1_50HPH_2019-12-17_final
2019-12-20 10:04:33	ga_s2am_ard_3-2-1_54JYQ_2019-12-20_final
2019-12-20 10:04:48	ga_s2am_ard_3-2-1_54JYP_2019-12-20_final
2019-12-20 11:45:51	ga_s2am_ard_3-2-1_51JTG_2019-12-20_final
2019-12-20 11:46:07	ga_s2am_ard_3-2-1_50JMM_2019-12-20_final
2019-12-20 11:46:20	ga_s2am_ard_3-2-1_50JML_2019-12-20_final
2019-12-20 11:47:00	ga_s2am_ard_3-2-1_50HNH_2019-12-20_final
2019-12-20 11:47:08	ga_s2am_ard_3-2-1_50HLH_2019-12-20_final
2019-12-21 11:10:52	ga_s2am_ard_3-2-1_52LGL_2019-12-21_final
2019-12-21 11:16:06	ga_s2am_ard_3-2-1_51JXF_2019-12-21_final
2019-12-21 11:16:25	ga_s2am_ard_3-2-1_51HWE_2019-12-21_final
2019-12-23 10:14:00	ga_s2am_ard_3-2-1_54JVT_2019-12-23_final
2019-12-23 10:14:37	ga_s2am_ard_3-2-1_54JWQ_2019-12-23_final
2019-12-23 10:15:06	ga_s2am_ard_3-2-1_54JWN_2019-12-23_final
2019-12-23 11:56:05	ga_s2am_ard_3-2-1_50JLM_2019-12-23_final
2019-12-23 11:56:16	ga_s2am_ard_3-2-1_50JML_2019-12-23_final
2019-12-23 11:56:20	ga_s2am_ard_3-2-1_50JLL_2019-12-23_final
2019-12-23 11:56:45	ga_s2am_ard_3-2-1_50HMJ_2019-12-23_final
2019-12-26 10:24:07	ga_s2am_ard_3-2-1_54JVS_2019-12-26_final
2019-12-27 11:32:41	ga_s2am_ard_3-2-1_51KVV_2019-12-27_final
2019-12-27 11:36:00	ga_s2am_ard_3-2-1_50JQM_2019-12-27_final
2019-12-27 11:36:28	ga_s2am_ard_3-2-1_50HQK_2019-12-27_final
2019-12-27 11:36:43	ga_s2am_ard_3-2-1_50HQJ_2019-12-27_final
2019-12-27 11:36:59	ga_s2am_ard_3-2-1_50HPH_2019-12-27_final
2019-12-27 11:37:05	ga_s2am_ard_3-2-1_50HPH_2019-12-27_final
2019-12-28 11:00:43	ga_s2am_ard_3-2-1_52LGM_2019-12-28_final
2019-12-30 10:04:38	ga_s2am_ard_3-2-1_54JXQ_2019-12-30_final
2019-12-30 10:04:49	ga_s2am_ard_3-2-1_54JYP_2019-12-30_final
2019-12-30 10:04:52	ga_s2am_ard_3-2-1_54JXP_2019-12-30_final
2019-12-30 11:46:02	ga_s2am_ard_3-2-1_51JTF_2019-12-30_final
2019-12-30 11:46:24	ga_s2am_ard_3-2-1_50HQK_2019-12-30_final
2019-12-30 11:46:38	ga_s2am_ard_3-2-1_50HQJ_2019-12-30_final
2019-12-30 11:47:09	ga_s2am_ard_3-2-1_50HLH_2019-12-30_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