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
2022-06-01 11:24:52	ga_s2am_ard_3-2-1_51JWM_2022-06-01_final
2022-06-01 11:25:03	ga_s2am_ard_3-2-1_51JXL_2022-06-01_final
2022-06-03 12:04:07	ga_s2am_ard_3-2-1_49KHR_2022-06-03_final
2022-06-03 12:05:31	ga_s2am_ard_3-2-1_50JLQ_2022-06-03_final
2022-06-06 12:13:50	ga_s2am_ard_3-2-1_50KKB_2022-06-06_final
2022-06-06 12:14:29	ga_s2am_ard_3-2-1_49KHP_2022-06-06_final
2022-06-06 12:14:49	ga_s2am_ard_3-2-1_49JGN_2022-06-06_final
2022-06-07 11:44:57	ga_s2am_ard_3-2-1_50JQS_2022-06-07_final
2022-06-07 11:44:59	ga_s2am_ard_3-2-1_51JUL_2022-06-07_final
2022-06-07 11:46:02	ga_s2am_ard_3-2-1_50JNN_2022-06-07_final
2022-06-10 11:56:02	ga_s2am_ard_3-2-1_50JMN_2022-06-10_final
2022-06-11 11:24:54	ga_s2am_ard_3-2-1_51JWM_2022-06-11_final
2022-06-11 11:25:05	ga_s2am_ard_3-2-1_51JXL_2022-06-11_final
2022-06-13 12:04:37	ga_s2am_ard_3-2-1_49KHP_2022-06-13_final
2022-06-13 12:04:44	ga_s2am_ard_3-2-1_50JKT_2022-06-13_final
2022-06-13 12:04:52	ga_s2am_ard_3-2-1_49JHN_2022-06-13_final
2022-06-13 12:05:18	ga_s2am_ard_3-2-1_50JLR_2022-06-13_final
2022-06-14 11:35:11	ga_s2am_ard_3-2-1_51JUL_2022-06-14_final
2022-06-14 11:35:37	ga_s2am_ard_3-2-1_51JVJ_2022-06-14_final
2022-06-16 12:13:50	ga_s2am_ard_3-2-1_50KKB_2022-06-16_final
2022-06-16 12:14:05	ga_s2am_ard_3-2-1_49KHR_2022-06-16_final
2022-06-16 12:14:19	ga_s2am_ard_3-2-1_49KHQ_2022-06-16_final
2022-06-17 11:46:05	ga_s2am_ard_3-2-1_50JNN_2022-06-17_final
2022-06-20 11:55:39	ga_s2am_ard_3-2-1_50JLQ_2022-06-20_final
2022-06-20 11:56:01	ga_s2am_ard_3-2-1_50JNN_2022-06-20_final
2022-06-21 11:25:28	ga_s2am_ard_3-2-1_51JVK_2022-06-21_final
2022-06-23 12:04:11	ga_s2am_ard_3-2-1_49KHR_2022-06-23_final
2022-06-23 12:04:45	ga_s2am_ard_3-2-1_49JHN_2022-06-23_final
2022-06-23 12:04:55	ga_s2am_ard_3-2-1_49JHN_2022-06-23_final
2022-06-24 11:34:52	ga_s2am_ard_3-2-1_51JWM_2022-06-24_final
2022-06-24 11:35:39	ga_s2am_ard_3-2-1_51JVJ_2022-06-24_final
2022-06-26 12:13:52	ga_s2am_ard_3-2-1_50KKB_2022-06-26_final
2022-06-26 12:14:33	ga_s2am_ard_3-2-1_49KHP_2022-06-26_final
2022-06-26 12:14:54	ga_s2am_ard_3-2-1_49JGN_2022-06-26_final
2022-06-26 12:14:58	ga_s2am_ard_3-2-1_49JFN_2022-06-26_final
2022-06-27 11:44:53	ga_s2am_ard_3-2-1_51JUM_2022-06-27_final
2022-06-27 11:44:58	ga_s2am_ard_3-2-1_51JTM_2022-06-27_final
2022-06-27 11:46:03	ga_s2am_ard_3-2-1_50JPN_2022-06-27_final
2022-06-27 11:46:07	ga_s2am_ard_3-2-1_50JNN_2022-06-27_final
2022-06-30 11:55:40	ga_s2am_ard_3-2-1_50JLQ_2022-06-30_final
2022-06-30 11:56:02	ga_s2am_ard_3-2-1_50JNN_2022-06-30_final
2022-07-01 11:26:51	ga_s2am_ard_3-2-1_51HWD_2022-07-01_final
2022-07-04 11:34:53	ga_s2am_ard_3-2-1_51JWM_2022-07-04_final
2022-07-04 11:36:16	ga_s2am_ard_3-2-1_51JTG_2022-07-04_final
2022-07-04 11:36:59	ga_s2am_ard_3-2-1_51HTD_2022-07-04_final
2022-07-04 11:37:01	ga_s2am_ard_3-2-1_50HQJ_2022-07-04_final
2022-07-04 11:37:14	ga_s2am_ard_3-2-1_51HTC_2022-07-04_final
2022-07-04 11:37:16	ga_s2am_ard_3-2-1_50HQH_2022-07-04_final
2022-07-07 11:43:22	ga_s2am_ard_3-2-1_51KTT_2022-07-07_final
2022-07-07 11:43:23	ga_s2am_ard_3-2-1_50KRC_2022-07-07_final
2022-07-07 11:46:10	ga_s2am_ard_3-2-1_51JTG_2022-07-07_final
2022-07-07 11:46:18	ga_s2am_ard_3-2-1_50JPM_2022-07-07_final
2022-07-07 11:46:21	ga_s2am_ard_3-2-1_50JNM_2022-07-07_final
2022-07-07 11:46:28	ga_s2am_ard_3-2-1_50JQL_2022-07-07_final
2022-07-07 11:46:32	ga_s2am_ard_3-2-1_50JPL_2022-07-07_final
2022-07-07 11:46:43	ga_s2am_ard_3-2-1_50HQK_2022-07-07_final
2022-07-07 11:47:06	ga_s2am_ard_3-2-1_50HQH_2022-07-07_final
2022-07-07 11:47:08	ga_s2am_ard_3-2-1_50HMJ_2022-07-07_final
2022-07-07 11:47:19	ga_s2am_ard_3-2-1_50HNH_2022-07-07_final
2022-07-07 11:47:27	ga_s2am_ard_3-2-1_50HLH_2022-07-07_final
2022-07-08 11:16:43	ga_s2am_ard_3-2-1_51HWE_2022-07-08_final
2022-07-10 11:56:17	ga_s2am_ard_3-2-1_50JNM_2022-07-10_final
2022-07-10 11:56:49	ga_s2am_ard_3-2-1_50HMK_2022-07-10_final
2022-07-10 11:56:53	ga_s2am_ard_3-2-1_50HLK_2022-07-10_final
2022-07-10 11:57:08	ga_s2am_ard_3-2-1_50HLJ_2022-07-10_final
2022-07-11 11:26:51	ga_s2am_ard_3-2-1_51HWD_2022-07-11_final
2022-07-14 11:36:15	ga_s2am_ard_3-2-1_51JTG_2022-07-14_final
2022-07-14 11:36:39	ga_s2am_ard_3-2-1_50JPL_2022-07-14_final
2022-07-14 11:36:59	ga_s2am_ard_3-2-1_51HTD_2022-07-14_final
2022-07-14 11:37:01	ga_s2am_ard_3-2-1_50HQJ_2022-07-14_final
2022-07-14 11:37:19	ga_s2am_ard_3-2-1_50HPH_2022-07-14_final
2022-07-17 11:46:09	ga_s2am_ard_3-2-1_51JTG_2022-07-17_final
2022-07-17 11:46:17	ga_s2am_ard_3-2-1_50JPM_2022-07-17_final
2022-07-17 11:46:20	ga_s2am_ard_3-2-1_50JNM_2022-07-17_final
2022-07-17 11:46:27	ga_s2am_ard_3-2-1_50JQL_2022-07-17_final
2022-07-17 11:46:31	ga_s2am_ard_3-2-1_50JPL_2022-07-17_final
2022-07-17 11:46:42	ga_s2am_ard_3-2-1_50HQK_2022-07-17_final
2022-07-17 11:46:53	ga_s2am_ard_3-2-1_50HMK_2022-07-17_final
2022-07-17 11:47:14	ga_s2am_ard_3-2-1_50HPH_2022-07-17_final
2022-07-17 11:47:19	ga_s2am_ard_3-2-1_50HNH_2022-07-17_final
2022-07-17 11:47:26	ga_s2am_ard_3-2-1_50HLH_2022-07-17_final
2022-07-20 11:56:16	ga_s2am_ard_3-2-1_50JNM_2022-07-20_final
2022-07-20 11:56:48	ga_s2am_ard_3-2-1_50HMK_2022-07-20_final
2022-07-20 11:56:52	ga_s2am_ard_3-2-1_50HLK_2022-07-20_final
2022-07-21 11:25:28	ga_s2am_ard_3-2-1_51JVK_2022-07-21_final
2022-07-21 11:26:49	ga_s2am_ard_3-2-1_51HWD_2022-07-21_final
2022-07-24 11:34:57	ga_s2am_ard_3-2-1_51JUM_2022-07-24_final
2022-07-24 11:36:37	ga_s2am_ard_3-2-1_50JPL_2022-07-24_final
2022-07-24 11:36:39	ga_s2am_ard_3-2-1_51HUE_2022-07-24_final
2022-07-24 11:36:44	ga_s2am_ard_3-2-1_50HQK_2022-07-24_final
2022-07-24 11:36:57	ga_s2am_ard_3-2-1_51HTD_2022-07-24_final
2022-07-24 11:36:59	ga_s2am_ard_3-2-1_50HQJ_2022-07-24_final
2022-07-27 11:46:18	ga_s2am_ard_3-2-1_50JNM_2022-07-27_final
2022-07-27 11:46:29	ga_s2am_ard_3-2-1_50JPL_2022-07-27_final
2022-07-27 11:46:40	ga_s2am_ard_3-2-1_50HQK_2022-07-27_final
2022-07-27 11:47:16	ga_s2am_ard_3-2-1_50HNH_2022-07-27_final
2022-07-30 11:56:46	ga_s2am_ard_3-2-1_50HMK_2022-07-30_final
2022-07-30 11:56:50	ga_s2am_ard_3-2-1_50HLK_2022-07-30_final
2022-07-30 11:57:19	ga_s2am_ard_3-2-1_50HLH_2022-07-30_final
2022-07-31 11:26:42	ga_s2am_ard_3-2-1_51HUE_2022-07-31_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

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