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
2022-02-03 12:06:10	ga_s2am_ard_3-2-1_50JKM_2022-02-03_final
2022-02-10 11:56:13	ga_s2am_ard_3-2-1_50JKM_2022-02-10_final
2022-02-13 12:06:09	ga_s2am_ard_3-2-1_50JKM_2022-02-13_final
2022-02-20 11:56:16	ga_s2am_ard_3-2-1_50JKM_2022-02-20_final
2022-02-23 12:04:09	ga_s2am_ard_3-2-1_50KMV_2022-02-23_final
2022-02-23 12:06:12	ga_s2am_ard_3-2-1_50JKM_2022-02-23_final
2022-02-24 11:37:00	ga_s2am_ard_3-2-1_51HUC_2022-02-24_final
2022-03-02 11:55:16	ga_s2am_ard_3-2-1_50JLR_2022-03-02_final
2022-03-02 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2022-03-02_final
2022-03-02 11:55:42	ga_s2am_ard_3-2-1_50JMP_2022-03-02_final
2022-03-02 11:55:45	ga_s2am_ard_3-2-1_50JLP_2022-03-02_final
2022-03-02 11:55:53	ga_s2am_ard_3-2-1_50JNN_2022-03-02_final
2022-03-02 11:55:56	ga_s2am_ard_3-2-1_50JMN_2022-03-02_final
2022-03-02 11:56:00	ga_s2am_ard_3-2-1_50JLN_2022-03-02_final
2022-03-05 12:04:03	ga_s2am_ard_3-2-1_49KHR_2022-03-05_final
2022-03-05 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2022-03-05_final
2022-03-05 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2022-03-05_final
2022-03-05 12:04:35	ga_s2am_ard_3-2-1_49KGP_2022-03-05_final
2022-03-05 12:04:46	ga_s2am_ard_3-2-1_50JKT_2022-03-05_final
2022-03-05 12:04:50	ga_s2am_ard_3-2-1_49JGN_2022-03-05_final
2022-03-05 12:05:07	ga_s2am_ard_3-2-1_50JLR_2022-03-05_final
2022-03-05 12:05:13	ga_s2am_ard_3-2-1_50JLR_2022-03-05_final
2022-03-05 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2022-03-05_final
2022-03-05 12:05:41	ga_s2am_ard_3-2-1_50JLP_2022-03-05_final
2022-03-05 12:05:55	ga_s2am_ard_3-2-1_50JLN_2022-03-05_final
2022-03-06 11:34:40	ga_s2am_ard_3-2-1_50JRT_2022-03-06_final
2022-03-06 11:34:53	ga_s2am_ard_3-2-1_50JRS_2022-03-06_final
2022-03-06 11:35:54	ga_s2am_ard_3-2-1_50JQN_2022-03-06_final
2022-03-08 12:13:58	ga_s2am_ard_3-2-1_49KHR_2022-03-08_final
2022-03-08 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2022-03-08_final
2022-03-08 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2022-03-08_final
2022-03-08 12:14:31	ga_s2am_ard_3-2-1_49KGP_2022-03-08_final
2022-03-08 12:14:45	ga_s2am_ard_3-2-1_49JGN_2022-03-08_final
2022-03-09 11:43:37	ga_s2am_ard_3-2-1_50KRB_2022-03-09_final
2022-03-09 11:44:49	ga_s2am_ard_3-2-1_50JRS_2022-03-09_final
2022-03-09 11:45:50	ga_s2am_ard_3-2-1_50JQN_2022-03-09_final
2022-03-09 11:45:54	ga_s2am_ard_3-2-1_50JPN_2022-03-09_final
2022-03-09 11:45:58	ga_s2am_ard_3-2-1_50JNN_2022-03-09_final
2022-03-12 11:55:17	ga_s2am_ard_3-2-1_50JLR_2022-03-12_final
2022-03-12 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2022-03-12_final
2022-03-12 11:55:43	ga_s2am_ard_3-2-1_50JMP_2022-03-12_final
2022-03-12 11:55:46	ga_s2am_ard_3-2-1_50JLP_2022-03-12_final
2022-03-12 11:55:53	ga_s2am_ard_3-2-1_50JNN_2022-03-12_final
2022-03-12 11:55:57	ga_s2am_ard_3-2-1_50JMN_2022-03-12_final
2022-03-12 11:56:00	ga_s2am_ard_3-2-1_50JLN_2022-03-12_final
2022-03-15 12:04:03	ga_s2am_ard_3-2-1_49KHR_2022-03-15_final
2022-03-15 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2022-03-15_final
2022-03-15 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2022-03-15_final
2022-03-15 12:04:35	ga_s2am_ard_3-2-1_49KGP_2022-03-15_final
2022-03-15 12:04:46	ga_s2am_ard_3-2-1_50JKT_2022-03-15_final
2022-03-15 12:04:50	ga_s2am_ard_3-2-1_49JGN_2022-03-15_final
2022-03-15 12:05:12	ga_s2am_ard_3-2-1_50JLR_2022-03-15_final
2022-03-15 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2022-03-15_final
2022-03-15 12:05:38	ga_s2am_ard_3-2-1_50JLP_2022-03-15_final
2022-03-15 12:05:44	ga_s2am_ard_3-2-1_50JLP_2022-03-15_final
2022-03-15 12:05:55	ga_s2am_ard_3-2-1_50JLN_2022-03-15_final
2022-03-16 11:34:53	ga_s2am_ard_3-2-1_50JRS_2022-03-16_final
2022-03-16 11:35:54	ga_s2am_ard_3-2-1_50JQN_2022-03-16_final
2022-03-18 12:13:58	ga_s2am_ard_3-2-1_49KHR_2022-03-18_final
2022-03-18 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2022-03-18_final
2022-03-18 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2022-03-18_final
2022-03-18 12:14:31	ga_s2am_ard_3-2-1_49KGP_2022-03-18_final
2022-03-18 12:14:45	ga_s2am_ard_3-2-1_49JGN_2022-03-18_final
2022-03-19 11:43:22	ga_s2am_ard_3-2-1_50KRC_2022-03-19_final
2022-03-19 11:44:48	ga_s2am_ard_3-2-1_50JRS_2022-03-19_final
2022-03-19 11:45:50	ga_s2am_ard_3-2-1_50JQN_2022-03-19_final
2022-03-19 11:45:54	ga_s2am_ard_3-2-1_50JPN_2022-03-19_final
2022-03-19 11:45:57	ga_s2am_ard_3-2-1_50JNN_2022-03-19_final
2022-03-22 11:55:16	ga_s2am_ard_3-2-1_50JLR_2022-03-22_final
2022-03-22 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2022-03-22_final
2022-03-22 11:55:42	ga_s2am_ard_3-2-1_50JMP_2022-03-22_final
2022-03-22 11:55:45	ga_s2am_ard_3-2-1_50JLP_2022-03-22_final
2022-03-22 11:55:53	ga_s2am_ard_3-2-1_50JNN_2022-03-22_final
2022-03-22 11:55:56	ga_s2am_ard_3-2-1_50JMN_2022-03-22_final
2022-03-22 11:55:59	ga_s2am_ard_3-2-1_50JLN_2022-03-22_final
2022-03-25 12:04:02	ga_s2am_ard_3-2-1_49KHR_2022-03-25_final
2022-03-25 12:04:16	ga_s2am_ard_3-2-1_49KHQ_2022-03-25_final
2022-03-25 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2022-03-25_final
2022-03-25 12:04:34	ga_s2am_ard_3-2-1_49KGP_2022-03-25_final
2022-03-25 12:04:49	ga_s2am_ard_3-2-1_49JGN_2022-03-25_final
2022-03-25 12:05:06	ga_s2am_ard_3-2-1_50JLR_2022-03-25_final
2022-03-25 12:05:12	ga_s2am_ard_3-2-1_50JLR_2022-03-25_final
2022-03-25 12:05:25	ga_s2am_ard_3-2-1_50JLQ_2022-03-25_final
2022-03-25 12:05:40	ga_s2am_ard_3-2-1_50JLP_2022-03-25_final
2022-03-25 12:05:54	ga_s2am_ard_3-2-1_50JLN_2022-03-25_final
2022-03-26 11:34:39	ga_s2am_ard_3-2-1_50JRT_2022-03-26_final
2022-03-26 11:34:52	ga_s2am_ard_3-2-1_50JRS_2022-03-26_final
2022-03-26 11:35:53	ga_s2am_ard_3-2-1_50JQN_2022-03-26_final
2022-03-28 12:13:57	ga_s2am_ard_3-2-1_49KHR_2022-03-28_final
2022-03-28 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2022-03-28_final
2022-03-28 12:14:14	ga_s2am_ard_3-2-1_49KGQ_2022-03-28_final
2022-03-28 12:14:19	ga_s2am_ard_3-2-1_49KHQ_2022-03-28_final
2022-03-28 12:14:21	ga_s2am_ard_3-2-1_49KGP_2022-03-28_final
2022-03-28 12:14:21	ga_s2am_ard_3-2-1_49KGQ_2022-03-28_final
2022-03-28 12:14:29	ga_s2am_ard_3-2-1_49KGP_2022-03-28_final
2022-03-28 12:14:44	ga_s2am_ard_3-2-1_49JGN_2022-03-28_final
2022-03-29 11:44:33	ga_s2am_ard_3-2-1_50JRT_2022-03-29_final
2022-03-29 11:44:47	ga_s2am_ard_3-2-1_50JRS_2022-03-29_final
2022-03-29 11:45:49	ga_s2am_ard_3-2-1_50JQN_2022-03-29_final
2022-03-29 11:45:53	ga_s2am_ard_3-2-1_50JPN_2022-03-29_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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