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
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JMS_2015-11-14_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50JNN_2016-01-03_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50JLM_2016-01-16_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50JLT_2016-02-15_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JMS_2016-03-03_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49KHP_2016-03-16_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HLH_2016-07-08_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50JKQ_2016-07-14_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JKT_2016-08-13_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49JHM_2016-10-22_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50JKR_2016-11-01_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50JKT_2016-11-01_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HNG_2017-02-03_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50HMK_2017-03-05_final
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_50JLT_2017-03-31_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50JMP_2017-04-07_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49KGQ_2017-05-10_final
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49KHP_2017-05-10_final
2017-10-27 12:03:47	ga_s2am_ard_3-2-1_49KHQ_2017-10-27_final
2017-11-16 12:04:39	ga_s2am_ard_3-2-1_50JMS_2017-11-16_final
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_49KHS_2017-11-26_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50JNN_2017-12-30_final
2018-01-25 12:02:44	ga_s2am_ard_3-2-1_49KGQ_2018-01-25_final
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50JLR_2018-02-24_final
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_50JKS_2018-03-26_final
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50JMP_2018-04-02_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JNN_2018-09-19_final
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JLT_2018-10-22_final
2018-11-08 11:55:44	ga_s2am_ard_3-2-1_50JNN_2018-11-08_final
2018-12-05 11:45:45	ga_s2am_ard_3-2-1_50JNN_2018-12-05_final
2019-01-07 11:55:08	ga_s2am_ard_3-2-1_50JLR_2019-01-07_final
2019-02-03 11:45:51	ga_s2am_ard_3-2-1_50JNN_2019-02-03_final
2019-03-28 11:55:38	ga_s2am_ard_3-2-1_50JMP_2019-03-28_final
2019-04-03 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2019-04-03_final
2019-04-20 12:05:00	ga_s2am_ard_3-2-1_49JHM_2019-04-20_final
2019-05-14 11:46:57	ga_s2am_ard_3-2-1_50HQH_2019-05-14_final
2019-07-09 12:04:44	ga_s2am_ard_3-2-1_50JLT_2019-07-09_final
2019-08-15 11:57:09	ga_s2am_ard_3-2-1_50HMH_2019-08-15_final
2019-09-17 12:04:56	ga_s2am_ard_3-2-1_49JHM_2019-09-17_final
2019-09-20 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2019-09-20_final
2019-11-16 12:04:58	ga_s2am_ard_3-2-1_49JHM_2019-11-16_final
2019-11-26 12:04:57	ga_s2am_ard_3-2-1_49JHM_2019-11-26_final
2019-12-06 12:03:42	ga_s2am_ard_3-2-1_49KHS_2019-12-06_final.stac-item
2019-12-30 11:45:49	ga_s2am_ard_3-2-1_50JNN_2019-12-30_final
2020-03-12 11:55:09	ga_s2am_ard_3-2-1_50JLR_2020-03-12_final
2020-03-22 11:56:33	ga_s2am_ard_3-2-1_50HMK_2020-03-22_final
2020-04-04 12:04:45	ga_s2am_ard_3-2-1_50JMS_2020-04-04_final
2020-04-04 12:04:50	ga_s2am_ard_3-2-1_50JLS_2020-04-04_final
2020-04-07 12:13:37	ga_s2am_ard_3-2-1_49KHS_2020-04-07_final.stac-item
2020-05-27 12:14:27	ga_s2am_ard_3-2-1_49KHP_2020-05-27_final
2020-06-30 11:55:03	ga_s2am_ard_3-2-1_50JLS_2020-06-30_final
2020-07-10 11:57:27	ga_s2am_ard_3-2-1_50HLG_2020-07-10_final.stac-item
2020-09-11 12:03:48	ga_s2am_ard_3-2-1_49KHS_2020-09-11_final.stac-item
2020-11-07 11:55:43	ga_s2am_ard_3-2-1_50JMP_2020-11-07_final
2020-11-10 12:03:49	ga_s2am_ard_3-2-1_49KHS_2020-11-10_final.stac-item
2020-11-10 12:04:58	ga_s2am_ard_3-2-1_50JLS_2020-11-10_final
2020-11-17 11:54:58	ga_s2am_ard_3-2-1_50JMS_2020-11-17_final
2020-11-24 11:45:52	ga_s2am_ard_3-2-1_50JNN_2020-11-24_final
2021-01-06 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2021-01-06_final
2021-02-15 11:54:39	ga_s2am_ard_3-2-1_50JMT_2021-02-15_final
2021-04-16 11:57:17	ga_s2am_ard_3-2-1_50HLG_2021-04-16_final.stac-item
2021-05-09 12:04:38	ga_s2am_ard_3-2-1_50JLT_2021-05-09_final
2021-06-05 11:54:56	ga_s2am_ard_3-2-1_50JMS_2021-06-05_final
2021-07-08 12:05:11	ga_s2am_ard_3-2-1_50JLR_2021-07-08_final
2021-07-28 12:04:39	ga_s2am_ard_3-2-1_50JMT_2021-07-28_final
2021-08-24 11:55:29	ga_s2am_ard_3-2-1_50JLQ_2021-08-24_final
2021-08-27 12:05:10	ga_s2am_ard_3-2-1_50JLR_2021-08-27_final
2021-08-30 12:14:23	ga_s2am_ard_3-2-1_49KHP_2021-08-30_final
2021-10-23 11:55:55	ga_s2am_ard_3-2-1_50JNN_2021-10-23_final
2021-12-02 11:55:49	ga_s2am_ard_3-2-1_50JNN_2021-12-02_final
2021-12-22 11:55:50	ga_s2am_ard_3-2-1_50JNN_2021-12-22_final
2022-01-04 12:04:59	ga_s2am_ard_3-2-1_50JKS_2022-01-04_final
2022-01-28 11:45:54	ga_s2am_ard_3-2-1_50JNN_2022-01-28_final
2022-02-20 11:57:25	ga_s2am_ard_3-2-1_50HLG_2022-02-20_final.stac-item
2022-02-26 12:14:24	ga_s2am_ard_3-2-1_49KHP_2022-02-26_final
2022-03-06 11:36:33	ga_s2am_ard_3-2-1_50HQK_2022-03-06_final
2022-03-25 12:04:56	ga_s2am_ard_3-2-1_50JLS_2022-03-25_final
2022-03-28 12:14:21	ga_s2am_ard_3-2-1_49KGP_2022-03-28_final
2022-05-07 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2022-05-07_final
2022-07-20 11:55:24	ga_s2am_ard_3-2-1_50JLR_2022-07-20_final
2022-08-02 12:03:55	ga_s2am_ard_3-2-1_49KHS_2022-08-02_final.stac-item
2022-08-12 12:03:57	ga_s2am_ard_3-2-1_49KHS_2022-08-12_final.stac-item
2022-10-11 12:04:38	ga_s2am_ard_3-2-1_50JLT_2022-10-11_final.stac-item
2022-10-18 11:55:52	ga_s2am_ard_3-2-1_50JNN_2022-10-18_final.stac-item
2022-10-31 12:05:16	ga_s2am_ard_3-2-1_50JKR_2022-10-31_final.stac-item
2022-11-27 11:55:49	ga_s2am_ard_3-2-1_50JNN_2022-11-27_final.stac-item
2022-11-30 12:03:44	ga_s2am_ard_3-2-1_49KHS_2022-11-30_final.stac-item
2023-01-02 12:14:20	ga_s2am_ard_3-2-1_49KHP_2023-01-02_final.stac-item
2023-03-10 12:04:27	ga_s2am_ard_3-2-1_50JLT_2023-03-10_final.stac-item
2023-05-03 11:45:54	ga_s2am_ard_3-2-1_50JNN_2023-05-03_final.stac-item
2023-05-09 12:04:39	ga_s2am_ard_3-2-1_50JLT_2023-05-09_final.stac-item
2023-05-16 11:57:07	ga_s2am_ard_3-2-1_50HMH_2023-05-16_final.stac-item
2023-07-12 11:45:59	ga_s2am_ard_3-2-1_50JNN_2023-07-12_final.stac-item
2023-07-21 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2023-07-21_final.stac-item
2023-08-17 12:04:45	ga_s2am_ard_3-2-1_50JLT_2023-08-17_final.stac-item
2023-09-17 11:37:30	ga_s2am_ard_3-2-1_50HNG_2023-09-17_final.stac-item
2023-10-29 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2023-10-29_final.stac-item
2024-01-01 11:54:55	ga_s2am_ard_3-2-1_50JLS_2024-01-01_final.stac-item
2024-01-21 11:57:14	ga_s2am_ard_3-2-1_50HLG_2024-01-21_final.stac-item
2024-05-16 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2024-05-16_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

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