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
2015-11-27 12:04:40	ga_s2am_ard_3-2-1_50JKS_2015-11-27_final.stac-item
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_50JKR_2015-12-07_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_50JLQ_2016-06-24_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50HMJ_2016-07-01_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50HMG_2016-10-09_final.stac-item
2017-03-28 11:56:02	ga_s2am_ard_3-2-1_50HMK_2017-03-28_final
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50HMJ_2017-05-27_final
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_49JHM_2017-06-19_final
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49KHS_2017-08-01_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49JHM_2017-08-18_final
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50JMQ_2017-08-25_final
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JKS_2017-09-17_final
2017-11-03 11:56:07	ga_s2am_ard_3-2-1_50JNM_2017-11-03_final
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50JLT_2017-11-13_final
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50JLQ_2017-12-23_final
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50HQH_2017-12-30_final
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50JLT_2018-03-23_final
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50JMP_2018-03-23_final
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_49KHQ_2018-04-08_final
2018-04-15 12:05:11	ga_s2am_ard_3-2-1_50JLQ_2018-04-15_final
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_50JKS_2018-05-15_final
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50HMH_2018-06-01_final
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49KGQ_2018-07-14_final
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50JLQ_2018-08-20_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JKQ_2018-09-02_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KGQ_2018-09-12_final
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_49KHQ_2018-09-25_final
2018-10-12 12:02:46	ga_s2am_ard_3-2-1_49KGQ_2018-10-12_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JHM_2018-10-12_final
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2018-10-15_final
2018-10-16 11:40:28	ga_s2am_ard_3-2-1_50JNM_2018-10-16_final
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49KHS_2018-10-22_final.stac-item
2018-11-15 11:45:33	ga_s2am_ard_3-2-1_50JNP_2018-11-15_final
2018-12-01 12:03:36	ga_s2am_ard_3-2-1_49KHS_2018-12-01_final.stac-item
2018-12-24 12:14:01	ga_s2am_ard_3-2-1_49KHQ_2018-12-24_final
2019-02-12 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2019-02-12_final
2019-02-22 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2019-02-22_final
2019-04-20 12:05:26	ga_s2am_ard_3-2-1_50JLQ_2019-04-20_final
2019-05-13 12:13:44	ga_s2am_ard_3-2-1_49KHS_2019-05-13_final.stac-item
2019-05-14 11:45:55	ga_s2am_ard_3-2-1_50JNN_2019-05-14_final
2019-05-27 11:57:09	ga_s2am_ard_3-2-1_50HMH_2019-05-27_final
2019-06-09 12:03:47	ga_s2am_ard_3-2-1_49KHS_2019-06-09_final.stac-item
2019-07-02 12:14:26	ga_s2am_ard_3-2-1_49KHP_2019-07-02_final
2019-07-19 12:05:02	ga_s2am_ard_3-2-1_49JHM_2019-07-19_final
2019-09-21 11:45:54	ga_s2am_ard_3-2-1_50JNN_2019-09-21_final
2019-10-31 11:47:31	ga_s2am_ard_3-2-1_50HLG_2019-10-31_final.stac-item
2019-12-30 11:45:19	ga_s2am_ard_3-2-1_50JNQ_2019-12-30_final
2020-06-13 12:05:03	ga_s2am_ard_3-2-1_49JHM_2020-06-13_final
2020-06-17 11:46:07	ga_s2am_ard_3-2-1_50JNM_2020-06-17_final
2020-06-27 11:46:06	ga_s2am_ard_3-2-1_50JNM_2020-06-27_final
2020-07-07 11:47:25	ga_s2am_ard_3-2-1_50HMG_2020-07-07_final.stac-item
2020-07-23 12:05:17	ga_s2am_ard_3-2-1_50JKR_2020-07-23_final
2020-09-01 12:03:49	ga_s2am_ard_3-2-1_49KHS_2020-09-01_final.stac-item
2020-11-13 12:13:43	ga_s2am_ard_3-2-1_49KHS_2020-11-13_final.stac-item
2020-11-17 11:55:27	ga_s2am_ard_3-2-1_50JMQ_2020-11-17_final
2021-01-19 12:05:12	ga_s2am_ard_3-2-1_50JKR_2021-01-19_final
2021-01-26 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2021-01-26_final
2021-03-07 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2021-03-07_final
2021-03-17 11:56:36	ga_s2am_ard_3-2-1_50HMK_2021-03-17_final
2021-04-06 11:55:31	ga_s2am_ard_3-2-1_50JNP_2021-04-06_final
2021-05-12 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2021-05-12_final
2021-07-15 11:54:58	ga_s2am_ard_3-2-1_50JMS_2021-07-15_final
2021-07-25 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2021-07-25_final
2021-08-14 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2021-08-14_final
2021-09-03 11:55:14	ga_s2am_ard_3-2-1_50JLR_2021-09-03_final
2021-09-09 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2021-09-09_final
2021-10-16 12:04:45	ga_s2am_ard_3-2-1_50JLT_2021-10-16_final
2021-11-05 12:05:15	ga_s2am_ard_3-2-1_50JKR_2021-11-05_final
2021-12-19 11:45:25	ga_s2am_ard_3-2-1_50JNQ_2021-12-19_final
2022-02-03 12:05:12	ga_s2am_ard_3-2-1_50JKR_2022-02-03_final
2022-03-08 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2022-03-08_final
2022-04-07 12:14:22	ga_s2am_ard_3-2-1_49KHP_2022-04-07_final
2022-05-05 11:37:26	ga_s2am_ard_3-2-1_50HPG_2022-05-05_final.stac-item
2022-05-21 11:55:56	ga_s2am_ard_3-2-1_50JNN_2022-05-21_final
2022-06-23 12:04:52	ga_s2am_ard_3-2-1_50JLT_2022-06-23_final
2022-08-12 12:05:20	ga_s2am_ard_3-2-1_49JFM_2022-08-12_final
2022-10-01 12:04:38	ga_s2am_ard_3-2-1_50JMT_2022-10-01_final.stac-item
2022-10-18 11:55:23	ga_s2am_ard_3-2-1_50JNQ_2022-10-18_final.stac-item
2022-11-03 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2022-11-03_final.stac-item
2022-11-20 12:03:45	ga_s2am_ard_3-2-1_49KHS_2022-11-20_final.stac-item
2022-12-14 11:45:54	ga_s2am_ard_3-2-1_50JNN_2022-12-14_final.stac-item
2022-12-24 11:45:52	ga_s2am_ard_3-2-1_50JNN_2022-12-24_final.stac-item
2022-12-27 11:55:11	ga_s2am_ard_3-2-1_50JLR_2022-12-27_final.stac-item
2023-02-11 12:14:19	ga_s2am_ard_3-2-1_49KHP_2023-02-11_final.stac-item
2023-02-21 12:14:06	ga_s2am_ard_3-2-1_49KHQ_2023-02-21_final.stac-item
2023-03-27 11:55:19	ga_s2am_ard_3-2-1_50JNQ_2023-03-27_final.stac-item
2023-04-09 12:05:23	ga_s2am_ard_3-2-1_50JLQ_2023-04-09_final.stac-item
2023-04-22 12:14:20	ga_s2am_ard_3-2-1_49KHP_2023-04-22_final.stac-item
2023-04-23 11:46:52	ga_s2am_ard_3-2-1_50HQH_2023-04-23_final.stac-item
2023-05-22 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2023-05-22_final.stac-item
2023-06-25 11:54:47	ga_s2am_ard_3-2-1_50JLT_2023-06-25_final.stac-item
2023-07-02 11:45:59	ga_s2am_ard_3-2-1_50JNN_2023-07-02_final.stac-item
2023-07-05 11:57:27	ga_s2am_ard_3-2-1_50HLG_2023-07-05_final.stac-item
2023-10-03 11:55:40	ga_s2am_ard_3-2-1_50JMP_2023-10-03_final.stac-item
2023-10-16 12:04:38	ga_s2am_ard_3-2-1_50JLT_2023-10-16_final.stac-item
2023-12-25 12:05:05	ga_s2am_ard_3-2-1_50JLR_2023-12-25_final.stac-item
2024-01-14 12:04:47	ga_s2am_ard_3-2-1_50JLS_2024-01-14_final.stac-item
2024-01-14 12:05:05	ga_s2am_ard_3-2-1_50JKR_2024-01-14_final.stac-item
2024-01-27 12:14:16	ga_s2am_ard_3-2-1_49KHP_2024-01-27_final.stac-item
2024-03-01 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2024-03-01_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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