Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50JMP_2016-01-03_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JHN_2016-01-26_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50JKR_2016-02-15_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50JLS_2016-02-15_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JLT_2016-04-02_final.stac-item
2016-09-02 12:03:47	ga_s2am_ard_3-2-1_49KHQ_2016-09-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KGQ_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KHP_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50JLQ_2016-10-02_final.stac-item
2016-10-12 12:03:43	ga_s2am_ard_3-2-1_49KHQ_2016-10-12_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49KHQ_2016-11-24_final.stac-item
2017-04-03 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2017-04-03_final.stac-item
2017-04-23 12:13:36	ga_s2am_ard_3-2-1_49KHQ_2017-04-23_final.stac-item
2017-04-30 12:04:44	ga_s2am_ard_3-2-1_49JHM_2017-04-30_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_49KGQ_2017-07-29_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_50JLT_2017-10-07_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50JMP_2017-10-24_final.stac-item
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_50JLS_2017-10-27_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50JLR_2018-04-25_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49KHQ_2018-04-28_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50HQH_2018-04-29_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HMH_2018-05-22_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50HNK_2018-06-01_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50HMH_2018-07-11_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JLR_2018-08-10_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50JLT_2018-10-09_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JLQ_2018-10-22_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49KHP_2018-11-04_final.stac-item
2018-11-21 12:04:42	ga_s2am_ard_3-2-1_50JMS_2018-11-21_final.stac-item
2018-11-21 12:05:01	ga_s2am_ard_3-2-1_50JLR_2018-11-21_final.stac-item
2019-01-07 11:55:04	ga_s2am_ard_3-2-1_50JMR_2019-01-07_final.stac-item
2019-01-07 11:55:22	ga_s2am_ard_3-2-1_50JLQ_2019-01-07_final.stac-item
2019-01-20 12:05:08	ga_s2am_ard_3-2-1_50JKR_2019-01-20_final.stac-item
2019-02-06 11:54:52	ga_s2am_ard_3-2-1_50JMS_2019-02-06_final.stac-item
2019-05-10 12:04:43	ga_s2am_ard_3-2-1_50JLT_2019-05-10_final.stac-item
2019-05-10 12:05:01	ga_s2am_ard_3-2-1_49JHM_2019-05-10_final.stac-item
2019-06-03 11:47:12	ga_s2am_ard_3-2-1_50HMH_2019-06-03_final.stac-item
2019-06-03 11:47:16	ga_s2am_ard_3-2-1_50HLH_2019-06-03_final.stac-item
2019-06-29 12:05:13	ga_s2am_ard_3-2-1_50JLR_2019-06-29_final.stac-item
2019-07-09 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2019-07-09_final.stac-item
2019-08-22 11:45:56	ga_s2am_ard_3-2-1_50JNN_2019-08-22_final.stac-item
2019-12-13 11:54:53	ga_s2am_ard_3-2-1_50JLS_2019-12-13_final.stac-item
2020-01-12 11:54:35	ga_s2am_ard_3-2-1_50JMT_2020-01-12_final.stac-item
2020-03-22 11:55:06	ga_s2am_ard_3-2-1_50JMR_2020-03-22_final.stac-item
2020-04-14 12:05:11	ga_s2am_ard_3-2-1_50JKR_2020-04-14_final.stac-item
2020-04-14 12:05:22	ga_s2am_ard_3-2-1_50JLQ_2020-04-14_final.stac-item
2020-06-26 12:14:14	ga_s2am_ard_3-2-1_49KHQ_2020-06-26_final.stac-item
2020-07-23 12:05:02	ga_s2am_ard_3-2-1_49JHM_2020-07-23_final.stac-item
2020-07-26 12:14:14	ga_s2am_ard_3-2-1_49KHQ_2020-07-26_final.stac-item
2020-08-02 12:04:45	ga_s2am_ard_3-2-1_50JLT_2020-08-02_final.stac-item
2020-09-04 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2020-09-04_final.stac-item
2020-09-15 11:46:57	ga_s2am_ard_3-2-1_50HQH_2020-09-15_final.stac-item
2020-10-21 12:04:54	ga_s2am_ard_3-2-1_50JMS_2020-10-21_final.stac-item
2020-10-28 11:55:03	ga_s2am_ard_3-2-1_50JLS_2020-10-28_final.stac-item
2020-11-07 11:55:02	ga_s2am_ard_3-2-1_50JLS_2020-11-07_final.stac-item
2020-11-27 11:54:41	ga_s2am_ard_3-2-1_50JMT_2020-11-27_final.stac-item
2020-11-30 12:04:54	ga_s2am_ard_3-2-1_50JLS_2020-11-30_final.stac-item
2020-12-10 12:04:50	ga_s2am_ard_3-2-1_50JLS_2020-12-10_final.stac-item
2021-01-09 12:04:54	ga_s2am_ard_3-2-1_50JLS_2021-01-09_final.stac-item
2021-01-16 11:54:59	ga_s2am_ard_3-2-1_50JLS_2021-01-16_final.stac-item
2021-02-18 12:04:53	ga_s2am_ard_3-2-1_50JLS_2021-02-18_final.stac-item
2021-02-28 12:04:48	ga_s2am_ard_3-2-1_50JMS_2021-02-28_final.stac-item
2021-03-17 11:55:38	ga_s2am_ard_3-2-1_50JMP_2021-03-17_final.stac-item
2021-03-27 11:55:25	ga_s2am_ard_3-2-1_50JLQ_2021-03-27_final.stac-item
2021-03-30 12:04:37	ga_s2am_ard_3-2-1_50JLT_2021-03-30_final.stac-item
2021-04-19 12:04:34	ga_s2am_ard_3-2-1_50JLT_2021-04-19_final.stac-item
2021-04-26 11:55:09	ga_s2am_ard_3-2-1_50JLR_2021-04-26_final.stac-item
2021-04-26 11:56:33	ga_s2am_ard_3-2-1_50HMK_2021-04-26_final.stac-item
2021-04-29 12:05:20	ga_s2am_ard_3-2-1_50JLQ_2021-04-29_final.stac-item
2021-08-11 11:47:29	ga_s2am_ard_3-2-1_50HLG_2021-08-11_final
2021-08-20 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2021-08-20_final.stac-item
2021-11-12 11:55:51	ga_s2am_ard_3-2-1_50JNN_2021-11-12_final.stac-item
2022-01-15 11:36:28	ga_s2am_ard_3-2-1_50HQK_2022-01-15_final.stac-item
2022-01-27 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2022-01-27_final.stac-item
2022-02-13 12:04:53	ga_s2am_ard_3-2-1_50JLS_2022-02-13_final.stac-item
2022-03-18 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2022-03-18_final.stac-item
2022-05-14 12:05:12	ga_s2am_ard_3-2-1_50JLR_2022-05-14_final.stac-item
2022-05-21 11:55:45	ga_s2am_ard_3-2-1_50JMP_2022-05-21_final.stac-item
2022-05-24 12:04:46	ga_s2am_ard_3-2-1_50JLT_2022-05-24_final.stac-item
2022-06-20 11:55:39	ga_s2am_ard_3-2-1_50JLQ_2022-06-20_final.stac-item
2022-07-20 11:54:52	ga_s2am_ard_3-2-1_50JMT_2022-07-20_final.stac-item
2022-08-19 11:55:37	ga_s2am_ard_3-2-1_50JMQ_2022-08-19_final.stac-item
2022-09-01 12:05:24	ga_s2am_ard_3-2-1_50JKR_2022-09-01_final.stac-item
2022-09-11 12:05:33	ga_s2am_ard_3-2-1_50JLQ_2022-09-11_final.stac-item
2022-11-04 11:45:58	ga_s2am_ard_3-2-1_50JNN_2022-11-04_final.stac-item
2022-11-07 11:55:17	ga_s2am_ard_3-2-1_50JLR_2022-11-07_final.stac-item
2022-11-13 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2022-11-13_final.stac-item
2022-11-17 11:54:57	ga_s2am_ard_3-2-1_50JMS_2022-11-17_final.stac-item
2022-12-07 11:54:41	ga_s2am_ard_3-2-1_50JMT_2022-12-07_final.stac-item
2022-12-27 11:54:39	ga_s2am_ard_3-2-1_50JMT_2022-12-27_final.stac-item
2023-01-02 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2023-01-02_final.stac-item
2023-01-19 12:04:44	ga_s2am_ard_3-2-1_50JMS_2023-01-19_final.stac-item
2023-02-02 11:45:52	ga_s2am_ard_3-2-1_50JNN_2023-02-02_final
2023-07-15 11:57:11	ga_s2am_ard_3-2-1_50HMH_2023-07-15_final
2023-07-25 11:55:14	ga_s2am_ard_3-2-1_50JMR_2023-07-25_final
2023-10-06 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2023-10-06_final
2023-10-16 12:05:07	ga_s2am_ard_3-2-1_50JLR_2023-10-16_final
2024-01-01 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2024-01-01_final
2024-05-07 11:46:56	ga_s2am_ard_3-2-1_50HQH_2024-05-07_final
2024-05-16 12:14:23	ga_s2am_ard_3-2-1_49KHP_2024-05-16_nrt

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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

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