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
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KHQ_2015-11-30_final.stac-item
2015-12-24 11:56:44	ga_s2am_ard_3-2-1_50HMK_2015-12-24_final.stac-item
2016-05-05 12:04:47	ga_s2am_ard_3-2-1_50JKR_2016-05-05_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_49JHM_2016-06-14_final.stac-item
2016-09-02 12:03:47	ga_s2am_ard_3-2-1_49KHQ_2016-09-02_final.stac-item
2016-09-22 12:04:37	ga_s2am_ard_3-2-1_50JKS_2016-09-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50JKS_2016-10-22_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50JKT_2016-11-01_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_50JKS_2016-12-21_final.stac-item
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_50HQK_2017-01-01_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50HMK_2017-03-05_final.stac-item
2017-04-10 12:04:40	ga_s2am_ard_3-2-1_49JHN_2017-04-10_final.stac-item
2017-04-10 12:04:40	ga_s2am_ard_3-2-1_50JKS_2017-04-10_final.stac-item
2017-04-27 11:56:35	ga_s2am_ard_3-2-1_50HMJ_2017-04-27_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49KHP_2017-05-10_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_49KGQ_2017-07-29_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49KGQ_2017-08-18_final.stac-item
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_50JKS_2017-10-27_final.stac-item
2017-12-06 12:04:36	ga_s2am_ard_3-2-1_50JKS_2017-12-06_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50JLP_2018-02-11_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50HMH_2018-04-29_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HMH_2018-05-19_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50HMH_2018-06-01_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50HNK_2018-06-01_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50HMH_2018-06-08_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JLQ_2018-07-11_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_50JLM_2018-08-03_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKQ_2018-08-13_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKR_2018-08-23_final.stac-item
2018-08-26 12:13:20	ga_s2am_ard_3-2-1_49KHP_2018-08-26_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50HQK_2018-10-26_final.stac-item
2018-12-04 12:14:00	ga_s2am_ard_3-2-1_49KHQ_2018-12-04_final.stac-item
2019-01-30 12:04:54	ga_s2am_ard_3-2-1_49JHM_2019-01-30_final.stac-item
2019-04-20 12:05:00	ga_s2am_ard_3-2-1_49JHM_2019-04-20_final.stac-item
2019-06-03 11:46:56	ga_s2am_ard_3-2-1_50HQH_2019-06-03_final.stac-item
2019-06-16 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2019-06-16_final.stac-item
2019-08-12 11:47:18	ga_s2am_ard_3-2-1_50HLH_2019-08-12_final.stac-item
2019-09-01 11:46:54	ga_s2am_ard_3-2-1_50HQH_2019-09-01_final.stac-item
2019-09-20 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2019-09-20_final.stac-item
2019-11-16 12:04:58	ga_s2am_ard_3-2-1_49JHM_2019-11-16_final.stac-item
2019-11-26 12:05:12	ga_s2am_ard_3-2-1_50JKR_2019-11-26_final.stac-item
2020-01-15 12:05:02	ga_s2am_ard_3-2-1_50JLR_2020-01-15_final.stac-item
2020-03-22 11:56:33	ga_s2am_ard_3-2-1_50HMK_2020-03-22_final.stac-item
2020-04-28 11:46:56	ga_s2am_ard_3-2-1_50HQH_2020-04-28_final.stac-item
2020-05-14 12:05:02	ga_s2am_ard_3-2-1_50JKS_2020-05-14_final.stac-item
2020-06-16 12:14:27	ga_s2am_ard_3-2-1_49KHP_2020-06-16_final.stac-item
2020-07-30 11:57:11	ga_s2am_ard_3-2-1_50HMH_2020-07-30_final.stac-item
2020-08-15 12:14:14	ga_s2am_ard_3-2-1_49KHQ_2020-08-15_final.stac-item
2020-09-15 11:46:57	ga_s2am_ard_3-2-1_50HQH_2020-09-15_final.stac-item
2020-09-28 11:55:18	ga_s2am_ard_3-2-1_50JLR_2020-09-28_final.stac-item
2020-10-01 12:05:14	ga_s2am_ard_3-2-1_49JFM_2020-10-01_final.stac-item
2021-01-06 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2021-01-06_final.stac-item
2021-01-09 12:04:58	ga_s2am_ard_3-2-1_50JKS_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
2021-02-19 11:37:17	ga_s2am_ard_3-2-1_50HQG_2021-02-19_final
2021-03-10 12:05:11	ga_s2am_ard_3-2-1_50JKR_2021-03-10_final.stac-item
2021-03-17 11:56:36	ga_s2am_ard_3-2-1_50HMK_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
2021-04-06 11:55:09	ga_s2am_ard_3-2-1_50JLR_2021-04-06_final.stac-item
2021-04-16 11:55:06	ga_s2am_ard_3-2-1_50JLR_2021-04-16_final.stac-item
2021-04-22 12:14:04	ga_s2am_ard_3-2-1_49KHQ_2021-04-22_final.stac-item
2021-06-05 11:54:59	ga_s2am_ard_3-2-1_50JLS_2021-06-05_final.stac-item
2021-06-15 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2021-06-15_final.stac-item
2021-08-14 11:55:15	ga_s2am_ard_3-2-1_50JLR_2021-08-14_final.stac-item
2021-08-17 12:05:25	ga_s2am_ard_3-2-1_50JLQ_2021-08-17_final.stac-item
2021-08-20 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2021-08-20_final.stac-item
2021-08-24 11:57:08	ga_s2am_ard_3-2-1_50HMH_2021-08-24_final.stac-item
2021-09-03 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-09-03_final
2021-10-03 11:55:02	ga_s2am_ard_3-2-1_50JLS_2021-10-03_final.stac-item
2021-10-16 12:04:59	ga_s2am_ard_3-2-1_50JLS_2021-10-16_final.stac-item
2021-11-08 12:14:24	ga_s2am_ard_3-2-1_49KHP_2021-11-08_final.stac-item
2021-11-18 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2021-11-18_final.stac-item
2021-12-15 12:05:12	ga_s2am_ard_3-2-1_50JKR_2021-12-15_final.stac-item
2022-02-03 12:04:54	ga_s2am_ard_3-2-1_50JLS_2022-02-03_final.stac-item
2022-06-07 11:47:18	ga_s2am_ard_3-2-1_50HMH_2022-06-07_final.stac-item
2022-06-07 11:47:22	ga_s2am_ard_3-2-1_50HLH_2022-06-07_final.stac-item
2022-06-27 11:47:06	ga_s2am_ard_3-2-1_50HQH_2022-06-27_final.stac-item
2022-08-13 11:36:52	ga_s2am_ard_3-2-1_50HQJ_2022-08-13_final.stac-item
2022-10-21 12:04:55	ga_s2am_ard_3-2-1_49JHM_2022-10-21_final.stac-item
2022-12-10 12:04:54	ga_s2am_ard_3-2-1_50JLS_2022-12-10_final.stac-item
2023-02-08 12:05:07	ga_s2am_ard_3-2-1_49JFM_2023-02-08_final
2023-02-22 11:46:51	ga_s2am_ard_3-2-1_50HQH_2023-02-22_nrt.stac-item
2023-02-22 11:46:51	ga_s2am_ard_3-2-1_50HQH_2023-02-22_final
2023-03-10 12:04:52	ga_s2am_ard_3-2-1_50JKS_2023-03-10_final
2023-03-10 12:05:07	ga_s2am_ard_3-2-1_50JKR_2023-03-10_final
2023-05-02 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2023-05-02_final
2023-06-21 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2023-06-21_final
2023-06-28 12:05:01	ga_s2am_ard_3-2-1_49JHM_2023-06-28_final
2023-07-02 11:46:58	ga_s2am_ard_3-2-1_50HQH_2023-07-02_final
2023-07-11 12:14:26	ga_s2am_ard_3-2-1_49KHP_2023-07-11_final
2023-07-31 12:14:26	ga_s2am_ard_3-2-1_49KHP_2023-07-31_final
2023-08-11 11:47:29	ga_s2am_ard_3-2-1_50HMG_2023-08-11_final
2023-08-21 11:47:30	ga_s2am_ard_3-2-1_50HMG_2023-08-21_final
2023-08-30 12:14:36	ga_s2am_ard_3-2-1_49KFP_2023-08-30_nrt
2023-09-06 12:05:14	ga_s2am_ard_3-2-1_49JFM_2023-09-06_final
2023-10-23 11:56:26	ga_s2am_ard_3-2-1_50HMK_2023-10-23_final
2023-10-29 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2023-10-29_final
2023-11-02 11:57:21	ga_s2am_ard_3-2-1_50HLG_2023-11-02_final
2024-01-01 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2024-01-01_final
2024-01-14 12:05:05	ga_s2am_ard_3-2-1_50JKR_2024-01-14_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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