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
2015-09-11 12:13:46	ga_s2am_ard_3-2-1_49KHR_2015-09-11_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HPK_2015-12-21_final.stac-item
2015-12-30 12:16:05	ga_s2am_ard_3-2-1_49JGN_2015-12-30_final.stac-item
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50HPK_2016-01-07_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HPH_2016-03-20_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49JGL_2016-04-15_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49JGN_2016-04-15_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGN_2016-09-12_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49JGN_2016-10-02_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50HPG_2016-10-23_final
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50HLJ_2016-11-18_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_50HQH_2016-11-22_final.stac-item
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49KGR_2016-12-04_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HQK_2017-01-14_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50HNJ_2017-03-05_final.stac-item
2017-04-03 12:14:19	ga_s2am_ard_3-2-1_49JGN_2017-04-03_final.stac-item
2017-04-13 12:13:43	ga_s2am_ard_3-2-1_49KHR_2017-04-13_final.stac-item
2017-04-14 11:45:07	ga_s2am_ard_3-2-1_50HPG_2017-04-14_final
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49JGL_2017-05-30_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JGN_2017-06-29_final.stac-item
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_49KGR_2017-11-29_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50HPH_2017-12-30_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HMK_2018-03-20_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HLJ_2018-05-12_final.stac-item
2018-08-16 12:13:21	ga_s2am_ard_3-2-1_49JGM_2018-08-16_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49JGL_2018-09-05_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50HQK_2018-09-26_final.stac-item
2018-10-12 12:02:46	ga_s2am_ard_3-2-1_49KHQ_2018-10-12_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49KHQ_2018-10-22_final.stac-item
2018-12-04 12:14:33	ga_s2am_ard_3-2-1_49JGN_2018-12-04_final.stac-item
2019-01-04 11:46:44	ga_s2am_ard_3-2-1_50HNJ_2019-01-04_final.stac-item
2019-05-20 12:05:30	ga_s2am_ard_3-2-1_50JKQ_2019-05-20_final.stac-item
2019-06-09 12:04:30	ga_s2am_ard_3-2-1_49KHP_2019-06-09_final.stac-item
2019-08-15 11:57:12	ga_s2am_ard_3-2-1_50HLH_2019-08-15_final.stac-item
2019-08-21 12:14:58	ga_s2am_ard_3-2-1_49JGM_2019-08-21_final.stac-item
2019-09-07 12:04:42	ga_s2am_ard_3-2-1_49JHN_2019-09-07_final.stac-item
2019-11-23 11:57:03	ga_s2am_ard_3-2-1_50HLH_2019-11-23_final.stac-item
2019-12-10 11:46:37	ga_s2am_ard_3-2-1_50HMK_2019-12-10_final.stac-item
2020-01-02 11:56:31	ga_s2am_ard_3-2-1_50HMK_2020-01-02_final.stac-item
2020-01-22 11:55:40	ga_s2am_ard_3-2-1_50JKP_2020-01-22_final.stac-item
2020-01-29 11:46:55	ga_s2am_ard_3-2-1_50HPH_2020-01-29_final.stac-item
2020-02-04 12:04:34	ga_s2am_ard_3-2-1_49JHN_2020-02-04_final.stac-item
2020-02-07 12:14:33	ga_s2am_ard_3-2-1_49JGN_2020-02-07_final.stac-item
2020-02-11 11:56:58	ga_s2am_ard_3-2-1_50HMH_2020-02-11_final.stac-item
2020-02-18 11:46:31	ga_s2am_ard_3-2-1_50HMK_2020-02-18_final.stac-item
2020-03-12 11:55:43	ga_s2am_ard_3-2-1_50JKP_2020-03-12_final.stac-item
2020-04-08 11:47:04	ga_s2am_ard_3-2-1_50HNH_2020-04-08_final.stac-item
2020-04-15 11:36:37	ga_s2am_ard_3-2-1_50HPK_2020-04-15_final.stac-item
2020-06-06 12:14:48	ga_s2am_ard_3-2-1_49JGN_2020-06-06_final.stac-item
2020-07-20 11:56:16	ga_s2am_ard_3-2-1_50JLM_2020-07-20_final.stac-item
2020-07-20 11:56:45	ga_s2am_ard_3-2-1_50HLK_2020-07-20_final.stac-item
2020-08-02 12:04:34	ga_s2am_ard_3-2-1_49KHP_2020-08-02_final.stac-item
2020-12-03 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2020-12-03_final.stac-item
2021-03-10 12:06:04	ga_s2am_ard_3-2-1_50JLM_2021-03-10_final.stac-item
2021-08-28 11:36:36	ga_s2am_ard_3-2-1_50HQK_2021-08-28_final.stac-item
2021-11-28 12:14:41	ga_s2am_ard_3-2-1_49JGN_2021-11-28_final.stac-item
2022-02-20 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2022-02-20_final.stac-item
2022-04-18 11:46:38	ga_s2am_ard_3-2-1_50HPK_2022-04-18_final.stac-item
2022-04-25 11:36:37	ga_s2am_ard_3-2-1_50HPK_2022-04-25_final.stac-item
2022-05-21 11:57:01	ga_s2am_ard_3-2-1_50HLJ_2022-05-21_final.stac-item
2022-07-03 12:05:28	ga_s2am_ard_3-2-1_49JGL_2022-07-03_final.stac-item
2022-07-27 11:47:20	ga_s2am_ard_3-2-1_50HMH_2022-07-27_final.stac-item
2022-08-05 12:15:11	ga_s2am_ard_3-2-1_49JFM_2022-08-05_final.stac-item
2022-12-07 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2022-12-07_final.stac-item
2022-12-11 11:36:38	ga_s2am_ard_3-2-1_50HPK_2022-12-11_final.stac-item
2022-12-17 11:57:05	ga_s2am_ard_3-2-1_50HMH_2022-12-17_final.stac-item
2023-01-06 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2023-01-06_final.stac-item
2023-02-02 11:47:14	ga_s2am_ard_3-2-1_50HMH_2023-02-02_final
2023-02-12 11:47:12	ga_s2am_ard_3-2-1_50HLH_2023-02-12_nrt.stac-item
2023-02-12 11:47:12	ga_s2am_ard_3-2-1_50HLH_2023-02-12_final
2023-02-22 11:46:40	ga_s2am_ard_3-2-1_50HQJ_2023-02-22_nrt.stac-item
2023-02-22 11:46:40	ga_s2am_ard_3-2-1_50HQJ_2023-02-22_final
2023-04-02 12:14:30	ga_s2am_ard_3-2-1_49KFP_2023-04-02_nrt
2023-04-16 11:57:09	ga_s2am_ard_3-2-1_50HLH_2023-04-16_final
2023-05-19 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2023-05-19_final
2023-06-08 12:05:33	ga_s2am_ard_3-2-1_49JGK_2023-06-08_final
2023-06-21 12:13:58	ga_s2am_ard_3-2-1_49KHR_2023-06-21_final
2023-07-28 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2023-07-28_final
2023-08-21 11:47:16	ga_s2am_ard_3-2-1_50HMH_2023-08-21_final
2023-08-24 11:56:05	ga_s2am_ard_3-2-1_50JKN_2023-08-24_final
2023-08-24 11:56:32	ga_s2am_ard_3-2-1_50JLL_2023-08-24_final
2023-09-19 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2023-09-19_final
2023-10-07 11:37:03	ga_s2am_ard_3-2-1_50HQH_2023-10-07_final
2023-10-29 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-10-29_final
2023-11-05 12:04:56	ga_s2am_ard_3-2-1_50JKS_2023-11-05_final
2023-11-09 11:46:29	ga_s2am_ard_3-2-1_50HQK_2023-11-09_final
2023-12-12 11:55:42	ga_s2am_ard_3-2-1_50JKP_2023-12-12_final
2024-01-11 11:56:35	ga_s2am_ard_3-2-1_50HLK_2024-01-11_final
2024-01-18 11:47:08	ga_s2am_ard_3-2-1_50HPG_2024-01-18_final
2024-01-18 11:47:12	ga_s2am_ard_3-2-1_50HNG_2024-01-18_final
2024-03-07 12:15:11	ga_s2am_ard_3-2-1_49JGL_2024-03-07_final
2024-04-04 11:36:31	ga_s2am_ard_3-2-1_50HQK_2024-04-04_final
2024-04-06 12:14:54	ga_s2am_ard_3-2-1_49JGM_2024-04-06_final
2024-04-07 11:46:32	ga_s2am_ard_3-2-1_50HPK_2024-04-07_final
2024-04-16 12:15:02	ga_s2am_ard_3-2-1_49JFM_2024-04-16_final
2024-04-20 11:56:40	ga_s2am_ard_3-2-1_50HMK_2024-04-20_final
2024-04-20 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2024-04-20_final
2024-04-23 12:05:15	ga_s2am_ard_3-2-1_50JKR_2024-04-23_final
2024-05-07 11:47:17	ga_s2am_ard_3-2-1_50HLH_2024-05-07_final
2024-05-17 11:47:05	ga_s2am_ard_3-2-1_50HPH_2024-05-17_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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