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
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_50HNH_2015-11-21_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49JGL_2016-04-15_final.stac-item
2016-04-18 12:14:43	ga_s2am_ard_3-2-1_49JGN_2016-04-18_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50HPK_2016-10-16_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HPK_2016-11-12_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HLG_2016-11-15_final
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HPK_2016-11-15_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50HNG_2016-12-22_final
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50HPH_2016-12-25_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50HMH_2017-02-26_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50HPK_2017-06-13_final.stac-item
2017-07-30 11:34:57	ga_s2am_ard_3-2-1_50HPH_2017-07-30_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49JHM_2017-10-07_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50HNH_2017-12-10_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50HNH_2017-12-30_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-03-06_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49JGL_2018-03-09_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_50HPK_2018-03-17_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HMK_2018-03-20_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HMH_2018-03-30_final.stac-item
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_49KHR_2018-06-04_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_49JGK_2018-06-14_final.stac-item
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HPJ_2018-07-08_final.stac-item
2018-10-12 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-10-12_final.stac-item
2018-11-21 12:05:08	ga_s2am_ard_3-2-1_49JGL_2018-11-21_final.stac-item
2019-01-14 11:47:02	ga_s2am_ard_3-2-1_50HNH_2019-01-14_final.stac-item
2019-01-17 11:56:32	ga_s2am_ard_3-2-1_50HMK_2019-01-17_final.stac-item
2019-03-18 11:57:03	ga_s2am_ard_3-2-1_50HMH_2019-03-18_final.stac-item
2019-04-07 11:56:52	ga_s2am_ard_3-2-1_50HMJ_2019-04-07_final.stac-item
2019-11-30 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2019-11-30_final.stac-item
2019-12-07 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2019-12-07_final.stac-item
2019-12-10 11:46:34	ga_s2am_ard_3-2-1_50HNK_2019-12-10_final.stac-item
2019-12-13 11:57:05	ga_s2am_ard_3-2-1_50HLH_2019-12-13_final.stac-item
2020-01-05 12:05:24	ga_s2am_ard_3-2-1_49JGK_2020-01-05_final.stac-item
2020-01-09 11:46:50	ga_s2am_ard_3-2-1_50HMJ_2020-01-09_final.stac-item
2020-01-29 11:46:48	ga_s2am_ard_3-2-1_50HMJ_2020-01-29_final.stac-item
2020-02-18 11:46:35	ga_s2am_ard_3-2-1_50HPK_2020-02-18_final.stac-item
2020-04-18 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2020-04-18_final.stac-item
2020-04-18 11:47:10	ga_s2am_ard_3-2-1_50HMH_2020-04-18_final.stac-item
2020-04-28 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2020-04-28_final.stac-item
2020-04-28 11:47:05	ga_s2am_ard_3-2-1_50HPH_2020-04-28_final.stac-item
2020-04-28 11:47:12	ga_s2am_ard_3-2-1_50HMH_2020-04-28_final.stac-item
2020-07-17 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2020-07-17_final.stac-item
2020-10-21 12:04:04	ga_s2am_ard_3-2-1_49KHR_2020-10-21_final.stac-item
2020-10-25 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2020-10-25_final.stac-item
2020-11-03 12:15:01	ga_s2am_ard_3-2-1_49JGM_2020-11-03_final.stac-item
2020-11-07 11:57:14	ga_s2am_ard_3-2-1_50HLH_2020-11-07_final.stac-item
2020-12-03 12:15:09	ga_s2am_ard_3-2-1_49JGL_2020-12-03_final.stac-item
2020-12-04 11:46:32	ga_s2am_ard_3-2-1_50HPK_2020-12-04_final.stac-item
2021-01-02 12:13:55	ga_s2am_ard_3-2-1_49KHR_2021-01-02_final.stac-item
2021-01-13 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-01-13_final.stac-item
2021-02-19 11:37:02	ga_s2am_ard_3-2-1_50HQH_2021-02-19_final.stac-item
2021-02-19 11:37:06	ga_s2am_ard_3-2-1_50HPH_2021-02-19_final.stac-item
2021-03-10 12:04:42	ga_s2am_ard_3-2-1_49JHN_2021-03-10_final.stac-item
2021-03-14 11:46:37	ga_s2am_ard_3-2-1_50HNK_2021-03-14_final.stac-item
2021-03-17 11:57:08	ga_s2am_ard_3-2-1_50HLH_2021-03-17_final.stac-item
2021-05-10 11:36:37	ga_s2am_ard_3-2-1_50HPK_2021-05-10_final.stac-item
2021-05-19 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-05-19_final
2021-06-28 12:05:02	ga_s2am_ard_3-2-1_49JGM_2021-06-28_final.stac-item
2021-07-02 11:46:36	ga_s2am_ard_3-2-1_50HPK_2021-07-02_final.stac-item
2021-07-28 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-07-28_final
2021-08-10 12:14:59	ga_s2am_ard_3-2-1_49JGM_2021-08-10_final.stac-item
2021-08-11 11:47:23	ga_s2am_ard_3-2-1_50HNG_2021-08-11_final
2021-09-26 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-09-26_final
2021-10-07 11:37:26	ga_s2am_ard_3-2-1_50HPG_2021-10-07_final
2021-10-10 11:47:29	ga_s2am_ard_3-2-1_50HMG_2021-10-10_final
2021-12-09 11:46:36	ga_s2am_ard_3-2-1_50HPK_2021-12-09_final.stac-item
2021-12-15 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2021-12-15_final.stac-item
2021-12-18 12:15:11	ga_s2am_ard_3-2-1_49JGL_2021-12-18_final.stac-item
2022-02-17 11:47:11	ga_s2am_ard_3-2-1_50HMH_2022-02-17_final.stac-item
2022-02-24 11:36:54	ga_s2am_ard_3-2-1_50HPJ_2022-02-24_final.stac-item
2022-03-22 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2022-03-22_final.stac-item
2022-04-11 11:57:16	ga_s2am_ard_3-2-1_50HMH_2022-04-11_final.stac-item
2022-04-11 11:57:17	ga_s2am_ard_3-2-1_50HLH_2022-04-11_final.stac-item
2022-06-17 11:47:03	ga_s2am_ard_3-2-1_50HNJ_2022-06-17_final.stac-item
2022-06-20 11:56:52	ga_s2am_ard_3-2-1_50HLK_2022-06-20_final.stac-item
2022-09-01 12:05:13	ga_s2am_ard_3-2-1_49JGM_2022-09-01_final.stac-item
2022-11-20 12:05:30	ga_s2am_ard_3-2-1_49JGK_2022-11-20_final.stac-item
2022-12-17 11:57:08	ga_s2am_ard_3-2-1_50HLH_2022-12-17_final.stac-item
2023-01-16 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2023-01-16_final.stac-item
2023-01-26 11:57:06	ga_s2am_ard_3-2-1_50HLH_2023-01-26_final.stac-item
2023-01-30 11:37:24	ga_s2am_ard_3-2-1_50HNG_2023-01-30_final
2023-02-05 11:56:35	ga_s2am_ard_3-2-1_50HMK_2023-02-05_final
2023-02-18 12:04:57	ga_s2am_ard_3-2-1_49JGM_2023-02-18_nrt.stac-item
2023-04-03 11:47:09	ga_s2am_ard_3-2-1_50HMH_2023-04-03_final
2023-04-19 12:03:58	ga_s2am_ard_3-2-1_49KHR_2023-04-19_final
2023-04-20 11:37:26	ga_s2am_ard_3-2-1_50HNG_2023-04-20_final
2023-09-10 11:47:26	ga_s2am_ard_3-2-1_50HNG_2023-09-10_final
2023-09-30 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2023-09-30_final
2023-10-06 12:04:00	ga_s2am_ard_3-2-1_49KHR_2023-10-06_final
2023-10-13 11:56:28	ga_s2am_ard_3-2-1_50HNK_2023-10-13_final
2023-11-22 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2023-11-22_final
2023-12-02 11:56:47	ga_s2am_ard_3-2-1_50HLJ_2023-12-02_final
2023-12-18 12:14:52	ga_s2am_ard_3-2-1_49JGM_2023-12-18_final
2024-01-11 11:56:49	ga_s2am_ard_3-2-1_50HLJ_2024-01-11_final
2024-02-16 12:14:54	ga_s2am_ard_3-2-1_49JGM_2024-02-16_final
2024-02-27 11:47:09	ga_s2am_ard_3-2-1_50HMH_2024-02-27_final
2024-03-01 11:57:06	ga_s2am_ard_3-2-1_50HMH_2024-03-01_final
2024-03-04 12:03:45	ga_s2am_ard_3-2-1_49KHS_2024-03-04_final
2024-03-14 12:05:15	ga_s2am_ard_3-2-1_49JGL_2024-03-14_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

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