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
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HNJ_2015-12-21_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HPK_2016-01-20_final.stac-item
2016-02-08 12:10:34	ga_s2am_ard_3-2-1_49JGL_2016-02-08_final.stac-item
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50HNG_2016-02-19_final
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49JGK_2016-04-15_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HMH_2016-05-09_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49JGN_2016-05-15_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HNK_2016-06-11_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_49JGM_2016-06-14_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HNH_2016-11-15_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50HLJ_2016-11-18_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49JGL_2016-12-24_final.stac-item
2017-07-23 11:45:09	ga_s2am_ard_3-2-1_50HPH_2017-07-23_final.stac-item
2017-09-20 12:13:39	ga_s2am_ard_3-2-1_49KHR_2017-09-20_final.stac-item
2017-10-10 12:13:43	ga_s2am_ard_3-2-1_49KGR_2017-10-10_final.stac-item
2017-10-30 12:14:41	ga_s2am_ard_3-2-1_49JGM_2017-10-30_final.stac-item
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50HLJ_2018-02-11_final.stac-item
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50HLH_2018-02-28_final.stac-item
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_50HMH_2018-04-09_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50HNJ_2018-07-18_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JGM_2018-08-23_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-09-12_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-10-02_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50HLH_2018-10-09_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HMJ_2018-10-29_final.stac-item
2018-11-15 11:46:50	ga_s2am_ard_3-2-1_50HMJ_2018-11-15_final.stac-item
2018-11-24 12:13:47	ga_s2am_ard_3-2-1_49KHR_2018-11-24_final.stac-item
2019-01-03 12:14:50	ga_s2am_ard_3-2-1_49JGM_2019-01-03_final.stac-item
2019-01-03 12:15:05	ga_s2am_ard_3-2-1_49JGL_2019-01-03_final.stac-item
2019-02-23 11:47:02	ga_s2am_ard_3-2-1_50HNH_2019-02-23_final.stac-item
2019-04-30 12:05:04	ga_s2am_ard_3-2-1_49JGM_2019-04-30_final.stac-item
2019-05-04 11:47:10	ga_s2am_ard_3-2-1_50HNH_2019-05-04_final.stac-item
2019-06-19 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2019-06-19_final.stac-item
2019-06-30 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2019-06-30_final.stac-item
2019-09-20 12:14:56	ga_s2am_ard_3-2-1_49JGM_2019-09-20_final.stac-item
2019-10-30 12:15:00	ga_s2am_ard_3-2-1_49JFM_2019-10-30_final.stac-item
2019-12-13 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2019-12-13_final.stac-item
2020-01-29 11:46:59	ga_s2am_ard_3-2-1_50HNH_2020-01-29_final.stac-item
2020-03-19 11:47:03	ga_s2am_ard_3-2-1_50HNH_2020-03-19_final.stac-item
2020-03-25 12:04:57	ga_s2am_ard_3-2-1_49JGM_2020-03-25_final.stac-item
2020-04-11 11:57:04	ga_s2am_ard_3-2-1_50HMH_2020-04-11_final.stac-item
2020-05-07 12:15:14	ga_s2am_ard_3-2-1_49JGL_2020-05-07_final.stac-item
2020-06-16 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-06-16_final.stac-item
2020-07-26 12:15:02	ga_s2am_ard_3-2-1_49JGM_2020-07-26_final.stac-item
2020-08-25 12:15:05	ga_s2am_ard_3-2-1_49JFM_2020-08-25_final.stac-item
2020-09-05 11:46:38	ga_s2am_ard_3-2-1_50HPK_2020-09-05_final.stac-item
2020-09-05 11:47:11	ga_s2am_ard_3-2-1_50HNH_2020-09-05_final.stac-item
2021-01-03 11:46:53	ga_s2am_ard_3-2-1_50HQH_2021-01-03_final.stac-item
2021-01-06 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-01-06_final.stac-item
2021-01-23 11:47:07	ga_s2am_ard_3-2-1_50HNH_2021-01-23_final.stac-item
2021-01-30 11:37:17	ga_s2am_ard_3-2-1_50HQG_2021-01-30_final
2021-02-28 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-02-28_final.stac-item
2021-03-10 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-03-10_final.stac-item
2021-03-21 11:37:16	ga_s2am_ard_3-2-1_50HQG_2021-03-21_final
2021-04-06 11:56:26	ga_s2am_ard_3-2-1_50HNK_2021-04-06_final.stac-item
2021-04-06 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2021-04-06_final.stac-item
2021-04-09 12:03:54	ga_s2am_ard_3-2-1_49KHR_2021-04-09_final.stac-item
2021-04-22 12:14:55	ga_s2am_ard_3-2-1_49JFM_2021-04-22_final.stac-item
2021-04-23 11:46:29	ga_s2am_ard_3-2-1_50HPK_2021-04-23_final.stac-item
2021-06-19 11:37:18	ga_s2am_ard_3-2-1_50HQG_2021-06-19_final
2021-06-22 11:47:25	ga_s2am_ard_3-2-1_50HMG_2021-06-22_final
2021-06-28 12:04:47	ga_s2am_ard_3-2-1_49JGN_2021-06-28_final.stac-item
2021-06-29 11:37:04	ga_s2am_ard_3-2-1_50HQH_2021-06-29_final.stac-item
2021-08-28 11:37:19	ga_s2am_ard_3-2-1_50HQG_2021-08-28_final
2021-09-03 11:56:41	ga_s2am_ard_3-2-1_50HLK_2021-09-03_final.stac-item
2021-09-03 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2021-09-03_final.stac-item
2021-09-13 11:57:07	ga_s2am_ard_3-2-1_50HMH_2021-09-13_final.stac-item
2021-10-23 11:57:11	ga_s2am_ard_3-2-1_50HMH_2021-10-23_final.stac-item
2021-11-02 11:57:13	ga_s2am_ard_3-2-1_50HLH_2021-11-02_final.stac-item
2021-12-12 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2021-12-12_final.stac-item
2022-01-07 12:15:01	ga_s2am_ard_3-2-1_49JFM_2022-01-07_final.stac-item
2022-01-31 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2022-01-31_final.stac-item
2022-07-27 11:46:58	ga_s2am_ard_3-2-1_50HPJ_2022-07-27_final.stac-item
2022-09-25 11:46:55	ga_s2am_ard_3-2-1_50HPJ_2022-09-25_final.stac-item
2022-10-08 11:56:43	ga_s2am_ard_3-2-1_50HMK_2022-10-08_final.stac-item
2022-11-10 12:05:18	ga_s2am_ard_3-2-1_49JGL_2022-11-10_final.stac-item
2023-01-13 11:47:12	ga_s2am_ard_3-2-1_50HLH_2023-01-13_final.stac-item
2023-02-02 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2023-02-02_final
2023-02-12 11:47:19	ga_s2am_ard_3-2-1_50HNG_2023-02-12_final
2023-02-18 12:04:57	ga_s2am_ard_3-2-1_49JGM_2023-02-18_nrt.stac-item
2023-03-04 11:47:03	ga_s2am_ard_3-2-1_50HNH_2023-03-04_final
2023-04-03 11:46:29	ga_s2am_ard_3-2-1_50HQK_2023-04-03_final
2023-04-03 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2023-04-03_final
2023-04-06 11:56:36	ga_s2am_ard_3-2-1_50HMK_2023-04-06_final
2023-05-19 12:03:46	ga_s2am_ard_3-2-1_49KHS_2023-05-19_final
2023-05-22 12:13:57	ga_s2am_ard_3-2-1_49KHR_2023-05-22_final
2023-06-21 12:15:00	ga_s2am_ard_3-2-1_49JGM_2023-06-21_final
2023-06-29 11:37:07	ga_s2am_ard_3-2-1_50HQH_2023-06-29_final
2023-07-05 11:56:45	ga_s2am_ard_3-2-1_50HLK_2023-07-05_final
2023-09-03 11:57:11	ga_s2am_ard_3-2-1_50HMH_2023-09-03_final
2023-09-03 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-09-03_final
2023-11-22 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2023-11-22_final
2023-12-02 11:57:01	ga_s2am_ard_3-2-1_50HLH_2023-12-02_final
2023-12-06 11:37:15	ga_s2am_ard_3-2-1_50HPG_2023-12-06_final
2023-12-19 11:47:13	ga_s2am_ard_3-2-1_50HPG_2023-12-19_final
2024-01-24 12:03:53	ga_s2am_ard_3-2-1_49KHR_2024-01-24_final
2024-01-31 11:57:05	ga_s2am_ard_3-2-1_50HLH_2024-01-31_final
2024-02-03 12:03:40	ga_s2am_ard_3-2-1_49KHS_2024-02-03_final
2024-02-13 12:03:42	ga_s2am_ard_3-2-1_49KHS_2024-02-13_final
2024-03-14 12:03:44	ga_s2am_ard_3-2-1_49KHS_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

Other products

All years