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
2015-10-22 11:46:57	ga_s2am_ard_3-2-1_50HMH_2015-10-22_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50HMH_2016-04-19_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HMG_2016-07-08_final.stac-item
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50HMK_2016-08-10_final.stac-item
2016-09-02 12:03:47	ga_s2am_ard_3-2-1_49KHR_2016-09-02_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49JHM_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49JHN_2016-10-22_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HMJ_2017-02-03_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HNJ_2017-02-03_final.stac-item
2017-04-27 11:56:35	ga_s2am_ard_3-2-1_50HMH_2017-04-27_final.stac-item
2017-06-09 12:04:43	ga_s2am_ard_3-2-1_49JGN_2017-06-09_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49JGN_2017-07-09_final.stac-item
2017-08-19 11:36:41	ga_s2am_ard_3-2-1_50HQH_2017-08-19_final.stac-item
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49JGN_2017-08-21_final.stac-item
2017-09-01 11:40:44	ga_s2am_ard_3-2-1_50HPJ_2017-09-01_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JHM_2017-09-17_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49JGM_2017-09-27_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_49JHM_2017-10-17_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KHQ_2017-12-19_final.stac-item
2017-12-29 12:14:35	ga_s2am_ard_3-2-1_49JGL_2017-12-29_final.stac-item
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50HMH_2018-02-28_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49JGM_2018-03-09_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49KGR_2018-03-09_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50HMJ_2018-03-13_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50HLH_2018-04-29_final.stac-item
2018-07-05 11:35:08	ga_s2am_ard_3-2-1_50HPK_2018-07-05_final.stac-item
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49JGL_2018-07-07_final.stac-item
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HNK_2018-07-08_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGN_2018-07-14_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49JFM_2018-07-17_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49JHN_2018-07-24_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49KHQ_2018-08-06_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JKN_2018-08-10_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGM_2018-08-13_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JGK_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JGL_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49KGP_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49KHR_2018-08-23_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-09-12_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-10-05_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49KHR_2018-10-05_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HMK_2018-10-16_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49JHN_2018-10-22_final.stac-item
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_50HQK_2018-10-23_final.stac-item
2018-10-25 12:14:37	ga_s2am_ard_3-2-1_49JGM_2018-10-25_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HMH_2018-10-29_final.stac-item
2018-11-08 11:57:05	ga_s2am_ard_3-2-1_50HLH_2018-11-08_final.stac-item
2018-12-21 12:04:34	ga_s2am_ard_3-2-1_49JHN_2018-12-21_final.stac-item
2018-12-21 12:04:48	ga_s2am_ard_3-2-1_49JHM_2018-12-21_final.stac-item
2019-02-03 11:46:52	ga_s2am_ard_3-2-1_50HMJ_2019-02-03_final.stac-item
2019-02-26 11:57:01	ga_s2am_ard_3-2-1_50HMH_2019-02-26_final.stac-item
2019-03-01 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2019-03-01_final.stac-item
2019-03-11 12:04:56	ga_s2am_ard_3-2-1_49JGM_2019-03-11_final.stac-item
2019-07-10 11:37:08	ga_s2am_ard_3-2-1_50HQH_2019-07-10_final.stac-item
2019-07-22 12:15:15	ga_s2am_ard_3-2-1_49JGL_2019-07-22_final.stac-item
2019-10-14 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2019-10-14_final.stac-item
2020-02-18 11:47:08	ga_s2am_ard_3-2-1_50HLH_2020-02-18_final.stac-item
2020-05-28 11:47:01	ga_s2am_ard_3-2-1_50HMJ_2020-05-28_final.stac-item
2020-07-07 11:46:42	ga_s2am_ard_3-2-1_50HNK_2020-07-07_final.stac-item
2020-07-13 12:04:50	ga_s2am_ard_3-2-1_49JGN_2020-07-13_final.stac-item
2020-08-12 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-08-12_final.stac-item
2020-10-08 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2020-10-08_final.stac-item
2020-10-25 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-10-25_final.stac-item
2020-11-10 12:05:05	ga_s2am_ard_3-2-1_49JGM_2020-11-10_final.stac-item
2020-11-17 11:56:17	ga_s2am_ard_3-2-1_50JKM_2020-11-17_final.stac-item
2020-11-24 11:46:57	ga_s2am_ard_3-2-1_50HMJ_2020-11-24_final.stac-item
2020-12-17 11:56:38	ga_s2am_ard_3-2-1_50HLK_2020-12-17_final.stac-item
2020-12-30 12:05:00	ga_s2am_ard_3-2-1_49JGM_2020-12-30_final.stac-item
2021-01-03 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2021-01-03_final.stac-item
2021-01-09 12:04:14	ga_s2am_ard_3-2-1_49KHQ_2021-01-09_final.stac-item
2021-01-23 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2021-01-23_final.stac-item
2021-02-25 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2021-02-25_final.stac-item
2021-03-14 11:46:29	ga_s2am_ard_3-2-1_50HQK_2021-03-14_final.stac-item
2021-03-14 11:47:20	ga_s2am_ard_3-2-1_50HNG_2021-03-14_final
2021-03-31 11:36:46	ga_s2am_ard_3-2-1_50HQJ_2021-03-31_final.stac-item
2021-04-26 11:56:26	ga_s2am_ard_3-2-1_50HNK_2021-04-26_final.stac-item
2021-06-02 11:47:22	ga_s2am_ard_3-2-1_50HNG_2021-06-02_final
2021-06-28 12:05:02	ga_s2am_ard_3-2-1_49JGM_2021-06-28_final.stac-item
2021-08-17 12:05:43	ga_s2am_ard_3-2-1_50JKP_2021-08-17_final.stac-item
2021-08-27 12:04:48	ga_s2am_ard_3-2-1_49JGN_2021-08-27_final.stac-item
2021-11-19 11:47:21	ga_s2am_ard_3-2-1_50HNG_2021-11-19_final
2022-02-10 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2022-02-10_final.stac-item
2022-02-20 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-02-20_final.stac-item
2022-03-28 12:14:24	ga_s2am_ard_3-2-1_49KHP_2022-03-28_final.stac-item
2022-07-16 12:15:08	ga_s2am_ard_3-2-1_49JGM_2022-07-16_final.stac-item
2022-07-30 11:57:07	ga_s2am_ard_3-2-1_50HLJ_2022-07-30_final.stac-item
2022-10-04 12:14:48	ga_s2am_ard_3-2-1_49JGN_2022-10-04_final.stac-item
2022-10-08 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2022-10-08_final.stac-item
2022-10-08 11:57:12	ga_s2am_ard_3-2-1_50HMH_2022-10-08_final.stac-item
2022-12-17 11:57:05	ga_s2am_ard_3-2-1_50HMH_2022-12-17_final.stac-item
2023-01-13 11:47:22	ga_s2am_ard_3-2-1_50HMG_2023-01-13_final
2023-02-15 11:55:56	ga_s2am_ard_3-2-1_50JKN_2023-02-15_nrt.stac-item
2023-02-15 11:55:56	ga_s2am_ard_3-2-1_50JKN_2023-02-15_final
2023-02-28 12:06:07	ga_s2am_ard_3-2-1_50JKM_2023-02-28_final
2023-06-02 11:47:28	ga_s2am_ard_3-2-1_50HMG_2023-06-02_final
2023-06-11 12:14:02	ga_s2am_ard_3-2-1_49KGR_2023-06-11_final
2023-08-27 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-08-27_final
2023-09-30 11:46:45	ga_s2am_ard_3-2-1_50HQJ_2023-09-30_final
2023-10-03 11:56:38	ga_s2am_ard_3-2-1_50HMK_2023-10-03_final
2023-12-06 11:37:11	ga_s2am_ard_3-2-1_50HQG_2023-12-06_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