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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49JGN_2015-10-28_final.stac-item
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HPK_2015-12-08_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50JML_2016-03-20_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50HMG_2016-04-02_final
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HLK_2016-06-11_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50JKP_2016-06-11_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50JKT_2016-07-14_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_49JHN_2016-08-23_final.stac-item
2016-09-29 11:56:03	ga_s2am_ard_3-2-1_50HNK_2016-09-29_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JLQ_2016-10-09_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49JGN_2016-10-25_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50JLQ_2016-12-11_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50JML_2017-01-14_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_50JLN_2017-02-19_final.stac-item
2017-04-03 12:14:19	ga_s2am_ard_3-2-1_49JGL_2017-04-03_final.stac-item
2017-04-14 11:45:07	ga_s2am_ard_3-2-1_50HNH_2017-04-14_final.stac-item
2017-05-03 12:13:46	ga_s2am_ard_3-2-1_49KGR_2017-05-03_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49JGK_2017-05-10_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_50JLP_2017-05-10_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JLM_2017-06-06_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50HQK_2017-06-13_final.stac-item
2017-06-16 11:56:08	ga_s2am_ard_3-2-1_50HLK_2017-06-16_final.stac-item
2017-06-16 11:56:08	ga_s2am_ard_3-2-1_50JLL_2017-06-16_final.stac-item
2017-11-23 11:56:04	ga_s2am_ard_3-2-1_50HLK_2017-11-23_final.stac-item
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50JML_2018-02-11_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50HNK_2018-04-12_final.stac-item
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_50JLP_2018-05-05_final.stac-item
2018-07-28 11:45:46	ga_s2am_ard_3-2-1_50HMH_2018-07-28_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JML_2018-09-26_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50HPJ_2018-10-26_final.stac-item
2019-01-20 12:04:39	ga_s2am_ard_3-2-1_50JKT_2019-01-20_final.stac-item
2019-01-20 12:05:48	ga_s2am_ard_3-2-1_50JLN_2019-01-20_final.stac-item
2019-01-21 11:36:48	ga_s2am_ard_3-2-1_50HPJ_2019-01-21_final.stac-item
2019-01-30 12:05:34	ga_s2am_ard_3-2-1_50JLP_2019-01-30_final.stac-item
2019-02-10 11:36:31	ga_s2am_ard_3-2-1_50HQK_2019-02-10_final.stac-item
2019-03-01 12:05:33	ga_s2am_ard_3-2-1_50JLP_2019-03-01_final.stac-item
2019-05-14 11:47:10	ga_s2am_ard_3-2-1_50HNH_2019-05-14_final.stac-item
2019-05-17 11:55:45	ga_s2am_ard_3-2-1_50JLP_2019-05-17_final.stac-item
2019-05-17 11:56:44	ga_s2am_ard_3-2-1_50HLK_2019-05-17_final.stac-item
2019-05-30 12:04:30	ga_s2am_ard_3-2-1_49KHP_2019-05-30_final.stac-item
2019-06-13 11:46:33	ga_s2am_ard_3-2-1_50HQK_2019-06-13_final.stac-item
2019-07-16 11:56:31	ga_s2am_ard_3-2-1_50JLL_2019-07-16_final.stac-item
2019-07-19 12:05:57	ga_s2am_ard_3-2-1_50JLN_2019-07-19_final.stac-item
2019-09-10 12:15:09	ga_s2am_ard_3-2-1_49JGL_2019-09-10_final.stac-item
2020-01-05 12:04:34	ga_s2am_ard_3-2-1_50JLT_2020-01-05_final.stac-item
2020-02-08 11:46:54	ga_s2am_ard_3-2-1_50HPH_2020-02-08_final.stac-item
2020-02-11 11:56:58	ga_s2am_ard_3-2-1_50HMH_2020-02-11_final.stac-item
2020-04-17 12:15:00	ga_s2am_ard_3-2-1_49JFM_2020-04-17_final.stac-item
2020-07-03 12:05:42	ga_s2am_ard_3-2-1_50JLP_2020-07-03_final.stac-item
2020-07-27 11:46:35	ga_s2am_ard_3-2-1_50HQK_2020-07-27_final.stac-item
2020-07-30 11:55:52	ga_s2am_ard_3-2-1_50JKP_2020-07-30_final.stac-item
2020-09-14 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2020-09-14_final.stac-item
2020-10-01 12:05:35	ga_s2am_ard_3-2-1_49JGK_2020-10-01_final.stac-item
2020-11-04 11:46:17	ga_s2am_ard_3-2-1_50JMM_2020-11-04_final.stac-item
2020-12-10 12:04:54	ga_s2am_ard_3-2-1_50JKS_2020-12-10_final.stac-item
2021-01-09 12:04:28	ga_s2am_ard_3-2-1_49KHP_2021-01-09_final.stac-item
2021-03-14 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2021-03-14_final.stac-item
2021-03-17 11:56:07	ga_s2am_ard_3-2-1_50JMM_2021-03-17_final.stac-item
2021-04-19 12:05:11	ga_s2am_ard_3-2-1_49JGL_2021-04-19_final.stac-item
2021-05-20 11:37:21	ga_s2am_ard_3-2-1_50HPG_2021-05-20_final
2021-08-20 12:14:00	ga_s2am_ard_3-2-1_49KGR_2021-08-20_final.stac-item
2021-09-16 12:04:41	ga_s2am_ard_3-2-1_50JLT_2021-09-16_final.stac-item
2021-10-03 11:57:25	ga_s2am_ard_3-2-1_50HMG_2021-10-03_final
2021-11-25 12:05:38	ga_s2am_ard_3-2-1_50JLP_2021-11-25_final.stac-item
2021-12-02 11:56:22	ga_s2am_ard_3-2-1_50JML_2021-12-02_final.stac-item
2021-12-08 12:14:11	ga_s2am_ard_3-2-1_49KGQ_2021-12-08_final.stac-item
2022-01-14 12:04:43	ga_s2am_ard_3-2-1_49JHN_2022-01-14_final.stac-item
2022-01-18 11:47:07	ga_s2am_ard_3-2-1_50HNH_2022-01-18_final.stac-item
2022-02-03 12:05:37	ga_s2am_ard_3-2-1_50JLP_2022-02-03_final.stac-item
2022-02-17 11:47:03	ga_s2am_ard_3-2-1_50HPH_2022-02-17_final.stac-item
2022-05-01 11:55:51	ga_s2am_ard_3-2-1_50JKP_2022-05-01_final.stac-item
2022-05-04 12:04:47	ga_s2am_ard_3-2-1_50JKT_2022-05-04_final.stac-item
2022-05-21 11:56:28	ga_s2am_ard_3-2-1_50JML_2022-05-21_final.stac-item
2022-07-03 12:04:31	ga_s2am_ard_3-2-1_49KGQ_2022-07-03_final.stac-item
2022-07-03 12:06:04	ga_s2am_ard_3-2-1_50JLN_2022-07-03_final.stac-item
2022-08-19 11:56:24	ga_s2am_ard_3-2-1_50JLM_2022-08-19_final.stac-item
2022-09-01 12:05:50	ga_s2am_ard_3-2-1_50JLP_2022-09-01_final.stac-item
2022-10-08 11:56:14	ga_s2am_ard_3-2-1_50JMM_2022-10-08_final.stac-item
2022-10-08 11:56:28	ga_s2am_ard_3-2-1_50JML_2022-10-08_final.stac-item
2022-10-08 11:56:32	ga_s2am_ard_3-2-1_50JLL_2022-10-08_final.stac-item
2022-11-24 11:46:33	ga_s2am_ard_3-2-1_50HPK_2022-11-24_final.stac-item
2022-12-24 11:46:46	ga_s2am_ard_3-2-1_50HPJ_2022-12-24_final.stac-item
2023-01-09 12:05:50	ga_s2am_ard_3-2-1_50JLN_2023-01-09_final.stac-item
2023-03-07 11:56:36	ga_s2am_ard_3-2-1_50HLK_2023-03-07_final
2023-04-16 11:57:05	ga_s2am_ard_3-2-1_50HMH_2023-04-16_final
2023-05-03 11:46:30	ga_s2am_ard_3-2-1_50HQK_2023-05-03_final
2023-08-24 11:56:28	ga_s2am_ard_3-2-1_50JML_2023-08-24_final
2023-11-12 11:56:36	ga_s2am_ard_3-2-1_50HMK_2023-11-12_final
2023-11-19 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-11-19_final
2023-12-06 11:36:45	ga_s2am_ard_3-2-1_50HPJ_2023-12-06_final
2023-12-09 11:46:28	ga_s2am_ard_3-2-1_50HPK_2023-12-09_final
2023-12-09 11:47:09	ga_s2am_ard_3-2-1_50HLH_2023-12-09_final
2024-01-14 12:04:12	ga_s2am_ard_3-2-1_49KGQ_2024-01-14_final
2024-01-21 11:56:58	ga_s2am_ard_3-2-1_50HMH_2024-01-21_final
2024-02-20 11:57:07	ga_s2am_ard_3-2-1_50HLH_2024-02-20_final
2024-03-21 11:56:36	ga_s2am_ard_3-2-1_50HMK_2024-03-21_final
2024-04-07 11:46:41	ga_s2am_ard_3-2-1_50HQJ_2024-04-07_final
2024-04-07 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2024-04-07_final
2024-04-10 11:56:22	ga_s2am_ard_3-2-1_50JML_2024-04-10_final
2024-04-13 12:04:47	ga_s2am_ard_3-2-1_49JGN_2024-04-13_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