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
2015-10-05 11:56:28	ga_s2am_ard_3-2-1_50HMK_2015-10-05_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HMH_2016-03-20_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50HNG_2016-09-06_final
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_49KGQ_2016-09-15_final.stac-item
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_49KHR_2016-09-15_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_49KHP_2017-01-30_final.stac-item
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_50JKQ_2017-03-11_final.stac-item
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50HMK_2017-05-24_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50JLM_2017-06-19_final.stac-item
2017-07-19 12:04:43	ga_s2am_ard_3-2-1_49JHM_2017-07-19_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HQJ_2017-10-31_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_50JLP_2017-11-06_final.stac-item
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50HNK_2017-11-13_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50HMH_2017-12-30_final.stac-item
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49KGQ_2018-01-08_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGL_2018-03-06_final.stac-item
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50JLL_2018-03-23_final.stac-item
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_49KGP_2018-04-08_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49JGL_2018-04-28_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HLH_2018-05-12_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JGL_2018-06-24_final.stac-item
2018-06-25 11:32:58	ga_s2am_ard_3-2-1_50HPH_2018-06-25_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50HNH_2018-06-28_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50HNJ_2018-06-28_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KHR_2018-07-27_final.stac-item
2018-07-28 11:45:46	ga_s2am_ard_3-2-1_50HMH_2018-07-28_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JLL_2018-08-10_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50HMK_2018-08-27_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49KHP_2018-10-02_final.stac-item
2018-11-08 11:55:48	ga_s2am_ard_3-2-1_50JLN_2018-11-08_final.stac-item
2019-01-20 12:05:34	ga_s2am_ard_3-2-1_50JLP_2019-01-20_final.stac-item
2019-02-09 12:05:34	ga_s2am_ard_3-2-1_50JLP_2019-02-09_final.stac-item
2019-03-11 12:05:33	ga_s2am_ard_3-2-1_50JLP_2019-03-11_final.stac-item
2019-03-25 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2019-03-25_final.stac-item
2019-03-28 11:56:40	ga_s2am_ard_3-2-1_50HLK_2019-03-28_final.stac-item
2019-04-20 12:05:00	ga_s2am_ard_3-2-1_50JKS_2019-04-20_final.stac-item
2019-05-10 12:05:19	ga_s2am_ard_3-2-1_49JGL_2019-05-10_final.stac-item
2019-05-27 11:56:33	ga_s2am_ard_3-2-1_50HNK_2019-05-27_final.stac-item
2019-06-19 12:05:41	ga_s2am_ard_3-2-1_50JLP_2019-06-19_final.stac-item
2019-07-03 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2019-07-03_final.stac-item
2019-07-03 11:47:11	ga_s2am_ard_3-2-1_50HNH_2019-07-03_final.stac-item
2019-10-20 12:14:44	ga_s2am_ard_3-2-1_49JGN_2019-10-20_final.stac-item
2019-12-13 11:57:01	ga_s2am_ard_3-2-1_50HMH_2019-12-13_final.stac-item
2020-02-11 11:56:58	ga_s2am_ard_3-2-1_50HMH_2020-02-11_final.stac-item
2020-03-09 11:46:44	ga_s2am_ard_3-2-1_50HPJ_2020-03-09_final.stac-item
2020-04-08 11:46:49	ga_s2am_ard_3-2-1_50HNJ_2020-04-08_final.stac-item
2020-06-16 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-06-16_final.stac-item
2020-07-03 12:05:01	ga_s2am_ard_3-2-1_49JHM_2020-07-03_final.stac-item
2020-07-10 11:56:30	ga_s2am_ard_3-2-1_50JLL_2020-07-10_final.stac-item
2020-07-20 11:56:19	ga_s2am_ard_3-2-1_50JKM_2020-07-20_final.stac-item
2020-08-02 12:05:43	ga_s2am_ard_3-2-1_50JLP_2020-08-02_final.stac-item
2020-08-25 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-08-25_final.stac-item
2020-09-25 11:47:15	ga_s2am_ard_3-2-1_50HMH_2020-09-25_final.stac-item
2020-10-12 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2020-10-12_final.stac-item
2020-10-25 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2020-10-25_final.stac-item
2021-01-13 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2021-01-13_final.stac-item
2021-01-23 11:46:49	ga_s2am_ard_3-2-1_50HPJ_2021-01-23_final.stac-item
2021-05-23 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2021-05-23_final.stac-item
2021-06-25 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-06-25_final
2021-07-15 11:55:45	ga_s2am_ard_3-2-1_50JLP_2021-07-15_final.stac-item
2021-08-10 12:14:24	ga_s2am_ard_3-2-1_49KHP_2021-08-10_final.stac-item
2021-08-14 11:55:44	ga_s2am_ard_3-2-1_50JLP_2021-08-14_final.stac-item
2021-11-25 12:04:13	ga_s2am_ard_3-2-1_49KHQ_2021-11-25_final.stac-item
2021-12-22 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-12-22_final
2021-12-26 11:36:39	ga_s2am_ard_3-2-1_50HPK_2021-12-26_final.stac-item
2022-01-18 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2022-01-18_final.stac-item
2022-01-18 11:47:10	ga_s2am_ard_3-2-1_50HMH_2022-01-18_final.stac-item
2022-01-28 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2022-01-28_final.stac-item
2022-02-23 12:04:25	ga_s2am_ard_3-2-1_49KGQ_2022-02-23_final.stac-item
2022-08-02 12:04:53	ga_s2am_ard_3-2-1_50JKT_2022-08-02_final.stac-item
2022-08-12 12:05:50	ga_s2am_ard_3-2-1_50JLP_2022-08-12_final.stac-item
2022-10-08 11:55:53	ga_s2am_ard_3-2-1_50JKP_2022-10-08_final.stac-item
2022-11-10 12:06:08	ga_s2am_ard_3-2-1_50JLM_2022-11-10_final.stac-item
2022-12-07 11:56:37	ga_s2am_ard_3-2-1_50HMK_2022-12-07_final.stac-item
2023-01-16 11:55:43	ga_s2am_ard_3-2-1_50JKP_2023-01-16_final.stac-item
2023-01-20 11:36:47	ga_s2am_ard_3-2-1_50HPJ_2023-01-20_final.stac-item
2023-02-02 11:47:01	ga_s2am_ard_3-2-1_50HPH_2023-02-02_final
2023-02-12 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2023-02-12_nrt.stac-item
2023-02-12 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2023-02-12_final
2023-02-12 11:47:00	ga_s2am_ard_3-2-1_50HPH_2023-02-12_nrt.stac-item
2023-02-12 11:47:00	ga_s2am_ard_3-2-1_50HPH_2023-02-12_final
2023-02-19 11:36:35	ga_s2am_ard_3-2-1_50HPK_2023-02-19_nrt.stac-item
2023-02-19 11:36:35	ga_s2am_ard_3-2-1_50HPK_2023-02-19_final
2023-03-14 11:46:45	ga_s2am_ard_3-2-1_50HPJ_2023-03-14_final
2023-03-27 11:56:35	ga_s2am_ard_3-2-1_50HMK_2023-03-27_final
2023-04-29 12:03:45	ga_s2am_ard_3-2-1_49KHS_2023-04-29_final
2023-05-19 12:03:46	ga_s2am_ard_3-2-1_49KHS_2023-05-19_final
2023-06-08 12:04:46	ga_s2am_ard_3-2-1_50JKT_2023-06-08_final
2023-06-18 12:06:04	ga_s2am_ard_3-2-1_50JLM_2023-06-18_final
2023-07-05 11:56:35	ga_s2am_ard_3-2-1_50HNK_2023-07-05_final
2023-08-31 11:47:22	ga_s2am_ard_3-2-1_50HPG_2023-08-31_final
2023-09-16 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2023-09-16_final
2023-09-16 12:04:46	ga_s2am_ard_3-2-1_49JHN_2023-09-16_final
2023-09-27 11:37:09	ga_s2am_ard_3-2-1_50HPH_2023-09-27_final
2023-12-12 11:57:08	ga_s2am_ard_3-2-1_50HKH_2023-12-12_final
2024-01-18 11:47:08	ga_s2am_ard_3-2-1_50HPG_2024-01-18_final
2024-01-21 11:56:58	ga_s2am_ard_3-2-1_50HMH_2024-01-21_final
2024-04-03 12:03:42	ga_s2am_ard_3-2-1_49KHS_2024-04-03_final
2024-04-04 11:37:18	ga_s2am_ard_3-2-1_50HPG_2024-04-04_final
2024-04-07 11:46:41	ga_s2am_ard_3-2-1_50HQJ_2024-04-07_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