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
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_50JKS_2015-12-07_final.stac-item
2015-12-30 12:16:05	ga_s2am_ard_3-2-1_49KGR_2015-12-30_final.stac-item
2016-05-12 11:56:32	ga_s2am_ard_3-2-1_50HNK_2016-05-12_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50HQH_2016-05-16_final.stac-item
2016-05-28 12:13:49	ga_s2am_ard_3-2-1_49KHR_2016-05-28_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50HLH_2016-07-21_final.stac-item
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50JKP_2016-08-10_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HNJ_2016-11-05_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HNG_2016-11-15_final
2017-01-04 11:46:21	ga_s2am_ard_3-2-1_50HNK_2017-01-04_final.stac-item
2017-03-04 12:14:35	ga_s2am_ard_3-2-1_49JGL_2017-03-04_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HQK_2017-07-03_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_50JKR_2017-07-29_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50JLM_2017-10-24_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HPK_2017-10-31_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50HPK_2017-11-20_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50HPH_2017-12-10_final.stac-item
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49KGP_2018-01-08_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_49JGN_2018-01-28_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HNH_2018-02-18_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HNK_2018-02-18_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_49KGP_2018-03-26_final.stac-item
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50HLJ_2018-04-02_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50HNK_2018-04-12_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_49KHP_2018-04-15_final.stac-item
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_49JGL_2018-05-15_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HPK_2018-05-19_final.stac-item
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49JGM_2018-06-17_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKS_2018-06-24_final.stac-item
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HQH_2018-07-08_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49KGP_2018-09-25_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50HLJ_2018-10-09_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-10-22_final.stac-item
2018-12-24 12:14:19	ga_s2am_ard_3-2-1_49KGP_2018-12-24_final.stac-item
2019-03-15 11:46:44	ga_s2am_ard_3-2-1_50HPJ_2019-03-15_final.stac-item
2019-05-24 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-05-24_final.stac-item
2019-09-27 12:04:29	ga_s2am_ard_3-2-1_49KHP_2019-09-27_final.stac-item
2019-10-08 11:37:09	ga_s2am_ard_3-2-1_50HPH_2019-10-08_final.stac-item
2019-11-17 11:36:53	ga_s2am_ard_3-2-1_50HPJ_2019-11-17_final.stac-item
2019-11-19 12:14:43	ga_s2am_ard_3-2-1_49JGN_2019-11-19_final.stac-item
2019-12-03 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2019-12-03_final.stac-item
2019-12-20 11:46:42	ga_s2am_ard_3-2-1_50HPJ_2019-12-20_final.stac-item
2019-12-23 11:55:50	ga_s2am_ard_3-2-1_50JLN_2019-12-23_final.stac-item
2020-01-18 12:14:35	ga_s2am_ard_3-2-1_49JGN_2020-01-18_final.stac-item
2020-03-22 11:56:36	ga_s2am_ard_3-2-1_50HLK_2020-03-22_final.stac-item
2020-04-07 12:14:24	ga_s2am_ard_3-2-1_49KGP_2020-04-07_final.stac-item
2020-05-14 12:04:51	ga_s2am_ard_3-2-1_49JGN_2020-05-14_final.stac-item
2020-07-23 12:04:12	ga_s2am_ard_3-2-1_49KHR_2020-07-23_final.stac-item
2020-07-23 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-07-23_final.stac-item
2020-09-05 11:46:45	ga_s2am_ard_3-2-1_50HMK_2020-09-05_final.stac-item
2020-09-18 11:57:10	ga_s2am_ard_3-2-1_50HMH_2020-09-18_final.stac-item
2020-10-24 12:14:32	ga_s2am_ard_3-2-1_49KGP_2020-10-24_final.stac-item
2021-02-21 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2021-02-21_final.stac-item
2021-03-14 11:46:37	ga_s2am_ard_3-2-1_50HNK_2021-03-14_final.stac-item
2021-03-27 11:55:54	ga_s2am_ard_3-2-1_50JLN_2021-03-27_final.stac-item
2021-04-22 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2021-04-22_final.stac-item
2021-06-02 11:47:25	ga_s2am_ard_3-2-1_50HMG_2021-06-02_final
2021-08-17 12:05:13	ga_s2am_ard_3-2-1_49JGL_2021-08-17_final.stac-item
2021-09-06 12:05:30	ga_s2am_ard_3-2-1_49JGK_2021-09-06_final.stac-item
2021-09-20 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2021-09-20_final.stac-item
2021-09-23 11:55:49	ga_s2am_ard_3-2-1_50JKP_2021-09-23_final.stac-item
2021-09-26 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-09-26_final
2021-10-03 11:57:14	ga_s2am_ard_3-2-1_50HLH_2021-10-03_final.stac-item
2022-02-04 11:36:34	ga_s2am_ard_3-2-1_50HQK_2022-02-04_final.stac-item
2022-03-12 11:56:00	ga_s2am_ard_3-2-1_50JLN_2022-03-12_final.stac-item
2022-03-22 11:56:43	ga_s2am_ard_3-2-1_50HLK_2022-03-22_final.stac-item
2022-04-18 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2022-04-18_final.stac-item
2022-05-15 11:36:42	ga_s2am_ard_3-2-1_50HPK_2022-05-15_final.stac-item
2022-05-24 12:05:04	ga_s2am_ard_3-2-1_50JKS_2022-05-24_final.stac-item
2022-05-25 11:36:41	ga_s2am_ard_3-2-1_50HQK_2022-05-25_final.stac-item
2022-06-03 12:05:23	ga_s2am_ard_3-2-1_49JGL_2022-06-03_final.stac-item
2022-06-23 12:04:39	ga_s2am_ard_3-2-1_49KHP_2022-06-23_final.stac-item
2022-07-10 11:57:04	ga_s2am_ard_3-2-1_50HMJ_2022-07-10_final.stac-item
2022-07-24 11:37:13	ga_s2am_ard_3-2-1_50HQH_2022-07-24_final.stac-item
2022-07-26 12:15:20	ga_s2am_ard_3-2-1_49JGL_2022-07-26_final.stac-item
2022-10-28 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-10-28_final.stac-item
2023-01-26 11:56:23	ga_s2am_ard_3-2-1_50JLL_2023-01-26_final.stac-item
2023-02-12 11:47:05	ga_s2am_ard_3-2-1_50HNH_2023-02-12_nrt.stac-item
2023-04-16 11:57:09	ga_s2am_ard_3-2-1_50HLH_2023-04-16_final
2023-04-30 11:37:21	ga_s2am_ard_3-2-1_50HPG_2023-04-30_final
2023-05-03 11:47:24	ga_s2am_ard_3-2-1_50HMG_2023-05-03_final
2023-05-16 11:56:26	ga_s2am_ard_3-2-1_50JLL_2023-05-16_final
2023-05-26 11:55:50	ga_s2am_ard_3-2-1_50JKP_2023-05-26_final
2023-06-22 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2023-06-22_final
2023-06-25 11:57:09	ga_s2am_ard_3-2-1_50HMH_2023-06-25_final
2023-07-18 12:04:04	ga_s2am_ard_3-2-1_49KHR_2023-07-18_final
2023-08-24 11:56:20	ga_s2am_ard_3-2-1_50JKM_2023-08-24_final
2023-08-31 11:46:39	ga_s2am_ard_3-2-1_50HPK_2023-08-31_final
2023-08-31 11:46:43	ga_s2am_ard_3-2-1_50HNK_2023-08-31_final
2023-08-31 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2023-08-31_final
2023-09-10 11:47:26	ga_s2am_ard_3-2-1_50HNG_2023-09-10_final
2023-10-10 11:46:40	ga_s2am_ard_3-2-1_50HMK_2023-10-10_final
2023-10-16 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-10-16_final
2023-10-20 11:46:37	ga_s2am_ard_3-2-1_50HNK_2023-10-20_final
2023-11-19 11:47:12	ga_s2am_ard_3-2-1_50HLH_2023-11-19_final
2024-01-25 11:37:11	ga_s2am_ard_3-2-1_50HQG_2024-01-25_final
2024-03-31 11:56:39	ga_s2am_ard_3-2-1_50HLK_2024-03-31_final
2024-04-07 11:46:36	ga_s2am_ard_3-2-1_50HNK_2024-04-07_final
2024-04-20 11:56:14	ga_s2am_ard_3-2-1_50JLM_2024-04-20_final
2024-04-20 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2024-04-20_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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