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
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_50HPH_2015-11-21_final.stac-item
2016-02-08 12:10:34	ga_s2am_ard_3-2-1_49JFM_2016-02-08_final.stac-item
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49KGP_2016-03-09_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KGP_2016-05-18_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JMM_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JNL_2016-05-22_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HPJ_2016-06-18_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49JGL_2016-07-14_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50JLT_2016-07-14_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50HMK_2016-07-21_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HMK_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HNK_2016-10-26_final.stac-item
2017-04-11 11:36:02	ga_s2am_ard_3-2-1_50JQL_2017-04-11_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50HQK_2017-05-04_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JKN_2017-06-06_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HLH_2017-10-31_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50HLK_2017-12-03_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_50HMJ_2018-03-10_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50JPL_2018-03-30_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49JGN_2018-04-05_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_49JGL_2018-04-25_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HNK_2018-05-29_final.stac-item
2018-08-26 12:13:20	ga_s2am_ard_3-2-1_49KHR_2018-08-26_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JNM_2018-09-09_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-09-12_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-09-12_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-10-02_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49KHP_2018-10-02_final.stac-item
2018-11-15 11:47:04	ga_s2am_ard_3-2-1_50HMH_2018-11-15_final.stac-item
2018-12-05 11:46:47	ga_s2am_ard_3-2-1_50HMJ_2018-12-05_final.stac-item
2018-12-25 11:46:05	ga_s2am_ard_3-2-1_50JMM_2018-12-25_final.stac-item
2018-12-31 12:05:45	ga_s2am_ard_3-2-1_50JLN_2018-12-31_final.stac-item
2019-02-19 12:04:42	ga_s2am_ard_3-2-1_49JGN_2019-02-19_final.stac-item
2019-03-05 11:45:48	ga_s2am_ard_3-2-1_50JNN_2019-03-05_final.stac-item
2019-05-07 11:56:29	ga_s2am_ard_3-2-1_50JLL_2019-05-07_final.stac-item
2019-05-30 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-05-30_final.stac-item
2019-08-05 11:55:39	ga_s2am_ard_3-2-1_50JNP_2019-08-05_final.stac-item
2019-08-08 12:04:03	ga_s2am_ard_3-2-1_49KHR_2019-08-08_final.stac-item
2019-09-11 11:46:21	ga_s2am_ard_3-2-1_50JNL_2019-09-11_final.stac-item
2020-01-29 11:46:26	ga_s2am_ard_3-2-1_50HPK_2020-01-29_final.stac-item
2020-02-08 11:47:06	ga_s2am_ard_3-2-1_50HLH_2020-02-08_final.stac-item
2020-02-18 11:45:48	ga_s2am_ard_3-2-1_50JNN_2020-02-18_final.stac-item
2020-02-28 11:45:42	ga_s2am_ard_3-2-1_50JQN_2020-02-28_final.stac-item
2020-03-02 11:57:05	ga_s2am_ard_3-2-1_50HLH_2020-03-02_final.stac-item
2020-03-18 12:14:23	ga_s2am_ard_3-2-1_49KGP_2020-03-18_final.stac-item
2020-03-19 11:46:15	ga_s2am_ard_3-2-1_50JPL_2020-03-19_final.stac-item
2020-05-05 11:36:30	ga_s2am_ard_3-2-1_50JPL_2020-05-05_final.stac-item
2020-05-18 11:46:31	ga_s2am_ard_3-2-1_50JML_2020-05-18_final.stac-item
2020-06-27 11:46:25	ga_s2am_ard_3-2-1_50JPL_2020-06-27_final.stac-item
2020-08-02 12:04:05	ga_s2am_ard_3-2-1_50KKA_2020-08-02_final.stac-item
2020-09-14 12:13:58	ga_s2am_ard_3-2-1_50KKA_2020-09-14_final.stac-item
2020-10-01 12:05:57	ga_s2am_ard_3-2-1_50JLN_2020-10-01_final.stac-item
2020-11-13 12:13:58	ga_s2am_ard_3-2-1_50KKA_2020-11-13_final.stac-item
2020-11-30 12:04:31	ga_s2am_ard_3-2-1_49KGP_2020-11-30_final.stac-item
2020-12-03 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2020-12-03_final.stac-item
2020-12-27 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2020-12-27_final.stac-item
2021-01-02 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-01-02_final.stac-item
2021-01-02 12:14:27	ga_s2am_ard_3-2-1_49KGP_2021-01-02_final.stac-item
2021-01-06 11:57:06	ga_s2am_ard_3-2-1_50HMH_2021-01-06_final.stac-item
2021-01-16 11:56:15	ga_s2am_ard_3-2-1_50JKM_2021-01-16_final.stac-item
2021-01-26 11:56:41	ga_s2am_ard_3-2-1_50HLK_2021-01-26_final.stac-item
2021-02-25 11:55:46	ga_s2am_ard_3-2-1_50JKP_2021-02-25_final.stac-item
2021-04-16 11:55:21	ga_s2am_ard_3-2-1_50JLQ_2021-04-16_final.stac-item
2021-07-02 11:46:28	ga_s2am_ard_3-2-1_50JML_2021-07-02_final.stac-item
2021-08-11 11:46:11	ga_s2am_ard_3-2-1_50JNM_2021-08-11_final.stac-item
2021-11-08 12:14:01	ga_s2am_ard_3-2-1_49KGR_2021-11-08_final.stac-item
2022-01-08 11:46:49	ga_s2am_ard_3-2-1_50HPJ_2022-01-08_final.stac-item
2022-02-20 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2022-02-20_final.stac-item
2022-03-08 12:15:04	ga_s2am_ard_3-2-1_49JFM_2022-03-08_final.stac-item
2022-03-18 12:15:00	ga_s2am_ard_3-2-1_49JGM_2022-03-18_final.stac-item
2022-03-22 11:56:29	ga_s2am_ard_3-2-1_50JLL_2022-03-22_final.stac-item
2022-05-15 11:36:38	ga_s2am_ard_3-2-1_50HQK_2022-05-15_final.stac-item
2022-05-21 11:54:47	ga_s2am_ard_3-2-1_50JMT_2022-05-21_final.stac-item
2022-06-17 11:46:30	ga_s2am_ard_3-2-1_50JPL_2022-06-17_final.stac-item
2022-07-24 11:37:13	ga_s2am_ard_3-2-1_50HQH_2022-07-24_final.stac-item
2022-07-30 11:57:05	ga_s2am_ard_3-2-1_50HMJ_2022-07-30_final.stac-item
2022-08-19 11:56:20	ga_s2am_ard_3-2-1_50JMM_2022-08-19_final.stac-item
2022-08-22 12:04:11	ga_s2am_ard_3-2-1_50KKA_2022-08-22_final.stac-item
2022-09-24 12:14:48	ga_s2am_ard_3-2-1_49JGN_2022-09-24_final.stac-item
2022-12-20 12:04:38	ga_s2am_ard_3-2-1_50JLT_2022-12-20_final.stac-item
2023-01-13 11:46:35	ga_s2am_ard_3-2-1_50HNK_2023-01-13_final.stac-item
2023-05-13 11:47:14	ga_s2am_ard_3-2-1_50HLH_2023-05-13_final
2023-06-12 11:47:10	ga_s2am_ard_3-2-1_50HNH_2023-06-12_final
2023-09-16 12:05:55	ga_s2am_ard_3-2-1_50JLN_2023-09-16_final
2023-10-09 12:14:41	ga_s2am_ard_3-2-1_49JGN_2023-10-09_final
2023-10-23 11:56:08	ga_s2am_ard_3-2-1_50JMM_2023-10-23_final
2023-10-29 12:14:41	ga_s2am_ard_3-2-1_49JGN_2023-10-29_final
2023-11-02 11:55:49	ga_s2am_ard_3-2-1_50JLN_2023-11-02_final
2023-11-25 12:04:37	ga_s2am_ard_3-2-1_50JKT_2023-11-25_final
2023-11-29 11:46:35	ga_s2am_ard_3-2-1_50HQJ_2023-11-29_final
2023-12-12 11:55:42	ga_s2am_ard_3-2-1_50JKP_2023-12-12_final
2023-12-15 12:05:47	ga_s2am_ard_3-2-1_50JLN_2023-12-15_final
2023-12-16 11:37:03	ga_s2am_ard_3-2-1_50HPH_2023-12-16_final
2024-01-15 11:36:13	ga_s2am_ard_3-2-1_50JQL_2024-01-15_final
2024-01-18 11:46:34	ga_s2am_ard_3-2-1_50HQJ_2024-01-18_final
2024-02-07 11:44:45	ga_s2am_ard_3-2-1_50JQS_2024-02-07_final
2024-02-17 11:46:28	ga_s2am_ard_3-2-1_50HQK_2024-02-17_final
2024-02-23 12:05:13	ga_s2am_ard_3-2-1_49JGL_2024-02-23_final
2024-03-04 12:05:01	ga_s2am_ard_3-2-1_49JGM_2024-03-04_final
2024-03-31 11:55:45	ga_s2am_ard_3-2-1_50JKP_2024-03-31_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

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