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_50HPH_2015-10-22_final.stac-item
2015-11-27 12:04:51	ga_s2am_ard_3-2-1_49JGM_2015-11-27_final.stac-item
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50JQN_2016-02-19_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50JKN_2016-05-15_final.stac-item
2016-05-25 12:04:47	ga_s2am_ard_3-2-1_49JGL_2016-05-25_final.stac-item
2016-08-06 12:13:25	ga_s2am_ard_3-2-1_49JGL_2016-08-06_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JML_2016-08-30_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JNM_2016-08-30_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_49KHR_2017-02-19_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50HPH_2017-03-25_final.stac-item
2017-07-10 11:34:59	ga_s2am_ard_3-2-1_50HPH_2017-07-10_final.stac-item
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50HLH_2017-10-04_final.stac-item
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50JLP_2017-12-23_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_50JKT_2018-01-25_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JLN_2018-02-21_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-02-24_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50JLN_2018-03-03_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_50HPH_2018-03-17_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JMM_2018-06-18_final.stac-item
2018-08-04 11:32:40	ga_s2am_ard_3-2-1_50HQJ_2018-08-04_final.stac-item
2018-08-07 11:46:07	ga_s2am_ard_3-2-1_50HNK_2018-08-07_final.stac-item
2019-02-26 11:56:09	ga_s2am_ard_3-2-1_50JKM_2019-02-26_final.stac-item
2019-04-07 11:57:10	ga_s2am_ard_3-2-1_50HLH_2019-04-07_final.stac-item
2019-04-14 11:46:46	ga_s2am_ard_3-2-1_50HQJ_2019-04-14_final.stac-item
2019-05-04 11:47:10	ga_s2am_ard_3-2-1_50HNH_2019-05-04_final.stac-item
2019-05-13 12:13:43	ga_s2am_ard_3-2-1_50KKB_2019-05-13_final.stac-item
2019-06-19 12:06:13	ga_s2am_ard_3-2-1_50JKM_2019-06-19_final.stac-item
2019-09-01 11:46:34	ga_s2am_ard_3-2-1_50HPK_2019-09-01_final.stac-item
2019-09-04 11:56:14	ga_s2am_ard_3-2-1_50JKM_2019-09-04_final.stac-item
2019-09-07 12:03:43	ga_s2am_ard_3-2-1_50KKB_2019-09-07_final.stac-item
2019-09-27 12:05:02	ga_s2am_ard_3-2-1_49JGM_2019-09-27_final.stac-item
2019-11-16 12:04:00	ga_s2am_ard_3-2-1_50KKA_2019-11-16_final.stac-item
2019-12-10 11:46:40	ga_s2am_ard_3-2-1_50HQJ_2019-12-10_final.stac-item
2019-12-26 12:05:38	ga_s2am_ard_3-2-1_49JGJ_2019-12-26_final.stac-item
2019-12-30 11:46:57	ga_s2am_ard_3-2-1_50HPH_2019-12-30_final.stac-item
2020-02-01 11:56:22	ga_s2am_ard_3-2-1_50HNK_2020-02-01_final.stac-item
2020-03-18 12:13:50	ga_s2am_ard_3-2-1_50KKA_2020-03-18_final.stac-item
2020-06-07 11:46:44	ga_s2am_ard_3-2-1_50HNK_2020-06-07_final.stac-item
2020-06-30 11:56:09	ga_s2am_ard_3-2-1_50JNM_2020-06-30_final.stac-item
2020-07-23 12:03:49	ga_s2am_ard_3-2-1_50KKB_2020-07-23_final.stac-item
2020-08-12 12:04:05	ga_s2am_ard_3-2-1_50KKA_2020-08-12_final.stac-item
2020-08-22 12:04:48	ga_s2am_ard_3-2-1_50JKT_2020-08-22_final.stac-item
2020-08-22 12:05:20	ga_s2am_ard_3-2-1_49JGL_2020-08-22_final.stac-item
2020-08-23 11:37:12	ga_s2am_ard_3-2-1_50HPH_2020-08-23_final.stac-item
2020-08-29 11:56:23	ga_s2am_ard_3-2-1_50JNL_2020-08-29_final.stac-item
2020-08-29 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2020-08-29_final.stac-item
2020-09-14 12:14:31	ga_s2am_ard_3-2-1_49KGP_2020-09-14_final.stac-item
2020-10-31 12:03:49	ga_s2am_ard_3-2-1_50KKB_2020-10-31_final.stac-item
2020-12-04 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2020-12-04_final.stac-item
2020-12-20 12:05:42	ga_s2am_ard_3-2-1_49JGJ_2020-12-20_final.stac-item
2021-01-29 12:05:52	ga_s2am_ard_3-2-1_50JLN_2021-01-29_final.stac-item
2021-03-10 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-03-10_final.stac-item
2021-04-10 11:36:44	ga_s2am_ard_3-2-1_50HQJ_2021-04-10_final.stac-item
2021-04-13 11:47:01	ga_s2am_ard_3-2-1_50HNH_2021-04-13_final.stac-item
2021-04-19 12:04:37	ga_s2am_ard_3-2-1_49JHN_2021-04-19_final.stac-item
2021-04-23 11:46:44	ga_s2am_ard_3-2-1_50HPJ_2021-04-23_final.stac-item
2021-05-02 12:14:57	ga_s2am_ard_3-2-1_49JFM_2021-05-02_final.stac-item
2021-05-03 11:46:41	ga_s2am_ard_3-2-1_50HQJ_2021-05-03_final.stac-item
2021-05-13 11:46:33	ga_s2am_ard_3-2-1_50HPK_2021-05-13_final.stac-item
2021-05-13 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2021-05-13_final.stac-item
2021-07-19 11:37:10	ga_s2am_ard_3-2-1_50HPH_2021-07-19_final.stac-item
2021-07-29 11:35:54	ga_s2am_ard_3-2-1_50JQN_2021-07-29_final.stac-item
2021-09-10 11:47:06	ga_s2am_ard_3-2-1_50HNH_2021-09-10_final.stac-item
2021-10-03 11:55:46	ga_s2am_ard_3-2-1_50JLP_2021-10-03_final.stac-item
2021-10-13 11:56:05	ga_s2am_ard_3-2-1_50JKN_2021-10-13_final.stac-item
2021-11-19 11:47:10	ga_s2am_ard_3-2-1_50HMH_2021-11-19_final.stac-item
2021-12-25 12:04:00	ga_s2am_ard_3-2-1_50KKA_2021-12-25_final.stac-item
2022-02-13 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2022-02-13_final.stac-item
2022-02-20 11:55:58	ga_s2am_ard_3-2-1_50JLN_2022-02-20_final.stac-item
2022-04-05 11:36:28	ga_s2am_ard_3-2-1_50JPL_2022-04-05_final.stac-item
2022-07-17 11:47:26	ga_s2am_ard_3-2-1_50HLH_2022-07-17_final.stac-item
2022-07-23 12:03:55	ga_s2am_ard_3-2-1_50KKB_2022-07-23_final.stac-item
2022-08-03 11:36:48	ga_s2am_ard_3-2-1_50HPK_2022-08-03_final.stac-item
2022-08-06 11:46:52	ga_s2am_ard_3-2-1_50HMK_2022-08-06_final.stac-item
2022-08-15 12:14:54	ga_s2am_ard_3-2-1_49JGN_2022-08-15_final.stac-item
2022-09-21 12:05:22	ga_s2am_ard_3-2-1_49JGL_2022-09-21_final.stac-item
2022-10-05 11:46:41	ga_s2am_ard_3-2-1_50HPK_2022-10-05_final.stac-item
2022-10-12 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2022-10-12_final.stac-item
2022-10-18 11:56:14	ga_s2am_ard_3-2-1_50JLM_2022-10-18_final.stac-item
2022-12-17 11:56:17	ga_s2am_ard_3-2-1_50JNL_2022-12-17_final.stac-item
2023-01-22 12:13:50	ga_s2am_ard_3-2-1_50KKA_2023-01-22_final.stac-item
2023-03-30 12:04:34	ga_s2am_ard_3-2-1_50JMT_2023-03-30_final
2023-04-13 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2023-04-13_final
2023-04-26 11:55:56	ga_s2am_ard_3-2-1_50JLN_2023-04-26_final
2023-06-11 12:14:02	ga_s2am_ard_3-2-1_49KGR_2023-06-11_final
2023-08-04 11:57:18	ga_s2am_ard_3-2-1_50HKH_2023-08-04_nrt
2023-08-11 11:47:25	ga_s2am_ard_3-2-1_50HNG_2023-08-11_final
2023-08-20 12:13:46	ga_s2am_ard_3-2-1_50KKB_2023-08-20_final
2023-09-06 12:04:48	ga_s2am_ard_3-2-1_49JHN_2023-09-06_final
2023-09-09 12:13:59	ga_s2am_ard_3-2-1_50KKA_2023-09-09_final
2023-09-16 12:04:35	ga_s2am_ard_3-2-1_49KGP_2023-09-16_final
2023-10-13 11:55:44	ga_s2am_ard_3-2-1_50JKP_2023-10-13_final
2023-10-16 12:03:43	ga_s2am_ard_3-2-1_50KKB_2023-10-16_final
2023-10-16 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-10-16_final
2023-11-29 11:46:44	ga_s2am_ard_3-2-1_50HNJ_2023-11-29_final
2023-12-25 12:05:34	ga_s2am_ard_3-2-1_50JLP_2023-12-25_final
2024-01-11 11:55:59	ga_s2am_ard_3-2-1_50JNM_2024-01-11_final
2024-01-21 11:56:48	ga_s2am_ard_3-2-1_50HMJ_2024-01-21_final
2024-04-13 12:05:02	ga_s2am_ard_3-2-1_49JGM_2024-04-13_final
2024-04-23 12:05:58	ga_s2am_ard_3-2-1_50JKN_2024-04-23_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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