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
2016-03-07 11:32:50	ga_s2am_ard_3-2-1_50JQP_2016-03-07_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HMK_2016-03-20_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50JMM_2016-03-20_final.stac-item
2016-04-16 11:36:04	ga_s2am_ard_3-2-1_50JPL_2016-04-16_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49JGM_2016-05-15_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50HLJ_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JLS_2016-05-22_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_49JGL_2016-07-24_final.stac-item
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HPH_2016-12-05_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49JHM_2016-12-11_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50HPH_2016-12-25_final.stac-item
2016-12-28 11:45:05	ga_s2am_ard_3-2-1_50JKN_2016-12-28_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JKR_2017-01-30_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HLH_2017-02-03_final.stac-item
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49KGQ_2017-02-12_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50JML_2017-05-04_final.stac-item
2017-06-12 12:14:42	ga_s2am_ard_3-2-1_49JGM_2017-06-12_final.stac-item
2017-07-19 12:04:43	ga_s2am_ard_3-2-1_50JKR_2017-07-19_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49JFM_2017-09-30_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50JPT_2017-12-30_final.stac-item
2018-01-15 12:03:40	ga_s2am_ard_3-2-1_50KKA_2018-01-15_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50HMH_2018-02-01_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50HMJ_2018-02-01_final.stac-item
2018-05-26 11:31:39	ga_s2am_ard_3-2-1_50HPH_2018-05-26_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JLQ_2018-06-11_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKN_2018-08-13_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49JGM_2018-11-04_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50HQK_2018-11-05_final.stac-item
2018-12-08 11:56:46	ga_s2am_ard_3-2-1_50HLJ_2018-12-08_final.stac-item
2019-02-03 11:47:11	ga_s2am_ard_3-2-1_50HLH_2019-02-03_final.stac-item
2019-02-06 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2019-02-06_final.stac-item
2019-02-19 12:05:52	ga_s2am_ard_3-2-1_50JKN_2019-02-19_final.stac-item
2019-02-26 11:57:01	ga_s2am_ard_3-2-1_50HMH_2019-02-26_final.stac-item
2019-03-01 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2019-03-01_final.stac-item
2019-05-27 11:55:45	ga_s2am_ard_3-2-1_50JLP_2019-05-27_final.stac-item
2019-05-30 12:05:03	ga_s2am_ard_3-2-1_49JGM_2019-05-30_final.stac-item
2019-06-13 11:46:29	ga_s2am_ard_3-2-1_50JML_2019-06-13_final.stac-item
2019-09-10 12:13:57	ga_s2am_ard_3-2-1_49KGR_2019-09-10_final.stac-item
2019-09-30 12:14:58	ga_s2am_ard_3-2-1_49JGM_2019-09-30_final.stac-item
2019-10-31 11:46:18	ga_s2am_ard_3-2-1_50JQL_2019-10-31_final.stac-item
2019-10-31 11:46:22	ga_s2am_ard_3-2-1_50JPL_2019-10-31_final.stac-item
2019-11-13 11:57:08	ga_s2am_ard_3-2-1_50HMH_2019-11-13_final.stac-item
2019-11-29 12:14:55	ga_s2am_ard_3-2-1_49JGM_2019-11-29_final.stac-item
2019-12-03 11:57:04	ga_s2am_ard_3-2-1_50HMH_2019-12-03_final.stac-item
2019-12-23 11:55:54	ga_s2am_ard_3-2-1_50JKN_2019-12-23_final.stac-item
2020-02-11 11:56:33	ga_s2am_ard_3-2-1_50HLK_2020-02-11_final.stac-item
2020-04-01 11:57:02	ga_s2am_ard_3-2-1_50HMH_2020-04-01_final.stac-item
2020-05-04 12:05:04	ga_s2am_ard_3-2-1_49JGM_2020-05-04_final.stac-item
2020-07-13 12:05:05	ga_s2am_ard_3-2-1_49JGM_2020-07-13_final.stac-item
2020-08-06 11:46:32	ga_s2am_ard_3-2-1_50JML_2020-08-06_final.stac-item
2020-09-01 12:04:47	ga_s2am_ard_3-2-1_50JKT_2020-09-01_final.stac-item
2020-09-28 11:56:05	ga_s2am_ard_3-2-1_50JKN_2020-09-28_final.stac-item
2020-09-28 11:57:15	ga_s2am_ard_3-2-1_50HLH_2020-09-28_final.stac-item
2021-01-02 12:13:55	ga_s2am_ard_3-2-1_49KHR_2021-01-02_final.stac-item
2021-01-06 11:56:00	ga_s2am_ard_3-2-1_50JKN_2021-01-06_final.stac-item
2021-01-23 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-01-23_final.stac-item
2021-01-29 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-01-29_final.stac-item
2021-05-13 11:46:37	ga_s2am_ard_3-2-1_50HNK_2021-05-13_final.stac-item
2021-06-01 12:13:55	ga_s2am_ard_3-2-1_50KKA_2021-06-01_final.stac-item
2021-06-11 12:13:55	ga_s2am_ard_3-2-1_50KKA_2021-06-11_final.stac-item
2021-07-05 11:56:57	ga_s2am_ard_3-2-1_50HLJ_2021-07-05_final.stac-item
2021-09-03 11:55:57	ga_s2am_ard_3-2-1_50JLN_2021-09-03_final.stac-item
2021-11-08 12:13:57	ga_s2am_ard_3-2-1_50KKA_2021-11-08_final.stac-item
2021-11-19 11:47:14	ga_s2am_ard_3-2-1_50HLH_2021-11-19_final.stac-item
2021-12-05 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-12-05_final.stac-item
2022-03-12 11:56:03	ga_s2am_ard_3-2-1_50JKN_2022-03-12_final.stac-item
2022-03-25 12:06:07	ga_s2am_ard_3-2-1_50JLM_2022-03-25_final.stac-item
2022-04-01 11:57:11	ga_s2am_ard_3-2-1_50HLH_2022-04-01_final.stac-item
2022-07-14 11:36:46	ga_s2am_ard_3-2-1_50HQK_2022-07-14_final.stac-item
2022-09-05 11:45:17	ga_s2am_ard_3-2-1_50JQR_2022-09-05_final.stac-item
2022-10-21 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2022-10-21_final.stac-item
2022-10-21 12:05:31	ga_s2am_ard_3-2-1_49JGK_2022-10-21_final.stac-item
2022-10-31 12:06:02	ga_s2am_ard_3-2-1_50JLN_2022-10-31_final.stac-item
2022-11-30 12:03:44	ga_s2am_ard_3-2-1_50KKB_2022-11-30_final.stac-item
2022-12-30 12:05:28	ga_s2am_ard_3-2-1_49JGK_2022-12-30_final.stac-item
2023-01-16 11:57:02	ga_s2am_ard_3-2-1_50HMH_2023-01-16_final.stac-item
2023-01-19 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2023-01-19_final.stac-item
2023-01-26 11:57:06	ga_s2am_ard_3-2-1_50HLH_2023-01-26_final.stac-item
2023-02-21 12:14:55	ga_s2am_ard_3-2-1_49JGM_2023-02-21_nrt.stac-item
2023-02-21 12:14:55	ga_s2am_ard_3-2-1_49JGM_2023-02-21_final
2023-02-22 11:45:33	ga_s2am_ard_3-2-1_50JPP_2023-02-22_final
2023-02-25 11:57:21	ga_s2am_ard_3-2-1_50HLG_2023-02-25_final
2023-03-03 12:13:51	ga_s2am_ard_3-2-1_50KKA_2023-03-03_final
2023-06-02 11:46:34	ga_s2am_ard_3-2-1_50HQK_2023-06-02_final
2023-06-02 11:47:06	ga_s2am_ard_3-2-1_50HPH_2023-06-02_final
2023-06-05 11:55:53	ga_s2am_ard_3-2-1_50JNN_2023-06-05_final
2023-06-15 11:57:17	ga_s2am_ard_3-2-1_50HLH_2023-06-15_final
2023-06-29 11:37:11	ga_s2am_ard_3-2-1_50HPH_2023-06-29_final
2023-08-17 12:05:35	ga_s2am_ard_3-2-1_49JGK_2023-08-17_final
2023-09-16 12:06:08	ga_s2am_ard_3-2-1_50JLM_2023-09-16_final
2023-10-13 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2023-10-13_final
2023-11-08 12:14:59	ga_s2am_ard_3-2-1_49JFM_2023-11-08_final
2023-11-29 11:46:44	ga_s2am_ard_3-2-1_50HNJ_2023-11-29_final
2023-11-29 11:47:09	ga_s2am_ard_3-2-1_50HPG_2023-11-29_final
2023-12-28 12:14:53	ga_s2am_ard_3-2-1_49JGM_2023-12-28_final
2024-01-11 11:56:06	ga_s2am_ard_3-2-1_50JLM_2024-01-11_final
2024-02-03 12:03:55	ga_s2am_ard_3-2-1_49KHR_2024-02-03_final
2024-03-24 12:04:00	ga_s2am_ard_3-2-1_49KHR_2024-03-24_final
2024-05-20 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2024-05-20_nrt
2024-05-23 12:05:40	ga_s2am_ard_3-2-1_50JKP_2024-05-23_nrt

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