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
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JKN_2015-11-14_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50HLJ_2016-01-03_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49KGP_2016-03-16_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50HLK_2016-04-02_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49KHR_2016-04-15_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50JLP_2016-05-15_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_49JHM_2016-07-24_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50HMK_2016-10-16_final.stac-item
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2016-12-05_final.stac-item
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_50HQJ_2017-01-01_final.stac-item
2017-02-13 11:44:16	ga_s2am_ard_3-2-1_50JML_2017-02-13_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_50JLS_2017-02-19_final.stac-item
2017-03-22 11:35:56	ga_s2am_ard_3-2-1_50JQM_2017-03-22_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_50JLM_2017-05-10_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49KHR_2017-05-30_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49KGP_2017-06-02_final.stac-item
2017-07-26 11:56:09	ga_s2am_ard_3-2-1_50JMM_2017-07-26_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49JHN_2017-08-18_final.stac-item
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50JNN_2018-03-23_final.stac-item
2018-04-19 11:46:08	ga_s2am_ard_3-2-1_50HMK_2018-04-19_final.stac-item
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_50HPJ_2018-05-16_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JMM_2018-06-11_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JNL_2018-06-11_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50JKP_2018-07-01_final.stac-item
2018-11-25 11:45:24	ga_s2am_ard_3-2-1_50JQP_2018-11-25_final.stac-item
2018-11-25 11:46:46	ga_s2am_ard_3-2-1_50HQH_2018-11-25_final.stac-item
2019-01-01 11:36:42	ga_s2am_ard_3-2-1_50HQJ_2019-01-01_final.stac-item
2019-01-07 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2019-01-07_final.stac-item
2019-01-21 11:36:30	ga_s2am_ard_3-2-1_50HQK_2019-01-21_final.stac-item
2019-02-16 11:57:06	ga_s2am_ard_3-2-1_50HLH_2019-02-16_final.stac-item
2019-02-19 12:05:25	ga_s2am_ard_3-2-1_49JGK_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
2019-03-05 11:46:20	ga_s2am_ard_3-2-1_50JML_2019-03-05_final.stac-item
2019-07-03 11:46:31	ga_s2am_ard_3-2-1_50JML_2019-07-03_final.stac-item
2019-11-20 11:46:53	ga_s2am_ard_3-2-1_50HNJ_2019-11-20_final.stac-item
2019-11-29 12:13:54	ga_s2am_ard_3-2-1_49KHR_2019-11-29_final.stac-item
2019-12-17 11:37:01	ga_s2am_ard_3-2-1_50HPH_2019-12-17_final.stac-item
2020-02-08 11:46:26	ga_s2am_ard_3-2-1_50HPK_2020-02-08_final.stac-item
2020-02-21 11:55:15	ga_s2am_ard_3-2-1_50JNQ_2020-02-21_final.stac-item
2020-03-05 12:04:56	ga_s2am_ard_3-2-1_49JGM_2020-03-05_final.stac-item
2020-04-04 12:04:14	ga_s2am_ard_3-2-1_49KGQ_2020-04-04_final.stac-item
2020-05-28 11:46:29	ga_s2am_ard_3-2-1_50JNL_2020-05-28_final.stac-item
2020-06-13 12:05:44	ga_s2am_ard_3-2-1_50JLP_2020-06-13_final.stac-item
2020-07-23 12:05:31	ga_s2am_ard_3-2-1_50JKQ_2020-07-23_final.stac-item
2020-09-05 11:46:27	ga_s2am_ard_3-2-1_50JML_2020-09-05_final.stac-item
2020-09-05 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2020-09-05_final.stac-item
2020-10-05 11:47:16	ga_s2am_ard_3-2-1_50HMH_2020-10-05_final.stac-item
2020-10-31 12:05:46	ga_s2am_ard_3-2-1_50JKP_2020-10-31_final.stac-item
2020-12-20 12:05:13	ga_s2am_ard_3-2-1_49JGL_2020-12-20_final.stac-item
2021-02-12 11:44:47	ga_s2am_ard_3-2-1_50JQS_2021-02-12_final.stac-item
2021-02-15 11:55:45	ga_s2am_ard_3-2-1_50JKP_2021-02-15_final.stac-item
2021-02-15 11:56:07	ga_s2am_ard_3-2-1_50JMM_2021-02-15_final.stac-item
2021-02-25 11:55:59	ga_s2am_ard_3-2-1_50JKN_2021-02-25_final.stac-item
2021-03-07 11:57:09	ga_s2am_ard_3-2-1_50HLH_2021-03-07_final.stac-item
2021-04-06 11:56:04	ga_s2am_ard_3-2-1_50JMM_2021-04-06_final.stac-item
2021-04-13 11:46:17	ga_s2am_ard_3-2-1_50JNL_2021-04-13_final.stac-item
2021-04-16 11:57:03	ga_s2am_ard_3-2-1_50HLH_2021-04-16_final.stac-item
2021-09-03 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-09-03_final
2021-09-06 12:05:01	ga_s2am_ard_3-2-1_49JGM_2021-09-06_final.stac-item
2021-09-16 12:04:58	ga_s2am_ard_3-2-1_49JHM_2021-09-16_final.stac-item
2021-11-18 12:13:55	ga_s2am_ard_3-2-1_49KHR_2021-11-18_final.stac-item
2021-11-22 11:55:42	ga_s2am_ard_3-2-1_50JLP_2021-11-22_final.stac-item
2021-12-09 11:46:32	ga_s2am_ard_3-2-1_50HMK_2021-12-09_final.stac-item
2021-12-19 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-12-19_final.stac-item
2021-12-29 11:46:24	ga_s2am_ard_3-2-1_50JNL_2021-12-29_final.stac-item
2022-02-20 11:56:24	ga_s2am_ard_3-2-1_50JML_2022-02-20_final.stac-item
2022-02-27 11:46:22	ga_s2am_ard_3-2-1_50JPL_2022-02-27_final.stac-item
2022-04-14 12:05:29	ga_s2am_ard_3-2-1_50JKQ_2022-04-14_final.stac-item
2022-05-05 11:37:07	ga_s2am_ard_3-2-1_50HQH_2022-05-05_final.stac-item
2022-06-06 12:14:35	ga_s2am_ard_3-2-1_49KGP_2022-06-06_final.stac-item
2022-06-20 11:56:19	ga_s2am_ard_3-2-1_50JMM_2022-06-20_final.stac-item
2022-07-03 12:04:59	ga_s2am_ard_3-2-1_49JGN_2022-07-03_final.stac-item
2022-07-07 11:46:26	ga_s2am_ard_3-2-1_50JMM_2022-07-07_final.stac-item
2022-07-20 11:55:14	ga_s2am_ard_3-2-1_50JPR_2022-07-20_final.stac-item
2022-08-16 11:45:19	ga_s2am_ard_3-2-1_50JPR_2022-08-16_final.stac-item
2022-09-02 11:36:02	ga_s2am_ard_3-2-1_50JQN_2022-09-02_final.stac-item
2022-11-07 11:56:34	ga_s2am_ard_3-2-1_50HNK_2022-11-07_final.stac-item
2022-11-21 11:36:38	ga_s2am_ard_3-2-1_50HPK_2022-11-21_final.stac-item
2022-11-24 11:46:08	ga_s2am_ard_3-2-1_50JNM_2022-11-24_final.stac-item
2023-01-22 12:14:37	ga_s2am_ard_3-2-1_49JGN_2023-01-22_final.stac-item
2023-02-18 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2023-02-18_final
2023-02-21 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-02-21_nrt.stac-item
2023-02-21 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-02-21_final
2023-04-19 12:05:40	ga_s2am_ard_3-2-1_50JKP_2023-04-19_final
2023-05-20 11:37:23	ga_s2am_ard_3-2-1_50HPG_2023-05-20_final
2023-05-29 12:04:50	ga_s2am_ard_3-2-1_49JGN_2023-05-29_final
2023-06-22 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2023-06-22_final
2023-06-28 12:06:08	ga_s2am_ard_3-2-1_50JLM_2023-06-28_final
2023-07-15 11:57:25	ga_s2am_ard_3-2-1_50HMG_2023-07-15_final
2023-10-03 11:55:52	ga_s2am_ard_3-2-1_50JLN_2023-10-03_final
2023-12-09 11:47:01	ga_s2am_ard_3-2-1_50HNH_2023-12-09_final
2024-01-04 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2024-01-04_final
2024-01-24 12:05:58	ga_s2am_ard_3-2-1_50JLM_2024-01-24_final
2024-02-03 12:06:00	ga_s2am_ard_3-2-1_50JLM_2024-02-03_final
2024-02-23 12:04:46	ga_s2am_ard_3-2-1_49JGN_2024-02-23_final
2024-03-21 11:56:26	ga_s2am_ard_3-2-1_50JLL_2024-03-21_final
2024-04-07 11:46:46	ga_s2am_ard_3-2-1_50HPJ_2024-04-07_final
2024-04-07 11:46:56	ga_s2am_ard_3-2-1_50HPH_2024-04-07_final
2024-04-14 11:35:52	ga_s2am_ard_3-2-1_50JQN_2024-04-14_final
2024-05-17 11:47:26	ga_s2am_ard_3-2-1_50HMG_2024-05-17_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