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
2015-09-29 11:36:06	ga_s2am_ard_3-2-1_50HQK_2015-09-29_final.stac-item
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_50JMR_2015-10-28_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JMR_2015-12-17_final.stac-item
2016-02-05 12:04:38	ga_s2am_ard_3-2-1_50JMR_2016-02-05_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50JQT_2016-06-11_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JPQ_2016-07-01_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HQH_2016-07-08_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JQT_2016-07-21_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JMR_2016-08-13_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JQT_2016-10-09_final.stac-item
2016-12-28 11:45:05	ga_s2am_ard_3-2-1_50JQT_2016-12-28_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50JQT_2017-02-26_final.stac-item
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_49JGN_2017-03-21_final.stac-item
2017-05-23 12:14:44	ga_s2am_ard_3-2-1_49JGK_2017-05-23_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JPP_2017-06-06_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JQT_2017-06-06_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50JQT_2017-07-16_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_50JMT_2017-08-18_final.stac-item
2017-11-13 11:49:19	ga_s2am_ard_3-2-1_50JQT_2017-11-13_final.stac-item
2018-01-15 12:03:40	ga_s2am_ard_3-2-1_50KKV_2018-01-15_final.stac-item
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_50JMR_2018-03-16_final.stac-item
2018-03-20 11:37:46	ga_s2am_ard_3-2-1_50JPT_2018-03-20_final.stac-item
2018-05-29 11:39:24	ga_s2am_ard_3-2-1_50JQR_2018-05-29_final.stac-item
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50JQM_2018-07-08_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JPP_2018-07-11_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JQT_2018-08-10_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50KLU_2018-09-29_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50KLU_2018-10-09_final.stac-item
2018-10-16 11:40:28	ga_s2am_ard_3-2-1_50JPM_2018-10-16_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JQT_2018-10-19_final.stac-item
2018-11-18 11:54:17	ga_s2am_ard_3-2-1_50JQT_2018-11-18_final.stac-item
2019-01-23 12:15:16	ga_s2am_ard_3-2-1_49JGK_2019-01-23_final.stac-item
2019-02-06 11:54:30	ga_s2am_ard_3-2-1_50KLU_2019-02-06_final.stac-item
2019-02-16 11:54:30	ga_s2am_ard_3-2-1_50KLU_2019-02-16_final.stac-item
2019-02-23 11:46:49	ga_s2am_ard_3-2-1_50HQH_2019-02-23_final.stac-item
2019-03-18 11:54:20	ga_s2am_ard_3-2-1_50JQT_2019-03-18_final.stac-item
2019-03-31 12:06:04	ga_s2am_ard_3-2-1_50JLM_2019-03-31_final.stac-item
2019-05-17 11:54:37	ga_s2am_ard_3-2-1_50KLU_2019-05-17_final.stac-item
2019-06-26 11:54:28	ga_s2am_ard_3-2-1_50JQT_2019-06-26_final.stac-item
2019-07-16 11:55:31	ga_s2am_ard_3-2-1_50JPP_2019-07-16_final.stac-item
2019-08-05 11:54:38	ga_s2am_ard_3-2-1_50KLU_2019-08-05_final.stac-item
2019-08-18 12:04:38	ga_s2am_ard_3-2-1_50JMT_2019-08-18_final.stac-item
2019-08-28 12:04:37	ga_s2am_ard_3-2-1_50JMT_2019-08-28_final.stac-item
2019-09-04 11:54:33	ga_s2am_ard_3-2-1_50KLU_2019-09-04_final.stac-item
2019-09-07 12:04:35	ga_s2am_ard_3-2-1_50JMT_2019-09-07_final.stac-item
2019-10-04 11:54:35	ga_s2am_ard_3-2-1_50KLU_2019-10-04_final.stac-item
2019-10-14 11:54:36	ga_s2am_ard_3-2-1_50KLU_2019-10-14_final.stac-item
2019-10-17 12:05:02	ga_s2am_ard_3-2-1_50JMR_2019-10-17_final.stac-item
2019-10-24 11:54:36	ga_s2am_ard_3-2-1_50KLU_2019-10-24_final.stac-item
2019-10-31 11:46:56	ga_s2am_ard_3-2-1_50HQH_2019-10-31_final.stac-item
2019-11-03 11:54:36	ga_s2am_ard_3-2-1_50KLU_2019-11-03_final.stac-item
2019-11-06 12:05:01	ga_s2am_ard_3-2-1_50JMR_2019-11-06_final.stac-item
2019-11-13 11:54:35	ga_s2am_ard_3-2-1_50KLU_2019-11-13_final.stac-item
2020-02-14 12:04:22	ga_s2am_ard_3-2-1_50JMT_2020-02-14_final.stac-item
2020-03-02 11:54:29	ga_s2am_ard_3-2-1_50KLU_2020-03-02_final.stac-item
2020-04-01 11:54:21	ga_s2am_ard_3-2-1_50JPT_2020-04-01_final.stac-item
2020-04-01 11:54:29	ga_s2am_ard_3-2-1_50KLU_2020-04-01_final.stac-item
2020-05-01 11:54:28	ga_s2am_ard_3-2-1_50JPT_2020-05-01_final.stac-item
2020-05-04 12:05:12	ga_s2am_ard_3-2-1_49JFM_2020-05-04_final.stac-item
2020-05-11 11:54:38	ga_s2am_ard_3-2-1_50KLU_2020-05-11_final.stac-item
2020-06-03 12:05:05	ga_s2am_ard_3-2-1_50JMR_2020-06-03_final.stac-item
2020-06-30 11:54:38	ga_s2am_ard_3-2-1_50KLU_2020-06-30_final.stac-item
2020-07-14 11:34:48	ga_s2am_ard_3-2-1_50JRS_2020-07-14_final.stac-item
2020-07-20 11:54:38	ga_s2am_ard_3-2-1_50KLU_2020-07-20_final.stac-item
2020-07-30 11:54:39	ga_s2am_ard_3-2-1_50KLU_2020-07-30_final.stac-item
2020-08-22 12:04:41	ga_s2am_ard_3-2-1_50JMT_2020-08-22_final.stac-item
2020-09-08 11:54:37	ga_s2am_ard_3-2-1_50KLU_2020-09-08_final.stac-item
2020-09-28 11:54:39	ga_s2am_ard_3-2-1_50KLU_2020-09-28_final.stac-item
2020-10-08 11:54:39	ga_s2am_ard_3-2-1_50KLU_2020-10-08_final.stac-item
2020-10-31 12:05:04	ga_s2am_ard_3-2-1_50JMR_2020-10-31_final.stac-item
2020-11-24 11:45:57	ga_s2am_ard_3-2-1_50JPM_2020-11-24_final.stac-item
2021-04-06 11:54:30	ga_s2am_ard_3-2-1_50KLU_2021-04-06_final.stac-item
2021-04-26 11:54:30	ga_s2am_ard_3-2-1_50KLU_2021-04-26_final.stac-item
2021-04-30 11:34:41	ga_s2am_ard_3-2-1_50JRS_2021-04-30_final.stac-item
2021-07-02 11:47:19	ga_s2am_ard_3-2-1_50HPG_2021-07-02_final
2021-07-18 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2021-07-18_final.stac-item
2021-09-13 11:54:24	ga_s2am_ard_3-2-1_50JQT_2021-09-13_final.stac-item
2022-01-18 11:45:45	ga_s2am_ard_3-2-1_50JNN_2022-01-18_final.stac-item
2022-03-05 12:05:09	ga_s2am_ard_3-2-1_49JGL_2022-03-05_final.stac-item
2022-03-12 11:54:37	ga_s2am_ard_3-2-1_50KLU_2022-03-12_final.stac-item
2022-04-04 12:05:05	ga_s2am_ard_3-2-1_50JLR_2022-04-04_final.stac-item
2022-04-05 11:36:33	ga_s2am_ard_3-2-1_50HPK_2022-04-05_final.stac-item
2022-04-21 11:54:27	ga_s2am_ard_3-2-1_50JQT_2022-04-21_final.stac-item
2022-05-14 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2022-05-14_final.stac-item
2022-05-24 12:04:40	ga_s2am_ard_3-2-1_49JHN_2022-05-24_final.stac-item
2022-08-22 12:05:11	ga_s2am_ard_3-2-1_50JMR_2022-08-22_final.stac-item
2022-09-11 12:05:09	ga_s2am_ard_3-2-1_50JMR_2022-09-11_final.stac-item
2022-09-18 11:54:32	ga_s2am_ard_3-2-1_50JQT_2022-09-18_final.stac-item
2022-09-28 11:54:30	ga_s2am_ard_3-2-1_50JQT_2022-09-28_final.stac-item
2022-10-18 11:54:26	ga_s2am_ard_3-2-1_50JQT_2022-10-18_final.stac-item
2022-10-21 12:04:59	ga_s2am_ard_3-2-1_50JLR_2022-10-21_final.stac-item
2023-02-22 11:47:25	ga_s2am_ard_3-2-1_50HLG_2023-02-22_final
2023-06-25 11:57:23	ga_s2am_ard_3-2-1_50HMG_2023-06-25_final
2023-06-28 12:04:49	ga_s2am_ard_3-2-1_50JMS_2023-06-28_final
2023-08-10 12:13:44	ga_s2am_ard_3-2-1_49KHS_2023-08-10_final
2023-08-10 12:15:23	ga_s2am_ard_3-2-1_49JGK_2023-08-10_final
2023-10-03 11:54:25	ga_s2am_ard_3-2-1_50JQT_2023-10-03_final
2023-10-13 11:54:21	ga_s2am_ard_3-2-1_50JQT_2023-10-13_final
2023-12-25 12:04:55	ga_s2am_ard_3-2-1_50JMR_2023-12-25_final
2024-02-10 11:55:11	ga_s2am_ard_3-2-1_50JMQ_2024-02-10_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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