Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2015-10-21 12:09:42	ga_s2am_ard_3-2-1_49KGP_2015-10-21_final.stac-item
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KGQ_2015-10-28_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HQJ_2015-12-21_final.stac-item
2016-01-06 12:05:24	ga_s2am_ard_3-2-1_49JGK_2016-01-06_final.stac-item
2016-01-06 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2016-01-06_final.stac-item
2016-06-25 11:32:00	ga_s2am_ard_3-2-1_50HPJ_2016-06-25_final.stac-item
2016-07-27 12:13:48	ga_s2am_ard_3-2-1_49KHQ_2016-07-27_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49KHP_2016-12-11_final
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49KHR_2016-12-11_final
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49JGL_2016-12-14_final.stac-item
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49JGN_2016-12-14_final.stac-item
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49KHQ_2016-12-14_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49JGM_2016-12-24_final
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49KHR_2016-12-24_final
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50HPH_2016-12-25_final
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49KHP_2017-02-22_final
2018-01-18 12:13:37	ga_s2am_ard_3-2-1_49KHR_2018-01-18_final
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HPH_2018-05-09_final
2019-01-20 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2019-01-20_final
2019-01-27 11:56:08	ga_s2am_ard_3-2-1_50JLM_2019-01-27_final
2019-01-31 11:37:00	ga_s2am_ard_3-2-1_50HQH_2019-01-31_final
2019-05-14 11:46:57	ga_s2am_ard_3-2-1_50HQH_2019-05-14_final
2019-05-17 11:57:13	ga_s2am_ard_3-2-1_50HLH_2019-05-17_final
2019-12-09 12:13:51	ga_s2am_ard_3-2-1_49KHR_2019-12-09_final
2020-01-15 12:05:38	ga_s2am_ard_3-2-1_49JGJ_2020-01-15_final
2020-12-10 12:04:15	ga_s2am_ard_3-2-1_49KGQ_2020-12-10_final
2020-12-13 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2020-12-13_final
2021-09-23 11:56:17	ga_s2am_ard_3-2-1_50JKM_2021-09-23_final
2021-11-22 11:56:26	ga_s2am_ard_3-2-1_50JLL_2021-11-22_final
2022-01-01 11:56:42	ga_s2am_ard_3-2-1_50HLK_2022-01-01_final
2022-01-04 12:05:31	ga_s2am_ard_3-2-1_49JGK_2022-01-04_final
2022-01-14 12:05:52	ga_s2am_ard_3-2-1_50JLN_2022-01-14_final
2022-02-13 12:06:04	ga_s2am_ard_3-2-1_50JLM_2022-02-13_final
2022-02-23 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2022-02-23_final
2022-02-27 11:46:51	ga_s2am_ard_3-2-1_50HPJ_2022-02-27_final
2022-03-06 11:36:42	ga_s2am_ard_3-2-1_50HPK_2022-03-06_final
2022-03-16 11:37:10	ga_s2am_ard_3-2-1_50HPH_2022-03-16_final
2022-05-05 11:37:11	ga_s2am_ard_3-2-1_50HPH_2022-05-05_final
2022-05-21 11:56:32	ga_s2am_ard_3-2-1_50JLL_2022-05-21_final
2022-06-24 11:37:04	ga_s2am_ard_3-2-1_50HPJ_2022-06-24_final
2022-06-27 11:47:04	ga_s2am_ard_3-2-1_50HNJ_2022-06-27_final
2022-06-30 11:57:22	ga_s2am_ard_3-2-1_50HLH_2022-06-30_final
2022-08-12 12:06:04	ga_s2am_ard_3-2-1_50JLN_2022-08-12_final
2022-08-19 11:56:24	ga_s2am_ard_3-2-1_50JLM_2022-08-19_final
2022-08-26 11:47:01	ga_s2am_ard_3-2-1_50HPJ_2022-08-26_final.stac-item
2022-10-21 12:05:31	ga_s2am_ard_3-2-1_49JGK_2022-10-21_final.stac-item
2022-10-28 11:56:14	ga_s2am_ard_3-2-1_50JLM_2022-10-28_final.stac-item
2022-11-17 11:56:27	ga_s2am_ard_3-2-1_50JLL_2022-11-17_final.stac-item
2022-12-04 11:46:41	ga_s2am_ard_3-2-1_50HMK_2022-12-04_final.stac-item
2022-12-27 11:56:24	ga_s2am_ard_3-2-1_50JLL_2022-12-27_final.stac-item
2023-01-03 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2023-01-03_final.stac-item
2023-01-13 11:46:51	ga_s2am_ard_3-2-1_50HQH_2023-01-13_final.stac-item
2023-01-19 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-01-19_final.stac-item
2023-02-02 11:46:52	ga_s2am_ard_3-2-1_50HQH_2023-02-02_final.stac-item
2023-02-08 12:05:28	ga_s2am_ard_3-2-1_49JGK_2023-02-08_final.stac-item
2023-02-15 11:56:08	ga_s2am_ard_3-2-1_50JLM_2023-02-15_final.stac-item
2023-02-25 11:56:09	ga_s2am_ard_3-2-1_50JLM_2023-02-25_final.stac-item
2023-03-17 11:56:09	ga_s2am_ard_3-2-1_50JLM_2023-03-17_final.stac-item
2023-04-23 11:47:01	ga_s2am_ard_3-2-1_50HPH_2023-04-23_final.stac-item
2023-04-26 11:56:14	ga_s2am_ard_3-2-1_50JKM_2023-04-26_final.stac-item
2023-05-16 11:56:31	ga_s2am_ard_3-2-1_50HNK_2023-05-16_final.stac-item
2023-06-25 11:57:12	ga_s2am_ard_3-2-1_50HLH_2023-06-25_final.stac-item
2023-07-15 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2023-07-15_final.stac-item
2023-07-22 11:47:11	ga_s2am_ard_3-2-1_50HNH_2023-07-22_final.stac-item
2023-08-04 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2023-08-04_final.stac-item
2023-08-24 11:56:02	ga_s2am_ard_3-2-1_50JLN_2023-08-24_final.stac-item
2023-09-17 11:36:55	ga_s2am_ard_3-2-1_50HPJ_2023-09-17_final.stac-item
2023-11-02 11:56:24	ga_s2am_ard_3-2-1_50JLL_2023-11-02_final.stac-item
2023-11-09 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2023-11-09_final.stac-item
2023-11-12 11:55:56	ga_s2am_ard_3-2-1_50JLN_2023-11-12_final.stac-item
2023-11-16 11:36:50	ga_s2am_ard_3-2-1_50HPJ_2023-11-16_final.stac-item
2023-11-19 11:46:51	ga_s2am_ard_3-2-1_50HQH_2023-11-19_final.stac-item
2023-11-19 11:47:00	ga_s2am_ard_3-2-1_50HPH_2023-11-19_final.stac-item
2023-11-28 12:14:01	ga_s2am_ard_3-2-1_49KHQ_2023-11-28_final.stac-item
2023-11-29 11:46:40	ga_s2am_ard_3-2-1_50HPJ_2023-11-29_final.stac-item
2023-12-05 12:05:57	ga_s2am_ard_3-2-1_50JLM_2023-12-05_final.stac-item
2023-12-19 11:46:44	ga_s2am_ard_3-2-1_50HPJ_2023-12-19_final.stac-item
2023-12-25 12:06:01	ga_s2am_ard_3-2-1_50JLM_2023-12-25_final.stac-item
2024-01-14 12:05:58	ga_s2am_ard_3-2-1_50JLM_2024-01-14_final.stac-item
2024-01-21 11:56:03	ga_s2am_ard_3-2-1_50JLM_2024-01-21_final.stac-item
2024-01-21 11:56:18	ga_s2am_ard_3-2-1_50JLL_2024-01-21_final.stac-item
2024-01-25 11:37:00	ga_s2am_ard_3-2-1_50HPH_2024-01-25_final.stac-item
2024-01-28 11:46:38	ga_s2am_ard_3-2-1_50HQJ_2024-01-28_final.stac-item
2024-01-28 11:46:48	ga_s2am_ard_3-2-1_50HQH_2024-01-28_final.stac-item
2024-02-07 11:46:39	ga_s2am_ard_3-2-1_50HQJ_2024-02-07_final.stac-item
2024-02-20 11:56:09	ga_s2am_ard_3-2-1_50JLM_2024-02-20_final.stac-item
2024-02-20 11:56:38	ga_s2am_ard_3-2-1_50HLK_2024-02-20_final.stac-item
2024-03-01 11:56:35	ga_s2am_ard_3-2-1_50HMK_2024-03-01_final.stac-item
2024-03-11 11:56:26	ga_s2am_ard_3-2-1_50JLL_2024-03-11_final.stac-item
2024-03-27 12:14:46	ga_s2am_ard_3-2-1_49JFN_2024-03-27_final.stac-item
2024-03-28 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2024-03-28_final.stac-item
2024-04-03 12:06:02	ga_s2am_ard_3-2-1_50JLM_2024-04-03_final.stac-item
2024-04-04 11:37:04	ga_s2am_ard_3-2-1_50HPH_2024-04-04_final.stac-item
2024-04-06 12:14:11	ga_s2am_ard_3-2-1_49KGQ_2024-04-06_final.stac-item
2024-04-14 11:36:54	ga_s2am_ard_3-2-1_50HPJ_2024-04-14_final.stac-item
2024-04-20 11:56:29	ga_s2am_ard_3-2-1_50JLL_2024-04-20_final.stac-item
2024-04-23 12:06:07	ga_s2am_ard_3-2-1_50JLM_2024-04-23_final.stac-item
2024-04-30 11:56:01	ga_s2am_ard_3-2-1_50JLN_2024-04-30_final.stac-item
2024-04-30 11:56:14	ga_s2am_ard_3-2-1_50JLM_2024-04-30_final.stac-item
2024-05-07 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2024-05-07_final.stac-item

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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

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