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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49JFM_2015-10-28_final.stac-item
2015-11-27 12:04:40	ga_s2am_ard_3-2-1_50JMS_2015-11-27_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JLL_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JNP_2015-12-04_final.stac-item
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_50JLS_2015-12-07_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50JLS_2016-01-03_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50JNL_2016-03-20_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JLL_2016-04-02_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HMH_2016-05-09_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49JGN_2016-05-15_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JLN_2016-05-22_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JNM_2016-05-29_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_50JMR_2016-06-14_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_49JGL_2016-09-02_final.stac-item
2016-09-26 11:40:08	ga_s2am_ard_3-2-1_50HPJ_2016-09-26_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JLP_2017-01-30_final
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50HLJ_2017-02-16_final
2017-09-14 11:51:53	ga_s2am_ard_3-2-1_50HLH_2017-09-14_final
2017-09-14 11:51:53	ga_s2am_ard_3-2-1_50JLL_2017-09-14_final
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JKR_2018-04-05_final
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49JGL_2018-04-28_final
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_49KHS_2018-05-18_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50JQL_2018-09-06_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JKM_2018-09-09_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50JKR_2018-09-12_final
2018-09-13 11:33:05	ga_s2am_ard_3-2-1_50JPL_2018-09-13_final
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50HLH_2018-09-29_final
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50HMJ_2018-10-09_final
2018-11-28 11:56:42	ga_s2am_ard_3-2-1_50HMJ_2018-11-28_final
2018-12-31 12:05:34	ga_s2am_ard_3-2-1_50JKP_2018-12-31_final
2019-01-14 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2019-01-14_final
2019-02-26 11:56:32	ga_s2am_ard_3-2-1_50HMK_2019-02-26_final
2019-03-31 12:05:38	ga_s2am_ard_3-2-1_50JLP_2019-03-31_final
2019-04-07 11:56:41	ga_s2am_ard_3-2-1_50HLK_2019-04-07_final
2019-07-29 12:05:13	ga_s2am_ard_3-2-1_49JFM_2019-07-29_final
2019-10-31 11:46:55	ga_s2am_ard_3-2-1_50HNJ_2019-10-31_final
2019-10-31 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2019-10-31_final
2019-11-20 11:46:44	ga_s2am_ard_3-2-1_50HQJ_2019-11-20_final
2019-12-03 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2019-12-03_final
2020-01-16 11:34:43	ga_s2am_ard_3-2-1_50JRS_2020-01-16_final
2020-03-02 11:56:25	ga_s2am_ard_3-2-1_50HNK_2020-03-02_final
2020-03-25 12:04:03	ga_s2am_ard_3-2-1_49KHQ_2020-03-25_final.stac-item
2020-04-04 12:04:50	ga_s2am_ard_3-2-1_50JLS_2020-04-04_final
2020-04-04 12:05:08	ga_s2am_ard_3-2-1_50JKR_2020-04-04_final
2020-04-07 12:13:37	ga_s2am_ard_3-2-1_49KHS_2020-04-07_final.stac-item
2020-04-08 11:45:58	ga_s2am_ard_3-2-1_50JQM_2020-04-08_final
2020-04-11 11:57:04	ga_s2am_ard_3-2-1_50HMH_2020-04-11_final
2020-05-17 12:13:59	ga_s2am_ard_3-2-1_50KKA_2020-05-17_final
2020-06-06 12:15:17	ga_s2am_ard_3-2-1_49JGL_2020-06-06_final
2020-06-30 11:56:09	ga_s2am_ard_3-2-1_50JNM_2020-06-30_final
2020-08-02 12:06:10	ga_s2am_ard_3-2-1_50JLM_2020-08-02_final
2020-09-05 11:46:31	ga_s2am_ard_3-2-1_50HPK_2020-09-05_final
2020-09-15 11:47:25	ga_s2am_ard_3-2-1_50HNG_2020-09-15_final.stac-item
2020-09-28 11:56:05	ga_s2am_ard_3-2-1_50JKN_2020-09-28_final
2020-10-21 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2020-10-21_final
2020-11-07 11:57:14	ga_s2am_ard_3-2-1_50HLH_2020-11-07_final
2020-11-14 11:47:06	ga_s2am_ard_3-2-1_50HPH_2020-11-14_final
2020-12-24 11:47:09	ga_s2am_ard_3-2-1_50HMH_2020-12-24_final
2021-01-06 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2021-01-06_final
2021-01-22 12:14:57	ga_s2am_ard_3-2-1_49JGM_2021-01-22_final
2021-02-01 12:13:54	ga_s2am_ard_3-2-1_50KKA_2021-02-01_final
2021-03-01 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2021-03-01_final
2021-03-23 12:14:55	ga_s2am_ard_3-2-1_49JGM_2021-03-23_final
2021-05-20 11:37:18	ga_s2am_ard_3-2-1_50HQG_2021-05-20_final.stac-item
2021-06-18 12:06:04	ga_s2am_ard_3-2-1_50JLM_2021-06-18_final
2021-07-25 11:54:44	ga_s2am_ard_3-2-1_50JMT_2021-07-25_final
2021-09-06 12:04:57	ga_s2am_ard_3-2-1_49JHM_2021-09-06_final
2021-09-06 12:05:01	ga_s2am_ard_3-2-1_49JGM_2021-09-06_final
2021-09-10 11:46:15	ga_s2am_ard_3-2-1_50JQL_2021-09-10_final
2021-09-10 11:47:06	ga_s2am_ard_3-2-1_50HNH_2021-09-10_final
2021-09-20 11:45:35	ga_s2am_ard_3-2-1_50JQP_2021-09-20_final
2021-10-03 11:55:31	ga_s2am_ard_3-2-1_50JPP_2021-10-03_final
2022-01-01 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2022-01-01_final
2022-02-10 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2022-02-10_final
2022-04-04 12:04:41	ga_s2am_ard_3-2-1_50JLT_2022-04-04_final
2022-05-18 11:47:30	ga_s2am_ard_3-2-1_50HMG_2022-05-18_final.stac-item
2022-06-13 12:05:36	ga_s2am_ard_3-2-1_50JKQ_2022-06-13_final
2022-09-01 12:05:01	ga_s2am_ard_3-2-1_50JMS_2022-09-01_final.stac-item
2022-09-01 12:05:20	ga_s2am_ard_3-2-1_50JLR_2022-09-01_final.stac-item
2022-09-11 12:05:37	ga_s2am_ard_3-2-1_50JKQ_2022-09-11_final.stac-item
2022-10-05 11:47:24	ga_s2am_ard_3-2-1_50HPG_2022-10-05_final.stac-item
2022-11-14 11:47:13	ga_s2am_ard_3-2-1_50HMH_2022-11-14_final.stac-item
2022-12-14 11:47:10	ga_s2am_ard_3-2-1_50HMH_2022-12-14_final.stac-item
2022-12-14 11:47:14	ga_s2am_ard_3-2-1_50HLH_2022-12-14_final.stac-item
2022-12-27 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2022-12-27_final.stac-item
2023-01-23 11:47:06	ga_s2am_ard_3-2-1_50HMH_2023-01-23_final.stac-item
2023-02-25 11:56:34	ga_s2am_ard_3-2-1_50HMK_2023-02-25_final.stac-item
2023-02-25 11:56:38	ga_s2am_ard_3-2-1_50HLK_2023-02-25_final.stac-item
2023-04-09 12:05:23	ga_s2am_ard_3-2-1_50JLQ_2023-04-09_final.stac-item
2023-04-16 11:57:05	ga_s2am_ard_3-2-1_50HMH_2023-04-16_final.stac-item
2023-05-26 11:56:33	ga_s2am_ard_3-2-1_50HNK_2023-05-26_final.stac-item
2023-09-03 11:57:05	ga_s2am_ard_3-2-1_50HLJ_2023-09-03_final.stac-item
2023-09-06 12:05:04	ga_s2am_ard_3-2-1_50JMR_2023-09-06_final.stac-item
2023-09-10 11:46:24	ga_s2am_ard_3-2-1_50JPL_2023-09-10_final.stac-item
2023-09-20 11:45:49	ga_s2am_ard_3-2-1_50JQN_2023-09-20_final.stac-item
2023-10-10 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2023-10-10_final.stac-item
2023-12-12 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2023-12-12_final.stac-item
2024-01-31 11:57:05	ga_s2am_ard_3-2-1_50HLH_2024-01-31_final.stac-item
2024-03-21 11:57:07	ga_s2am_ard_3-2-1_50HMH_2024-03-21_final.stac-item
2024-04-07 11:47:08	ga_s2am_ard_3-2-1_50HMH_2024-04-07_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

Other products

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