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
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HMH_2016-03-20_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50HLG_2016-04-02_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_50JLQ_2016-06-14_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50JKS_2016-08-23_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JMM_2016-12-05_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50HMJ_2016-12-08_final
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50JMM_2016-12-08_final
2016-12-21 12:04:53	ga_s2am_ard_3-2-1_50JLN_2016-12-21_final
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_50JLN_2016-12-31_final
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_50JKQ_2017-03-11_final
2017-05-17 11:56:36	ga_s2am_ard_3-2-1_50HMH_2017-05-17_final
2017-05-31 11:35:01	ga_s2am_ard_3-2-1_50HPG_2017-05-31_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50JLM_2017-06-19_final
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JGN_2017-06-29_final
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_50JKP_2017-08-18_final
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JGL_2017-09-17_final
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50JLM_2017-10-04_final
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50JMM_2017-10-24_final
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_50JLM_2017-11-06_final
2017-12-13 11:56:02	ga_s2am_ard_3-2-1_50HMK_2017-12-13_final
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_50JLP_2018-01-25_final
2018-02-01 11:49:16	ga_s2am_ard_3-2-1_50JKP_2018-02-01_final
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50JLR_2018-02-11_final
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50JNL_2018-02-18_final
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JNL_2018-04-12_final
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50JMN_2018-05-12_final
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50HLH_2018-06-08_final
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50HMJ_2018-06-28_final
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49JGL_2018-07-07_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HMK_2018-09-19_final
2018-11-08 11:55:08	ga_s2am_ard_3-2-1_50JLR_2018-11-08_final
2018-12-25 11:47:07	ga_s2am_ard_3-2-1_50HLH_2018-12-25_final
2019-01-27 11:55:50	ga_s2am_ard_3-2-1_50JMN_2019-01-27_final
2019-02-06 11:56:27	ga_s2am_ard_3-2-1_50HNK_2019-02-06_final
2019-02-09 12:04:53	ga_s2am_ard_3-2-1_49JHM_2019-02-09_final
2019-03-05 11:46:07	ga_s2am_ard_3-2-1_50JMM_2019-03-05_final
2019-03-11 12:05:47	ga_s2am_ard_3-2-1_50JLN_2019-03-11_final
2019-03-31 12:04:13	ga_s2am_ard_3-2-1_49KHQ_2019-03-31_final
2019-04-10 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2019-04-10_final
2019-04-27 11:55:13	ga_s2am_ard_3-2-1_50JMR_2019-04-27_final
2019-06-02 12:13:42	ga_s2am_ard_3-2-1_49KHS_2019-06-02_final.stac-item
2019-07-16 11:56:27	ga_s2am_ard_3-2-1_50JML_2019-07-16_final
2019-08-08 12:05:42	ga_s2am_ard_3-2-1_50JLP_2019-08-08_final
2019-08-15 11:56:14	ga_s2am_ard_3-2-1_50JLM_2019-08-15_final
2019-08-22 11:47:26	ga_s2am_ard_3-2-1_50HMG_2019-08-22_final.stac-item
2019-08-25 11:55:48	ga_s2am_ard_3-2-1_50JKP_2019-08-25_final
2019-08-25 11:55:55	ga_s2am_ard_3-2-1_50JMN_2019-08-25_final
2019-10-07 12:05:40	ga_s2am_ard_3-2-1_50JLP_2019-10-07_final
2019-11-23 11:56:26	ga_s2am_ard_3-2-1_50JLL_2019-11-23_final
2019-12-16 12:04:37	ga_s2am_ard_3-2-1_49JHN_2019-12-16_final
2019-12-16 12:04:40	ga_s2am_ard_3-2-1_49JGN_2019-12-16_final
2019-12-16 12:05:21	ga_s2am_ard_3-2-1_50JKQ_2019-12-16_final
2020-01-12 11:55:36	ga_s2am_ard_3-2-1_50JLP_2020-01-12_final
2020-01-29 11:46:55	ga_s2am_ard_3-2-1_50HPH_2020-01-29_final
2020-02-01 11:55:45	ga_s2am_ard_3-2-1_50JMN_2020-02-01_final
2020-03-02 11:56:18	ga_s2am_ard_3-2-1_50JML_2020-03-02_final
2020-03-02 11:57:01	ga_s2am_ard_3-2-1_50HMH_2020-03-02_final
2020-03-22 11:54:41	ga_s2am_ard_3-2-1_50JLT_2020-03-22_final
2020-04-11 11:55:40	ga_s2am_ard_3-2-1_50JLP_2020-04-11_final
2020-06-10 11:55:59	ga_s2am_ard_3-2-1_50JMN_2020-06-10_final
2020-06-16 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-06-16_final
2020-09-11 12:06:08	ga_s2am_ard_3-2-1_50JLM_2020-09-11_final
2020-10-25 11:46:28	ga_s2am_ard_3-2-1_50JNL_2020-10-25_final
2020-11-07 11:55:57	ga_s2am_ard_3-2-1_50JMN_2020-11-07_final
2020-12-07 11:55:51	ga_s2am_ard_3-2-1_50JMN_2020-12-07_final
2020-12-07 11:56:05	ga_s2am_ard_3-2-1_50JMM_2020-12-07_final
2020-12-07 11:57:03	ga_s2am_ard_3-2-1_50HMH_2020-12-07_final
2021-01-23 11:47:07	ga_s2am_ard_3-2-1_50HNH_2021-01-23_final
2021-03-10 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2021-03-10_final
2021-04-06 11:55:06	ga_s2am_ard_3-2-1_50JMR_2021-04-06_final
2021-06-18 12:05:17	ga_s2am_ard_3-2-1_49JGL_2021-06-18_final
2021-07-15 11:56:40	ga_s2am_ard_3-2-1_50HMK_2021-07-15_final
2021-07-18 12:05:39	ga_s2am_ard_3-2-1_50JLP_2021-07-18_final
2021-09-20 11:46:43	ga_s2am_ard_3-2-1_50HMK_2021-09-20_final
2021-09-29 12:14:25	ga_s2am_ard_3-2-1_49KGP_2021-09-29_final
2021-10-16 12:05:19	ga_s2am_ard_3-2-1_50JLR_2021-10-16_final
2021-11-02 11:54:48	ga_s2am_ard_3-2-1_50JLT_2021-11-02_final
2021-11-15 12:04:19	ga_s2am_ard_3-2-1_49KGQ_2021-11-15_final
2021-11-15 12:04:47	ga_s2am_ard_3-2-1_49JGN_2021-11-15_final
2021-12-05 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-12-05_final
2022-01-04 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2022-01-04_final
2022-01-08 11:46:53	ga_s2am_ard_3-2-1_50HNJ_2022-01-08_final
2022-01-08 11:47:16	ga_s2am_ard_3-2-1_50HLH_2022-01-08_final
2022-01-18 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2022-01-18_final
2022-01-24 12:04:28	ga_s2am_ard_3-2-1_49KHP_2022-01-24_final
2022-01-31 11:56:22	ga_s2am_ard_3-2-1_50JML_2022-01-31_final
2022-02-10 11:56:24	ga_s2am_ard_3-2-1_50JLL_2022-02-10_final
2022-02-23 12:04:25	ga_s2am_ard_3-2-1_49KGQ_2022-02-23_final
2022-03-15 12:05:01	ga_s2am_ard_3-2-1_49JHM_2022-03-15_final
2022-05-08 11:47:00	ga_s2am_ard_3-2-1_50HMJ_2022-05-08_final
2023-01-19 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2023-01-19_final.stac-item
2023-02-22 11:46:10	ga_s2am_ard_3-2-1_50JMM_2023-02-22_final.stac-item
2023-04-09 12:03:45	ga_s2am_ard_3-2-1_49KHS_2023-04-09_final.stac-item
2023-05-29 12:04:46	ga_s2am_ard_3-2-1_50JKT_2023-05-29_final.stac-item
2023-08-31 11:46:46	ga_s2am_ard_3-2-1_50HMK_2023-08-31_final.stac-item
2023-09-23 11:55:57	ga_s2am_ard_3-2-1_50JMN_2023-09-23_final.stac-item
2023-10-03 11:55:44	ga_s2am_ard_3-2-1_50JLP_2023-10-03_final.stac-item
2024-01-01 11:55:39	ga_s2am_ard_3-2-1_50JLP_2024-01-01_final.stac-item
2024-01-04 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2024-01-04_final.stac-item
2024-01-15 11:36:31	ga_s2am_ard_3-2-1_50HPK_2024-01-15_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

All years