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_50JMT_2015-10-28_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JLT_2015-12-17_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50JLM_2016-01-16_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50JLQ_2016-04-15_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JMS_2016-08-13_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JLR_2016-11-18_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JNP_2016-11-18_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50JLR_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50JMS_2016-11-21_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_50JMT_2016-12-01_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49JGN_2016-12-11_final
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50JNP_2017-01-24_final
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JMT_2017-01-30_final
2017-03-01 12:04:35	ga_s2am_ard_3-2-1_50JMR_2017-03-01_final
2019-02-16 11:55:31	ga_s2am_ard_3-2-1_50JNP_2019-02-16_final
2019-02-19 12:05:04	ga_s2am_ard_3-2-1_50JLR_2019-02-19_final
2019-02-22 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2019-02-22_final
2019-02-26 11:54:40	ga_s2am_ard_3-2-1_50JLT_2019-02-26_final
2019-03-01 12:04:44	ga_s2am_ard_3-2-1_50JMS_2019-03-01_final
2019-03-11 12:04:31	ga_s2am_ard_3-2-1_50JMT_2019-03-11_final
2019-03-18 11:55:32	ga_s2am_ard_3-2-1_50JNP_2019-03-18_final
2019-06-02 12:14:33	ga_s2am_ard_3-2-1_49JHN_2019-06-02_final
2019-07-29 12:04:40	ga_s2am_ard_3-2-1_50JMT_2019-07-29_final
2019-07-29 12:04:53	ga_s2am_ard_3-2-1_50JMS_2019-07-29_final
2019-11-03 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2019-11-03_final
2019-11-10 11:46:56	ga_s2am_ard_3-2-1_50HQH_2019-11-10_final
2019-11-26 12:04:36	ga_s2am_ard_3-2-1_50JMT_2019-11-26_final
2019-11-26 12:04:49	ga_s2am_ard_3-2-1_50JMS_2019-11-26_final
2019-11-30 11:46:53	ga_s2am_ard_3-2-1_50HQH_2019-11-30_final
2019-12-07 11:37:24	ga_s2am_ard_3-2-1_50HNG_2019-12-07_final.stac-item
2019-12-13 11:54:36	ga_s2am_ard_3-2-1_50JMT_2019-12-13_final
2020-08-02 12:04:54	ga_s2am_ard_3-2-1_50JMS_2020-08-02_final
2020-09-18 11:54:45	ga_s2am_ard_3-2-1_50JMT_2020-09-18_final
2020-09-18 11:55:17	ga_s2am_ard_3-2-1_50JLR_2020-09-18_final
2020-09-21 12:04:40	ga_s2am_ard_3-2-1_50JMT_2020-09-21_final
2020-10-05 11:45:45	ga_s2am_ard_3-2-1_50JNP_2020-10-05_final
2020-11-13 12:14:25	ga_s2am_ard_3-2-1_49KHP_2020-11-13_final
2021-08-24 11:55:37	ga_s2am_ard_3-2-1_50JNP_2021-08-24_final
2021-08-24 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2021-08-24_final
2021-11-15 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2021-11-15_final
2021-11-22 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2021-11-22_final
2021-11-22 11:55:35	ga_s2am_ard_3-2-1_50JNP_2021-11-22_final
2021-12-02 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2021-12-02_final
2021-12-19 11:45:40	ga_s2am_ard_3-2-1_50JNP_2021-12-19_final
2021-12-22 11:55:36	ga_s2am_ard_3-2-1_50JNP_2021-12-22_final
2021-12-22 11:56:41	ga_s2am_ard_3-2-1_50HLK_2021-12-22_final
2022-01-04 12:05:00	ga_s2am_ard_3-2-1_50JMR_2022-01-04_final
2022-02-10 11:55:12	ga_s2am_ard_3-2-1_50JLR_2022-02-10_final
2022-03-05 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2022-03-05_final
2022-03-09 11:47:32	ga_s2am_ard_3-2-1_50HLG_2022-03-09_final.stac-item
2022-03-12 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2022-03-12_final
2022-04-14 12:05:26	ga_s2am_ard_3-2-1_50JLQ_2022-04-14_final
2022-05-04 12:04:53	ga_s2am_ard_3-2-1_50JMS_2022-05-04_final
2022-05-04 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2022-05-04_final
2022-06-03 12:05:16	ga_s2am_ard_3-2-1_50JLR_2022-06-03_final
2022-06-30 11:55:26	ga_s2am_ard_3-2-1_50JLR_2022-06-30_final
2022-06-30 11:55:40	ga_s2am_ard_3-2-1_50JLQ_2022-06-30_final
2022-06-30 11:55:48	ga_s2am_ard_3-2-1_50JNP_2022-06-30_final
2022-07-23 12:05:09	ga_s2am_ard_3-2-1_50JMR_2022-07-23_final
2022-07-27 11:45:49	ga_s2am_ard_3-2-1_50JNP_2022-07-27_final
2022-08-06 11:45:50	ga_s2am_ard_3-2-1_50JNP_2022-08-06_final.stac-item
2022-08-22 12:05:35	ga_s2am_ard_3-2-1_50JLQ_2022-08-22_final.stac-item
2022-10-18 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2022-10-18_final.stac-item
2022-10-25 11:45:47	ga_s2am_ard_3-2-1_50JNP_2022-10-25_final.stac-item
2022-10-28 11:55:16	ga_s2am_ard_3-2-1_50JLR_2022-10-28_final.stac-item
2022-11-20 12:05:09	ga_s2am_ard_3-2-1_50JLR_2022-11-20_final.stac-item
2022-12-24 11:46:51	ga_s2am_ard_3-2-1_50HQH_2022-12-24_final.stac-item
2023-02-18 12:04:45	ga_s2am_ard_3-2-1_50JMS_2023-02-18_final.stac-item
2023-02-18 12:04:55	ga_s2am_ard_3-2-1_50JMR_2023-02-18_final.stac-item
2023-03-10 12:04:28	ga_s2am_ard_3-2-1_49JHN_2023-03-10_final.stac-item
2023-03-10 12:05:18	ga_s2am_ard_3-2-1_50JLQ_2023-03-10_final.stac-item
2023-04-13 11:45:39	ga_s2am_ard_3-2-1_50JNP_2023-04-13_final.stac-item
2023-04-19 12:05:07	ga_s2am_ard_3-2-1_50JLR_2023-04-19_final.stac-item
2023-04-19 12:05:22	ga_s2am_ard_3-2-1_50JLQ_2023-04-19_final.stac-item
2023-05-16 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2023-05-16_final.stac-item
2023-05-16 11:55:36	ga_s2am_ard_3-2-1_50JNP_2023-05-16_final.stac-item
2023-06-28 12:04:51	ga_s2am_ard_3-2-1_50JLT_2023-06-28_final.stac-item
2023-06-28 12:04:51	ga_s2am_ard_3-2-1_50JLS_2023-06-28_final.stac-item
2023-08-14 11:55:40	ga_s2am_ard_3-2-1_50JNP_2023-08-14_final.stac-item
2023-08-31 11:47:19	ga_s2am_ard_3-2-1_50HLH_2023-08-31_final.stac-item
2023-11-15 12:05:21	ga_s2am_ard_3-2-1_50JLQ_2023-11-15_final.stac-item
2023-11-25 12:05:03	ga_s2am_ard_3-2-1_50JLR_2023-11-25_final.stac-item
2023-12-08 12:14:15	ga_s2am_ard_3-2-1_49KHP_2023-12-08_final.stac-item
2023-12-12 11:54:50	ga_s2am_ard_3-2-1_50JMS_2023-12-12_final.stac-item
2023-12-12 11:55:08	ga_s2am_ard_3-2-1_50JLR_2023-12-12_final.stac-item
2024-02-13 12:04:46	ga_s2am_ard_3-2-1_50JMS_2024-02-13_final.stac-item
2024-02-23 12:04:41	ga_s2am_ard_3-2-1_50JMT_2024-02-23_final.stac-item
2024-02-23 12:04:43	ga_s2am_ard_3-2-1_50JLS_2024-02-23_final.stac-item
2024-02-23 12:04:47	ga_s2am_ard_3-2-1_50JMS_2024-02-23_final.stac-item
2024-03-17 12:14:21	ga_s2am_ard_3-2-1_49KHP_2024-03-17_final.stac-item
2024-03-21 11:55:36	ga_s2am_ard_3-2-1_50JNP_2024-03-21_final.stac-item
2024-03-24 12:05:09	ga_s2am_ard_3-2-1_50JLR_2024-03-24_final.stac-item
2024-03-27 12:14:46	ga_s2am_ard_3-2-1_49JFN_2024-03-27_final.stac-item
2024-03-31 11:55:02	ga_s2am_ard_3-2-1_50JMS_2024-03-31_final.stac-item
2024-03-31 11:55:12	ga_s2am_ard_3-2-1_50JLR_2024-03-31_final.stac-item
2024-04-04 11:37:24	ga_s2am_ard_3-2-1_50HNG_2024-04-04_final.stac-item
2024-04-10 11:55:13	ga_s2am_ard_3-2-1_50JLR_2024-04-10_final.stac-item
2024-04-10 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2024-04-10_final.stac-item
2024-04-17 11:46:56	ga_s2am_ard_3-2-1_50HQH_2024-04-17_final.stac-item
2024-04-20 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2024-04-20_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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