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_49KHP_2015-10-21_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JKR_2015-12-17_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50JMT_2016-01-16_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_50JLR_2016-01-26_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_50JLS_2016-01-26_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_50JMS_2016-01-26_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50JLS_2016-03-16_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JPQ_2016-04-02_final.stac-item
2016-05-08 12:14:47	ga_s2am_ard_3-2-1_49JFN_2016-05-08_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50JLR_2016-11-28_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50JNQ_2016-12-15_final
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50JPR_2016-12-15_final
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_50JMT_2016-12-21_final
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49KHP_2017-02-22_final
2017-03-02 11:35:57	ga_s2am_ard_3-2-1_50HQK_2017-03-02_final
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50JPQ_2017-04-07_final.stac-item
2017-04-30 12:04:44	ga_s2am_ard_3-2-1_50JMS_2017-04-30_final
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JPP_2017-06-06_final
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JPQ_2017-06-06_final
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_50JLT_2017-06-29_final
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_50JMR_2017-06-29_final
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_50JMS_2017-08-18_final
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50HQH_2017-12-10_final
2019-01-17 11:55:12	ga_s2am_ard_3-2-1_50JPQ_2019-01-17_final
2019-01-27 11:55:23	ga_s2am_ard_3-2-1_50JPP_2019-01-27_final
2019-01-30 12:05:20	ga_s2am_ard_3-2-1_50JLQ_2019-01-30_final
2019-02-06 11:55:13	ga_s2am_ard_3-2-1_50JPQ_2019-02-06_final
2019-02-09 12:04:32	ga_s2am_ard_3-2-1_50JMT_2019-02-09_final
2019-02-16 11:55:09	ga_s2am_ard_3-2-1_50JLR_2019-02-16_final
2019-02-26 11:55:19	ga_s2am_ard_3-2-1_50JMQ_2019-02-26_final
2019-03-18 11:55:13	ga_s2am_ard_3-2-1_50JPQ_2019-03-18_final
2019-07-29 12:05:03	ga_s2am_ard_3-2-1_50JMR_2019-07-29_final
2019-11-03 11:55:19	ga_s2am_ard_3-2-1_50JPQ_2019-11-03_final
2019-12-09 12:14:18	ga_s2am_ard_3-2-1_49KHP_2019-12-09_final
2020-02-17 12:14:24	ga_s2am_ard_3-2-1_49KHP_2020-02-17_final
2020-07-20 11:55:40	ga_s2am_ard_3-2-1_50JNP_2020-07-20_final
2020-07-30 11:54:39	ga_s2am_ard_3-2-1_50JPT_2020-07-30_final
2020-08-02 12:05:14	ga_s2am_ard_3-2-1_50JLR_2020-08-02_final
2020-09-18 11:55:07	ga_s2am_ard_3-2-1_50JPR_2020-09-18_final
2020-09-18 11:55:39	ga_s2am_ard_3-2-1_50JNP_2020-09-18_final
2020-12-10 12:04:32	ga_s2am_ard_3-2-1_50JMT_2020-12-10_final
2021-01-29 12:04:36	ga_s2am_ard_3-2-1_50JMT_2021-01-29_final
2021-02-18 12:04:58	ga_s2am_ard_3-2-1_50JMR_2021-02-18_final
2021-08-24 11:57:08	ga_s2am_ard_3-2-1_50HMH_2021-08-24_final
2021-10-30 11:45:26	ga_s2am_ard_3-2-1_50JPQ_2021-10-30_final
2021-11-25 12:05:23	ga_s2am_ard_3-2-1_50JLQ_2021-11-25_final
2021-11-29 11:45:39	ga_s2am_ard_3-2-1_50JNP_2021-11-29_final
2021-12-12 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2021-12-12_final
2021-12-25 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2021-12-25_final
2022-01-01 11:55:36	ga_s2am_ard_3-2-1_50JNP_2022-01-01_final
2022-01-04 12:05:10	ga_s2am_ard_3-2-1_50JLR_2022-01-04_final
2022-01-11 11:55:14	ga_s2am_ard_3-2-1_50JLR_2022-01-11_final
2022-01-11 11:55:27	ga_s2am_ard_3-2-1_50JPP_2022-01-11_final
2022-01-18 11:45:45	ga_s2am_ard_3-2-1_50JNN_2022-01-18_final
2022-01-21 11:55:26	ga_s2am_ard_3-2-1_50JPP_2022-01-21_final
2022-02-07 11:47:16	ga_s2am_ard_3-2-1_50HPG_2022-02-07_final.stac-item
2022-02-10 11:55:25	ga_s2am_ard_3-2-1_50JPP_2022-02-10_final
2022-02-17 11:46:54	ga_s2am_ard_3-2-1_50HQH_2022-02-17_final
2022-03-15 12:05:02	ga_s2am_ard_3-2-1_50JMR_2022-03-15_final
2022-03-22 11:55:16	ga_s2am_ard_3-2-1_50JLR_2022-03-22_final
2022-03-22 11:55:29	ga_s2am_ard_3-2-1_50JPP_2022-03-22_final
2022-04-14 12:05:12	ga_s2am_ard_3-2-1_50JLR_2022-04-14_final.stac-item
2022-05-04 12:05:09	ga_s2am_ard_3-2-1_50JKR_2022-05-04_final
2022-05-11 11:55:30	ga_s2am_ard_3-2-1_50JPP_2022-05-11_final
2022-05-21 11:55:41	ga_s2am_ard_3-2-1_50JNP_2022-05-21_final
2022-06-30 11:55:11	ga_s2am_ard_3-2-1_50JLS_2022-06-30_final
2022-07-27 11:45:31	ga_s2am_ard_3-2-1_50JPQ_2022-07-27_final
2022-08-12 12:05:20	ga_s2am_ard_3-2-1_50JLR_2022-08-12_final
2022-08-22 12:05:21	ga_s2am_ard_3-2-1_49JFM_2022-08-22_final
2022-11-04 11:45:43	ga_s2am_ard_3-2-1_50JNP_2022-11-04_final.stac-item
2022-11-20 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2022-11-20_final.stac-item
2023-01-06 11:55:34	ga_s2am_ard_3-2-1_50JNP_2023-01-06_final.stac-item
2023-02-02 11:46:52	ga_s2am_ard_3-2-1_50HQH_2023-02-02_final.stac-item
2023-02-18 12:05:12	ga_s2am_ard_3-2-1_50JLR_2023-02-18_final.stac-item
2023-02-22 11:46:51	ga_s2am_ard_3-2-1_50HQH_2023-02-22_final.stac-item
2023-02-25 11:55:10	ga_s2am_ard_3-2-1_50JLR_2023-02-25_final.stac-item
2023-03-04 11:45:57	ga_s2am_ard_3-2-1_50JQM_2023-03-04_final.stac-item
2023-03-17 11:55:24	ga_s2am_ard_3-2-1_50JPP_2023-03-17_final.stac-item
2023-03-20 12:05:06	ga_s2am_ard_3-2-1_50JLR_2023-03-20_final.stac-item
2023-04-19 12:04:47	ga_s2am_ard_3-2-1_50JMS_2023-04-19_final.stac-item
2023-05-03 11:45:36	ga_s2am_ard_3-2-1_50JPP_2023-05-03_final.stac-item
2023-06-28 12:05:12	ga_s2am_ard_3-2-1_50JLR_2023-06-28_final.stac-item
2023-07-08 12:05:04	ga_s2am_ard_3-2-1_50JMR_2023-07-08_final.stac-item
2023-08-01 11:47:19	ga_s2am_ard_3-2-1_50HLH_2023-08-01_final.stac-item
2023-08-24 11:55:22	ga_s2am_ard_3-2-1_50JPQ_2023-08-24_final.stac-item
2023-12-02 11:55:08	ga_s2am_ard_3-2-1_50JPQ_2023-12-02_final.stac-item
2023-12-12 11:54:28	ga_s2am_ard_3-2-1_50JPT_2023-12-12_final.stac-item
2023-12-19 11:45:32	ga_s2am_ard_3-2-1_50JPP_2023-12-19_final.stac-item
2023-12-22 11:55:22	ga_s2am_ard_3-2-1_50JPP_2023-12-22_final.stac-item
2024-02-10 11:55:31	ga_s2am_ard_3-2-1_50JNP_2024-02-10_final.stac-item
2024-02-13 12:05:05	ga_s2am_ard_3-2-1_50JLR_2024-02-13_final.stac-item
2024-02-13 12:05:20	ga_s2am_ard_3-2-1_50JLQ_2024-02-13_final.stac-item
2024-02-27 11:45:20	ga_s2am_ard_3-2-1_50JPQ_2024-02-27_final.stac-item
2024-03-01 11:55:13	ga_s2am_ard_3-2-1_50JLR_2024-03-01_final.stac-item
2024-03-01 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2024-03-01_final.stac-item
2024-03-11 11:57:20	ga_s2am_ard_3-2-1_50HMG_2024-03-11_final.stac-item
2024-03-21 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2024-03-21_final.stac-item
2024-04-10 11:55:16	ga_s2am_ard_3-2-1_50JPQ_2024-04-10_final.stac-item
2024-04-20 11:55:16	ga_s2am_ard_3-2-1_50JLR_2024-04-20_final.stac-item
2024-05-03 12:04:51	ga_s2am_ard_3-2-1_50JMS_2024-05-03_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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