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
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JPQ_2015-11-14_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JPR_2015-11-14_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JLT_2015-12-17_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_50JMS_2016-01-26_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JNN_2016-02-02_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JNQ_2016-02-02_final.stac-item
2016-03-06 12:04:37	ga_s2am_ard_3-2-1_50JLR_2016-03-06_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_50HQG_2016-09-13_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49KHP_2016-11-14_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50JNP_2016-11-28_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50JNP_2016-12-15_final
2017-01-31 11:26:14	ga_s2am_ard_3-2-1_50JRS_2017-01-31_final
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_50KKV_2017-02-22_final
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_50KKV_2017-08-01_final
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_50KKU_2017-11-19_final
2018-12-14 12:13:59	ga_s2am_ard_3-2-1_50KKV_2018-12-14_final
2018-12-14 12:14:00	ga_s2am_ard_3-2-1_49KHQ_2018-12-14_final
2019-01-24 11:45:18	ga_s2am_ard_3-2-1_50JPQ_2019-01-24_final
2019-01-27 11:55:12	ga_s2am_ard_3-2-1_50JPQ_2019-01-27_final
2019-01-27 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2019-01-27_final
2019-01-30 12:04:32	ga_s2am_ard_3-2-1_50JMT_2019-01-30_final
2019-01-30 12:05:20	ga_s2am_ard_3-2-1_50JLQ_2019-01-30_final
2019-02-16 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2019-02-16_final
2019-02-19 12:04:32	ga_s2am_ard_3-2-1_50JMT_2019-02-19_final
2019-02-26 11:55:16	ga_s2am_ard_3-2-1_50JNQ_2019-02-26_final
2019-08-01 12:14:23	ga_s2am_ard_3-2-1_50KKU_2019-08-01_final
2019-12-13 11:54:29	ga_s2am_ard_3-2-1_50JPT_2019-12-13_final
2019-12-13 11:55:22	ga_s2am_ard_3-2-1_50JPP_2019-12-13_final
2019-12-20 11:45:55	ga_s2am_ard_3-2-1_50JQM_2019-12-20_final
2020-07-30 11:55:21	ga_s2am_ard_3-2-1_50JPQ_2020-07-30_final
2020-09-02 11:34:54	ga_s2am_ard_3-2-1_50JRS_2020-09-02_final
2020-09-04 12:14:25	ga_s2am_ard_3-2-1_49KHP_2020-09-04_final
2020-09-18 11:55:31	ga_s2am_ard_3-2-1_50JPP_2020-09-18_final
2020-09-18 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2020-09-18_final
2020-09-22 11:34:54	ga_s2am_ard_3-2-1_50JRS_2020-09-22_final
2020-09-22 11:36:10	ga_s2am_ard_3-2-1_50JQM_2020-09-22_final
2021-08-24 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2021-08-24_final
2021-08-24 11:57:08	ga_s2am_ard_3-2-1_50HMH_2021-08-24_final
2021-11-25 12:05:23	ga_s2am_ard_3-2-1_50JLQ_2021-11-25_final
2021-12-06 11:36:04	ga_s2am_ard_3-2-1_50JQM_2021-12-06_final
2021-12-12 11:55:15	ga_s2am_ard_3-2-1_50JPQ_2021-12-12_final
2021-12-25 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2021-12-25_final
2021-12-26 11:36:07	ga_s2am_ard_3-2-1_50JQM_2021-12-26_final
2022-03-09 11:46:57	ga_s2am_ard_3-2-1_50HQH_2022-03-09_final
2022-03-16 11:36:09	ga_s2am_ard_3-2-1_50JQM_2022-03-16_final
2022-03-19 11:46:04	ga_s2am_ard_3-2-1_50JQM_2022-03-19_final
2022-03-22 11:55:16	ga_s2am_ard_3-2-1_50JLR_2022-03-22_final
2022-04-14 12:05:06	ga_s2am_ard_3-2-1_50JLR_2022-04-14_final
2022-04-14 12:05:12	ga_s2am_ard_3-2-1_50JLR_2022-04-14_final.stac-item
2022-05-04 12:05:03	ga_s2am_ard_3-2-1_50JMR_2022-05-04_final
2022-05-04 12:05:08	ga_s2am_ard_3-2-1_50JLR_2022-05-04_final
2022-05-04 12:05:14	ga_s2am_ard_3-2-1_50JLR_2022-05-04_final
2022-05-14 12:04:37	ga_s2am_ard_3-2-1_49JHN_2022-05-14_final
2022-05-21 11:55:33	ga_s2am_ard_3-2-1_50JPP_2022-05-21_final
2022-07-27 11:45:31	ga_s2am_ard_3-2-1_50JPQ_2022-07-27_final
2022-08-12 12:05:35	ga_s2am_ard_3-2-1_50JLQ_2022-08-12_final
2022-10-18 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2022-10-18_final.stac-item
2022-11-04 11:46:05	ga_s2am_ard_3-2-1_50JQM_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
2022-11-27 11:55:26	ga_s2am_ard_3-2-1_50JPP_2022-11-27_final.stac-item
2022-12-14 11:45:21	ga_s2am_ard_3-2-1_50JPQ_2022-12-14_final.stac-item
2022-12-27 11:55:14	ga_s2am_ard_3-2-1_50JPQ_2022-12-27_final.stac-item
2022-12-27 11:55:33	ga_s2am_ard_3-2-1_50JNP_2022-12-27_final.stac-item
2023-01-03 11:45:20	ga_s2am_ard_3-2-1_50JPQ_2023-01-03_final.stac-item
2023-02-15 11:55:10	ga_s2am_ard_3-2-1_50JLR_2023-02-15_final.stac-item
2023-03-04 11:45:57	ga_s2am_ard_3-2-1_50JQM_2023-03-04_final.stac-item
2023-03-10 12:05:03	ga_s2am_ard_3-2-1_50JLR_2023-03-10_final.stac-item
2023-03-17 11:55:25	ga_s2am_ard_3-2-1_50JLQ_2023-03-17_final.stac-item
2023-03-27 11:55:11	ga_s2am_ard_3-2-1_50JLR_2023-03-27_final.stac-item
2023-03-27 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2023-03-27_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 11:56:52	ga_s2am_ard_3-2-1_50HMJ_2023-05-16_final.stac-item
2023-05-20 11:36:07	ga_s2am_ard_3-2-1_50JQM_2023-05-20_final.stac-item
2023-06-28 12:04:54	ga_s2am_ard_3-2-1_50JMS_2023-06-28_final.stac-item
2023-07-15 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2023-07-15_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 11:55:41	ga_s2am_ard_3-2-1_50JNP_2023-08-24_final.stac-item
2023-09-17 11:36:09	ga_s2am_ard_3-2-1_50JQM_2023-09-17_final.stac-item
2023-10-07 11:36:06	ga_s2am_ard_3-2-1_50JQM_2023-10-07_final.stac-item
2023-11-12 11:55:12	ga_s2am_ard_3-2-1_50JLR_2023-11-12_final.stac-item
2023-11-12 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2023-11-12_final.stac-item
2023-11-15 12:05:21	ga_s2am_ard_3-2-1_50JLQ_2023-11-15_final.stac-item
2023-11-22 11:55:22	ga_s2am_ard_3-2-1_50JPP_2023-11-22_final.stac-item
2023-12-02 11:55:27	ga_s2am_ard_3-2-1_50JNP_2023-12-02_final.stac-item
2023-12-08 12:14:15	ga_s2am_ard_3-2-1_49KHP_2023-12-08_final.stac-item
2023-12-09 11:45:55	ga_s2am_ard_3-2-1_50JQM_2023-12-09_final.stac-item
2023-12-15 12:05:04	ga_s2am_ard_3-2-1_50JLR_2023-12-15_final.stac-item
2024-01-08 11:45:56	ga_s2am_ard_3-2-1_50JQM_2024-01-08_final.stac-item
2024-01-15 11:35:58	ga_s2am_ard_3-2-1_50JQM_2024-01-15_final.stac-item
2024-01-21 11:55:27	ga_s2am_ard_3-2-1_50JNP_2024-01-21_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
2024-02-14 11:36:03	ga_s2am_ard_3-2-1_50JQM_2024-02-14_final.stac-item
2024-03-01 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2024-03-01_final.stac-item
2024-03-21 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2024-03-21_final.stac-item
2024-04-03 12:04:33	ga_s2am_ard_3-2-1_50JMT_2024-04-03_final.stac-item
2024-04-10 11:55:35	ga_s2am_ard_3-2-1_50JNP_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
2024-04-27 11:46:03	ga_s2am_ard_3-2-1_50JQM_2024-04-27_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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