Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

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_49KHR_2015-10-21_final.stac-item
2015-10-21 12:09:42	ga_s2am_ard_3-2-1_50KKU_2015-10-21_final.stac-item
2015-10-22 11:38:10	ga_s2am_ard_3-2-1_50HQH_2015-10-22_final.stac-item
2015-10-22 11:38:10	ga_s2am_ard_3-2-1_50JQM_2015-10-22_final.stac-item
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_50KLV_2015-10-28_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JPQ_2015-11-14_final.stac-item
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_50KKV_2015-11-30_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JKR_2015-12-17_final.stac-item
2015-12-24 11:56:44	ga_s2am_ard_3-2-1_50HMK_2015-12-24_final.stac-item
2016-01-09 12:16:04	ga_s2am_ard_3-2-1_49KGR_2016-01-09_final.stac-item
2016-02-05 12:04:38	ga_s2am_ard_3-2-1_50JLT_2016-02-05_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50JKM_2016-02-15_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JNN_2016-03-03_final.stac-item
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49KGR_2016-03-09_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50JLS_2016-04-15_final.stac-item
2016-04-25 12:03:51	ga_s2am_ard_3-2-1_50KLA_2016-04-25_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KHQ_2016-05-18_final.stac-item
2016-06-07 12:13:25	ga_s2am_ard_3-2-1_49KHP_2016-06-07_final.stac-item
2016-07-27 12:13:48	ga_s2am_ard_3-2-1_49KGR_2016-07-27_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KHS_2016-08-26_final
2016-10-12 12:04:37	ga_s2am_ard_3-2-1_50JMR_2016-10-12_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_50JMS_2016-12-01_final.stac-item
2016-12-21 12:04:53	ga_s2am_ard_3-2-1_50JLM_2016-12-21_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49KHP_2017-01-20_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50JQM_2017-02-03_final.stac-item
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49KGQ_2017-03-14_final.stac-item
2017-04-03 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2017-04-03_final.stac-item
2017-05-23 12:13:46	ga_s2am_ard_3-2-1_49KGR_2017-05-23_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_49KHQ_2017-09-17_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_50KKU_2017-09-30_final.stac-item
2017-10-20 12:13:21	ga_s2am_ard_3-2-1_49KGQ_2017-10-20_final.stac-item
2017-10-20 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2017-10-20_final.stac-item
2017-10-20 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2017-10-20_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2017-11-19_final.stac-item
2018-12-14 12:13:59	ga_s2am_ard_3-2-1_50KKV_2018-12-14_final.stac-item
2018-12-14 12:14:13	ga_s2am_ard_3-2-1_49KHP_2018-12-14_final.stac-item
2019-01-20 12:04:50	ga_s2am_ard_3-2-1_50JLS_2019-01-20_final.stac-item
2019-01-20 12:05:04	ga_s2am_ard_3-2-1_50JLR_2019-01-20_final.stac-item
2019-01-21 11:34:45	ga_s2am_ard_3-2-1_50JRS_2019-01-21_final.stac-item
2019-01-31 11:34:46	ga_s2am_ard_3-2-1_50JRS_2019-01-31_final.stac-item
2019-02-09 12:03:52	ga_s2am_ard_3-2-1_50KLA_2019-02-09_final.stac-item
2019-02-09 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2019-02-09_final.stac-item
2019-02-09 12:04:45	ga_s2am_ard_3-2-1_50JMS_2019-02-09_final.stac-item
2019-02-09 12:04:50	ga_s2am_ard_3-2-1_50JLS_2019-02-09_final.stac-item
2019-02-09 12:05:05	ga_s2am_ard_3-2-1_50JLR_2019-02-09_final.stac-item
2019-02-16 11:55:12	ga_s2am_ard_3-2-1_50JPQ_2019-02-16_final.stac-item
2019-02-16 11:55:23	ga_s2am_ard_3-2-1_50JPP_2019-02-16_final.stac-item
2019-02-19 12:04:50	ga_s2am_ard_3-2-1_50JLS_2019-02-19_final.stac-item
2019-02-19 12:05:04	ga_s2am_ard_3-2-1_50JLR_2019-02-19_final.stac-item
2019-02-20 11:34:45	ga_s2am_ard_3-2-1_50JRS_2019-02-20_final.stac-item
2019-02-23 11:45:17	ga_s2am_ard_3-2-1_50JPQ_2019-02-23_final.stac-item
2019-02-23 11:45:56	ga_s2am_ard_3-2-1_50JQM_2019-02-23_final.stac-item
2019-02-26 11:55:23	ga_s2am_ard_3-2-1_50JLQ_2019-02-26_final.stac-item
2019-03-11 12:03:51	ga_s2am_ard_3-2-1_50KLA_2019-03-11_final.stac-item
2019-03-11 12:04:01	ga_s2am_ard_3-2-1_50KLV_2019-03-11_final.stac-item
2019-03-11 12:04:44	ga_s2am_ard_3-2-1_50JMS_2019-03-11_final.stac-item
2019-03-21 12:04:08	ga_s2am_ard_3-2-1_50KLV_2019-03-21_final.stac-item
2019-03-21 12:04:16	ga_s2am_ard_3-2-1_49KGQ_2019-03-21_final.stac-item
2019-05-04 11:46:01	ga_s2am_ard_3-2-1_50JQM_2019-05-04_final.stac-item
2019-05-14 11:46:05	ga_s2am_ard_3-2-1_50JQM_2019-05-14_final.stac-item
2019-12-13 11:55:11	ga_s2am_ard_3-2-1_50JPQ_2019-12-13_final.stac-item
2019-12-13 11:55:22	ga_s2am_ard_3-2-1_50JPP_2019-12-13_final.stac-item
2020-01-25 12:03:20	ga_s2am_ard_3-2-1_50KLC_2020-01-25_final.stac-item
2020-01-28 12:14:24	ga_s2am_ard_3-2-1_49JHN_2020-01-28_final.stac-item
2020-07-26 12:14:24	ga_s2am_ard_3-2-1_50KKU_2020-07-26_final.stac-item
2020-09-08 11:55:39	ga_s2am_ard_3-2-1_50JNP_2020-09-08_final.stac-item
2020-09-18 11:55:07	ga_s2am_ard_3-2-1_50JPR_2020-09-18_final.stac-item
2020-09-18 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2020-09-18_final.stac-item
2020-09-18 11:56:41	ga_s2am_ard_3-2-1_50HMK_2020-09-18_final.stac-item
2020-09-18 11:56:45	ga_s2am_ard_3-2-1_50HLK_2020-09-18_final.stac-item
2020-09-21 12:04:59	ga_s2am_ard_3-2-1_50JLS_2020-09-21_final.stac-item
2020-09-21 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2020-09-21_final.stac-item
2020-09-25 11:46:06	ga_s2am_ard_3-2-1_50JQM_2020-09-25_final.stac-item
2020-09-28 11:55:21	ga_s2am_ard_3-2-1_50JPQ_2020-09-28_final.stac-item
2020-10-01 12:03:32	ga_s2am_ard_3-2-1_50KLC_2020-10-01_final.stac-item
2020-10-01 12:04:16	ga_s2am_ard_3-2-1_50KLV_2020-10-01_final.stac-item
2020-10-01 12:04:41	ga_s2am_ard_3-2-1_50JMT_2020-10-01_final.stac-item
2020-10-05 11:45:27	ga_s2am_ard_3-2-1_50JPQ_2020-10-05_final.stac-item
2021-01-29 12:04:59	ga_s2am_ard_3-2-1_50JMR_2021-01-29_final.stac-item
2021-01-29 12:05:08	ga_s2am_ard_3-2-1_50JLR_2021-01-29_final.stac-item
2021-11-22 11:57:23	ga_s2am_ard_3-2-1_50HLG_2021-11-22_final
2022-02-17 11:46:54	ga_s2am_ard_3-2-1_50HQH_2022-02-17_final.stac-item
2022-03-09 11:46:05	ga_s2am_ard_3-2-1_50JQM_2022-03-09_final.stac-item
2022-11-04 11:46:05	ga_s2am_ard_3-2-1_50JQM_2022-11-04_final.stac-item
2023-02-18 12:05:12	ga_s2am_ard_3-2-1_50JLQ_2023-02-18_nrt.stac-item
2023-02-18 12:05:12	ga_s2am_ard_3-2-1_50JLQ_2023-02-18_final
2023-05-03 11:45:27	ga_s2am_ard_3-2-1_50JPQ_2023-05-03_final
2023-05-16 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2023-05-16_final
2023-05-16 11:57:10	ga_s2am_ard_3-2-1_50HLH_2023-05-16_final
2023-05-16 11:57:21	ga_s2am_ard_3-2-1_50HMG_2023-05-16_final
2023-07-02 11:46:58	ga_s2am_ard_3-2-1_50HQH_2023-07-02_final
2023-07-15 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2023-07-15_final
2023-08-01 11:47:19	ga_s2am_ard_3-2-1_50HLH_2023-08-01_final
2023-11-28 12:14:12	ga_s2am_ard_3-2-1_50KKU_2023-11-28_final
2023-12-05 12:04:52	ga_s2am_ard_3-2-1_50JMR_2023-12-05_final
2023-12-08 12:14:03	ga_s2am_ard_3-2-1_49KHQ_2023-12-08_final
2023-12-15 12:06:00	ga_s2am_ard_3-2-1_50JLM_2023-12-15_final
2023-12-19 11:45:17	ga_s2am_ard_3-2-1_50JPQ_2023-12-19_final
2024-01-18 11:45:52	ga_s2am_ard_3-2-1_50JQM_2024-01-18_final
2024-03-01 11:56:37	ga_s2am_ard_3-2-1_50HLK_2024-03-01_final

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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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