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
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_49JHM_2015-12-07_final.stac-item
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HPG_2015-12-08_final
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JKS_2015-12-17_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49KGQ_2016-03-16_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49KHS_2016-03-16_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50JKQ_2016-04-15_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_50JKQ_2016-06-24_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50JLQ_2016-07-14_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50HQH_2016-09-06_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_50JKR_2016-09-12_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_50HQG_2016-09-13_final
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KHS_2016-10-22_final
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50JKQ_2016-11-01_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50JKT_2016-11-01_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHQ_2016-11-11_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50JKQ_2016-11-21_final.stac-item
2017-01-04 11:46:21	ga_s2am_ard_3-2-1_50HMK_2017-01-04_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_50JKS_2017-01-20_final.stac-item
2017-03-01 12:03:41	ga_s2am_ard_3-2-1_49KHQ_2017-03-01_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50HMK_2017-03-05_final.stac-item
2017-03-08 11:56:00	ga_s2am_ard_3-2-1_50HMK_2017-03-08_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49KHP_2017-05-10_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_50JKQ_2017-05-10_final.stac-item
2017-06-26 11:56:32	ga_s2am_ard_3-2-1_50HMJ_2017-06-26_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_50JKT_2017-06-29_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49JHM_2017-07-09_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50HMK_2017-08-25_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JHM_2017-09-17_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_50JKQ_2017-11-06_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_49KGQ_2018-01-25_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49KGQ_2018-02-14_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JLQ_2018-03-13_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50HMK_2018-04-29_final.stac-item
2018-05-28 12:13:23	ga_s2am_ard_3-2-1_49KHP_2018-05-28_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_49JHM_2018-06-14_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_49KGQ_2018-06-14_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JLQ_2018-06-14_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKQ_2018-06-24_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50HMK_2018-07-11_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_49JHM_2018-08-03_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50JKQ_2018-09-12_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49JHN_2018-10-02_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50HMK_2018-10-09_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JLQ_2018-10-22_final.stac-item
2019-03-28 11:56:36	ga_s2am_ard_3-2-1_50HMK_2019-03-28_final.stac-item
2019-03-31 12:04:57	ga_s2am_ard_3-2-1_49JHM_2019-03-31_final.stac-item
2019-04-20 12:05:00	ga_s2am_ard_3-2-1_49JHM_2019-04-20_final.stac-item
2019-04-24 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2019-04-24_final.stac-item
2019-04-30 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2019-04-30_final.stac-item
2019-05-27 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2019-05-27_final.stac-item
2019-06-29 12:05:31	ga_s2am_ard_3-2-1_50JKQ_2019-06-29_final.stac-item
2019-07-03 11:47:19	ga_s2am_ard_3-2-1_50HLH_2019-07-03_final.stac-item
2019-07-19 12:05:02	ga_s2am_ard_3-2-1_49JHM_2019-07-19_final.stac-item
2019-08-25 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2019-08-25_final.stac-item
2019-10-27 12:05:10	ga_s2am_ard_3-2-1_50JKR_2019-10-27_final.stac-item
2019-10-27 12:05:29	ga_s2am_ard_3-2-1_50JKQ_2019-10-27_final.stac-item
2019-10-31 11:46:56	ga_s2am_ard_3-2-1_50HQH_2019-10-31_final.stac-item
2019-11-16 12:04:58	ga_s2am_ard_3-2-1_49JHM_2019-11-16_final.stac-item
2019-12-06 12:04:55	ga_s2am_ard_3-2-1_50JKS_2019-12-06_final.stac-item
2020-03-22 11:56:33	ga_s2am_ard_3-2-1_50HMK_2020-03-22_final.stac-item
2020-06-07 11:47:16	ga_s2am_ard_3-2-1_50HMH_2020-06-07_final.stac-item
2020-06-16 12:14:15	ga_s2am_ard_3-2-1_49KHQ_2020-06-16_final.stac-item
2020-06-20 11:57:12	ga_s2am_ard_3-2-1_50HMH_2020-06-20_final.stac-item
2020-10-04 12:14:14	ga_s2am_ard_3-2-1_49KHQ_2020-10-04_final.stac-item
2021-01-26 11:55:13	ga_s2am_ard_3-2-1_50JLR_2021-01-26_final.stac-item
2021-01-29 12:05:12	ga_s2am_ard_3-2-1_50JKR_2021-01-29_final.stac-item
2021-04-22 12:14:04	ga_s2am_ard_3-2-1_49KHQ_2021-04-22_final.stac-item
2021-04-22 12:14:17	ga_s2am_ard_3-2-1_49KHP_2021-04-22_final.stac-item
2021-06-05 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2021-06-05_final.stac-item
2021-06-25 11:57:13	ga_s2am_ard_3-2-1_50HMH_2021-06-25_final.stac-item
2021-07-29 11:37:30	ga_s2am_ard_3-2-1_50HNG_2021-07-29_final
2021-09-13 11:55:13	ga_s2am_ard_3-2-1_50JLR_2021-09-13_final.stac-item
2021-10-06 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2021-10-06_final.stac-item
2021-10-10 11:47:33	ga_s2am_ard_3-2-1_50HLG_2021-10-10_final
2021-11-05 12:05:15	ga_s2am_ard_3-2-1_50JKR_2021-11-05_final.stac-item
2022-02-13 12:04:57	ga_s2am_ard_3-2-1_50JKS_2022-02-13_final.stac-item
2022-02-23 12:04:59	ga_s2am_ard_3-2-1_49JHM_2022-02-23_final.stac-item
2022-02-26 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2022-02-26_final.stac-item
2022-03-15 12:05:01	ga_s2am_ard_3-2-1_50JKS_2022-03-15_final.stac-item
2022-04-14 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2022-04-14_final.stac-item
2022-09-11 12:04:29	ga_s2am_ard_3-2-1_49KGQ_2022-09-11_final.stac-item
2022-10-21 12:05:28	ga_s2am_ard_3-2-1_50JKQ_2022-10-21_final.stac-item
2022-10-31 12:05:16	ga_s2am_ard_3-2-1_50JKR_2022-10-31_final.stac-item
2022-11-24 11:46:53	ga_s2am_ard_3-2-1_50HQH_2022-11-24_final.stac-item
2022-12-03 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2022-12-03_final.stac-item
2022-12-30 12:05:11	ga_s2am_ard_3-2-1_50JKR_2022-12-30_final.stac-item
2023-03-04 11:47:24	ga_s2am_ard_3-2-1_50HLG_2023-03-04_final
2023-04-20 11:37:23	ga_s2am_ard_3-2-1_50HPG_2023-04-20_final
2023-04-29 12:05:12	ga_s2am_ard_3-2-1_50JKR_2023-04-29_final
2023-07-15 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2023-07-15_final
2023-08-30 12:14:14	ga_s2am_ard_3-2-1_49KHQ_2023-08-30_final
2023-09-26 12:06:06	ga_s2am_ard_3-2-1_50JLM_2023-09-26_final
2023-09-29 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2023-09-29_final
2023-11-25 12:05:06	ga_s2am_ard_3-2-1_50JKR_2023-11-25_final
2023-12-02 11:57:12	ga_s2am_ard_3-2-1_50HMG_2023-12-02_final
2023-12-09 11:47:21	ga_s2am_ard_3-2-1_50HLG_2023-12-09_final
2023-12-19 11:47:23	ga_s2am_ard_3-2-1_50HLG_2023-12-19_final
2023-12-28 12:14:18	ga_s2am_ard_3-2-1_49KHP_2023-12-28_final
2024-01-14 12:05:16	ga_s2am_ard_3-2-1_50JLQ_2024-01-14_final
2024-02-07 11:47:22	ga_s2am_ard_3-2-1_50HLG_2024-02-07_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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