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
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KGP_2015-11-30_final.stac-item
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HNG_2015-12-08_final
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_50JKQ_2015-12-17_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50JNR_2016-05-09_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JMQ_2016-05-22_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_50JLT_2016-06-14_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JLQ_2016-07-01_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_50JKQ_2016-09-12_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50JNQ_2016-09-19_final.stac-item
2016-10-12 12:04:37	ga_s2am_ard_3-2-1_49JHM_2016-10-12_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_50JKR_2016-12-01_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50JLS_2016-12-11_final.stac-item
2016-12-21 12:04:53	ga_s2am_ard_3-2-1_50JKS_2016-12-21_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50JNN_2017-02-03_final.stac-item
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_50JKS_2017-03-11_final.stac-item
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_50JKS_2017-03-21_final.stac-item
2017-04-27 11:49:47	ga_s2am_ard_3-2-1_50HMK_2017-04-27_final.stac-item
2017-05-17 11:49:48	ga_s2am_ard_3-2-1_50JLR_2017-05-17_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50HMK_2017-06-06_final.stac-item
2017-08-28 12:04:42	ga_s2am_ard_3-2-1_50JLR_2017-08-28_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_49JHM_2017-11-06_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49JHM_2017-12-16_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_50JKS_2017-12-16_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_49KHP_2018-01-05_final.stac-item
2018-02-21 11:50:43	ga_s2am_ard_3-2-1_50JLT_2018-02-21_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JNQ_2018-02-21_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50JKQ_2018-02-24_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50HMK_2018-04-29_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLT_2018-05-22_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
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JNN_2018-08-10_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50HMJ_2018-08-20_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JKS_2018-09-02_final.stac-item
2018-11-08 11:55:05	ga_s2am_ard_3-2-1_50JMR_2018-11-08_final.stac-item
2018-12-11 12:04:48	ga_s2am_ard_3-2-1_49JHM_2018-12-11_final.stac-item
2019-01-04 11:45:48	ga_s2am_ard_3-2-1_50JNN_2019-01-04_final.stac-item
2019-01-11 11:36:29	ga_s2am_ard_3-2-1_50HQK_2019-01-11_final.stac-item
2019-01-23 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2019-01-23_final.stac-item
2019-01-30 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2019-01-30_final.stac-item
2019-03-25 11:45:23	ga_s2am_ard_3-2-1_50JNQ_2019-03-25_final.stac-item
2019-04-27 11:56:40	ga_s2am_ard_3-2-1_50HMK_2019-04-27_final.stac-item
2019-04-27 11:57:09	ga_s2am_ard_3-2-1_50HMH_2019-04-27_final.stac-item
2019-04-30 12:05:30	ga_s2am_ard_3-2-1_50JKQ_2019-04-30_final.stac-item
2019-06-22 12:14:25	ga_s2am_ard_3-2-1_49KHP_2019-06-22_final.stac-item
2019-06-23 11:47:18	ga_s2am_ard_3-2-1_50HLH_2019-06-23_final.stac-item
2019-07-26 11:55:18	ga_s2am_ard_3-2-1_50JLR_2019-07-26_final.stac-item
2019-08-22 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2019-08-22_final.stac-item
2019-11-23 11:55:50	ga_s2am_ard_3-2-1_50JNN_2019-11-23_final.stac-item
2020-01-29 11:46:46	ga_s2am_ard_3-2-1_50HQH_2020-01-29_final.stac-item
2020-03-19 11:45:50	ga_s2am_ard_3-2-1_50JNN_2020-03-19_final.stac-item
2020-03-25 12:04:53	ga_s2am_ard_3-2-1_49JHM_2020-03-25_final.stac-item
2020-04-18 11:45:25	ga_s2am_ard_3-2-1_50JNQ_2020-04-18_final.stac-item
2020-07-23 12:04:59	ga_s2am_ard_3-2-1_50JLS_2020-07-23_final.stac-item
2020-08-19 11:55:15	ga_s2am_ard_3-2-1_50JMR_2020-08-19_final.stac-item
2020-11-24 11:45:59	ga_s2am_ard_3-2-1_50JNN_2020-11-24_final.stac-item
2020-12-03 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2020-12-03_final.stac-item
2020-12-17 11:54:42	ga_s2am_ard_3-2-1_50JLT_2020-12-17_final.stac-item
2020-12-27 11:55:49	ga_s2am_ard_3-2-1_50JNN_2020-12-27_final.stac-item
2021-01-06 11:54:52	ga_s2am_ard_3-2-1_50JNS_2021-01-06_final.stac-item
2021-02-08 12:04:35	ga_s2am_ard_3-2-1_50JMT_2021-02-08_final.stac-item
2021-02-22 11:46:40	ga_s2am_ard_3-2-1_50HMK_2021-02-22_final.stac-item
2021-03-30 12:05:09	ga_s2am_ard_3-2-1_50JKR_2021-03-30_final.stac-item
2021-05-16 11:55:13	ga_s2am_ard_3-2-1_50JLR_2021-05-16_final.stac-item
2021-05-26 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2021-05-26_final.stac-item
2021-10-17 11:36:39	ga_s2am_ard_3-2-1_50HQK_2021-10-17_final.stac-item
2021-11-19 11:45:11	ga_s2am_ard_3-2-1_50JNR_2021-11-19_final.stac-item
2021-11-22 11:55:39	ga_s2am_ard_3-2-1_50JMP_2021-11-22_final.stac-item
2021-11-26 11:36:34	ga_s2am_ard_3-2-1_50HQK_2021-11-26_final.stac-item
2022-05-01 11:55:44	ga_s2am_ard_3-2-1_50JMP_2022-05-01_final.stac-item
2022-06-27 11:46:07	ga_s2am_ard_3-2-1_50JNN_2022-06-27_final.stac-item
2022-07-13 12:05:06	ga_s2am_ard_3-2-1_50JLS_2022-07-13_final.stac-item
2022-09-14 12:14:18	ga_s2am_ard_3-2-1_49KHQ_2022-09-14_final.stac-item
2022-12-20 12:05:21	ga_s2am_ard_3-2-1_50JLQ_2022-12-20_final.stac-item
2023-01-29 12:05:10	ga_s2am_ard_3-2-1_50JKR_2023-01-29_final.stac-item
2023-02-05 11:55:52	ga_s2am_ard_3-2-1_50JNN_2023-02-05_final
2023-04-16 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2023-04-16_final
2023-04-16 11:55:49	ga_s2am_ard_3-2-1_50JNN_2023-04-16_final
2023-04-19 12:05:25	ga_s2am_ard_3-2-1_50JKQ_2023-04-19_final
2023-05-23 11:45:14	ga_s2am_ard_3-2-1_50JNR_2023-05-23_final
2023-06-28 12:05:01	ga_s2am_ard_3-2-1_50JKS_2023-06-28_final
2023-07-12 11:47:32	ga_s2am_ard_3-2-1_50HLG_2023-07-12_final
2023-08-27 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-08-27_final
2023-08-27 12:05:32	ga_s2am_ard_3-2-1_50JKQ_2023-08-27_final
2023-09-03 11:54:46	ga_s2am_ard_3-2-1_50JMT_2023-09-03_final
2023-11-22 11:54:40	ga_s2am_ard_3-2-1_50JLT_2023-11-22_final
2023-11-29 11:45:31	ga_s2am_ard_3-2-1_50JNP_2023-11-29_final
2023-12-08 12:14:03	ga_s2am_ard_3-2-1_49KHQ_2023-12-08_final
2023-12-12 11:55:23	ga_s2am_ard_3-2-1_50JLQ_2023-12-12_final
2023-12-18 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2023-12-18_final
2023-12-25 12:05:09	ga_s2am_ard_3-2-1_50JKR_2023-12-25_final
2023-12-29 11:45:51	ga_s2am_ard_3-2-1_50JNN_2023-12-29_final
2024-01-31 11:55:45	ga_s2am_ard_3-2-1_50JNN_2024-01-31_final
2024-02-06 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2024-02-06_final
2024-03-27 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2024-03-27_final
2024-04-10 11:54:52	ga_s2am_ard_3-2-1_50JNS_2024-04-10_final
2024-04-13 12:04:41	ga_s2am_ard_3-2-1_50JLT_2024-04-13_final
2024-04-23 12:04:38	ga_s2am_ard_3-2-1_50JMT_2024-04-23_final
2024-05-20 11:54:45	ga_s2am_ard_3-2-1_50JLT_2024-05-20_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

All years