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
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JMS_2015-12-17_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HQH_2015-12-21_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50JMT_2016-03-16_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50JMT_2016-04-15_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50JRT_2016-04-29_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HNH_2016-06-18_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50HMG_2016-07-01_final
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50JPT_2016-07-08_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50JQS_2016-07-08_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50JRS_2016-07-08_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50JLN_2016-07-14_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50HLH_2016-07-21_final.stac-item
2016-08-17 11:40:15	ga_s2am_ard_3-2-1_50JPT_2016-08-17_final.stac-item
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49KGQ_2016-12-04_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49KHR_2016-12-31_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50KKA_2017-01-30_final.stac-item
2017-01-31 11:26:14	ga_s2am_ard_3-2-1_50JRT_2017-01-31_final.stac-item
2017-03-12 11:33:53	ga_s2am_ard_3-2-1_50JRS_2017-03-12_final.stac-item
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50HLH_2017-05-24_final.stac-item
2017-07-10 11:34:59	ga_s2am_ard_3-2-1_50JPL_2017-07-10_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50JKM_2017-08-25_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49KHR_2017-11-09_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49KGP_2017-12-16_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49KHQ_2017-12-16_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KHQ_2017-12-19_final.stac-item
2017-12-26 12:04:47	ga_s2am_ard_3-2-1_49JGM_2017-12-26_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_49JGN_2018-01-05_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_49JHN_2018-01-05_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_50JRS_2018-01-06_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_49KGQ_2018-01-28_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-03-06_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49KHQ_2018-03-06_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HLJ_2018-05-22_final.stac-item
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50JPS_2018-07-08_final.stac-item
2018-08-07 11:40:42	ga_s2am_ard_3-2-1_50JPT_2018-08-07_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JKP_2018-08-10_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JNS_2018-08-10_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JPP_2018-08-10_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JHN_2018-08-23_final.stac-item
2018-09-13 11:33:05	ga_s2am_ard_3-2-1_50HQH_2018-09-13_final.stac-item
2018-11-18 11:54:17	ga_s2am_ard_3-2-1_50JQT_2018-11-18_final.stac-item
2018-12-11 12:04:10	ga_s2am_ard_3-2-1_49KGQ_2018-12-11_final.stac-item
2018-12-11 12:05:32	ga_s2am_ard_3-2-1_50JKP_2018-12-11_final.stac-item
2018-12-21 12:05:06	ga_s2am_ard_3-2-1_49JGL_2018-12-21_final.stac-item
2019-01-03 12:13:49	ga_s2am_ard_3-2-1_49KHR_2019-01-03_final.stac-item
2019-01-04 11:44:29	ga_s2am_ard_3-2-1_50JQT_2019-01-04_final.stac-item
2019-02-09 12:05:52	ga_s2am_ard_3-2-1_50JKN_2019-02-09_final.stac-item
2019-05-24 11:46:44	ga_s2am_ard_3-2-1_50HMK_2019-05-24_final.stac-item
2019-06-23 11:47:14	ga_s2am_ard_3-2-1_50HMH_2019-06-23_final.stac-item
2019-07-03 11:47:00	ga_s2am_ard_3-2-1_50HMJ_2019-07-03_final.stac-item
2019-07-13 11:47:19	ga_s2am_ard_3-2-1_50HLH_2019-07-13_final.stac-item
2019-07-16 11:57:11	ga_s2am_ard_3-2-1_50HMH_2019-07-16_final.stac-item
2019-10-30 12:15:00	ga_s2am_ard_3-2-1_49JFM_2019-10-30_final.stac-item
2019-12-10 11:44:27	ga_s2am_ard_3-2-1_50JRT_2019-12-10_final.stac-item
2019-12-20 11:44:39	ga_s2am_ard_3-2-1_50JPT_2019-12-20_final.stac-item
2020-03-05 12:04:14	ga_s2am_ard_3-2-1_49KGQ_2020-03-05_final.stac-item
2020-03-09 11:44:34	ga_s2am_ard_3-2-1_50JPT_2020-03-09_final.stac-item
2020-03-09 11:44:48	ga_s2am_ard_3-2-1_50JPS_2020-03-09_final.stac-item
2020-03-09 11:45:03	ga_s2am_ard_3-2-1_50JPR_2020-03-09_final.stac-item
2020-03-16 11:35:33	ga_s2am_ard_3-2-1_50JQP_2020-03-16_final.stac-item
2020-04-28 11:46:03	ga_s2am_ard_3-2-1_50JNM_2020-04-28_final.stac-item
2020-06-30 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-06-30_final.stac-item
2020-08-12 12:04:37	ga_s2am_ard_3-2-1_49KGP_2020-08-12_final.stac-item
2020-08-16 11:45:23	ga_s2am_ard_3-2-1_50JQQ_2020-08-16_final.stac-item
2020-09-08 11:56:55	ga_s2am_ard_3-2-1_50HMJ_2020-09-08_final.stac-item
2020-11-13 12:15:03	ga_s2am_ard_3-2-1_49JFM_2020-11-13_final.stac-item
2020-12-10 12:05:34	ga_s2am_ard_3-2-1_50JLP_2020-12-10_final.stac-item
2021-01-13 11:47:22	ga_s2am_ard_3-2-1_50HNG_2021-01-13_final
2021-01-22 12:13:59	ga_s2am_ard_3-2-1_49KGR_2021-01-22_final.stac-item
2021-03-14 11:47:27	ga_s2am_ard_3-2-1_50HLG_2021-03-14_final
2021-04-23 11:47:23	ga_s2am_ard_3-2-1_50HLG_2021-04-23_final
2021-05-23 11:47:10	ga_s2am_ard_3-2-1_50HMH_2021-05-23_final.stac-item
2021-06-05 11:57:21	ga_s2am_ard_3-2-1_50HMG_2021-06-05_final
2021-06-22 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2021-06-22_final.stac-item
2021-06-25 11:56:01	ga_s2am_ard_3-2-1_50JKN_2021-06-25_final.stac-item
2021-08-11 11:45:24	ga_s2am_ard_3-2-1_50JPQ_2021-08-11_final.stac-item
2021-08-18 11:34:51	ga_s2am_ard_3-2-1_50JRS_2021-08-18_final.stac-item
2021-08-21 11:45:09	ga_s2am_ard_3-2-1_50JPR_2021-08-21_final.stac-item
2021-08-21 11:45:27	ga_s2am_ard_3-2-1_50JNQ_2021-08-21_final.stac-item
2021-11-22 11:55:53	ga_s2am_ard_3-2-1_50JMN_2021-11-22_final.stac-item
2021-12-26 11:37:22	ga_s2am_ard_3-2-1_50HPG_2021-12-26_final
2022-02-17 11:44:32	ga_s2am_ard_3-2-1_50JRT_2022-02-17_final.stac-item
2022-03-08 12:13:58	ga_s2am_ard_3-2-1_50KKA_2022-03-08_final.stac-item
2023-02-19 11:37:00	ga_s2am_ard_3-2-1_50HQH_2023-02-19_nrt.stac-item
2023-02-22 11:44:28	ga_s2am_ard_3-2-1_50JRT_2023-02-22_nrt.stac-item
2023-02-22 11:44:28	ga_s2am_ard_3-2-1_50JRT_2023-02-22_final
2023-03-01 11:37:24	ga_s2am_ard_3-2-1_50HNG_2023-03-01_final
2023-03-11 11:36:44	ga_s2am_ard_3-2-1_50HQJ_2023-03-11_final
2023-04-13 11:44:53	ga_s2am_ard_3-2-1_50JPS_2023-04-13_final
2023-05-29 12:05:30	ga_s2am_ard_3-2-1_50JKQ_2023-05-29_final
2023-06-22 11:44:56	ga_s2am_ard_3-2-1_50JPS_2023-06-22_final
2023-07-08 12:04:48	ga_s2am_ard_3-2-1_49JHN_2023-07-08_final
2023-10-07 11:37:27	ga_s2am_ard_3-2-1_50HNG_2023-10-07_final
2023-10-30 11:46:29	ga_s2am_ard_3-2-1_50HQK_2023-10-30_final
2023-11-29 11:46:54	ga_s2am_ard_3-2-1_50HPH_2023-11-29_final
2023-12-05 12:04:54	ga_s2am_ard_3-2-1_49JGM_2023-12-05_final
2024-01-15 11:36:56	ga_s2am_ard_3-2-1_50HQH_2024-01-15_final
2024-02-14 11:37:00	ga_s2am_ard_3-2-1_50HQH_2024-02-14_final
2024-03-25 11:37:22	ga_s2am_ard_3-2-1_50HPG_2024-03-25_final
2024-03-28 11:44:31	ga_s2am_ard_3-2-1_50JRT_2024-03-28_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

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