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
2016-09-25 12:13:39	ga_s2am_ard_3-2-1_49KHQ_2016-09-25_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49JGL_2016-10-25_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50JNM_2016-10-26_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JNL_2016-10-29_final.stac-item
2017-03-01 12:04:35	ga_s2am_ard_3-2-1_49JGN_2017-03-01_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JNL_2017-06-26_final.stac-item
2017-07-30 11:34:57	ga_s2am_ard_3-2-1_50JQM_2017-07-30_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_50JRT_2017-09-28_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_50JKT_2017-10-07_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_50JLN_2017-10-17_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_50KMC_2017-10-17_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_50KKB_2017-11-19_final.stac-item
2017-12-26 12:03:42	ga_s2am_ard_3-2-1_50KKA_2017-12-26_final.stac-item
2018-01-22 11:56:02	ga_s2am_ard_3-2-1_50HNK_2018-01-22_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_50HQJ_2018-03-17_final.stac-item
2018-03-19 12:13:18	ga_s2am_ard_3-2-1_49KHR_2018-03-19_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JLN_2018-05-02_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JKP_2018-05-22_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JLQ_2018-06-11_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JKP_2018-06-21_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JLM_2018-06-21_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JKP_2018-07-11_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KKB_2018-07-14_final.stac-item
2018-07-28 11:45:46	ga_s2am_ard_3-2-1_50JNM_2018-07-28_final.stac-item
2018-08-17 11:45:55	ga_s2am_ard_3-2-1_50JML_2018-08-17_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50JPL_2018-08-27_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_50HPJ_2018-09-03_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50HLJ_2018-09-09_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_50KKU_2018-10-05_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50KKB_2018-10-22_final.stac-item
2018-10-26 11:46:33	ga_s2am_ard_3-2-1_50HNK_2018-10-26_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-11-01_final.stac-item
2019-01-24 11:46:16	ga_s2am_ard_3-2-1_50JPL_2019-01-24_final.stac-item
2019-01-30 12:03:20	ga_s2am_ard_3-2-1_50KMC_2019-01-30_final.stac-item
2019-04-14 11:46:46	ga_s2am_ard_3-2-1_50HQJ_2019-04-14_final.stac-item
2019-05-31 11:36:54	ga_s2am_ard_3-2-1_50HPJ_2019-05-31_final.stac-item
2019-06-16 11:56:00	ga_s2am_ard_3-2-1_50JLN_2019-06-16_final.stac-item
2019-07-20 11:36:39	ga_s2am_ard_3-2-1_50HQK_2019-07-20_final.stac-item
2019-08-05 11:56:04	ga_s2am_ard_3-2-1_50JKN_2019-08-05_final.stac-item
2019-08-05 11:56:44	ga_s2am_ard_3-2-1_50HLK_2019-08-05_final.stac-item
2019-09-04 11:56:14	ga_s2am_ard_3-2-1_50JKM_2019-09-04_final.stac-item
2019-09-11 11:46:11	ga_s2am_ard_3-2-1_50JMM_2019-09-11_final.stac-item
2019-09-27 12:03:24	ga_s2am_ard_3-2-1_50KMC_2019-09-27_final.stac-item
2019-10-07 12:03:26	ga_s2am_ard_3-2-1_50KMC_2019-10-07_final.stac-item
2020-03-12 11:53:51	ga_s2am_ard_3-2-1_50KNA_2020-03-12_final.stac-item
2020-04-24 12:03:46	ga_s2am_ard_3-2-1_50KKB_2020-04-24_final.stac-item
2020-04-24 12:05:42	ga_s2am_ard_3-2-1_50JKP_2020-04-24_final.stac-item
2020-07-07 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2020-07-07_final.stac-item
2020-09-25 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2020-09-25_final.stac-item
2020-11-21 11:37:09	ga_s2am_ard_3-2-1_50HPH_2020-11-21_final.stac-item
2020-12-21 11:37:01	ga_s2am_ard_3-2-1_50HQH_2020-12-21_final.stac-item
2021-01-10 11:36:20	ga_s2am_ard_3-2-1_50JQL_2021-01-10_final.stac-item
2021-01-16 11:56:19	ga_s2am_ard_3-2-1_50JNL_2021-01-16_final.stac-item
2021-01-19 12:05:01	ga_s2am_ard_3-2-1_49JGM_2021-01-19_final.stac-item
2021-02-08 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-02-08_final.stac-item
2021-02-18 12:03:43	ga_s2am_ard_3-2-1_50KKB_2021-02-18_final.stac-item
2021-03-10 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-03-10_final.stac-item
2021-03-20 12:03:43	ga_s2am_ard_3-2-1_49KHS_2021-03-20_final
2021-03-27 11:55:57	ga_s2am_ard_3-2-1_50JKN_2021-03-27_final.stac-item
2021-04-06 11:57:05	ga_s2am_ard_3-2-1_50HLH_2021-04-06_final.stac-item
2021-04-23 11:46:48	ga_s2am_ard_3-2-1_50HNJ_2021-04-23_final.stac-item
2021-04-23 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2021-04-23_final.stac-item
2021-05-23 11:45:12	ga_s2am_ard_3-2-1_50JNR_2021-05-23_final.stac-item
2021-06-02 11:45:47	ga_s2am_ard_3-2-1_50JQN_2021-06-02_final.stac-item
2021-06-18 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-06-18_final.stac-item
2021-06-21 12:14:28	ga_s2am_ard_3-2-1_49KGP_2021-06-21_final.stac-item
2021-06-22 11:46:09	ga_s2am_ard_3-2-1_50JNM_2021-06-22_final.stac-item
2021-07-09 11:36:22	ga_s2am_ard_3-2-1_50JQL_2021-07-09_final.stac-item
2021-07-18 12:03:47	ga_s2am_ard_3-2-1_50KKB_2021-07-18_final.stac-item
2021-07-25 11:56:33	ga_s2am_ard_3-2-1_50HNK_2021-07-25_final.stac-item
2021-08-17 12:04:34	ga_s2am_ard_3-2-1_49KGP_2021-08-17_final.stac-item
2021-08-27 12:05:02	ga_s2am_ard_3-2-1_49JGM_2021-08-27_final.stac-item
2021-09-10 11:47:02	ga_s2am_ard_3-2-1_50HPH_2021-09-10_final.stac-item
2021-09-26 12:03:48	ga_s2am_ard_3-2-1_50KKB_2021-09-26_final.stac-item
2021-11-18 12:14:56	ga_s2am_ard_3-2-1_49JGM_2021-11-18_final.stac-item
2021-12-18 12:13:54	ga_s2am_ard_3-2-1_50KKA_2021-12-18_final.stac-item
2022-02-03 12:03:23	ga_s2am_ard_3-2-1_50KMC_2022-02-03_final.stac-item
2022-02-07 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2022-02-07_final.stac-item
2022-04-04 12:03:25	ga_s2am_ard_3-2-1_50KMC_2022-04-04_final.stac-item
2022-06-03 12:04:50	ga_s2am_ard_3-2-1_49JHN_2022-06-03_final.stac-item
2022-06-24 11:36:17	ga_s2am_ard_3-2-1_50JQM_2022-06-24_final.stac-item
2022-06-30 11:56:42	ga_s2am_ard_3-2-1_50HNK_2022-06-30_final.stac-item
2022-07-20 11:56:16	ga_s2am_ard_3-2-1_50JNM_2022-07-20_final.stac-item
2022-09-04 12:14:10	ga_s2am_ard_3-2-1_49KGR_2022-09-04_final.stac-item
2022-09-05 11:45:17	ga_s2am_ard_3-2-1_50JQR_2022-09-05_final.stac-item
2022-11-04 11:47:10	ga_s2am_ard_3-2-1_50HNH_2022-11-04_final.stac-item
2022-12-30 12:05:54	ga_s2am_ard_3-2-1_50JKN_2022-12-30_final.stac-item
2023-01-19 12:05:10	ga_s2am_ard_3-2-1_49JGL_2023-01-19_final.stac-item
2023-03-30 12:04:11	ga_s2am_ard_3-2-1_50KKV_2023-03-30_final
2023-04-13 11:47:17	ga_s2am_ard_3-2-1_50HPG_2023-04-13_final
2023-04-22 12:13:53	ga_s2am_ard_3-2-1_50KKA_2023-04-22_final
2023-05-09 12:03:44	ga_s2am_ard_3-2-1_49KHS_2023-05-09_final
2023-05-13 11:47:24	ga_s2am_ard_3-2-1_50HMG_2023-05-13_final
2023-06-28 12:03:48	ga_s2am_ard_3-2-1_49KHS_2023-06-28_final
2023-08-17 12:06:01	ga_s2am_ard_3-2-1_50JKN_2023-08-17_final
2023-09-09 12:13:59	ga_s2am_ard_3-2-1_50KKA_2023-09-09_final
2024-01-14 12:05:49	ga_s2am_ard_3-2-1_50JKN_2024-01-14_final
2024-01-27 12:13:49	ga_s2am_ard_3-2-1_50KKA_2024-01-27_final
2024-01-28 11:47:05	ga_s2am_ard_3-2-1_50HMH_2024-01-28_final
2024-04-17 11:44:41	ga_s2am_ard_3-2-1_50JPT_2024-04-17_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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