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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KHR_2015-10-28_final.stac-item
2016-01-06 12:05:24	ga_s2am_ard_3-2-1_49JHN_2016-01-06_final.stac-item
2016-04-15 12:05:35	ga_s2am_ard_3-2-1_50JKP_2016-04-15_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50JLL_2016-06-11_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_50HQK_2016-10-03_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JPT_2016-10-29_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49KHQ_2016-12-01_final.stac-item
2016-12-24 12:14:52	ga_s2am_ard_3-2-1_49JGM_2016-12-24_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_49KHQ_2017-03-31_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_50JLN_2017-05-30_final.stac-item
2017-07-19 12:04:43	ga_s2am_ard_3-2-1_50JLQ_2017-07-19_final.stac-item
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50HMK_2017-11-13_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50JLT_2018-01-12_final.stac-item
2018-02-01 11:49:16	ga_s2am_ard_3-2-1_50JLM_2018-02-01_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49KHQ_2018-02-14_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49JGK_2018-02-24_final.stac-item
2018-05-28 12:13:23	ga_s2am_ard_3-2-1_49JGN_2018-05-28_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JLM_2018-06-11_final.stac-item
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49KGP_2018-06-17_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JNQ_2018-06-28_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_50HPH_2018-08-14_final.stac-item
2018-08-16 12:13:21	ga_s2am_ard_3-2-1_49KGP_2018-08-16_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JLQ_2018-08-23_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JNM_2018-09-09_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JLL_2018-09-19_final.stac-item
2018-11-21 12:04:39	ga_s2am_ard_3-2-1_49JGN_2018-11-21_final.stac-item
2018-12-25 11:46:01	ga_s2am_ard_3-2-1_50JNM_2018-12-25_final.stac-item
2018-12-28 11:55:49	ga_s2am_ard_3-2-1_50JLN_2018-12-28_final.stac-item
2019-01-27 11:55:43	ga_s2am_ard_3-2-1_50JKP_2019-01-27_final.stac-item
2019-02-22 12:14:37	ga_s2am_ard_3-2-1_49JGN_2019-02-22_final.stac-item
2019-03-05 11:46:14	ga_s2am_ard_3-2-1_50JPL_2019-03-05_final.stac-item
2019-03-05 11:46:20	ga_s2am_ard_3-2-1_50JML_2019-03-05_final.stac-item
2019-03-28 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2019-03-28_final.stac-item
2019-05-10 12:05:45	ga_s2am_ard_3-2-1_50JKP_2019-05-10_final.stac-item
2019-05-20 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-05-20_final.stac-item
2019-06-19 12:04:35	ga_s2am_ard_3-2-1_49KGP_2019-06-19_final.stac-item
2019-07-02 12:14:03	ga_s2am_ard_3-2-1_49KGR_2019-07-02_final.stac-item
2019-07-02 12:15:01	ga_s2am_ard_3-2-1_49JGM_2019-07-02_final.stac-item
2019-08-01 12:15:15	ga_s2am_ard_3-2-1_49JGL_2019-08-01_final.stac-item
2019-08-15 11:56:29	ga_s2am_ard_3-2-1_50JLL_2019-08-15_final.stac-item
2019-10-21 11:46:08	ga_s2am_ard_3-2-1_50JPM_2019-10-21_final.stac-item
2019-11-29 12:13:54	ga_s2am_ard_3-2-1_49KHR_2019-11-29_final.stac-item
2019-12-03 11:55:55	ga_s2am_ard_3-2-1_50JLN_2019-12-03_final.stac-item
2020-01-22 11:55:40	ga_s2am_ard_3-2-1_50JKP_2020-01-22_final.stac-item
2020-06-07 11:45:17	ga_s2am_ard_3-2-1_50JNR_2020-06-07_final.stac-item
2020-06-07 11:46:15	ga_s2am_ard_3-2-1_50JNM_2020-06-07_final.stac-item
2020-06-24 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2020-06-24_final.stac-item
2020-09-01 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-09-01_final.stac-item
2021-01-26 11:55:57	ga_s2am_ard_3-2-1_50JLN_2021-01-26_final.stac-item
2021-02-02 11:45:07	ga_s2am_ard_3-2-1_50JPR_2021-02-02_final.stac-item
2021-03-20 12:05:50	ga_s2am_ard_3-2-1_50JLN_2021-03-20_final.stac-item
2021-03-30 12:04:11	ga_s2am_ard_3-2-1_49KHQ_2021-03-30_final.stac-item
2021-05-06 11:55:14	ga_s2am_ard_3-2-1_50JPQ_2021-05-06_final.stac-item
2021-08-14 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2021-08-14_final.stac-item
2021-08-28 11:37:23	ga_s2am_ard_3-2-1_50HPG_2021-08-28_final
2021-09-19 12:14:44	ga_s2am_ard_3-2-1_49JGN_2021-09-19_final.stac-item
2021-10-29 12:15:15	ga_s2am_ard_3-2-1_49JGL_2021-10-29_final.stac-item
2021-11-18 12:13:55	ga_s2am_ard_3-2-1_49KHR_2021-11-18_final.stac-item
2021-11-28 12:15:10	ga_s2am_ard_3-2-1_49JGL_2021-11-28_final.stac-item
2022-01-11 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-01-11_final.stac-item
2022-01-21 11:56:40	ga_s2am_ard_3-2-1_50HLK_2022-01-21_final.stac-item
2022-02-13 12:05:51	ga_s2am_ard_3-2-1_50JLN_2022-02-13_final.stac-item
2022-02-20 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2022-02-20_final.stac-item
2022-04-14 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2022-04-14_final.stac-item
2022-04-28 11:46:31	ga_s2am_ard_3-2-1_50JML_2022-04-28_final.stac-item
2022-05-01 11:56:16	ga_s2am_ard_3-2-1_50JLM_2022-05-01_final.stac-item
2022-06-03 12:05:45	ga_s2am_ard_3-2-1_50JLP_2022-06-03_final.stac-item
2022-06-04 11:36:42	ga_s2am_ard_3-2-1_50HQK_2022-06-04_final.stac-item
2022-06-27 11:46:46	ga_s2am_ard_3-2-1_50HPK_2022-06-27_final.stac-item
2022-08-23 11:36:46	ga_s2am_ard_3-2-1_50HQK_2022-08-23_final
2022-09-18 11:56:20	ga_s2am_ard_3-2-1_50JLM_2022-09-18_final.stac-item
2022-10-25 11:45:24	ga_s2am_ard_3-2-1_50JPQ_2022-10-25_final.stac-item
2022-11-11 11:36:23	ga_s2am_ard_3-2-1_50JQL_2022-11-11_final.stac-item
2022-11-20 12:04:00	ga_s2am_ard_3-2-1_49KHR_2022-11-20_final.stac-item
2022-12-24 11:46:35	ga_s2am_ard_3-2-1_50HNK_2022-12-24_final.stac-item
2023-01-13 11:47:04	ga_s2am_ard_3-2-1_50HNH_2023-01-13_final.stac-item
2023-01-29 12:05:35	ga_s2am_ard_3-2-1_50JLP_2023-01-29_final.stac-item
2023-02-12 11:46:36	ga_s2am_ard_3-2-1_50HNK_2023-02-12_final
2023-02-18 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2023-02-18_nrt.stac-item
2023-03-17 11:56:38	ga_s2am_ard_3-2-1_50HLK_2023-03-17_final
2023-04-29 12:04:57	ga_s2am_ard_3-2-1_49JHM_2023-04-29_final
2023-05-03 11:46:34	ga_s2am_ard_3-2-1_50HPK_2023-05-03_final
2023-07-01 12:15:00	ga_s2am_ard_3-2-1_49JGM_2023-07-01_final
2023-07-15 11:56:30	ga_s2am_ard_3-2-1_50JLL_2023-07-15_final
2023-08-27 12:04:24	ga_s2am_ard_3-2-1_49KGQ_2023-08-27_final
2023-08-30 12:14:32	ga_s2am_ard_3-2-1_49KGP_2023-08-30_final
2023-08-31 11:47:12	ga_s2am_ard_3-2-1_50HNH_2023-08-31_final
2023-10-03 11:55:52	ga_s2am_ard_3-2-1_50JLN_2023-10-03_final
2023-10-23 11:55:46	ga_s2am_ard_3-2-1_50JKP_2023-10-23_final
2023-11-02 11:55:55	ga_s2am_ard_3-2-1_50JLN_2023-11-02_final
2023-11-12 11:56:39	ga_s2am_ard_3-2-1_50HLK_2023-11-12_final
2023-12-02 11:55:51	ga_s2am_ard_3-2-1_50JKN_2023-12-02_final
2023-12-12 11:56:21	ga_s2am_ard_3-2-1_50JLL_2023-12-12_final
2023-12-25 12:04:15	ga_s2am_ard_3-2-1_49KGQ_2023-12-25_final
2024-01-07 12:13:54	ga_s2am_ard_3-2-1_49KGR_2024-01-07_final
2024-01-14 12:05:08	ga_s2am_ard_3-2-1_49JGL_2024-01-14_final
2024-03-01 11:55:53	ga_s2am_ard_3-2-1_50JMN_2024-03-01_final
2024-04-14 11:36:36	ga_s2am_ard_3-2-1_50HQK_2024-04-14_final
2024-04-17 11:47:20	ga_s2am_ard_3-2-1_50HPG_2024-04-17_final
2024-05-24 11:37:06	ga_s2am_ard_3-2-1_50HPH_2024-05-24_nrt

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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