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
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JML_2015-12-04_final.stac-item
2016-01-19 12:13:57	ga_s2am_ard_3-2-1_50KKA_2016-01-19_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HLH_2016-03-20_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JLS_2016-04-02_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50KNC_2016-04-02_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HNG_2016-05-09_final
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50KRD_2016-05-09_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50JKP_2016-05-15_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50KMB_2016-05-22_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50KQC_2016-05-29_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50HMG_2016-07-01_final
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50KQC_2016-08-30_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50JLM_2016-11-01_final.stac-item
2016-11-04 12:13:19	ga_s2am_ard_3-2-1_49JGM_2016-11-04_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HTD_2016-11-12_final.stac-item
2017-04-23 12:13:36	ga_s2am_ard_3-2-1_49KGR_2017-04-23_final.stac-item
2017-04-27 11:49:47	ga_s2am_ard_3-2-1_50JMT_2017-04-27_final.stac-item
2017-09-21 11:40:44	ga_s2am_ard_3-2-1_50JQL_2017-09-21_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_50JLP_2017-09-27_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50JNM_2017-12-03_final.stac-item
2017-12-26 12:03:42	ga_s2am_ard_3-2-1_49KHR_2017-12-26_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50KQC_2017-12-30_final.stac-item
2018-01-15 12:04:34	ga_s2am_ard_3-2-1_49JGM_2018-01-15_final.stac-item
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_50HPJ_2018-04-09_final.stac-item
2018-04-16 11:33:46	ga_s2am_ard_3-2-1_50HPK_2018-04-16_final.stac-item
2018-04-16 11:33:46	ga_s2am_ard_3-2-1_50JQM_2018-04-16_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50JNL_2018-06-08_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50HNK_2018-06-11_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKN_2018-08-13_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50HMK_2018-08-30_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JQP_2018-09-26_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50KNC_2018-10-09_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50KQC_2018-10-09_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49JFM_2018-10-15_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_50KKA_2018-10-15_final.stac-item
2018-12-08 11:55:48	ga_s2am_ard_3-2-1_50JLN_2018-12-08_final.stac-item
2018-12-18 11:53:22	ga_s2am_ard_3-2-1_50KMC_2018-12-18_final.stac-item
2018-12-28 11:53:18	ga_s2am_ard_3-2-1_50KNC_2018-12-28_final.stac-item
2019-01-04 11:44:25	ga_s2am_ard_3-2-1_50JRT_2019-01-04_final.stac-item
2019-01-30 12:05:38	ga_s2am_ard_3-2-1_50JKP_2019-01-30_final.stac-item
2019-02-02 12:14:24	ga_s2am_ard_3-2-1_49KGP_2019-02-02_final.stac-item
2019-03-15 11:43:00	ga_s2am_ard_3-2-1_50KRD_2019-03-15_final.stac-item
2019-05-23 12:14:59	ga_s2am_ard_3-2-1_49JGM_2019-05-23_final.stac-item
2019-06-09 12:05:43	ga_s2am_ard_3-2-1_50JKP_2019-06-09_final.stac-item
2019-06-27 11:27:06	ga_s2am_ard_3-2-1_51HUC_2019-06-27_final.stac-item
2019-07-09 12:04:09	ga_s2am_ard_3-2-1_50KLA_2019-07-09_final.stac-item
2019-08-02 11:46:24	ga_s2am_ard_3-2-1_50JPL_2019-08-02_final.stac-item
2019-09-04 11:55:56	ga_s2am_ard_3-2-1_50JLN_2019-09-04_final.stac-item
2019-09-04 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2019-09-04_final.stac-item
2019-10-24 11:53:14	ga_s2am_ard_3-2-1_50KRC_2019-10-24_final.stac-item
2019-12-20 11:44:28	ga_s2am_ard_3-2-1_50JQT_2019-12-20_final.stac-item
2020-01-15 12:05:23	ga_s2am_ard_3-2-1_49JGK_2020-01-15_final.stac-item
2020-05-24 12:04:09	ga_s2am_ard_3-2-1_50KMV_2020-05-24_final.stac-item
2020-05-27 12:14:00	ga_s2am_ard_3-2-1_50KKA_2020-05-27_final.stac-item
2020-06-10 11:53:23	ga_s2am_ard_3-2-1_50KQC_2020-06-10_final.stac-item
2020-08-12 12:05:47	ga_s2am_ard_3-2-1_50JKP_2020-08-12_final.stac-item
2020-08-20 11:27:07	ga_s2am_ard_3-2-1_51HUC_2020-08-20_final.stac-item
2020-10-28 11:53:30	ga_s2am_ard_3-2-1_50KNC_2020-10-28_final.stac-item
2020-10-28 11:57:11	ga_s2am_ard_3-2-1_50HMH_2020-10-28_final.stac-item
2020-11-21 11:37:05	ga_s2am_ard_3-2-1_50HQH_2020-11-21_final.stac-item
2021-01-03 11:43:27	ga_s2am_ard_3-2-1_50KQB_2021-01-03_final.stac-item
2021-01-03 11:44:16	ga_s2am_ard_3-2-1_50KRU_2021-01-03_final.stac-item
2021-01-09 12:05:30	ga_s2am_ard_3-2-1_49JGK_2021-01-09_final.stac-item
2021-01-13 11:47:18	ga_s2am_ard_3-2-1_50HPG_2021-01-13_final
2021-01-20 11:36:20	ga_s2am_ard_3-2-1_50JQL_2021-01-20_final.stac-item
2021-02-09 11:36:56	ga_s2am_ard_3-2-1_51HUC_2021-02-09_final.stac-item
2021-02-11 12:13:53	ga_s2am_ard_3-2-1_50KKA_2021-02-11_final.stac-item
2021-04-13 11:45:16	ga_s2am_ard_3-2-1_50JPQ_2021-04-13_final.stac-item
2021-04-26 11:57:08	ga_s2am_ard_3-2-1_50HMH_2021-04-26_final.stac-item
2021-04-29 12:03:20	ga_s2am_ard_3-2-1_50KMC_2021-04-29_final.stac-item
2021-05-16 11:56:36	ga_s2am_ard_3-2-1_50HMK_2021-05-16_final.stac-item
2021-06-05 11:57:21	ga_s2am_ard_3-2-1_50HMG_2021-06-05_final
2021-06-22 11:45:33	ga_s2am_ard_3-2-1_50JQP_2021-06-22_final.stac-item
2021-06-26 11:27:09	ga_s2am_ard_3-2-1_51HTC_2021-06-26_final.stac-item
2021-07-05 11:56:09	ga_s2am_ard_3-2-1_50JLM_2021-07-05_final.stac-item
2021-08-21 11:43:06	ga_s2am_ard_3-2-1_50KRD_2021-08-21_final.stac-item
2021-08-28 11:37:02	ga_s2am_ard_3-2-1_51HTC_2021-08-28_final.stac-item
2021-10-30 11:43:26	ga_s2am_ard_3-2-1_50KQC_2021-10-30_final.stac-item
2021-11-02 11:52:38	ga_s2am_ard_3-2-1_50KQF_2021-11-02_final
2021-12-09 11:47:23	ga_s2am_ard_3-2-1_50HMG_2021-12-09_final
2021-12-28 12:14:58	ga_s2am_ard_3-2-1_49JGM_2021-12-28_final.stac-item
2022-01-08 11:43:05	ga_s2am_ard_3-2-1_50KRD_2022-01-08_final.stac-item
2022-05-11 11:56:44	ga_s2am_ard_3-2-1_50HLK_2022-05-11_final.stac-item
2022-05-21 11:53:24	ga_s2am_ard_3-2-1_50KQC_2022-05-21_final.stac-item
2022-06-07 11:43:12	ga_s2am_ard_3-2-1_50KRD_2022-06-07_final.stac-item
2022-09-08 11:53:28	ga_s2am_ard_3-2-1_50KQC_2022-09-08_final.stac-item
2023-02-01 12:13:52	ga_s2am_ard_3-2-1_50KKA_2023-02-01_final.stac-item
2023-02-15 11:53:28	ga_s2am_ard_3-2-1_50KMC_2023-02-15_nrt.stac-item
2023-04-03 11:47:16	ga_s2am_ard_3-2-1_50HPG_2023-04-03_final
2023-05-23 11:43:07	ga_s2am_ard_3-2-1_50KRD_2023-05-23_final
2023-06-28 12:03:48	ga_s2am_ard_3-2-1_50KKB_2023-06-28_final
2023-10-17 11:37:16	ga_s2am_ard_3-2-1_50HQG_2023-10-17_final
2023-10-30 11:46:29	ga_s2am_ard_3-2-1_50HQK_2023-10-30_final
2024-01-14 12:03:38	ga_s2am_ard_3-2-1_50KKB_2024-01-14_final
2024-01-24 12:03:13	ga_s2am_ard_3-2-1_50KNC_2024-01-24_final
2024-02-04 11:37:22	ga_s2am_ard_3-2-1_50HNG_2024-02-04_final
2024-04-03 12:05:53	ga_s2am_ard_3-2-1_50JKN_2024-04-03_final
2024-05-07 11:47:19	ga_s2am_ard_3-2-1_50HPG_2024-05-07_final
2024-05-10 11:53:24	ga_s2am_ard_3-2-1_50KPC_2024-05-10_final
2024-05-23 12:05:40	ga_s2am_ard_3-2-1_50JKP_2024-05-23_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

Other products

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