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
2015-11-27 12:04:51	ga_s2am_ard_3-2-1_49JGM_2015-11-27_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51HTC_2016-04-23_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HPK_2016-05-09_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50HNK_2016-05-29_final.stac-item
2016-08-17 11:40:15	ga_s2am_ard_3-2-1_50HPJ_2016-08-17_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50KKB_2016-08-23_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50KQC_2016-08-30_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50KMC_2016-10-02_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HPK_2016-10-26_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JML_2016-10-29_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKP_2016-11-11_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HQJ_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HTD_2016-11-12_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50HPH_2017-03-25_final.stac-item
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50JLM_2017-05-27_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_50JLP_2017-09-27_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_49JGM_2017-10-17_final.stac-item
2017-12-06 12:03:42	ga_s2am_ard_3-2-1_50KKA_2017-12-06_final.stac-item
2017-12-26 12:03:42	ga_s2am_ard_3-2-1_49KHR_2017-12-26_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50KNC_2018-01-12_final.stac-item
2018-04-16 11:33:46	ga_s2am_ard_3-2-1_50HPK_2018-04-16_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JLQ_2018-05-25_final.stac-item
2018-06-11 11:48:18	ga_s2am_ard_3-2-1_50KNA_2018-06-11_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50KMC_2018-07-24_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_50KKA_2018-08-06_final.stac-item
2018-08-07 11:46:07	ga_s2am_ard_3-2-1_50HPJ_2018-08-07_final.stac-item
2018-08-26 12:13:20	ga_s2am_ard_3-2-1_49JGN_2018-08-26_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50HMK_2018-08-30_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50JMP_2018-08-30_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JML_2018-09-19_final.stac-item
2018-10-06 11:46:03	ga_s2am_ard_3-2-1_50JPL_2018-10-06_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50KNC_2018-10-09_final.stac-item
2018-11-11 12:04:37	ga_s2am_ard_3-2-1_50JKT_2018-11-11_final.stac-item
2018-11-15 11:47:09	ga_s2am_ard_3-2-1_50HLH_2018-11-15_final.stac-item
2018-12-11 12:03:15	ga_s2am_ard_3-2-1_50KMC_2018-12-11_final.stac-item
2018-12-11 12:05:47	ga_s2am_ard_3-2-1_50JKN_2018-12-11_final.stac-item
2019-03-04 12:13:49	ga_s2am_ard_3-2-1_50KKA_2019-03-04_final.stac-item
2019-03-28 11:53:10	ga_s2am_ard_3-2-1_50KRC_2019-03-28_final.stac-item
2019-07-06 11:57:11	ga_s2am_ard_3-2-1_50HMH_2019-07-06_final.stac-item
2019-07-19 12:06:00	ga_s2am_ard_3-2-1_50JKN_2019-07-19_final.stac-item
2019-07-20 11:36:37	ga_s2am_ard_3-2-1_51HTE_2019-07-20_final.stac-item
2019-08-02 11:46:24	ga_s2am_ard_3-2-1_50JPL_2019-08-02_final.stac-item
2019-08-29 11:36:47	ga_s2am_ard_3-2-1_51HTD_2019-08-29_final.stac-item
2019-09-01 11:46:38	ga_s2am_ard_3-2-1_50HNK_2019-09-01_final.stac-item
2019-10-20 12:13:55	ga_s2am_ard_3-2-1_49KHR_2019-10-20_final.stac-item
2020-01-02 11:52:14	ga_s2am_ard_3-2-1_50KQG_2020-01-02_final
2020-01-16 11:36:46	ga_s2am_ard_3-2-1_50HPJ_2020-01-16_final.stac-item
2020-03-22 11:54:33	ga_s2am_ard_3-2-1_50JNT_2020-03-22_final.stac-item
2020-03-25 12:03:19	ga_s2am_ard_3-2-1_50KMC_2020-03-25_final.stac-item
2020-04-04 12:04:03	ga_s2am_ard_3-2-1_50KKV_2020-04-04_final.stac-item
2020-04-18 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2020-04-18_final.stac-item
2020-04-24 12:03:21	ga_s2am_ard_3-2-1_50KNC_2020-04-24_final.stac-item
2020-05-14 12:03:46	ga_s2am_ard_3-2-1_50KLB_2020-05-14_final.stac-item
2020-05-28 11:46:40	ga_s2am_ard_3-2-1_50HPK_2020-05-28_final.stac-item
2020-09-21 12:03:49	ga_s2am_ard_3-2-1_50KKB_2020-09-21_final.stac-item
2021-01-19 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-01-19_final.stac-item
2021-03-10 12:04:42	ga_s2am_ard_3-2-1_49JHN_2021-03-10_final.stac-item
2021-04-13 11:46:24	ga_s2am_ard_3-2-1_50HQK_2021-04-13_final.stac-item
2021-05-23 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-05-23_final.stac-item
2021-05-30 11:37:02	ga_s2am_ard_3-2-1_51HTC_2021-05-30_final.stac-item
2021-06-18 12:05:41	ga_s2am_ard_3-2-1_50JKP_2021-06-18_final.stac-item
2021-06-21 12:14:57	ga_s2am_ard_3-2-1_49JGM_2021-06-21_final.stac-item
2021-06-22 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-06-22_final.stac-item
2021-06-25 11:53:18	ga_s2am_ard_3-2-1_50KQC_2021-06-25_final.stac-item
2021-07-05 11:55:49	ga_s2am_ard_3-2-1_50JKP_2021-07-05_final.stac-item
2021-07-05 11:56:57	ga_s2am_ard_3-2-1_50HLJ_2021-07-05_final.stac-item
2021-07-15 11:56:11	ga_s2am_ard_3-2-1_50JMM_2021-07-15_final.stac-item
2021-07-26 11:27:05	ga_s2am_ard_3-2-1_51HUC_2021-07-26_final.stac-item
2021-07-28 12:05:18	ga_s2am_ard_3-2-1_49JGL_2021-07-28_final.stac-item
2021-08-21 11:46:21	ga_s2am_ard_3-2-1_50JPL_2021-08-21_final.stac-item
2021-09-07 11:36:58	ga_s2am_ard_3-2-1_51HUC_2021-09-07_final.stac-item
2021-09-10 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-09-10_final
2021-09-29 12:13:58	ga_s2am_ard_3-2-1_50KKA_2021-09-29_final.stac-item
2021-10-13 11:53:16	ga_s2am_ard_3-2-1_50KRC_2021-10-13_final.stac-item
2021-10-26 12:04:36	ga_s2am_ard_3-2-1_49KGP_2021-10-26_final.stac-item
2021-10-29 12:13:45	ga_s2am_ard_3-2-1_49KHS_2021-10-29_final
2022-02-10 11:53:20	ga_s2am_ard_3-2-1_50KPC_2022-02-10_final.stac-item
2022-02-13 12:03:55	ga_s2am_ard_3-2-1_50KLA_2022-02-13_final.stac-item
2022-03-28 12:13:57	ga_s2am_ard_3-2-1_50KKA_2022-03-28_final.stac-item
2022-04-08 11:43:05	ga_s2am_ard_3-2-1_50KRD_2022-04-08_final.stac-item
2022-05-31 11:56:33	ga_s2am_ard_3-2-1_50JLL_2022-05-31_final.stac-item
2022-07-17 11:46:31	ga_s2am_ard_3-2-1_50JPL_2022-07-17_final.stac-item
2022-09-08 11:56:22	ga_s2am_ard_3-2-1_50JLM_2022-09-08_final.stac-item
2022-09-15 11:43:14	ga_s2am_ard_3-2-1_50KRD_2022-09-15_final.stac-item
2022-09-15 11:46:14	ga_s2am_ard_3-2-1_50JPM_2022-09-15_final.stac-item
2022-10-15 11:43:26	ga_s2am_ard_3-2-1_50KQC_2022-10-15_final.stac-item
2022-10-21 12:03:42	ga_s2am_ard_3-2-1_50KLB_2022-10-21_final.stac-item
2023-01-09 12:03:43	ga_s2am_ard_3-2-1_50KKB_2023-01-09_final.stac-item
2023-03-01 11:36:44	ga_s2am_ard_3-2-1_51HTD_2023-03-01_final
2023-03-07 11:53:17	ga_s2am_ard_3-2-1_50KPC_2023-03-07_final
2023-03-27 11:55:51	ga_s2am_ard_3-2-1_50JMN_2023-03-27_final
2023-04-10 11:36:58	ga_s2am_ard_3-2-1_51HUC_2023-04-10_final
2023-05-13 11:43:18	ga_s2am_ard_3-2-1_50KRC_2023-05-13_final
2023-05-20 11:37:05	ga_s2am_ard_3-2-1_50HQH_2023-05-20_final
2023-06-02 11:47:28	ga_s2am_ard_3-2-1_50HMG_2023-06-02_final
2023-09-03 11:55:21	ga_s2am_ard_3-2-1_50JPQ_2023-09-03_final
2023-09-03 11:55:47	ga_s2am_ard_3-2-1_50JLP_2023-09-03_final
2023-09-23 11:53:26	ga_s2am_ard_3-2-1_50KNC_2023-09-23_final
2023-10-03 11:53:19	ga_s2am_ard_3-2-1_50KQC_2023-10-03_final
2023-11-03 11:27:06	ga_s2am_ard_3-2-1_51HTC_2023-11-03_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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