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
2015-12-07 10:22:23	ga_s2am_ard_3-2-1_53KRP_2015-12-07_final.stac-item
2016-01-23 10:17:44	ga_s2am_ard_3-2-1_54HUG_2016-01-23_final.stac-item
2016-02-08 12:10:34	ga_s2am_ard_3-2-1_49KGR_2016-02-08_final.stac-item
2016-09-01 10:55:14	ga_s2am_ard_3-2-1_52JGP_2016-09-01_final.stac-item
2016-09-30 09:45:59	ga_s2am_ard_3-2-1_54GYA_2016-09-30_final.stac-item
2016-10-10 11:22:34	ga_s2am_ard_3-2-1_51KWQ_2016-10-10_final.stac-item
2017-01-03 10:28:36	ga_s2am_ard_3-2-1_54KVD_2017-01-03_final.stac-item
2017-03-31 10:18:50	ga_s2am_ard_3-2-1_54LZP_2017-03-31_final.stac-item
2017-04-20 10:18:55	ga_s2am_ard_3-2-1_54LXP_2017-04-20_final.stac-item
2017-09-10 10:31:59	ga_s2am_ard_3-2-1_54KVF_2017-09-10_final.stac-item
2017-09-27 10:18:51	ga_s2am_ard_3-2-1_54LXP_2017-09-27_final.stac-item
2017-11-08 10:57:14	ga_s2am_ard_3-2-1_52KGG_2017-11-08_final.stac-item
2017-11-08 11:02:57	ga_s2am_ard_3-2-1_52JER_2017-11-08_final.stac-item
2017-12-08 11:02:31	ga_s2am_ard_3-2-1_52KHV_2017-12-08_final.stac-item
2018-02-21 10:07:01	ga_s2am_ard_3-2-1_54KZG_2018-02-21_final.stac-item
2018-04-11 10:37:28	ga_s2am_ard_3-2-1_53JMN_2018-04-11_final.stac-item
2018-04-24 10:47:27	ga_s2am_ard_3-2-1_53LPE_2018-04-24_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_50HQH_2018-04-26_final.stac-item
2018-06-14 10:17:05	ga_s2am_ard_3-2-1_54LZL_2018-06-14_final.stac-item
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_54HXK_2018-06-28_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KTA_2018-10-15_final.stac-item
2019-01-03 12:15:14	ga_s2am_ard_3-2-1_49JGK_2019-01-03_final.stac-item
2019-02-01 11:01:29	ga_s2am_ard_3-2-1_52LGJ_2019-02-01_final.stac-item
2019-02-27 11:26:36	ga_s2am_ard_3-2-1_51HXD_2019-02-27_final.stac-item
2019-03-13 11:00:58	ga_s2am_ard_3-2-1_52LGL_2019-03-13_final.stac-item
2019-04-01 11:34:14	ga_s2am_ard_3-2-1_51KVP_2019-04-01_final.stac-item
2019-04-16 10:43:54	ga_s2am_ard_3-2-1_53KNP_2019-04-16_final.stac-item
2019-04-26 10:43:29	ga_s2am_ard_3-2-1_53KMR_2019-04-26_final.stac-item
2019-05-01 11:36:00	ga_s2am_ard_3-2-1_51JVG_2019-05-01_final.stac-item
2019-07-09 12:04:10	ga_s2am_ard_3-2-1_50KKA_2019-07-09_final.stac-item
2019-08-07 10:55:53	ga_s2am_ard_3-2-1_52JEM_2019-08-07_final.stac-item
2019-10-15 11:22:58	ga_s2am_ard_3-2-1_51KXU_2019-10-15_final.stac-item
2019-12-17 11:32:57	ga_s2am_ard_3-2-1_51KVU_2019-12-17_final.stac-item
2020-02-07 12:14:48	ga_s2am_ard_3-2-1_49JGM_2020-02-07_final.stac-item
2020-03-06 09:57:47	ga_s2am_ard_3-2-1_54HYB_2020-03-06_final.stac-item
2020-03-29 11:45:57	ga_s2am_ard_3-2-1_50JNN_2020-03-29_final.stac-item
2020-04-27 10:33:47	ga_s2am_ard_3-2-1_54KTU_2020-04-27_final.stac-item
2020-05-20 10:43:54	ga_s2am_ard_3-2-1_53KPP_2020-05-20_final.stac-item
2020-05-20 10:44:18	ga_s2am_ard_3-2-1_53JLN_2020-05-20_final.stac-item
2020-06-07 10:07:22	ga_s2am_ard_3-2-1_54HVE_2020-06-07_final.stac-item
2020-07-15 11:03:12	ga_s2am_ard_3-2-1_53KKS_2020-07-15_final.stac-item
2020-07-18 11:13:31	ga_s2am_ard_3-2-1_52KBB_2020-07-18_final.stac-item
2020-07-31 09:48:36	ga_s2am_ard_3-2-1_55GDP_2020-07-31_final.stac-item
2020-08-03 11:33:44	ga_s2am_ard_3-2-1_51KXR_2020-08-03_final.stac-item
2020-08-25 10:33:22	ga_s2am_ard_3-2-1_53KRR_2020-08-25_final.stac-item
2020-09-23 11:00:34	ga_s2am_ard_3-2-1_53LKH_2020-09-23_final.stac-item
2020-12-16 10:41:41	ga_s2am_ard_3-2-1_54KTG_2020-12-16_final.stac-item
2021-01-25 10:44:07	ga_s2am_ard_3-2-1_53JNN_2021-01-25_final.stac-item
2021-02-08 10:23:05	ga_s2am_ard_3-2-1_54KXA_2021-02-08_final.stac-item
2021-03-02 11:05:34	ga_s2am_ard_3-2-1_52JDN_2021-03-02_final.stac-item
2021-04-27 11:23:17	ga_s2am_ard_3-2-1_52KBB_2021-04-27_final.stac-item
2021-05-04 09:38:51	ga_s2am_ard_3-2-1_55GCN_2021-05-04_final.stac-item
2021-05-17 09:47:58	ga_s2am_ard_3-2-1_55GER_2021-05-17_final.stac-item
2021-06-11 10:36:25	ga_s2am_ard_3-2-1_53HMD_2021-06-11_final.stac-item
2021-06-16 11:23:14	ga_s2am_ard_3-2-1_51KXT_2021-06-16_final.stac-item
2021-06-22 10:07:15	ga_s2am_ard_3-2-1_54HYD_2021-06-22_final.stac-item
2021-06-24 10:45:27	ga_s2am_ard_3-2-1_53JLH_2021-06-24_final.stac-item
2021-10-03 10:16:57	ga_s2am_ard_3-2-1_54HWF_2021-10-03_final.stac-item
2021-10-13 11:57:15	ga_s2am_ard_3-2-1_50HLH_2021-10-13_final.stac-item
2021-11-06 11:35:01	ga_s2am_ard_3-2-1_51JVL_2021-11-06_final.stac-item
2021-12-13 11:23:42	ga_s2am_ard_3-2-1_51KXR_2021-12-13_final.stac-item
2022-01-08 11:43:13	ga_s2am_ard_3-2-1_51KVT_2022-01-08_final.stac-item
2022-04-28 11:43:41	ga_s2am_ard_3-2-1_50KQB_2022-04-28_final.stac-item
2022-06-03 10:24:27	ga_s2am_ard_3-2-1_54JTS_2022-06-03_final.stac-item
2022-07-30 11:53:56	ga_s2am_ard_3-2-1_50KQA_2022-07-30_final.stac-item
2022-08-31 10:52:42	ga_s2am_ard_3-2-1_53KKV_2022-08-31_final.stac-item
2022-09-04 12:14:19	ga_s2am_ard_3-2-1_50KKV_2022-09-04_final.stac-item
2022-09-19 11:25:50	ga_s2am_ard_3-2-1_51JWH_2022-09-19_final.stac-item
2022-10-04 10:33:48	ga_s2am_ard_3-2-1_54KUU_2022-10-04_final.stac-item
2022-10-06 11:15:07	ga_s2am_ard_3-2-1_52JDQ_2022-10-06_final.stac-item
2022-11-15 11:16:10	ga_s2am_ard_3-2-1_51JYF_2022-11-15_final.stac-item
2022-12-26 10:42:42	ga_s2am_ard_3-2-1_53KMU_2022-12-26_final.stac-item
2023-01-05 10:46:08	ga_s2am_ard_3-2-1_53HLE_2023-01-05_final.stac-item
2023-01-21 11:03:03	ga_s2am_ard_3-2-1_53KKS_2023-01-21_final.stac-item
2023-01-30 11:33:40	ga_s2am_ard_3-2-1_51KWR_2023-01-30_final.stac-item
2023-02-19 11:31:02	ga_s2am_ard_3-2-1_52LBL_2023-02-19_final
2023-02-28 12:04:40	ga_s2am_ard_3-2-1_49JHN_2023-02-28_final
2023-03-17 11:57:12	ga_s2am_ard_3-2-1_49HGC_2023-03-17_nrt
2023-04-19 10:22:59	ga_s2am_ard_3-2-1_54KVB_2023-04-19_final
2023-04-21 11:00:38	ga_s2am_ard_3-2-1_53LLG_2023-04-21_final
2023-05-02 10:29:54	ga_s2am_ard_3-2-1_54LXP_2023-05-02_final
2023-05-24 09:38:15	ga_s2am_ard_3-2-1_55GFQ_2023-05-24_final
2023-05-24 12:51:03	ga_s2am_ard_3-2-1_48LWP_2023-05-24_final
2023-06-14 10:45:51	ga_s2am_ard_3-2-1_52JGM_2023-06-14_final
2023-06-27 10:54:14	ga_s2am_ard_3-2-1_53JKN_2023-06-27_final
2023-07-05 10:15:06	ga_s2am_ard_3-2-1_54JVP_2023-07-05_final
2023-08-14 11:56:19	ga_s2am_ard_3-2-1_50JKM_2023-08-14_final
2023-08-15 11:25:11	ga_s2am_ard_3-2-1_51JYK_2023-08-15_final
2023-09-13 11:57:19	ga_s2am_ard_3-2-1_49HGC_2023-09-13_nrt
2023-10-06 10:24:05	ga_s2am_ard_3-2-1_54JTT_2023-10-06_final
2023-12-10 11:11:07	ga_s2am_ard_3-2-1_52LGK_2023-12-10_final
2024-01-23 10:55:15	ga_s2am_ard_3-2-1_52JEP_2024-01-23_final
2024-01-24 10:21:30	ga_s2am_ard_3-2-1_54KYG_2024-01-24_final
2024-01-26 11:01:58	ga_s2am_ard_3-2-1_52KHG_2024-01-26_final
2024-02-08 11:13:25	ga_s2am_ard_3-2-1_51KZS_2024-02-08_final
2024-02-21 11:22:20	ga_s2am_ard_3-2-1_52KBF_2024-02-21_final
2024-03-14 12:04:13	ga_s2am_ard_3-2-1_50KKV_2024-03-14_final
2024-03-20 10:41:42	ga_s2am_ard_3-2-1_53LNC_2024-03-20_final
2024-03-26 11:04:15	ga_s2am_ard_3-2-1_52JFT_2024-03-26_final
2024-03-26 11:04:36	ga_s2am_ard_3-2-1_52JGR_2024-03-26_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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