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
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_52JBR_2015-12-25_final.stac-item
2016-04-18 12:14:43	ga_s2am_ard_3-2-1_49JGN_2016-04-18_final.stac-item
2016-05-30 11:11:45	ga_s2am_ard_3-2-1_52KEU_2016-05-30_final.stac-item
2016-07-02 11:22:40	ga_s2am_ard_3-2-1_51KZQ_2016-07-02_final.stac-item
2016-10-17 11:11:30	ga_s2am_ard_3-2-1_52KCD_2016-10-17_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_51LZD_2016-11-22_final.stac-item
2017-08-23 11:12:16	ga_s2am_ard_3-2-1_52KEB_2017-08-23_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_51KUV_2017-12-10_final.stac-item
2018-02-06 11:02:07	ga_s2am_ard_3-2-1_52KFB_2018-02-06_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JKN_2018-02-21_final.stac-item
2018-03-27 11:33:07	ga_s2am_ard_3-2-1_50HPK_2018-03-27_final.stac-item
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50JPS_2018-04-02_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_50HQH_2018-04-26_final.stac-item
2018-04-27 10:57:18	ga_s2am_ard_3-2-1_52LHL_2018-04-27_final.stac-item
2018-05-21 10:37:29	ga_s2am_ard_3-2-1_53JKF_2018-05-21_final.stac-item
2018-05-23 11:17:08	ga_s2am_ard_3-2-1_51KZU_2018-05-23_final.stac-item
2018-05-28 10:27:09	ga_s2am_ard_3-2-1_53JQJ_2018-05-28_final.stac-item
2018-05-28 12:13:23	ga_s2am_ard_3-2-1_49KGQ_2018-05-28_final.stac-item
2018-08-31 11:16:57	ga_s2am_ard_3-2-1_51KYS_2018-08-31_final.stac-item
2018-10-05 10:27:04	ga_s2am_ard_3-2-1_53JQK_2018-10-05_final.stac-item
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52KDA_2018-10-17_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JLM_2018-10-22_final.stac-item
2019-03-29 11:21:46	ga_s2am_ard_3-2-1_52LDH_2019-03-29_final.stac-item
2019-04-20 12:03:19	ga_s2am_ard_3-2-1_50KMC_2019-04-20_final.stac-item
2019-05-13 12:13:58	ga_s2am_ard_3-2-1_49KHR_2019-05-13_final.stac-item
2019-06-19 12:04:10	ga_s2am_ard_3-2-1_50KMV_2019-06-19_final.stac-item
2019-06-26 11:56:04	ga_s2am_ard_3-2-1_50JKN_2019-06-26_final.stac-item
2019-06-27 11:22:28	ga_s2am_ard_3-2-1_51KZA_2019-06-27_final.stac-item
2019-07-07 11:24:03	ga_s2am_ard_3-2-1_51KWQ_2019-07-07_final.stac-item
2019-09-05 11:25:05	ga_s2am_ard_3-2-1_51JYK_2019-09-05_final.stac-item
2019-09-25 11:23:43	ga_s2am_ard_3-2-1_51KXR_2019-09-25_final.stac-item
2019-12-24 11:23:08	ga_s2am_ard_3-2-1_51KXT_2019-12-24_final.stac-item
2020-03-28 10:36:28	ga_s2am_ard_3-2-1_53HPC_2020-03-28_final.stac-item
2020-05-04 12:04:49	ga_s2am_ard_3-2-1_49JGN_2020-05-04_final.stac-item
2020-05-05 11:34:03	ga_s2am_ard_3-2-1_51KVQ_2020-05-05_final.stac-item
2020-06-16 10:36:34	ga_s2am_ard_3-2-1_53HLD_2020-06-16_final.stac-item
2020-08-20 11:23:16	ga_s2am_ard_3-2-1_51KYT_2020-08-20_final.stac-item
2020-09-01 12:06:09	ga_s2am_ard_3-2-1_50JLM_2020-09-01_final.stac-item
2020-10-07 10:42:01	ga_s2am_ard_3-2-1_53KNB_2020-10-07_final.stac-item
2020-12-09 10:55:39	ga_s2am_ard_3-2-1_52JGM_2020-12-09_final.stac-item
2021-01-10 11:34:37	ga_s2am_ard_3-2-1_50JRT_2021-01-10_final.stac-item
2021-01-29 10:25:20	ga_s2am_ard_3-2-1_53JQH_2021-01-29_final.stac-item
2021-02-13 11:13:47	ga_s2am_ard_3-2-1_52KDV_2021-02-13_final.stac-item
2021-02-20 11:01:51	ga_s2am_ard_3-2-1_53KLB_2021-02-20_final.stac-item
2021-03-13 12:14:59	ga_s2am_ard_3-2-1_49JFM_2021-03-13_final.stac-item
2021-07-19 11:33:42	ga_s2am_ard_3-2-1_51KWR_2021-07-19_final.stac-item
2021-07-19 11:37:01	ga_s2am_ard_3-2-1_51HUC_2021-07-19_final.stac-item
2021-08-05 11:23:30	ga_s2am_ard_3-2-1_52KCA_2021-08-05_final.stac-item
2021-08-31 11:42:47	ga_s2am_ard_3-2-1_51KUV_2021-08-31_final.stac-item
2021-09-10 11:42:46	ga_s2am_ard_3-2-1_51KUV_2021-09-10_final.stac-item
2021-10-25 10:54:26	ga_s2am_ard_3-2-1_52JFT_2021-10-25_final.stac-item
2021-10-27 11:33:00	ga_s2am_ard_3-2-1_51KXU_2021-10-27_final.stac-item
2021-11-10 11:16:14	ga_s2am_ard_3-2-1_51JXF_2021-11-10_final.stac-item
2021-11-25 12:03:59	ga_s2am_ard_3-2-1_50KKA_2021-11-25_final.stac-item
2021-12-04 10:55:24	ga_s2am_ard_3-2-1_53JKH_2021-12-04_final.stac-item
2022-01-05 11:32:16	ga_s2am_ard_3-2-1_51KWB_2022-01-05_final.stac-item
2022-01-13 10:53:00	ga_s2am_ard_3-2-1_52KHC_2022-01-13_final.stac-item
2022-04-01 11:53:59	ga_s2am_ard_3-2-1_50KMA_2022-04-01_final.stac-item
2022-04-12 11:26:38	ga_s2am_ard_3-2-1_51HXD_2022-04-12_final.stac-item
2022-05-04 12:04:18	ga_s2am_ard_3-2-1_50KKV_2022-05-04_final.stac-item
2022-05-05 11:33:46	ga_s2am_ard_3-2-1_51KWR_2022-05-05_final.stac-item
2022-05-15 11:32:24	ga_s2am_ard_3-2-1_51KVB_2022-05-15_final.stac-item
2022-05-24 12:04:39	ga_s2am_ard_3-2-1_50KLU_2022-05-24_final.stac-item
2022-05-30 10:42:32	ga_s2am_ard_3-2-1_53KNV_2022-05-30_final.stac-item
2022-06-04 11:33:50	ga_s2am_ard_3-2-1_51KWR_2022-06-04_final.stac-item
2022-06-13 12:06:14	ga_s2am_ard_3-2-1_50JLM_2022-06-13_final.stac-item
2022-07-17 11:47:26	ga_s2am_ard_3-2-1_50HLH_2022-07-17_final.stac-item
2022-09-02 11:34:15	ga_s2am_ard_3-2-1_51KUQ_2022-09-02_final.stac-item
2022-09-20 10:55:35	ga_s2am_ard_3-2-1_52JGN_2022-09-20_final.stac-item
2022-09-22 11:33:41	ga_s2am_ard_3-2-1_51KUS_2022-09-22_final.stac-item
2022-09-22 11:34:44	ga_s2am_ard_3-2-1_50JRT_2022-09-22_final.stac-item
2022-10-23 11:06:01	ga_s2am_ard_3-2-1_52JBM_2022-10-23_final.stac-item
2022-10-26 11:16:43	ga_s2am_ard_3-2-1_51HXD_2022-10-26_final.stac-item
2022-11-04 11:43:48	ga_s2am_ard_3-2-1_51KUR_2022-11-04_final.stac-item
2022-11-04 11:43:55	ga_s2am_ard_3-2-1_50KQA_2022-11-04_final.stac-item
2022-12-03 10:34:33	ga_s2am_ard_3-2-1_53JQL_2022-12-03_final.stac-item
2022-12-11 11:31:05	ga_s2am_ard_3-2-1_52LBL_2022-12-11_final
2022-12-25 11:10:35	ga_s2am_ard_3-2-1_52LHM_2022-12-25_final.stac-item
2022-12-29 10:52:19	ga_s2am_ard_3-2-1_53KNV_2022-12-29_final.stac-item
2023-01-15 10:45:57	ga_s2am_ard_3-2-1_52JGL_2023-01-15_final.stac-item
2023-01-30 11:32:24	ga_s2am_ard_3-2-1_51KXA_2023-01-30_final.stac-item
2023-03-26 10:45:53	ga_s2am_ard_3-2-1_53JLF_2023-03-26_final
2023-04-07 11:26:47	ga_s2am_ard_3-2-1_51HUD_2023-04-07_final
2023-04-28 10:55:05	ga_s2am_ard_3-2-1_53JKJ_2023-04-28_final
2023-04-29 10:26:54	ga_s2am_ard_3-2-1_53HNB_2023-04-29_final
2023-05-02 12:15:11	ga_s2am_ard_3-2-1_49JGL_2023-05-02_final
2023-05-06 11:55:16	ga_s2am_ard_3-2-1_50JPQ_2023-05-06_final
2023-05-19 10:26:42	ga_s2am_ard_3-2-1_53HNC_2023-05-19_final
2023-06-29 11:33:27	ga_s2am_ard_3-2-1_51KXS_2023-06-29_final
2023-08-21 11:46:58	ga_s2am_ard_3-2-1_50HNJ_2023-08-21_final
2023-08-25 11:23:26	ga_s2am_ard_3-2-1_52KBB_2023-08-25_final
2023-09-22 10:46:00	ga_s2am_ard_3-2-1_53JKF_2023-09-22_final
2023-11-20 11:12:51	ga_s2am_ard_3-2-1_52KFC_2023-11-20_final
2023-12-21 10:43:52	ga_s2am_ard_3-2-1_53KNP_2023-12-21_final
2024-01-07 10:35:08	ga_s2am_ard_3-2-1_53JQH_2024-01-07_final
2024-02-08 11:12:16	ga_s2am_ard_3-2-1_52KDF_2024-02-08_final
2024-02-19 10:45:45	ga_s2am_ard_3-2-1_52JGM_2024-02-19_final
2024-03-09 11:11:27	ga_s2am_ard_3-2-1_52LGJ_2024-03-09_final
2024-04-07 11:43:42	ga_s2am_ard_3-2-1_51KUR_2024-04-07_final
2024-04-30 11:53:13	ga_s2am_ard_3-2-1_50KRC_2024-04-30_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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