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
2016-01-19 12:15:17	ga_s2am_ard_3-2-1_49JGL_2016-01-19_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JPT_2016-01-20_final.stac-item
2016-01-29 10:30:47	ga_s2am_ard_3-2-1_53JPL_2016-01-29_final.stac-item
2016-05-28 10:34:29	ga_s2am_ard_3-2-1_53JNM_2016-05-28_final.stac-item
2016-06-20 10:45:18	ga_s2am_ard_3-2-1_53JNH_2016-06-20_final.stac-item
2016-12-01 10:25:00	ga_s2am_ard_3-2-1_53HQC_2016-12-01_final.stac-item
2016-12-23 10:57:35	ga_s2am_ard_3-2-1_53KKB_2016-12-23_final.stac-item
2017-02-01 10:57:59	ga_s2am_ard_3-2-1_52KEA_2017-02-01_final.stac-item
2017-03-12 11:27:30	ga_s2am_ard_3-2-1_51KWT_2017-03-12_final.stac-item
2017-05-25 11:12:04	ga_s2am_ard_3-2-1_52KBC_2017-05-25_final.stac-item
2017-06-29 10:23:05	ga_s2am_ard_3-2-1_53HNC_2017-06-29_final.stac-item
2017-07-20 11:36:04	ga_s2am_ard_3-2-1_50JQM_2017-07-20_final.stac-item
2017-08-19 11:36:41	ga_s2am_ard_3-2-1_51HUD_2017-08-19_final.stac-item
2017-09-25 11:26:05	ga_s2am_ard_3-2-1_51JVF_2017-09-25_final.stac-item
2018-01-18 12:14:35	ga_s2am_ard_3-2-1_49JFM_2018-01-18_final.stac-item
2018-01-26 11:29:50	ga_s2am_ard_3-2-1_51KXA_2018-01-26_final.stac-item
2018-03-18 11:05:41	ga_s2am_ard_3-2-1_52JEL_2018-03-18_final.stac-item
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_51KWS_2018-06-05_final.stac-item
2018-07-26 10:57:17	ga_s2am_ard_3-2-1_52LHN_2018-07-26_final.stac-item
2018-08-02 10:47:25	ga_s2am_ard_3-2-1_52JGN_2018-08-02_final.stac-item
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_51KUT_2018-09-23_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JPL_2018-09-26_final.stac-item
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_51KUV_2018-10-06_final.stac-item
2018-10-25 10:27:05	ga_s2am_ard_3-2-1_53HPC_2018-10-25_final.stac-item
2018-11-16 11:14:03	ga_s2am_ard_3-2-1_51KZP_2018-11-16_final.stac-item
2019-01-21 11:33:09	ga_s2am_ard_3-2-1_51KWT_2019-01-21_final.stac-item
2019-01-31 11:36:35	ga_s2am_ard_3-2-1_50HPK_2019-01-31_final.stac-item
2019-02-09 12:03:20	ga_s2am_ard_3-2-1_50KMC_2019-02-09_final.stac-item
2019-03-21 12:04:58	ga_s2am_ard_3-2-1_49JGM_2019-03-21_final.stac-item
2019-03-23 11:02:53	ga_s2am_ard_3-2-1_52KHC_2019-03-23_final.stac-item
2019-04-25 11:10:28	ga_s2am_ard_3-2-1_52LHN_2019-04-25_final.stac-item
2019-05-08 11:24:08	ga_s2am_ard_3-2-1_51KWQ_2019-05-08_final.stac-item
2019-05-27 11:53:20	ga_s2am_ard_3-2-1_50KQC_2019-05-27_final.stac-item
2019-06-21 11:04:47	ga_s2am_ard_3-2-1_52JFR_2019-06-21_final.stac-item
2019-07-09 10:24:45	ga_s2am_ard_3-2-1_53JQL_2019-07-09_final.stac-item
2019-08-24 10:42:59	ga_s2am_ard_3-2-1_53KMT_2019-08-24_final.stac-item
2019-08-29 11:36:39	ga_s2am_ard_3-2-1_50HPK_2019-08-29_final.stac-item
2019-10-11 11:46:46	ga_s2am_ard_3-2-1_50HQJ_2019-10-11_final.stac-item
2019-11-15 10:55:41	ga_s2am_ard_3-2-1_53JKG_2019-11-15_final.stac-item
2019-12-17 11:32:48	ga_s2am_ard_3-2-1_51KXU_2019-12-17_final.stac-item
2020-02-10 10:45:36	ga_s2am_ard_3-2-1_53JKG_2020-02-10_final.stac-item
2020-02-24 12:05:50	ga_s2am_ard_3-2-1_50JKN_2020-02-24_final.stac-item
2020-02-25 11:33:00	ga_s2am_ard_3-2-1_51KVU_2020-02-25_final.stac-item
2020-05-15 11:34:45	ga_s2am_ard_3-2-1_51JWM_2020-05-15_final.stac-item
2020-05-29 11:14:37	ga_s2am_ard_3-2-1_52JDS_2020-05-29_final.stac-item
2020-06-17 11:42:52	ga_s2am_ard_3-2-1_51KUV_2020-06-17_final.stac-item
2020-07-04 11:34:04	ga_s2am_ard_3-2-1_51KVQ_2020-07-04_final.stac-item
2020-07-11 11:26:48	ga_s2am_ard_3-2-1_51HVD_2020-07-11_final.stac-item
2020-08-12 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-08-12_final.stac-item
2020-08-23 11:33:44	ga_s2am_ard_3-2-1_51KXR_2020-08-23_final.stac-item
2020-08-28 10:43:57	ga_s2am_ard_3-2-1_53KNP_2020-08-28_final.stac-item
2020-09-17 10:41:42	ga_s2am_ard_3-2-1_53LPC_2020-09-17_final
2020-09-20 10:50:43	ga_s2am_ard_3-2-1_53LNG_2020-09-20_final.stac-item
2020-10-31 12:05:57	ga_s2am_ard_3-2-1_50JLN_2020-10-31_final.stac-item
2020-12-03 10:34:53	ga_s2am_ard_3-2-1_53JNK_2020-12-03_final.stac-item
2020-12-10 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2020-12-10_final.stac-item
2021-02-11 10:36:57	ga_s2am_ard_3-2-1_53HPA_2021-02-11_final.stac-item
2021-03-15 11:10:24	ga_s2am_ard_3-2-1_52LHN_2021-03-15_final.stac-item
2021-03-30 12:04:43	ga_s2am_ard_3-2-1_49JGN_2021-03-30_final.stac-item
2021-04-24 11:16:33	ga_s2am_ard_3-2-1_51HYD_2021-04-24_final.stac-item
2021-04-28 10:50:35	ga_s2am_ard_3-2-1_53LNG_2021-04-28_final.stac-item
2021-05-08 10:51:21	ga_s2am_ard_3-2-1_53LND_2021-05-08_final.stac-item
2021-06-01 12:14:19	ga_s2am_ard_3-2-1_50KKU_2021-06-01_final.stac-item
2021-06-02 11:42:28	ga_s2am_ard_3-2-1_51KVA_2021-06-02_final.stac-item
2021-07-10 11:03:05	ga_s2am_ard_3-2-1_52KFC_2021-07-10_final.stac-item
2021-07-21 12:15:03	ga_s2am_ard_3-2-1_49JFM_2021-07-21_final.stac-item
2021-12-04 10:50:23	ga_s2am_ard_3-2-1_53LNH_2021-12-04_final
2022-01-25 11:34:40	ga_s2am_ard_3-2-1_51JWM_2022-01-25_final.stac-item
2022-01-27 10:33:35	ga_s2am_ard_3-2-1_53KQQ_2022-01-27_final.stac-item
2022-02-02 10:52:29	ga_s2am_ard_3-2-1_53KKV_2022-02-02_final.stac-item
2022-02-04 11:31:39	ga_s2am_ard_3-2-1_51LYD_2022-02-04_final.stac-item
2022-02-09 10:44:05	ga_s2am_ard_3-2-1_53JNN_2022-02-09_final.stac-item
2022-04-02 11:25:47	ga_s2am_ard_3-2-1_51JXH_2022-04-02_final.stac-item
2022-04-13 10:51:06	ga_s2am_ard_3-2-1_53LPE_2022-04-13_final.stac-item
2022-06-15 11:06:21	ga_s2am_ard_3-2-1_52JBL_2022-06-15_final.stac-item
2022-07-24 11:33:45	ga_s2am_ard_3-2-1_51KUS_2022-07-24_final.stac-item
2022-08-17 11:13:26	ga_s2am_ard_3-2-1_52KBC_2022-08-17_final.stac-item
2022-08-20 11:24:24	ga_s2am_ard_3-2-1_51KXP_2022-08-20_final.stac-item
2022-09-05 11:46:31	ga_s2am_ard_3-2-1_50JPL_2022-09-05_final.stac-item
2022-09-21 12:05:51	ga_s2am_ard_3-2-1_49JGJ_2022-09-21_final.stac-item
2022-09-25 11:42:35	ga_s2am_ard_3-2-1_51KVA_2022-09-25_final.stac-item
2022-11-10 10:24:43	ga_s2am_ard_3-2-1_53JQL_2022-11-10_final.stac-item
2022-11-11 11:32:23	ga_s2am_ard_3-2-1_51KVB_2022-11-11_final.stac-item
2022-12-26 10:45:49	ga_s2am_ard_3-2-1_53JKF_2022-12-26_final.stac-item
2023-01-09 10:26:25	ga_s2am_ard_3-2-1_53HQC_2023-01-09_final.stac-item
2023-02-18 10:24:37	ga_s2am_ard_3-2-1_53JQL_2023-02-18_final
2023-04-09 10:24:04	ga_s2am_ard_3-2-1_53JRN_2023-04-09_final
2023-04-22 12:13:38	ga_s2am_ard_3-2-1_50KKB_2023-04-22_final
2023-05-06 11:53:25	ga_s2am_ard_3-2-1_50KNC_2023-05-06_final
2023-05-06 11:56:14	ga_s2am_ard_3-2-1_50JKM_2023-05-06_final
2023-06-26 11:26:43	ga_s2am_ard_3-2-1_51HWD_2023-06-26_final
2023-08-07 12:05:19	ga_s2am_ard_3-2-1_49JGL_2023-08-07_final
2023-08-27 10:27:00	ga_s2am_ard_3-2-1_53HNB_2023-08-27_final
2023-09-03 11:55:26	ga_s2am_ard_3-2-1_50JNQ_2023-09-03_final
2023-09-09 10:33:43	ga_s2am_ard_3-2-1_53KPQ_2023-09-09_final
2023-10-24 11:27:02	ga_s2am_ard_3-2-1_51HUC_2023-10-24_final
2024-01-15 11:33:41	ga_s2am_ard_3-2-1_51KUR_2024-01-15_final
2024-01-28 11:46:38	ga_s2am_ard_3-2-1_50HQJ_2024-01-28_final
2024-02-07 11:43:11	ga_s2am_ard_3-2-1_51KUT_2024-02-07_final
2024-02-27 11:42:27	ga_s2am_ard_3-2-1_51KVA_2024-02-27_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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