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
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51KZR_2016-05-03_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_51KTS_2016-05-29_final.stac-item
2016-06-07 12:13:25	ga_s2am_ard_3-2-1_49KGR_2016-06-07_final.stac-item
2016-08-11 11:17:03	ga_s2am_ard_3-2-1_51LZC_2016-08-11_final.stac-item
2016-09-24 11:03:54	ga_s2am_ard_3-2-1_52JDT_2016-09-24_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JLL_2016-11-18_final.stac-item
2016-12-31 10:25:21	ga_s2am_ard_3-2-1_53HQA_2016-12-31_final.stac-item
2017-01-19 10:52:06	ga_s2am_ard_3-2-1_52KHU_2017-01-19_final.stac-item
2017-02-02 12:13:15	ga_s2am_ard_3-2-1_49JGK_2017-02-02_final.stac-item
2017-02-22 12:15:07	ga_s2am_ard_3-2-1_49JGK_2017-02-22_final.stac-item
2017-03-06 11:07:05	ga_s2am_ard_3-2-1_52LGM_2017-03-06_final.stac-item
2017-03-16 11:10:28	ga_s2am_ard_3-2-1_52LFL_2017-03-16_final.stac-item
2017-07-04 11:12:00	ga_s2am_ard_3-2-1_52JBP_2017-07-04_final.stac-item
2017-10-25 11:21:08	ga_s2am_ard_3-2-1_52LBK_2017-10-25_final.stac-item
2017-10-30 10:32:32	ga_s2am_ard_3-2-1_53HMD_2017-10-30_final.stac-item
2017-12-04 11:16:54	ga_s2am_ard_3-2-1_51LZC_2017-12-04_final.stac-item
2017-12-21 11:12:09	ga_s2am_ard_3-2-1_52JDT_2017-12-21_final.stac-item
2018-01-13 11:19:15	ga_s2am_ard_3-2-1_52LBH_2018-01-13_final.stac-item
2018-04-10 11:09:59	ga_s2am_ard_3-2-1_52LFL_2018-04-10_final.stac-item
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_51KWB_2018-04-29_final.stac-item
2018-05-23 11:17:08	ga_s2am_ard_3-2-1_52LDJ_2018-05-23_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_53HQB_2018-06-04_final.stac-item
2018-08-17 11:45:55	ga_s2am_ard_3-2-1_50HPJ_2018-08-17_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49KHQ_2018-08-23_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53HME_2018-10-28_final.stac-item
2018-10-30 11:24:52	ga_s2am_ard_3-2-1_51HWE_2018-10-30_final.stac-item
2018-11-06 11:14:05	ga_s2am_ard_3-2-1_52KBU_2018-11-06_final.stac-item
2018-11-29 11:26:53	ga_s2am_ard_3-2-1_51HUC_2018-11-29_final.stac-item
2018-12-15 11:42:37	ga_s2am_ard_3-2-1_51KUV_2018-12-15_final.stac-item
2018-12-15 11:44:26	ga_s2am_ard_3-2-1_50JQT_2018-12-15_final.stac-item
2018-12-19 11:21:15	ga_s2am_ard_3-2-1_52LBK_2018-12-19_final.stac-item
2019-01-14 11:44:47	ga_s2am_ard_3-2-1_51JUL_2019-01-14_final.stac-item
2019-02-07 11:22:24	ga_s2am_ard_3-2-1_51KYA_2019-02-07_final.stac-item
2019-02-11 11:00:27	ga_s2am_ard_3-2-1_52LHN_2019-02-11_final.stac-item
2019-03-04 12:13:49	ga_s2am_ard_3-2-1_50KKA_2019-03-04_final.stac-item
2019-03-24 12:14:11	ga_s2am_ard_3-2-1_49KGQ_2019-03-24_final.stac-item
2019-06-07 11:24:06	ga_s2am_ard_3-2-1_51KWQ_2019-06-07_final.stac-item
2019-06-14 11:11:05	ga_s2am_ard_3-2-1_52LFL_2019-06-14_final.stac-item
2019-09-19 11:06:03	ga_s2am_ard_3-2-1_52JDL_2019-09-19_final.stac-item
2019-11-01 11:13:11	ga_s2am_ard_3-2-1_52KCC_2019-11-01_final.stac-item
2019-11-20 11:47:03	ga_s2am_ard_3-2-1_50HPH_2019-11-20_final.stac-item
2019-12-14 11:23:23	ga_s2am_ard_3-2-1_51KXS_2019-12-14_final.stac-item
2020-01-17 11:00:24	ga_s2am_ard_3-2-1_52LHN_2020-01-17_final.stac-item
2020-01-23 11:25:06	ga_s2am_ard_3-2-1_51JWK_2020-01-23_final.stac-item
2020-02-18 11:44:57	ga_s2am_ard_3-2-1_50JQR_2020-02-18_final.stac-item
2020-04-05 11:33:20	ga_s2am_ard_3-2-1_51KXS_2020-04-05_final.stac-item
2020-04-22 11:23:29	ga_s2am_ard_3-2-1_51KXS_2020-04-22_final.stac-item
2020-05-01 11:53:24	ga_s2am_ard_3-2-1_50KPC_2020-05-01_final.stac-item
2020-06-28 11:13:35	ga_s2am_ard_3-2-1_52KEA_2020-06-28_final.stac-item
2020-09-19 11:26:41	ga_s2am_ard_3-2-1_51HXD_2020-09-19_final.stac-item
2020-10-21 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-10-21_final.stac-item
2020-10-22 11:32:25	ga_s2am_ard_3-2-1_51KVB_2020-10-22_final.stac-item
2020-11-01 11:36:51	ga_s2am_ard_3-2-1_51HTD_2020-11-01_final.stac-item
2020-12-27 10:16:51	ga_s2am_ard_3-2-1_53HQB_2020-12-27_final.stac-item
2021-01-08 10:54:22	ga_s2am_ard_3-2-1_52JFT_2021-01-08_final.stac-item
2021-01-09 10:26:54	ga_s2am_ard_3-2-1_53HNB_2021-01-09_final.stac-item
2021-02-19 11:32:14	ga_s2am_ard_3-2-1_51KWB_2021-02-19_final.stac-item
2021-03-12 11:04:24	ga_s2am_ard_3-2-1_52JGS_2021-03-12_final.stac-item
2021-03-15 11:13:28	ga_s2am_ard_3-2-1_51KZS_2021-03-15_final.stac-item
2021-03-27 11:57:10	ga_s2am_ard_3-2-1_50HMH_2021-03-27_final.stac-item
2021-04-13 11:41:53	ga_s2am_ard_3-2-1_51LVC_2021-04-13_final.stac-item
2021-04-22 10:36:46	ga_s2am_ard_3-2-1_53HNB_2021-04-22_final.stac-item
2021-06-29 11:36:54	ga_s2am_ard_3-2-1_50HPJ_2021-06-29_final.stac-item
2021-08-15 11:23:16	ga_s2am_ard_3-2-1_51KXT_2021-08-15_final.stac-item
2021-10-05 10:55:59	ga_s2am_ard_3-2-1_53JKF_2021-10-05_final.stac-item
2021-10-08 11:03:04	ga_s2am_ard_3-2-1_52KGC_2021-10-08_final.stac-item
2021-10-17 11:33:53	ga_s2am_ard_3-2-1_51KUR_2021-10-17_final.stac-item
2021-12-26 11:31:44	ga_s2am_ard_3-2-1_51LXD_2021-12-26_final.stac-item
2021-12-27 11:02:02	ga_s2am_ard_3-2-1_52KGG_2021-12-27_final.stac-item
2022-01-04 12:05:02	ga_s2am_ard_3-2-1_49JGM_2022-01-04_final.stac-item
2022-01-12 11:21:25	ga_s2am_ard_3-2-1_52LBK_2022-01-12_final.stac-item
2022-02-04 11:33:16	ga_s2am_ard_3-2-1_51KVT_2022-02-04_final.stac-item
2022-02-09 10:45:43	ga_s2am_ard_3-2-1_53JKG_2022-02-09_final.stac-item
2022-04-04 10:26:42	ga_s2am_ard_3-2-1_53HNC_2022-04-04_final.stac-item
2022-05-05 11:34:15	ga_s2am_ard_3-2-1_51KWP_2022-05-05_final.stac-item
2022-05-19 11:14:15	ga_s2am_ard_3-2-1_51KZP_2022-05-19_final.stac-item
2022-08-17 11:14:07	ga_s2am_ard_3-2-1_51KZQ_2022-08-17_final.stac-item
2022-10-09 11:21:42	ga_s2am_ard_3-2-1_52LCJ_2022-10-09_final.stac-item
2022-10-29 11:24:48	ga_s2am_ard_3-2-1_51JWM_2022-10-29_final.stac-item
2022-12-14 11:41:33	ga_s2am_ard_3-2-1_51LUE_2022-12-14_final.stac-item
2022-12-14 11:43:15	ga_s2am_ard_3-2-1_51KUT_2022-12-14_final.stac-item
2023-01-10 11:32:18	ga_s2am_ard_3-2-1_51KVB_2023-01-10_final.stac-item
2023-03-31 11:34:04	ga_s2am_ard_3-2-1_51KXP_2023-03-31_final
2023-04-13 11:42:57	ga_s2am_ard_3-2-1_51KVU_2023-04-13_final
2023-05-07 11:23:49	ga_s2am_ard_3-2-1_52KBV_2023-05-07_final
2023-05-09 10:26:53	ga_s2am_ard_3-2-1_53HNB_2023-05-09_final
2023-05-14 11:13:54	ga_s2am_ard_3-2-1_52KBV_2023-05-14_final
2023-06-01 12:15:23	ga_s2am_ard_3-2-1_49JGK_2023-06-01_final
2023-06-27 10:52:34	ga_s2am_ard_3-2-1_52KHE_2023-06-27_final
2023-07-25 11:55:17	ga_s2am_ard_3-2-1_50JLR_2023-07-25_final
2023-07-30 11:05:28	ga_s2am_ard_3-2-1_52JCP_2023-07-30_final
2023-08-15 11:24:38	ga_s2am_ard_3-2-1_52JBS_2023-08-15_final
2023-09-06 12:05:06	ga_s2am_ard_3-2-1_49JGM_2023-09-06_final
2023-10-04 11:23:12	ga_s2am_ard_3-2-1_51KYT_2023-10-04_final
2023-11-06 11:33:12	ga_s2am_ard_3-2-1_51KWT_2023-11-06_final
2023-11-30 11:12:12	ga_s2am_ard_3-2-1_52KDF_2023-11-30_final
2023-12-15 10:26:35	ga_s2am_ard_3-2-1_53HQC_2023-12-15_final
2024-02-13 12:03:56	ga_s2am_ard_3-2-1_50KKA_2024-02-13_final
2024-03-02 11:23:54	ga_s2am_ard_3-2-1_51KYQ_2024-03-02_final
2024-05-08 11:11:36	ga_s2am_ard_3-2-1_52LEJ_2024-05-08_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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