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
2015-10-03 11:13:11	ga_s2am_ard_3-2-1_52KBC_2015-10-03_final.stac-item
2017-03-16 11:12:06	ga_s2am_ard_3-2-1_52KBC_2017-03-16_final.stac-item
2017-05-05 11:12:04	ga_s2am_ard_3-2-1_52KBC_2017-05-05_final.stac-item
2017-06-13 11:40:49	ga_s2am_ard_3-2-1_51LUE_2017-06-13_final.stac-item
2017-10-11 11:40:47	ga_s2am_ard_3-2-1_50HMJ_2017-10-11_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_50KKB_2018-03-06_final.stac-item
2018-03-07 11:30:40	ga_s2am_ard_3-2-1_51KXU_2018-03-07_final.stac-item
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_51LUF_2018-04-29_final.stac-item
2018-05-03 11:21:11	ga_s2am_ard_3-2-1_51KXT_2018-05-03_final.stac-item
2018-05-09 11:34:47	ga_s2am_ard_3-2-1_51KUS_2018-05-09_final.stac-item
2018-05-26 11:31:39	ga_s2am_ard_3-2-1_51KXT_2018-05-26_final.stac-item
2018-07-09 11:13:18	ga_s2am_ard_3-2-1_52KEA_2018-07-09_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51KXT_2018-08-14_final.stac-item
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_51KXT_2018-09-23_final.stac-item
2018-11-25 11:42:05	ga_s2am_ard_3-2-1_51KVB_2018-11-25_final.stac-item
2018-12-19 11:22:47	ga_s2am_ard_3-2-1_51KYU_2018-12-19_final.stac-item
2019-01-31 11:33:27	ga_s2am_ard_3-2-1_51KVS_2019-01-31_final.stac-item
2019-02-13 11:43:21	ga_s2am_ard_3-2-1_51KVS_2019-02-13_final.stac-item
2019-03-19 11:23:11	ga_s2am_ard_3-2-1_51KXT_2019-03-19_final.stac-item
2019-03-22 11:32:56	ga_s2am_ard_3-2-1_51KWU_2019-03-22_final.stac-item
2019-05-18 11:23:24	ga_s2am_ard_3-2-1_52KBB_2019-05-18_final.stac-item
2019-05-18 11:24:02	ga_s2am_ard_3-2-1_52KBU_2019-05-18_final.stac-item
2019-07-10 11:33:11	ga_s2am_ard_3-2-1_51KVU_2019-07-10_final.stac-item
2019-07-27 11:24:02	ga_s2am_ard_3-2-1_51KXQ_2019-07-27_final.stac-item
2019-08-26 11:23:08	ga_s2am_ard_3-2-1_51KZT_2019-08-26_final.stac-item
2019-12-07 11:32:55	ga_s2am_ard_3-2-1_51KWU_2019-12-07_final.stac-item
2020-02-05 11:33:30	ga_s2am_ard_3-2-1_51KXR_2020-02-05_final.stac-item
2020-02-06 11:03:11	ga_s2am_ard_3-2-1_52KEB_2020-02-06_final.stac-item
2020-03-16 11:33:12	ga_s2am_ard_3-2-1_51KVT_2020-03-16_final.stac-item
2020-03-25 12:05:34	ga_s2am_ard_3-2-1_50JLP_2020-03-25_final.stac-item
2020-03-30 11:14:25	ga_s2am_ard_3-2-1_51JYN_2020-03-30_final.stac-item
2020-04-02 11:23:09	ga_s2am_ard_3-2-1_51KXT_2020-04-02_final.stac-item
2020-04-02 11:25:16	ga_s2am_ard_3-2-1_51JYJ_2020-04-02_final.stac-item
2020-04-25 11:33:40	ga_s2am_ard_3-2-1_51KXR_2020-04-25_final.stac-item
2020-04-28 11:46:25	ga_s2am_ard_3-2-1_50JNL_2020-04-28_final.stac-item
2020-05-22 11:23:41	ga_s2am_ard_3-2-1_51KZR_2020-05-22_final.stac-item
2020-06-24 11:33:51	ga_s2am_ard_3-2-1_51KVR_2020-06-24_final.stac-item
2020-07-14 11:32:59	ga_s2am_ard_3-2-1_51KXU_2020-07-14_final.stac-item
2020-07-18 11:13:28	ga_s2am_ard_3-2-1_52KCB_2020-07-18_final.stac-item
2020-09-15 11:43:04	ga_s2am_ard_3-2-1_51KUU_2020-09-15_final.stac-item
2020-09-26 11:13:13	ga_s2am_ard_3-2-1_52KCC_2020-09-26_final.stac-item
2020-11-28 11:26:44	ga_s2am_ard_3-2-1_51HVD_2020-11-28_final.stac-item
2020-12-14 11:43:08	ga_s2am_ard_3-2-1_51KVT_2020-12-14_final.stac-item
2020-12-14 11:47:03	ga_s2am_ard_3-2-1_50HNH_2020-12-14_final.stac-item
2020-12-25 11:13:33	ga_s2am_ard_3-2-1_52KDA_2020-12-25_final.stac-item
2021-02-16 11:23:15	ga_s2am_ard_3-2-1_52KCB_2021-02-16_final.stac-item
2021-04-17 11:22:57	ga_s2am_ard_3-2-1_52KCC_2021-04-17_final.stac-item
2021-04-24 11:13:26	ga_s2am_ard_3-2-1_52KEA_2021-04-24_final.stac-item
2021-05-04 11:13:31	ga_s2am_ard_3-2-1_52KDA_2021-05-04_final.stac-item
2021-06-26 11:22:57	ga_s2am_ard_3-2-1_51KYU_2021-06-26_final.stac-item
2021-07-15 11:53:14	ga_s2am_ard_3-2-1_50KRC_2021-07-15_final.stac-item
2021-08-21 11:43:14	ga_s2am_ard_3-2-1_51KVT_2021-08-21_final.stac-item
2021-08-28 11:37:19	ga_s2am_ard_3-2-1_50HQG_2021-08-28_final
2021-09-10 11:41:55	ga_s2am_ard_3-2-1_51LWC_2021-09-10_final.stac-item
2021-10-17 11:33:39	ga_s2am_ard_3-2-1_51KUS_2021-10-17_final.stac-item
2021-11-06 11:33:37	ga_s2am_ard_3-2-1_51KUS_2021-11-06_final.stac-item
2021-11-13 11:23:41	ga_s2am_ard_3-2-1_51KYR_2021-11-13_final.stac-item
2021-11-19 11:43:25	ga_s2am_ard_3-2-1_51KVS_2021-11-19_final.stac-item
2022-01-09 11:13:35	ga_s2am_ard_3-2-1_52KDA_2022-01-09_final.stac-item
2022-02-04 11:31:39	ga_s2am_ard_3-2-1_51LYD_2022-02-04_final.stac-item
2022-03-26 11:33:30	ga_s2am_ard_3-2-1_51KWS_2022-03-26_final.stac-item
2022-03-29 11:41:00	ga_s2am_ard_3-2-1_51LWG_2022-03-29_final
2022-04-05 11:33:39	ga_s2am_ard_3-2-1_51KXR_2022-04-05_final.stac-item
2022-04-09 11:13:55	ga_s2am_ard_3-2-1_52KBV_2022-04-09_final.stac-item
2022-06-24 11:33:03	ga_s2am_ard_3-2-1_51KYU_2022-06-24_final.stac-item
2022-07-01 11:23:20	ga_s2am_ard_3-2-1_51KZT_2022-07-01_final.stac-item
2022-07-04 11:33:08	ga_s2am_ard_3-2-1_51KXU_2022-07-04_final.stac-item
2022-07-11 11:23:48	ga_s2am_ard_3-2-1_52KBA_2022-07-11_final.stac-item
2022-07-11 11:24:10	ga_s2am_ard_3-2-1_51KXQ_2022-07-11_final.stac-item
2022-07-17 11:41:30	ga_s2am_ard_3-2-1_51LUF_2022-07-17_final.stac-item
2022-07-31 11:23:23	ga_s2am_ard_3-2-1_51KXT_2022-07-31_final.stac-item
2022-08-13 11:34:08	ga_s2am_ard_3-2-1_51KWQ_2022-08-13_final.stac-item
2022-09-27 10:46:07	ga_s2am_ard_3-2-1_52JGL_2022-09-27_final.stac-item
2022-10-05 11:43:22	ga_s2am_ard_3-2-1_51KUT_2022-10-05_final.stac-item
2022-10-13 11:03:25	ga_s2am_ard_3-2-1_52KEB_2022-10-13_final.stac-item
2022-11-14 11:43:00	ga_s2am_ard_3-2-1_51KVU_2022-11-14_final.stac-item
2022-11-18 11:23:26	ga_s2am_ard_3-2-1_51KYS_2022-11-18_final.stac-item
2022-11-18 11:23:51	ga_s2am_ard_3-2-1_52KBV_2022-11-18_final.stac-item
2022-12-14 11:43:25	ga_s2am_ard_3-2-1_51KVS_2022-12-14_final.stac-item
2023-01-23 11:42:53	ga_s2am_ard_3-2-1_51KVU_2023-01-23_final.stac-item
2023-03-31 11:33:32	ga_s2am_ard_3-2-1_51KUS_2023-03-31_final
2023-03-31 11:33:40	ga_s2am_ard_3-2-1_51KWR_2023-03-31_final
2023-05-07 11:23:49	ga_s2am_ard_3-2-1_52KBV_2023-05-07_final
2023-05-10 11:32:54	ga_s2am_ard_3-2-1_51KXU_2023-05-10_final
2023-08-11 11:41:37	ga_s2am_ard_3-2-1_51LUE_2023-08-11_final
2023-08-18 11:33:33	ga_s2am_ard_3-2-1_51KWS_2023-08-18_final
2023-09-21 11:13:27	ga_s2am_ard_3-2-1_52KDB_2023-09-21_final
2023-09-27 11:33:44	ga_s2am_ard_3-2-1_51KWR_2023-09-27_final
2023-09-30 11:43:05	ga_s2am_ard_3-2-1_51KTU_2023-09-30_final
2023-10-04 11:23:15	ga_s2am_ard_3-2-1_51KXT_2023-10-04_final
2023-10-24 11:23:13	ga_s2am_ard_3-2-1_51KXT_2023-10-24_final
2023-11-03 11:23:08	ga_s2am_ard_3-2-1_51KYT_2023-11-03_final
2023-11-26 11:33:03	ga_s2am_ard_3-2-1_51KXT_2023-11-26_final
2023-12-16 11:32:58	ga_s2am_ard_3-2-1_51KYT_2023-12-16_final
2024-01-02 11:23:10	ga_s2am_ard_3-2-1_51KXT_2024-01-02_final
2024-01-23 10:55:35	ga_s2am_ard_3-2-1_52JGM_2024-01-23_final
2024-04-24 11:32:57	ga_s2am_ard_3-2-1_51KXU_2024-04-24_final
2024-04-28 11:13:32	ga_s2am_ard_3-2-1_52KEA_2024-04-28_final
2024-05-04 11:33:55	ga_s2am_ard_3-2-1_51KXQ_2024-05-04_final
2024-05-24 11:32:57	ga_s2am_ard_3-2-1_51KWU_2024-05-24_nrt

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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