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
2015-10-04 10:45:32	ga_s2am_ard_3-2-1_52JGM_2015-10-04_final.stac-item
2015-11-27 12:03:46	ga_s2am_ard_3-2-1_50KMV_2015-11-27_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HQJ_2015-12-21_final.stac-item
2016-01-21 11:14:09	ga_s2am_ard_3-2-1_52JDT_2016-01-21_final.stac-item
2016-02-06 11:26:58	ga_s2am_ard_3-2-1_51KWS_2016-02-06_final.stac-item
2016-03-06 12:04:37	ga_s2am_ard_3-2-1_50JLS_2016-03-06_final.stac-item
2016-03-11 11:12:21	ga_s2am_ard_3-2-1_52JBP_2016-03-11_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50JQM_2016-04-19_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_51KWQ_2016-09-13_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_51KVT_2016-10-03_final.stac-item
2017-01-31 11:26:14	ga_s2am_ard_3-2-1_51KWR_2017-01-31_final.stac-item
2017-04-08 11:20:55	ga_s2am_ard_3-2-1_51KXS_2017-04-08_final.stac-item
2017-04-10 12:03:46	ga_s2am_ard_3-2-1_50KMA_2017-04-10_final.stac-item
2017-04-28 11:20:48	ga_s2am_ard_3-2-1_51KXQ_2017-04-28_final.stac-item
2017-07-17 11:20:58	ga_s2am_ard_3-2-1_51KZR_2017-07-17_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_50KNC_2017-11-26_final.stac-item
2018-02-19 11:07:09	ga_s2am_ard_3-2-1_52JCT_2018-02-19_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_51KWR_2018-04-26_final.stac-item
2018-07-15 11:26:22	ga_s2am_ard_3-2-1_51KYT_2018-07-15_final.stac-item
2018-08-07 11:40:42	ga_s2am_ard_3-2-1_51KUU_2018-08-07_final.stac-item
2018-08-22 10:47:24	ga_s2am_ard_3-2-1_52JFL_2018-08-22_final.stac-item
2018-12-22 11:33:15	ga_s2am_ard_3-2-1_51KXS_2018-12-22_final.stac-item
2019-01-13 12:13:50	ga_s2am_ard_3-2-1_49KHR_2019-01-13_final.stac-item
2019-01-21 11:33:20	ga_s2am_ard_3-2-1_51KXS_2019-01-21_final.stac-item
2019-01-27 11:53:18	ga_s2am_ard_3-2-1_50KPC_2019-01-27_final.stac-item
2019-04-05 11:15:34	ga_s2am_ard_3-2-1_52JCN_2019-04-05_final.stac-item
2019-04-08 11:22:28	ga_s2am_ard_3-2-1_51KYA_2019-04-08_final.stac-item
2019-06-27 11:26:26	ga_s2am_ard_3-2-1_51HXE_2019-06-27_final.stac-item
2019-07-13 11:42:26	ga_s2am_ard_3-2-1_51KWA_2019-07-13_final.stac-item
2019-10-02 11:13:56	ga_s2am_ard_3-2-1_51KZQ_2019-10-02_final.stac-item
2019-10-21 11:43:47	ga_s2am_ard_3-2-1_51KUR_2019-10-21_final.stac-item
2019-10-31 11:46:51	ga_s2am_ard_3-2-1_50HPJ_2019-10-31_final.stac-item
2020-01-15 12:03:38	ga_s2am_ard_3-2-1_50KKB_2020-01-15_final.stac-item
2020-01-26 11:32:04	ga_s2am_ard_3-2-1_51KXB_2020-01-26_final.stac-item
2020-01-29 11:42:38	ga_s2am_ard_3-2-1_51KUV_2020-01-29_final.stac-item
2020-01-29 11:43:05	ga_s2am_ard_3-2-1_50KRC_2020-01-29_final.stac-item
2020-04-02 11:23:31	ga_s2am_ard_3-2-1_51KZR_2020-04-02_final.stac-item
2020-05-22 11:23:27	ga_s2am_ard_3-2-1_51KZS_2020-05-22_final.stac-item
2020-06-01 11:23:49	ga_s2am_ard_3-2-1_51KXR_2020-06-01_final.stac-item
2020-06-11 11:24:04	ga_s2am_ard_3-2-1_51KWQ_2020-06-11_final.stac-item
2020-06-27 11:41:03	ga_s2am_ard_3-2-1_51LWG_2020-06-27_final
2020-07-04 11:33:05	ga_s2am_ard_3-2-1_51KYT_2020-07-04_final.stac-item
2020-07-14 11:33:03	ga_s2am_ard_3-2-1_51KWU_2020-07-14_final.stac-item
2020-07-21 11:25:33	ga_s2am_ard_3-2-1_51JWJ_2020-07-21_final.stac-item
2020-07-27 11:43:41	ga_s2am_ard_3-2-1_51KVR_2020-07-27_final.stac-item
2020-09-02 11:33:27	ga_s2am_ard_3-2-1_51KUT_2020-09-02_final.stac-item
2020-09-04 12:13:44	ga_s2am_ard_3-2-1_50KKB_2020-09-04_final.stac-item
2020-09-12 11:33:37	ga_s2am_ard_3-2-1_51KXR_2020-09-12_final.stac-item
2020-09-12 11:36:18	ga_s2am_ard_3-2-1_51JUF_2020-09-12_final.stac-item
2020-09-16 11:14:12	ga_s2am_ard_3-2-1_52JET_2020-09-16_final.stac-item
2020-09-22 11:33:18	ga_s2am_ard_3-2-1_51KXT_2020-09-22_final.stac-item
2020-11-14 11:42:13	ga_s2am_ard_3-2-1_51KWB_2020-11-14_final.stac-item
2021-01-10 11:32:51	ga_s2am_ard_3-2-1_51KYU_2021-01-10_final.stac-item
2021-01-23 11:40:58	ga_s2am_ard_3-2-1_51LWG_2021-01-23_final
2021-02-02 11:41:33	ga_s2am_ard_3-2-1_51LUE_2021-02-02_final.stac-item
2021-02-22 11:43:18	ga_s2am_ard_3-2-1_50KRC_2021-02-22_final.stac-item
2021-03-31 11:33:59	ga_s2am_ard_3-2-1_51KWP_2021-03-31_final.stac-item
2021-05-06 11:53:09	ga_s2am_ard_3-2-1_50KRC_2021-05-06_final.stac-item
2021-05-06 11:56:06	ga_s2am_ard_3-2-1_50JMM_2021-05-06_final.stac-item
2021-06-22 11:43:30	ga_s2am_ard_3-2-1_51KUS_2021-06-22_final.stac-item
2021-07-02 11:40:59	ga_s2am_ard_3-2-1_51LWG_2021-07-02_final
2021-07-22 11:46:37	ga_s2am_ard_3-2-1_50HPK_2021-07-22_final.stac-item
2021-08-18 11:35:22	ga_s2am_ard_3-2-1_51JWJ_2021-08-18_final.stac-item
2021-09-27 11:33:45	ga_s2am_ard_3-2-1_51KWR_2021-09-27_final.stac-item
2021-11-19 11:44:52	ga_s2am_ard_3-2-1_50JPS_2021-11-19_final.stac-item
2021-12-01 10:45:47	ga_s2am_ard_3-2-1_52JGM_2021-12-01_final.stac-item
2022-01-01 11:57:11	ga_s2am_ard_3-2-1_50HLH_2022-01-01_final.stac-item
2022-01-13 10:55:47	ga_s2am_ard_3-2-1_52JFM_2022-01-13_final.stac-item
2022-02-07 11:42:09	ga_s2am_ard_3-2-1_51KWB_2022-02-07_final.stac-item
2022-02-11 11:23:49	ga_s2am_ard_3-2-1_51KZQ_2022-02-11_final.stac-item
2022-02-14 11:33:01	ga_s2am_ard_3-2-1_51KVU_2022-02-14_final.stac-item
2022-02-21 11:23:45	ga_s2am_ard_3-2-1_51KXR_2022-02-21_final.stac-item
2022-05-08 11:41:02	ga_s2am_ard_3-2-1_51LWG_2022-05-08_final
2022-05-14 12:04:38	ga_s2am_ard_3-2-1_50JKT_2022-05-14_final.stac-item
2022-06-20 11:52:46	ga_s2am_ard_3-2-1_50KQF_2022-06-20_final
2022-06-23 12:05:56	ga_s2am_ard_3-2-1_49JGJ_2022-06-23_final.stac-item
2022-11-11 11:32:23	ga_s2am_ard_3-2-1_51KVB_2022-11-11_final.stac-item
2022-12-02 11:05:45	ga_s2am_ard_3-2-1_52JFM_2022-12-02_final.stac-item
2023-02-16 11:23:18	ga_s2am_ard_3-2-1_51KZS_2023-02-16_final
2023-02-25 11:53:15	ga_s2am_ard_3-2-1_50KQC_2023-02-25_final
2023-03-05 11:15:30	ga_s2am_ard_3-2-1_52JCN_2023-03-05_final
2023-03-05 11:16:17	ga_s2am_ard_3-2-1_52HBK_2023-03-05_final
2023-03-08 11:21:21	ga_s2am_ard_3-2-1_51LZE_2023-03-08_final
2023-03-31 11:32:24	ga_s2am_ard_3-2-1_51KXA_2023-03-31_final
2023-04-13 11:43:47	ga_s2am_ard_3-2-1_50KRA_2023-04-13_final
2023-04-20 11:33:32	ga_s2am_ard_3-2-1_51KUS_2023-04-20_final
2023-04-24 11:16:40	ga_s2am_ard_3-2-1_51HXD_2023-04-24_final
2023-04-26 11:56:25	ga_s2am_ard_3-2-1_50JLL_2023-04-26_final
2023-06-06 11:27:11	ga_s2am_ard_3-2-1_51HTC_2023-06-06_final
2023-06-18 12:05:42	ga_s2am_ard_3-2-1_50JLP_2023-06-18_final
2023-08-05 11:23:33	ga_s2am_ard_3-2-1_51KXS_2023-08-05_final
2023-10-20 11:43:15	ga_s2am_ard_3-2-1_51KUT_2023-10-20_final
2023-11-28 12:13:47	ga_s2am_ard_3-2-1_49KHR_2023-11-28_final
2023-11-29 11:47:02	ga_s2am_ard_3-2-1_50HMH_2023-11-29_final
2023-12-24 10:55:57	ga_s2am_ard_3-2-1_52JFL_2023-12-24_final
2024-01-02 11:23:10	ga_s2am_ard_3-2-1_51KXT_2024-01-02_final
2024-02-11 11:24:16	ga_s2am_ard_3-2-1_52JBT_2024-02-11_final
2024-04-25 11:06:00	ga_s2am_ard_3-2-1_52JBM_2024-04-25_final
2024-04-29 10:46:03	ga_s2am_ard_3-2-1_52JGL_2024-04-29_final
2024-05-14 11:32:43	ga_s2am_ard_3-2-1_51KXV_2024-05-14_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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