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
2015-11-18 11:36:00	ga_s2am_ard_3-2-1_51JVF_2015-11-18_final.stac-item
2015-12-27 12:04:06	ga_s2am_ard_3-2-1_49KHR_2015-12-27_final.stac-item
2015-12-27 12:04:06	ga_s2am_ard_3-2-1_50KMA_2015-12-27_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50JPS_2016-03-20_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50KPV_2016-03-20_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51JVH_2016-04-23_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HLH_2016-04-29_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_51HWD_2016-05-10_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JNP_2016-05-29_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JPS_2016-05-29_final.stac-item
2016-06-02 11:26:14	ga_s2am_ard_3-2-1_51JVF_2016-06-02_final.stac-item
2016-10-13 11:35:59	ga_s2am_ard_3-2-1_51HUE_2016-10-13_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHS_2016-11-11_final
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HNG_2016-11-12_final
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HMH_2016-11-15_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50KKB_2016-12-11_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50HLH_2016-12-25_final.stac-item
2017-08-31 12:13:43	ga_s2am_ard_3-2-1_50KKA_2017-08-31_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_50JLQ_2017-10-07_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HLH_2017-10-31_final.stac-item
2017-11-04 11:26:08	ga_s2am_ard_3-2-1_51JUF_2017-11-04_final.stac-item
2017-11-17 11:36:01	ga_s2am_ard_3-2-1_51HVE_2017-11-17_final.stac-item
2017-12-14 11:26:04	ga_s2am_ard_3-2-1_51JUF_2017-12-14_final.stac-item
2017-12-26 12:03:42	ga_s2am_ard_3-2-1_50KLV_2017-12-26_final.stac-item
2017-12-26 12:04:36	ga_s2am_ard_3-2-1_49JGN_2017-12-26_final.stac-item
2017-12-26 12:04:36	ga_s2am_ard_3-2-1_49JHM_2017-12-26_final.stac-item
2017-12-26 12:04:36	ga_s2am_ard_3-2-1_50JKS_2017-12-26_final.stac-item
2018-02-08 11:45:59	ga_s2am_ard_3-2-1_50HMJ_2018-02-08_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JKP_2018-05-22_final.stac-item
2018-05-29 11:39:24	ga_s2am_ard_3-2-1_51KUS_2018-05-29_final.stac-item
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_51HUC_2018-06-05_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50HNJ_2018-07-18_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50JKP_2018-07-24_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JPS_2018-08-27_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50JLP_2018-08-30_final.stac-item
2018-08-31 11:24:03	ga_s2am_ard_3-2-1_51HVC_2018-08-31_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49JGM_2018-10-05_final.stac-item
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_51KTU_2018-11-05_final.stac-item
2018-11-28 11:56:57	ga_s2am_ard_3-2-1_50HMH_2018-11-28_final.stac-item
2018-12-18 11:56:42	ga_s2am_ard_3-2-1_50HMJ_2018-12-18_final.stac-item
2018-12-25 11:47:02	ga_s2am_ard_3-2-1_50HMH_2018-12-25_final.stac-item
2019-01-03 12:13:48	ga_s2am_ard_3-2-1_50KKA_2019-01-03_final.stac-item
2019-01-03 12:14:50	ga_s2am_ard_3-2-1_49JGM_2019-01-03_final.stac-item
2019-01-03 12:15:05	ga_s2am_ard_3-2-1_49JGL_2019-01-03_final.stac-item
2019-01-07 11:53:19	ga_s2am_ard_3-2-1_50KNC_2019-01-07_final.stac-item
2019-01-08 11:26:42	ga_s2am_ard_3-2-1_51HUD_2019-01-08_final.stac-item
2019-01-10 12:05:36	ga_s2am_ard_3-2-1_50JKP_2019-01-10_final.stac-item
2019-01-17 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2019-01-17_final.stac-item
2019-01-27 11:56:48	ga_s2am_ard_3-2-1_50HMJ_2019-01-27_final.stac-item
2019-02-06 11:56:48	ga_s2am_ard_3-2-1_50HMJ_2019-02-06_final.stac-item
2019-04-14 11:46:21	ga_s2am_ard_3-2-1_50JPL_2019-04-14_final.stac-item
2019-05-14 11:43:07	ga_s2am_ard_3-2-1_51KTU_2019-05-14_final.stac-item
2019-06-16 11:56:11	ga_s2am_ard_3-2-1_50JMM_2019-06-16_final.stac-item
2019-10-14 11:56:07	ga_s2am_ard_3-2-1_50JNM_2019-10-14_final.stac-item
2019-12-03 11:57:04	ga_s2am_ard_3-2-1_50HMH_2019-12-03_final.stac-item
2019-12-17 11:33:57	ga_s2am_ard_3-2-1_51KUQ_2019-12-17_final.stac-item
2019-12-30 11:43:24	ga_s2am_ard_3-2-1_51KUS_2019-12-30_final.stac-item
2020-01-29 11:43:03	ga_s2am_ard_3-2-1_51KUT_2020-01-29_final.stac-item
2020-03-06 11:33:18	ga_s2am_ard_3-2-1_51KUT_2020-03-06_final.stac-item
2020-04-08 11:43:01	ga_s2am_ard_3-2-1_51KTU_2020-04-08_final.stac-item
2020-04-15 11:33:22	ga_s2am_ard_3-2-1_51KUT_2020-04-15_final.stac-item
2020-06-17 11:43:24	ga_s2am_ard_3-2-1_51KTT_2020-06-17_final.stac-item
2020-10-09 11:26:28	ga_s2am_ard_3-2-1_51JUF_2020-10-09_final.stac-item
2020-10-11 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-10-11_final.stac-item
2020-12-24 11:44:12	ga_s2am_ard_3-2-1_51KUP_2020-12-24_final.stac-item
2020-12-27 11:57:05	ga_s2am_ard_3-2-1_50HMH_2020-12-27_final.stac-item
2021-01-04 11:16:44	ga_s2am_ard_3-2-1_51HWD_2021-01-04_final.stac-item
2021-01-26 11:52:20	ga_s2am_ard_3-2-1_50KQG_2021-01-26_final
2021-01-26 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2021-01-26_final.stac-item
2021-01-30 11:36:34	ga_s2am_ard_3-2-1_51HVD_2021-01-30_final.stac-item
2021-02-08 12:06:03	ga_s2am_ard_3-2-1_50JLM_2021-02-08_final.stac-item
2021-02-15 11:57:05	ga_s2am_ard_3-2-1_50HMH_2021-02-15_final.stac-item
2021-03-30 12:03:17	ga_s2am_ard_3-2-1_50KNC_2021-03-30_final.stac-item
2021-04-06 11:53:07	ga_s2am_ard_3-2-1_50KRC_2021-04-06_final.stac-item
2021-04-06 11:57:02	ga_s2am_ard_3-2-1_50HMH_2021-04-06_final.stac-item
2021-04-12 12:14:22	ga_s2am_ard_3-2-1_49KGP_2021-04-12_final.stac-item
2021-04-29 12:03:20	ga_s2am_ard_3-2-1_50KMC_2021-04-29_final.stac-item
2021-05-03 11:43:27	ga_s2am_ard_3-2-1_51KUS_2021-05-03_final.stac-item
2021-05-07 11:26:47	ga_s2am_ard_3-2-1_51HUD_2021-05-07_final.stac-item
2021-06-15 11:53:21	ga_s2am_ard_3-2-1_50KPC_2021-06-15_final.stac-item
2021-06-22 11:45:47	ga_s2am_ard_3-2-1_50JQN_2021-06-22_final.stac-item
2021-07-09 11:37:06	ga_s2am_ard_3-2-1_50HQH_2021-07-09_final.stac-item
2021-07-11 12:13:57	ga_s2am_ard_3-2-1_50KKA_2021-07-11_final.stac-item
2021-07-21 12:13:57	ga_s2am_ard_3-2-1_50KKA_2021-07-21_final.stac-item
2021-08-18 11:33:36	ga_s2am_ard_3-2-1_51KUS_2021-08-18_final.stac-item
2021-08-21 11:44:12	ga_s2am_ard_3-2-1_50KPV_2021-08-21_final.stac-item
2022-05-31 11:53:50	ga_s2am_ard_3-2-1_50KMB_2022-05-31_final.stac-item
2022-09-02 11:36:35	ga_s2am_ard_3-2-1_51HVE_2022-09-02_final.stac-item
2022-09-22 11:36:17	ga_s2am_ard_3-2-1_51JVF_2022-09-22_final.stac-item
2022-09-25 11:46:26	ga_s2am_ard_3-2-1_50JPL_2022-09-25_final.stac-item
2022-10-12 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2022-10-12_final.stac-item
2023-01-20 11:37:12	ga_s2am_ard_3-2-1_50HQG_2023-01-20_final
2023-01-26 11:57:03	ga_s2am_ard_3-2-1_50HMH_2023-01-26_final.stac-item
2023-02-25 11:57:03	ga_s2am_ard_3-2-1_50HMH_2023-02-25_final
2023-03-11 11:34:11	ga_s2am_ard_3-2-1_51JXN_2023-03-11_final
2023-04-09 12:05:52	ga_s2am_ard_3-2-1_50JLN_2023-04-09_final
2023-09-07 11:35:29	ga_s2am_ard_3-2-1_51JWJ_2023-09-07_final
2023-09-30 11:43:05	ga_s2am_ard_3-2-1_51KTU_2023-09-30_final
2023-12-26 11:34:14	ga_s2am_ard_3-2-1_51KUP_2023-12-26_final
2024-01-08 11:43:09	ga_s2am_ard_3-2-1_51KTT_2024-01-08_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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