Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2015-08-27 11:26:08	ga_s2am_ard_3-2-1_51HUE_2015-08-27_final.stac-item
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HQG_2015-12-08_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HMK_2015-12-21_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_50JPL_2016-02-06_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JLT_2016-03-03_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49KGP_2016-03-16_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50HMJ_2016-04-19_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50JNM_2016-04-29_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50JPS_2016-04-29_final.stac-item
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51HUC_2016-05-03_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50JNQ_2016-05-09_final.stac-item
2016-09-20 11:22:33	ga_s2am_ard_3-2-1_51HUD_2016-09-20_final.stac-item
2016-10-12 12:03:43	ga_s2am_ard_3-2-1_50KLA_2016-10-12_final.stac-item
2016-10-13 11:35:59	ga_s2am_ard_3-2-1_51HVE_2016-10-13_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HLG_2016-11-15_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HLH_2016-12-15_final
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50HLG_2017-02-16_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50HMH_2017-02-16_final
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_49JGM_2017-03-21_final
2017-04-11 11:36:02	ga_s2am_ard_3-2-1_50JQM_2017-04-11_final
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50HLK_2017-05-27_final
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50JNL_2017-05-27_final
2017-07-17 11:20:58	ga_s2am_ard_3-2-1_51HVD_2017-07-17_final
2017-09-28 11:36:22	ga_s2am_ard_3-2-1_51HVD_2017-09-28_final
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_50HQG_2017-11-27_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50HMJ_2017-12-03_final
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50JNM_2017-12-10_final
2017-12-26 12:03:42	ga_s2am_ard_3-2-1_50KMA_2017-12-26_final
2017-12-26 12:04:36	ga_s2am_ard_3-2-1_49JHM_2017-12-26_final
2017-12-26 12:04:47	ga_s2am_ard_3-2-1_50JKS_2017-12-26_final
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_49JHN_2018-01-05_final
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HMH_2018-02-18_final
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_49JGM_2018-03-26_final
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_49JGM_2018-04-25_final
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_49KHS_2018-05-05_final.stac-item
2018-05-19 11:40:33	ga_s2am_ard_3-2-1_50JPS_2018-05-19_final
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JKP_2018-05-22_final
2018-05-23 11:25:37	ga_s2am_ard_3-2-1_51HWC_2018-05-23_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JKP_2018-05-25_final
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HPG_2018-05-29_final.stac-item
2018-05-30 11:13:18	ga_s2am_ard_3-2-1_51HWC_2018-05-30_final.stac-item
2018-06-22 11:26:00	ga_s2am_ard_3-2-1_51HUD_2018-06-22_final
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49KHS_2018-07-24_final.stac-item
2018-08-01 11:23:55	ga_s2am_ard_3-2-1_51HTC_2018-08-01_final
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_50HPG_2018-08-14_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50KPV_2018-08-27_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50KQD_2018-09-09_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JLT_2018-09-29_final
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49KHP_2018-10-05_final
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50KQG_2018-10-09_final.stac-item
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HUE_2018-10-10_final
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50JPM_2018-10-26_final
2018-12-01 12:03:36	ga_s2am_ard_3-2-1_49KHS_2018-12-01_final.stac-item
2018-12-02 11:37:18	ga_s2am_ard_3-2-1_50HNG_2018-12-02_final.stac-item
2018-12-06 11:16:35	ga_s2am_ard_3-2-1_51HWD_2018-12-06_final
2019-01-03 12:13:48	ga_s2am_ard_3-2-1_50KKA_2019-01-03_final
2019-01-03 12:14:02	ga_s2am_ard_3-2-1_50KKV_2019-01-03_final
2019-01-03 12:14:03	ga_s2am_ard_3-2-1_49KHQ_2019-01-03_final
2019-01-04 11:44:32	ga_s2am_ard_3-2-1_50JPT_2019-01-04_final
2019-02-06 11:57:03	ga_s2am_ard_3-2-1_50HMH_2019-02-06_final
2019-04-14 11:46:21	ga_s2am_ard_3-2-1_50JPL_2019-04-14_final
2019-06-06 11:55:50	ga_s2am_ard_3-2-1_50JKP_2019-06-06_final
2019-07-26 11:53:08	ga_s2am_ard_3-2-1_50KQD_2019-07-26_final.stac-item
2019-10-04 11:53:01	ga_s2am_ard_3-2-1_50KRD_2019-10-04_final
2019-11-30 11:44:17	ga_s2am_ard_3-2-1_50KRU_2019-11-30_final
2019-12-03 11:57:04	ga_s2am_ard_3-2-1_50HMH_2019-12-03_final
2020-05-07 12:15:14	ga_s2am_ard_3-2-1_49JGL_2020-05-07_final
2020-06-07 11:47:20	ga_s2am_ard_3-2-1_50HLH_2020-06-07_final
2020-06-23 12:06:10	ga_s2am_ard_3-2-1_50JLM_2020-06-23_final
2020-08-09 11:55:01	ga_s2am_ard_3-2-1_50JMS_2020-08-09_final
2020-10-02 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2020-10-02_final
2020-10-16 11:17:04	ga_s2am_ard_3-2-1_51HWC_2020-10-16_final.stac-item
2020-11-23 12:15:12	ga_s2am_ard_3-2-1_49JGL_2020-11-23_final
2021-03-31 11:36:21	ga_s2am_ard_3-2-1_51HVE_2021-03-31_final
2021-04-06 11:52:55	ga_s2am_ard_3-2-1_50KRD_2021-04-06_final
2021-04-14 11:16:35	ga_s2am_ard_3-2-1_51HXD_2021-04-14_final
2021-04-29 12:03:38	ga_s2am_ard_3-2-1_50KLB_2021-04-29_final
2021-05-23 11:43:04	ga_s2am_ard_3-2-1_50KRD_2021-05-23_final
2021-07-22 11:47:06	ga_s2am_ard_3-2-1_50HPH_2021-07-22_final
2021-08-21 11:44:25	ga_s2am_ard_3-2-1_50KPU_2021-08-21_final
2021-08-21 11:47:30	ga_s2am_ard_3-2-1_50HLG_2021-08-21_final.stac-item
2021-10-04 11:27:06	ga_s2am_ard_3-2-1_51HUC_2021-10-04_final
2021-12-03 11:26:35	ga_s2am_ard_3-2-1_51HXD_2021-12-03_final
2021-12-20 11:16:56	ga_s2am_ard_3-2-1_51HXC_2021-12-20_final.stac-item
2022-06-10 11:52:29	ga_s2am_ard_3-2-1_50KQG_2022-06-10_final.stac-item
2022-09-02 11:36:35	ga_s2am_ard_3-2-1_51HVE_2022-09-02_final.stac-item
2022-10-11 12:04:42	ga_s2am_ard_3-2-1_50JMT_2022-10-11_final.stac-item
2022-10-18 11:53:24	ga_s2am_ard_3-2-1_50KPC_2022-10-18_final.stac-item
2022-11-07 11:53:21	ga_s2am_ard_3-2-1_50KQC_2022-11-07_final.stac-item
2022-11-17 11:56:06	ga_s2am_ard_3-2-1_50JNM_2022-11-17_final.stac-item
2022-12-20 12:05:13	ga_s2am_ard_3-2-1_49JGL_2022-12-20_final.stac-item
2023-01-30 11:37:24	ga_s2am_ard_3-2-1_50HNG_2023-01-30_final.stac-item
2023-02-25 11:57:03	ga_s2am_ard_3-2-1_50HMH_2023-02-25_final.stac-item
2023-03-05 11:16:55	ga_s2am_ard_3-2-1_51HWC_2023-03-05_final.stac-item
2023-03-31 11:37:25	ga_s2am_ard_3-2-1_50HNG_2023-03-31_final.stac-item
2023-04-07 11:26:26	ga_s2am_ard_3-2-1_51HWE_2023-04-07_final.stac-item
2023-04-09 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2023-04-09_final.stac-item
2023-04-13 11:44:50	ga_s2am_ard_3-2-1_50JQS_2023-04-13_final.stac-item
2023-05-06 11:57:20	ga_s2am_ard_3-2-1_50HMG_2023-05-06_final.stac-item
2023-09-16 12:03:48	ga_s2am_ard_3-2-1_50KKB_2023-09-16_final.stac-item

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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

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