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
2015-09-03 11:10:37	ga_s2am_ard_3-2-1_52LFL_2015-09-03_final.stac-item
2015-11-22 11:12:12	ga_s2am_ard_3-2-1_52KBC_2015-11-22_final.stac-item
2015-12-29 11:06:56	ga_s2am_ard_3-2-1_52KHD_2015-12-29_final.stac-item
2016-03-08 11:02:06	ga_s2am_ard_3-2-1_52KHF_2016-03-08_final.stac-item
2016-05-05 12:03:52	ga_s2am_ard_3-2-1_50KKA_2016-05-05_final.stac-item
2016-05-30 11:11:45	ga_s2am_ard_3-2-1_51HYD_2016-05-30_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_51KUR_2016-06-05_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_49JGN_2016-09-02_final.stac-item
2016-10-15 12:14:37	ga_s2am_ard_3-2-1_49JGN_2016-10-15_final.stac-item
2016-11-03 10:59:53	ga_s2am_ard_3-2-1_52KHB_2016-11-03_final.stac-item
2016-11-23 11:01:01	ga_s2am_ard_3-2-1_52KDU_2016-11-23_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JKS_2017-01-30_final
2017-01-31 11:26:14	ga_s2am_ard_3-2-1_51KUP_2017-01-31_final
2017-02-04 11:16:25	ga_s2am_ard_3-2-1_51HYD_2017-02-04_final
2017-04-17 11:56:08	ga_s2am_ard_3-2-1_50HMJ_2017-04-17_final
2017-05-31 11:28:39	ga_s2am_ard_3-2-1_51KVQ_2017-05-31_final
2017-09-02 11:12:01	ga_s2am_ard_3-2-1_51JXJ_2017-09-02_final
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_50JLR_2017-09-07_final
2017-09-08 11:29:54	ga_s2am_ard_3-2-1_51JVH_2017-09-08_final
2017-09-08 11:29:54	ga_s2am_ard_3-2-1_51JWK_2017-09-08_final
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_50JLN_2017-11-06_final
2018-02-15 11:34:02	ga_s2am_ard_3-2-1_51JWN_2018-02-15_final
2018-02-18 11:42:05	ga_s2am_ard_3-2-1_50KRU_2018-02-18_final
2018-04-06 11:31:45	ga_s2am_ard_3-2-1_50HQJ_2018-04-06_final
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50KRU_2018-06-08_final
2018-09-13 11:26:17	ga_s2am_ard_3-2-1_51KWT_2018-09-13_final
2018-10-14 10:57:13	ga_s2am_ard_3-2-1_52LGM_2018-10-14_final
2018-12-08 11:53:13	ga_s2am_ard_3-2-1_50KPC_2018-12-08_final
2019-02-10 11:33:31	ga_s2am_ard_3-2-1_51KUS_2019-02-10_final
2019-04-08 11:27:03	ga_s2am_ard_3-2-1_51HUC_2019-04-08_final
2019-05-31 11:33:05	ga_s2am_ard_3-2-1_51KYT_2019-05-31_final
2019-08-16 11:23:16	ga_s2am_ard_3-2-1_51KXT_2019-08-16_final
2019-12-20 11:44:25	ga_s2am_ard_3-2-1_51JTN_2019-12-20_final
2020-01-03 11:24:06	ga_s2am_ard_3-2-1_51KXP_2020-01-03_final
2020-01-20 11:10:26	ga_s2am_ard_3-2-1_52LFN_2020-01-20_final.stac-item
2020-01-30 11:15:28	ga_s2am_ard_3-2-1_51JXH_2020-01-30_final
2020-03-12 11:54:01	ga_s2am_ard_3-2-1_50KPV_2020-03-12_final
2020-03-19 11:46:48	ga_s2am_ard_3-2-1_50HNJ_2020-03-19_final
2020-03-29 11:46:30	ga_s2am_ard_3-2-1_50HPK_2020-03-29_final
2020-05-24 12:05:57	ga_s2am_ard_3-2-1_50JLN_2020-05-24_final
2020-05-25 11:36:44	ga_s2am_ard_3-2-1_50HPK_2020-05-25_final
2020-07-07 11:47:00	ga_s2am_ard_3-2-1_50HMJ_2020-07-07_final
2020-11-01 11:35:17	ga_s2am_ard_3-2-1_51JVK_2020-11-01_final
2020-11-28 11:21:54	ga_s2am_ard_3-2-1_52LBH_2020-11-28_final
2021-01-14 11:16:38	ga_s2am_ard_3-2-1_51HYD_2021-01-14_final
2021-01-31 11:00:45	ga_s2am_ard_3-2-1_52LHM_2021-01-31_final
2021-02-10 11:04:20	ga_s2am_ard_3-2-1_52JDT_2021-02-10_final
2021-03-01 11:36:05	ga_s2am_ard_3-2-1_50JQM_2021-03-01_final
2021-06-22 11:42:31	ga_s2am_ard_3-2-1_51KUA_2021-06-22_final
2021-06-22 11:47:03	ga_s2am_ard_3-2-1_50HPH_2021-06-22_final
2021-08-08 11:34:39	ga_s2am_ard_3-2-1_50JRT_2021-08-08_final
2021-08-11 11:42:48	ga_s2am_ard_3-2-1_51KUV_2021-08-11_final
2021-09-04 11:23:50	ga_s2am_ard_3-2-1_51KZQ_2021-09-04_final
2021-11-12 11:57:08	ga_s2am_ard_3-2-1_50HMH_2021-11-12_final
2021-11-23 11:26:15	ga_s2am_ard_3-2-1_51JVF_2021-11-23_final
2021-12-26 11:32:39	ga_s2am_ard_3-2-1_51KVA_2021-12-26_final
2022-01-05 11:36:44	ga_s2am_ard_3-2-1_51HUD_2022-01-05_final
2022-01-08 11:46:10	ga_s2am_ard_3-2-1_50JNM_2022-01-08_final
2022-02-03 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2022-02-03_final
2022-03-04 10:55:17	ga_s2am_ard_3-2-1_52JGP_2022-03-04_final
2022-03-30 11:16:33	ga_s2am_ard_3-2-1_51HWE_2022-03-30_final
2022-04-02 11:24:46	ga_s2am_ard_3-2-1_51JWM_2022-04-02_final
2022-04-28 11:44:25	ga_s2am_ard_3-2-1_50KQU_2022-04-28_final
2022-06-01 11:23:57	ga_s2am_ard_3-2-1_51KZQ_2022-06-01_final
2022-06-11 11:26:02	ga_s2am_ard_3-2-1_51JXG_2022-06-11_final
2022-07-24 11:35:48	ga_s2am_ard_3-2-1_50JQP_2022-07-24_final
2022-08-07 11:14:20	ga_s2am_ard_3-2-1_51KZP_2022-08-07_final
2022-09-05 11:44:46	ga_s2am_ard_3-2-1_50JQT_2022-09-05_final.stac-item
2022-09-12 11:35:11	ga_s2am_ard_3-2-1_51JUL_2022-09-12_final.stac-item
2022-10-02 11:37:08	ga_s2am_ard_3-2-1_51HTC_2022-10-02_final.stac-item
2022-10-03 11:05:15	ga_s2am_ard_3-2-1_52JCQ_2022-10-03_final.stac-item
2022-11-11 11:33:19	ga_s2am_ard_3-2-1_51KVT_2022-11-11_final.stac-item
2022-11-22 11:04:11	ga_s2am_ard_3-2-1_52JGT_2022-11-22_final.stac-item
2022-12-15 11:13:30	ga_s2am_ard_3-2-1_52KEA_2022-12-15_final.stac-item
2022-12-22 11:04:09	ga_s2am_ard_3-2-1_52JGT_2022-12-22_final.stac-item
2022-12-31 11:32:21	ga_s2am_ard_3-2-1_51KYA_2022-12-31_final.stac-item
2023-01-10 11:31:04	ga_s2am_ard_3-2-1_51LZF_2023-01-10_final.stac-item
2023-01-10 11:37:01	ga_s2am_ard_3-2-1_50HQH_2023-01-10_final.stac-item
2023-03-11 11:32:50	ga_s2am_ard_3-2-1_51KXU_2023-03-11_final.stac-item
2023-03-28 11:25:29	ga_s2am_ard_3-2-1_51JVJ_2023-03-28_final.stac-item
2023-05-04 11:16:08	ga_s2am_ard_3-2-1_51JYF_2023-05-04_final.stac-item
2023-05-07 11:23:35	ga_s2am_ard_3-2-1_52KBA_2023-05-07_final.stac-item
2023-05-21 11:06:06	ga_s2am_ard_3-2-1_52JDL_2023-05-21_final.stac-item
2023-06-03 11:16:41	ga_s2am_ard_3-2-1_51HYD_2023-06-03_final.stac-item
2023-06-08 12:05:12	ga_s2am_ard_3-2-1_49JFM_2023-06-08_final.stac-item
2023-06-09 11:36:37	ga_s2am_ard_3-2-1_50HQK_2023-06-09_final.stac-item
2023-06-26 11:23:17	ga_s2am_ard_3-2-1_51KXT_2023-06-26_final.stac-item
2023-06-30 11:04:55	ga_s2am_ard_3-2-1_52JDR_2023-06-30_final.stac-item
2023-08-11 11:46:45	ga_s2am_ard_3-2-1_50HMK_2023-08-11_final.stac-item
2023-10-06 12:03:45	ga_s2am_ard_3-2-1_50KKB_2023-10-06_final.stac-item
2023-11-10 11:16:22	ga_s2am_ard_3-2-1_51HYE_2023-11-10_final.stac-item
2024-01-23 10:53:25	ga_s2am_ard_3-2-1_52KGA_2024-01-23_final.stac-item
2024-01-25 11:35:50	ga_s2am_ard_3-2-1_51JVG_2024-01-25_final.stac-item
2024-01-26 11:00:43	ga_s2am_ard_3-2-1_52LGM_2024-01-26_final.stac-item
2024-03-02 11:21:10	ga_s2am_ard_3-2-1_52LBL_2024-03-02_final.stac-item
2024-03-03 10:52:20	ga_s2am_ard_3-2-1_52KHF_2024-03-03_final.stac-item
2024-03-06 11:06:38	ga_s2am_ard_3-2-1_51HYD_2024-03-06_final.stac-item
2024-03-09 11:12:38	ga_s2am_ard_3-2-1_52KCE_2024-03-09_final.stac-item
2024-03-12 11:23:39	ga_s2am_ard_3-2-1_51KYR_2024-03-12_final.stac-item
2024-03-22 11:23:11	ga_s2am_ard_3-2-1_51KYT_2024-03-22_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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