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
2016-03-07 11:25:48	ga_s2am_ard_3-2-1_51KYA_2016-03-07_final.stac-item
2016-03-25 10:52:14	ga_s2am_ard_3-2-1_52KHE_2016-03-25_final.stac-item
2016-08-16 12:13:46	ga_s2am_ard_3-2-1_49KHR_2016-08-16_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JNM_2016-10-28_final.stac-item
2016-10-30 11:18:19	ga_s2am_ard_3-2-1_51JYM_2016-10-30_final.stac-item
2016-11-03 10:59:53	ga_s2am_ard_3-2-1_52KEB_2016-11-03_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KWR_2016-12-22_final.stac-item
2016-12-27 10:43:36	ga_s2am_ard_3-2-1_53JLM_2016-12-27_final.stac-item
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_52KBA_2017-01-25_final.stac-item
2017-02-09 12:02:43	ga_s2am_ard_3-2-1_50KMU_2017-02-09_final.stac-item
2017-02-10 11:32:51	ga_s2am_ard_3-2-1_51HUE_2017-02-10_final.stac-item
2017-04-14 11:38:34	ga_s2am_ard_3-2-1_50KRD_2017-04-14_final.stac-item
2017-10-11 11:40:47	ga_s2am_ard_3-2-1_51LUE_2017-10-11_final.stac-item
2018-03-27 11:33:07	ga_s2am_ard_3-2-1_50HPK_2018-03-27_final.stac-item
2018-07-07 10:27:09	ga_s2am_ard_3-2-1_53HME_2018-07-07_final.stac-item
2018-09-27 11:07:08	ga_s2am_ard_3-2-1_52LEJ_2018-09-27_final.stac-item
2018-12-25 11:43:07	ga_s2am_ard_3-2-1_51KUT_2018-12-25_final.stac-item
2019-01-01 11:33:10	ga_s2am_ard_3-2-1_51KVT_2019-01-01_final.stac-item
2019-04-11 11:33:47	ga_s2am_ard_3-2-1_51KVR_2019-04-11_final.stac-item
2019-04-17 11:56:02	ga_s2am_ard_3-2-1_50JKN_2019-04-17_final.stac-item
2019-05-01 11:37:01	ga_s2am_ard_3-2-1_51HUC_2019-05-01_final.stac-item
2019-06-01 11:05:40	ga_s2am_ard_3-2-1_52JCN_2019-06-01_final.stac-item
2019-06-10 11:37:09	ga_s2am_ard_3-2-1_50HPH_2019-06-10_final.stac-item
2019-07-10 11:33:08	ga_s2am_ard_3-2-1_51KXT_2019-07-10_final.stac-item
2019-07-14 11:13:27	ga_s2am_ard_3-2-1_52KEB_2019-07-14_final.stac-item
2019-07-30 11:33:35	ga_s2am_ard_3-2-1_51KVS_2019-07-30_final.stac-item
2019-08-10 11:05:26	ga_s2am_ard_3-2-1_52JFN_2019-08-10_final.stac-item
2019-08-18 10:26:49	ga_s2am_ard_3-2-1_53HQB_2019-08-18_final.stac-item
2019-09-08 11:36:56	ga_s2am_ard_3-2-1_51HUC_2019-09-08_final.stac-item
2019-09-13 10:46:04	ga_s2am_ard_3-2-1_53HME_2019-09-13_final.stac-item
2019-09-18 11:36:37	ga_s2am_ard_3-2-1_50HPK_2019-09-18_final.stac-item
2019-10-30 12:15:00	ga_s2am_ard_3-2-1_49JFM_2019-10-30_final.stac-item
2019-11-27 11:33:16	ga_s2am_ard_3-2-1_51KVT_2019-11-27_final.stac-item
2020-01-07 11:04:23	ga_s2am_ard_3-2-1_52JFS_2020-01-07_final.stac-item
2020-01-19 11:40:51	ga_s2am_ard_3-2-1_51LWG_2020-01-19_final
2020-01-19 11:43:08	ga_s2am_ard_3-2-1_51KUT_2020-01-19_final.stac-item
2020-02-08 11:43:17	ga_s2am_ard_3-2-1_51KVS_2020-02-08_final.stac-item
2020-02-28 11:46:08	ga_s2am_ard_3-2-1_50JMM_2020-02-28_final.stac-item
2020-02-29 11:11:26	ga_s2am_ard_3-2-1_52LFJ_2020-02-29_final.stac-item
2020-03-03 11:26:54	ga_s2am_ard_3-2-1_51HVC_2020-03-03_final.stac-item
2020-03-15 12:03:19	ga_s2am_ard_3-2-1_50KMC_2020-03-15_final.stac-item
2020-03-25 10:26:28	ga_s2am_ard_3-2-1_53HQC_2020-03-25_final.stac-item
2020-04-05 11:33:09	ga_s2am_ard_3-2-1_51KWT_2020-04-05_final.stac-item
2020-04-14 10:26:31	ga_s2am_ard_3-2-1_53HQC_2020-04-14_final.stac-item
2020-04-27 10:36:48	ga_s2am_ard_3-2-1_53HPB_2020-04-27_final.stac-item
2020-04-28 11:43:14	ga_s2am_ard_3-2-1_51KVT_2020-04-28_final.stac-item
2020-04-29 11:16:43	ga_s2am_ard_3-2-1_51HXD_2020-04-29_final.stac-item
2020-05-08 11:43:15	ga_s2am_ard_3-2-1_51KVT_2020-05-08_final.stac-item
2020-05-08 11:43:19	ga_s2am_ard_3-2-1_51KUT_2020-05-08_final.stac-item
2020-05-28 11:41:39	ga_s2am_ard_3-2-1_51LUE_2020-05-28_final.stac-item
2020-06-04 11:33:15	ga_s2am_ard_3-2-1_51KXT_2020-06-04_final.stac-item
2020-07-17 11:43:16	ga_s2am_ard_3-2-1_51KVT_2020-07-17_final.stac-item
2020-07-24 11:34:02	ga_s2am_ard_3-2-1_51KWQ_2020-07-24_final.stac-item
2020-08-06 11:43:21	ga_s2am_ard_3-2-1_51KUT_2020-08-06_final.stac-item
2020-08-15 10:36:13	ga_s2am_ard_3-2-1_53HNE_2020-08-15_final.stac-item
2020-09-04 10:36:15	ga_s2am_ard_3-2-1_53HME_2020-09-04_final.stac-item
2020-11-06 10:44:25	ga_s2am_ard_3-2-1_53JNM_2020-11-06_final.stac-item
2020-11-14 11:41:36	ga_s2am_ard_3-2-1_51LUE_2020-11-14_final.stac-item
2020-11-17 11:56:02	ga_s2am_ard_3-2-1_50JKN_2020-11-17_final.stac-item
2020-11-28 11:23:29	ga_s2am_ard_3-2-1_51KXS_2020-11-28_final.stac-item
2020-12-04 11:42:26	ga_s2am_ard_3-2-1_51KVA_2020-12-04_final.stac-item
2020-12-18 11:24:27	ga_s2am_ard_3-2-1_51JWN_2020-12-18_final.stac-item
2021-03-20 10:26:45	ga_s2am_ard_3-2-1_53HQB_2021-03-20_final.stac-item
2021-03-20 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2021-03-20_final.stac-item
2021-05-10 11:37:05	ga_s2am_ard_3-2-1_50HPH_2021-05-10_final.stac-item
2021-08-24 11:52:21	ga_s2am_ard_3-2-1_50KQG_2021-08-24_final
2021-09-17 11:37:08	ga_s2am_ard_3-2-1_50HPH_2021-09-17_final.stac-item
2021-09-30 11:43:16	ga_s2am_ard_3-2-1_51KVT_2021-09-30_final.stac-item
2021-11-23 11:23:25	ga_s2am_ard_3-2-1_51KYS_2021-11-23_final.stac-item
2021-11-24 10:54:30	ga_s2am_ard_3-2-1_52JGS_2021-11-24_final.stac-item
2021-12-02 11:57:05	ga_s2am_ard_3-2-1_50HMH_2021-12-02_final.stac-item
2022-01-18 11:42:42	ga_s2am_ard_3-2-1_51KVV_2022-01-18_final.stac-item
2022-01-29 11:14:41	ga_s2am_ard_3-2-1_51JYM_2022-01-29_final.stac-item
2022-02-07 11:43:35	ga_s2am_ard_3-2-1_51KVR_2022-02-07_final.stac-item
2022-02-08 11:13:50	ga_s2am_ard_3-2-1_52KCV_2022-02-08_final.stac-item
2022-06-08 11:13:42	ga_s2am_ard_3-2-1_52KDA_2022-06-08_final.stac-item
2022-06-26 10:36:23	ga_s2am_ard_3-2-1_53HME_2022-06-26_final.stac-item
2022-07-02 10:55:55	ga_s2am_ard_3-2-1_52JGM_2022-07-02_final.stac-item
2022-10-13 11:00:50	ga_s2am_ard_3-2-1_52LHM_2022-10-13_final.stac-item
2022-11-15 11:11:47	ga_s2am_ard_3-2-1_52LFH_2022-11-15_final.stac-item
2022-12-08 11:24:19	ga_s2am_ard_3-2-1_52JBT_2022-12-08_final.stac-item
2023-01-04 11:11:29	ga_s2am_ard_3-2-1_52LFJ_2023-01-04_final.stac-item
2023-01-19 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-01-19_final.stac-item
2023-02-03 11:11:15	ga_s2am_ard_3-2-1_52LFK_2023-02-03_final.stac-item
2023-04-04 11:14:52	ga_s2am_ard_3-2-1_52JBR_2023-04-04_final
2023-06-11 10:35:56	ga_s2am_ard_3-2-1_53JNF_2023-06-11_final
2023-06-16 11:27:06	ga_s2am_ard_3-2-1_51HUC_2023-06-16_final
2023-07-09 11:34:01	ga_s2am_ard_3-2-1_51KWQ_2023-07-09_final
2023-07-29 11:36:48	ga_s2am_ard_3-2-1_51HUD_2023-07-29_final
2023-08-13 10:46:00	ga_s2am_ard_3-2-1_53JLF_2023-08-13_final
2023-11-02 11:55:50	ga_s2am_ard_3-2-1_50JKP_2023-11-02_final
2023-11-16 11:33:40	ga_s2am_ard_3-2-1_51KWR_2023-11-16_final
2024-01-05 11:33:41	ga_s2am_ard_3-2-1_51KVR_2024-01-05_final
2024-01-22 11:21:46	ga_s2am_ard_3-2-1_52LBH_2024-01-22_final
2024-01-25 11:33:03	ga_s2am_ard_3-2-1_51KXT_2024-01-25_final
2024-02-08 11:10:21	ga_s2am_ard_3-2-1_52LHN_2024-02-08_final
2024-03-07 10:36:32	ga_s2am_ard_3-2-1_53HPC_2024-03-07_final
2024-03-12 11:21:50	ga_s2am_ard_3-2-1_52LCH_2024-03-12_final
2024-04-04 11:33:10	ga_s2am_ard_3-2-1_51KWT_2024-04-04_final
2024-04-23 10:26:57	ga_s2am_ard_3-2-1_53HNB_2024-04-23_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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