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
2015-10-08 12:03:08	ga_s2am_ard_3-2-1_49JGM_2015-10-08_final.stac-item
2015-10-22 11:38:10	ga_s2am_ard_3-2-1_50HPK_2015-10-22_final.stac-item
2016-03-18 11:02:07	ga_s2am_ard_3-2-1_52KGD_2016-03-18_final.stac-item
2016-04-30 11:14:04	ga_s2am_ard_3-2-1_51JYJ_2016-04-30_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_52KCV_2016-05-10_final.stac-item
2016-05-30 11:11:45	ga_s2am_ard_3-2-1_51KZP_2016-05-30_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50KLU_2016-07-14_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_49JGM_2016-08-13_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50JLM_2016-09-09_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50JNL_2016-09-19_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51KYQ_2017-06-27_final.stac-item
2017-09-22 11:11:57	ga_s2am_ard_3-2-1_52JBP_2017-09-22_final.stac-item
2017-10-25 11:21:08	ga_s2am_ard_3-2-1_51KYT_2017-10-25_final.stac-item
2017-11-04 11:26:08	ga_s2am_ard_3-2-1_51HVE_2017-11-04_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49JGK_2017-12-16_final.stac-item
2018-03-07 11:30:40	ga_s2am_ard_3-2-1_51KYT_2018-03-07_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49JGJ_2018-07-04_final.stac-item
2018-07-05 11:29:39	ga_s2am_ard_3-2-1_51KWR_2018-07-05_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50HLK_2018-07-21_final.stac-item
2018-08-21 11:21:36	ga_s2am_ard_3-2-1_51KZS_2018-08-21_final.stac-item
2018-09-30 11:16:55	ga_s2am_ard_3-2-1_51KZR_2018-09-30_final.stac-item
2018-11-07 10:45:43	ga_s2am_ard_3-2-1_52JGM_2018-11-07_final.stac-item
2018-11-15 11:43:14	ga_s2am_ard_3-2-1_51KTT_2018-11-15_final.stac-item
2019-02-22 10:34:35	ga_s2am_ard_3-2-1_53JNL_2019-02-22_final.stac-item
2019-03-08 11:56:31	ga_s2am_ard_3-2-1_50HMK_2019-03-08_final.stac-item
2019-03-31 10:26:36	ga_s2am_ard_3-2-1_53HPC_2019-03-31_final.stac-item
2019-06-05 10:44:50	ga_s2am_ard_3-2-1_53JKL_2019-06-05_final.stac-item
2019-08-21 10:35:55	ga_s2am_ard_3-2-1_53JNF_2019-08-21_final.stac-item
2019-09-29 11:03:18	ga_s2am_ard_3-2-1_52KFB_2019-09-29_final.stac-item
2019-10-03 10:46:02	ga_s2am_ard_3-2-1_52JGL_2019-10-03_final.stac-item
2019-12-04 11:23:48	ga_s2am_ard_3-2-1_51KZQ_2019-12-04_final.stac-item
2019-12-07 11:36:55	ga_s2am_ard_3-2-1_51HUC_2019-12-07_final.stac-item
2020-01-17 11:03:28	ga_s2am_ard_3-2-1_52KEA_2020-01-17_final.stac-item
2020-01-29 11:43:08	ga_s2am_ard_3-2-1_51KVT_2020-01-29_final.stac-item
2020-01-30 11:13:44	ga_s2am_ard_3-2-1_52KCV_2020-01-30_final.stac-item
2020-02-12 11:24:08	ga_s2am_ard_3-2-1_51KWP_2020-02-12_final.stac-item
2020-04-02 11:23:45	ga_s2am_ard_3-2-1_51KZQ_2020-04-02_final.stac-item
2020-04-25 11:36:54	ga_s2am_ard_3-2-1_50HPJ_2020-04-25_final.stac-item
2020-05-01 11:53:13	ga_s2am_ard_3-2-1_50KRC_2020-05-01_final.stac-item
2020-05-25 11:37:03	ga_s2am_ard_3-2-1_51HUC_2020-05-25_final.stac-item
2020-06-11 11:22:59	ga_s2am_ard_3-2-1_51KZU_2020-06-11_final.stac-item
2020-07-10 11:56:44	ga_s2am_ard_3-2-1_50HLK_2020-07-10_final.stac-item
2020-07-15 11:03:53	ga_s2am_ard_3-2-1_52KEV_2020-07-15_final.stac-item
2020-07-21 11:26:02	ga_s2am_ard_3-2-1_51JWG_2020-07-21_final.stac-item
2020-07-24 11:33:08	ga_s2am_ard_3-2-1_51KXU_2020-07-24_final.stac-item
2020-08-10 11:27:04	ga_s2am_ard_3-2-1_51HVC_2020-08-10_final.stac-item
2020-09-01 12:06:00	ga_s2am_ard_3-2-1_50JKN_2020-09-01_final.stac-item
2020-10-09 11:21:38	ga_s2am_ard_3-2-1_52LDJ_2020-10-09_final.stac-item
2020-12-02 11:00:44	ga_s2am_ard_3-2-1_52LHM_2020-12-02_final.stac-item
2020-12-24 11:41:17	ga_s2am_ard_3-2-1_51LUF_2020-12-24_final.stac-item
2021-01-02 12:14:56	ga_s2am_ard_3-2-1_49JGM_2021-01-02_final.stac-item
2021-01-30 11:31:42	ga_s2am_ard_3-2-1_51LXD_2021-01-30_final.stac-item
2021-03-04 11:43:03	ga_s2am_ard_3-2-1_51KTU_2021-03-04_final.stac-item
2021-04-01 11:03:43	ga_s2am_ard_3-2-1_52KFV_2021-04-01_final.stac-item
2021-04-09 10:26:49	ga_s2am_ard_3-2-1_53HNB_2021-04-09_final.stac-item
2021-04-22 12:14:41	ga_s2am_ard_3-2-1_49JFN_2021-04-22_final.stac-item
2021-05-05 10:46:11	ga_s2am_ard_3-2-1_53HKE_2021-05-05_final
2021-05-14 11:13:36	ga_s2am_ard_3-2-1_52KCA_2021-05-14_final.stac-item
2021-06-19 11:37:01	ga_s2am_ard_3-2-1_51HTC_2021-06-19_final.stac-item
2021-07-03 11:11:04	ga_s2am_ard_3-2-1_52LFL_2021-07-03_final.stac-item
2021-07-06 11:27:01	ga_s2am_ard_3-2-1_51HVC_2021-07-06_final.stac-item
2021-07-28 12:05:00	ga_s2am_ard_3-2-1_49JHM_2021-07-28_final.stac-item
2021-08-16 10:56:02	ga_s2am_ard_3-2-1_52JFL_2021-08-16_final.stac-item
2021-08-24 11:55:55	ga_s2am_ard_3-2-1_50JMN_2021-08-24_final.stac-item
2021-11-15 12:04:00	ga_s2am_ard_3-2-1_49KHR_2021-11-15_final.stac-item
2021-11-19 11:40:57	ga_s2am_ard_3-2-1_51LWG_2021-11-19_final
2021-12-15 10:27:01	ga_s2am_ard_3-2-1_53HQA_2021-12-15_final.stac-item
2022-02-24 11:33:01	ga_s2am_ard_3-2-1_51KWU_2022-02-24_final.stac-item
2022-03-11 10:44:14	ga_s2am_ard_3-2-1_53JMN_2022-03-11_final.stac-item
2022-03-28 10:35:55	ga_s2am_ard_3-2-1_53JNF_2022-03-28_final.stac-item
2022-03-30 11:11:33	ga_s2am_ard_3-2-1_52LFJ_2022-03-30_final.stac-item
2022-04-11 11:53:12	ga_s2am_ard_3-2-1_50KRC_2022-04-11_final.stac-item
2022-06-09 10:44:21	ga_s2am_ard_3-2-1_53JLN_2022-06-09_final.stac-item
2022-07-24 11:34:16	ga_s2am_ard_3-2-1_51KXP_2022-07-24_final.stac-item
2022-08-05 10:36:43	ga_s2am_ard_3-2-1_53HPC_2022-08-05_final.stac-item
2022-08-24 11:05:00	ga_s2am_ard_3-2-1_52JER_2022-08-24_final.stac-item
2022-09-16 11:11:14	ga_s2am_ard_3-2-1_52LFL_2022-09-16_final.stac-item
2022-10-14 10:36:01	ga_s2am_ard_3-2-1_53HQE_2022-10-14_final.stac-item
2022-10-21 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2022-10-21_final.stac-item
2022-12-28 11:24:10	ga_s2am_ard_3-2-1_51KXP_2022-12-28_final.stac-item
2023-01-21 11:02:54	ga_s2am_ard_3-2-1_52KGC_2023-01-21_final.stac-item
2023-03-12 11:00:44	ga_s2am_ard_3-2-1_52LGM_2023-03-12_final
2023-04-24 11:13:44	ga_s2am_ard_3-2-1_52KEV_2023-04-24_final
2023-04-27 11:24:08	ga_s2am_ard_3-2-1_51KYP_2023-04-27_final
2023-07-05 11:55:51	ga_s2am_ard_3-2-1_50JKP_2023-07-05_final
2023-07-30 11:05:39	ga_s2am_ard_3-2-1_52JDN_2023-07-30_final
2023-08-01 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2023-08-01_final
2023-08-07 12:03:49	ga_s2am_ard_3-2-1_50KKB_2023-08-07_final
2023-09-11 11:15:05	ga_s2am_ard_3-2-1_52JDQ_2023-09-11_final
2023-10-03 11:53:32	ga_s2am_ard_3-2-1_50KMC_2023-10-03_final
2023-10-04 11:23:59	ga_s2am_ard_3-2-1_51KXQ_2023-10-04_final
2023-10-21 11:10:37	ga_s2am_ard_3-2-1_52LHM_2023-10-21_final
2023-10-24 11:23:25	ga_s2am_ard_3-2-1_51KYS_2023-10-24_final
2023-11-20 11:13:16	ga_s2am_ard_3-2-1_52KDB_2023-11-20_final
2023-11-27 11:03:13	ga_s2am_ard_3-2-1_52KEB_2023-11-27_final
2023-12-09 11:43:06	ga_s2am_ard_3-2-1_51KUT_2023-12-09_final
2024-01-08 11:46:33	ga_s2am_ard_3-2-1_50HNK_2024-01-08_final
2024-01-15 11:33:41	ga_s2am_ard_3-2-1_51KUR_2024-01-15_final
2024-02-13 12:03:56	ga_s2am_ard_3-2-1_49KHR_2024-02-13_final
2024-02-20 11:52:18	ga_s2am_ard_3-2-1_50KQG_2024-02-20_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

All years