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
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_51JTJ_2016-02-19_final.stac-item
2016-09-01 10:48:19	ga_s2am_ard_3-2-1_52KHC_2016-09-01_final.stac-item
2017-02-24 11:10:31	ga_s2am_ard_3-2-1_52LHM_2017-02-24_final.stac-item
2017-04-12 11:00:40	ga_s2am_ard_3-2-1_52LHL_2017-04-12_final.stac-item
2017-04-12 11:00:40	ga_s2am_ard_3-2-1_52LHM_2017-04-12_final.stac-item
2017-07-29 10:26:39	ga_s2am_ard_3-2-1_53HNB_2017-07-29_final.stac-item
2017-08-08 12:04:43	ga_s2am_ard_3-2-1_50JLQ_2017-08-08_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50JPN_2017-12-10_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_51KVS_2017-12-30_final.stac-item
2018-02-27 10:32:29	ga_s2am_ard_3-2-1_53HPA_2018-02-27_final.stac-item
2018-04-20 11:10:14	ga_s2am_ard_3-2-1_52KCE_2018-04-20_final.stac-item
2018-05-23 11:17:08	ga_s2am_ard_3-2-1_52KCE_2018-05-23_final.stac-item
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_51JTH_2018-06-05_final.stac-item
2018-06-06 10:57:16	ga_s2am_ard_3-2-1_52JDL_2018-06-06_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50KRU_2018-06-08_final.stac-item
2018-06-12 11:22:26	ga_s2am_ard_3-2-1_51JVG_2018-06-12_final.stac-item
2018-08-02 10:47:25	ga_s2am_ard_3-2-1_52KGV_2018-08-02_final.stac-item
2018-08-07 11:40:42	ga_s2am_ard_3-2-1_50JPN_2018-08-07_final.stac-item
2018-08-28 11:10:58	ga_s2am_ard_3-2-1_52LFL_2018-08-28_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50KKB_2018-09-12_final.stac-item
2018-12-03 11:04:35	ga_s2am_ard_3-2-1_52JFR_2018-12-03_final.stac-item
2019-02-05 10:45:55	ga_s2am_ard_3-2-1_53JKF_2019-02-05_final.stac-item
2019-03-02 11:32:06	ga_s2am_ard_3-2-1_51KXB_2019-03-02_final.stac-item
2019-03-02 11:32:50	ga_s2am_ard_3-2-1_51KXU_2019-03-02_final.stac-item
2019-04-05 11:10:26	ga_s2am_ard_3-2-1_52LHN_2019-04-05_final.stac-item
2019-04-10 12:03:43	ga_s2am_ard_3-2-1_50KLB_2019-04-10_final.stac-item
2019-06-17 11:23:39	ga_s2am_ard_3-2-1_51KXR_2019-06-17_final.stac-item
2019-06-27 11:25:50	ga_s2am_ard_3-2-1_51JVH_2019-06-27_final.stac-item
2019-08-03 11:16:41	ga_s2am_ard_3-2-1_51HYD_2019-08-03_final.stac-item
2019-12-14 11:25:12	ga_s2am_ard_3-2-1_51JVK_2019-12-14_final.stac-item
2020-01-04 10:55:53	ga_s2am_ard_3-2-1_52JGL_2020-01-04_final.stac-item
2020-02-02 11:22:44	ga_s2am_ard_3-2-1_52KBD_2020-02-02_final.stac-item
2020-03-03 11:23:17	ga_s2am_ard_3-2-1_51KZS_2020-03-03_final.stac-item
2020-03-04 10:53:38	ga_s2am_ard_3-2-1_52KHV_2020-03-04_final.stac-item
2020-03-07 11:00:41	ga_s2am_ard_3-2-1_52LHM_2020-03-07_final.stac-item
2020-03-23 11:25:49	ga_s2am_ard_3-2-1_51JXG_2020-03-23_final.stac-item
2020-03-29 11:42:09	ga_s2am_ard_3-2-1_51KVB_2020-03-29_final.stac-item
2020-04-15 11:33:15	ga_s2am_ard_3-2-1_51KVT_2020-04-15_final.stac-item
2020-04-23 10:55:14	ga_s2am_ard_3-2-1_52JGP_2020-04-23_final.stac-item
2020-05-22 11:21:31	ga_s2am_ard_3-2-1_51LZE_2020-05-22_final.stac-item
2020-06-18 11:16:36	ga_s2am_ard_3-2-1_51HWE_2020-06-18_final.stac-item
2020-06-27 11:46:46	ga_s2am_ard_3-2-1_50HMK_2020-06-27_final.stac-item
2020-07-17 11:46:38	ga_s2am_ard_3-2-1_50HPK_2020-07-17_final.stac-item
2020-09-06 11:16:41	ga_s2am_ard_3-2-1_51HYD_2020-09-06_final.stac-item
2020-11-23 10:37:00	ga_s2am_ard_3-2-1_53HPA_2020-11-23_final.stac-item
2021-02-23 11:12:10	ga_s2am_ard_3-2-1_52KCG_2021-02-23_final.stac-item
2021-03-11 11:32:19	ga_s2am_ard_3-2-1_51KVB_2021-03-11_final.stac-item
2021-04-21 11:02:54	ga_s2am_ard_3-2-1_52KGC_2021-04-21_final.stac-item
2021-04-30 11:35:48	ga_s2am_ard_3-2-1_50JQN_2021-04-30_final.stac-item
2021-06-09 11:34:18	ga_s2am_ard_3-2-1_51KUP_2021-06-09_final.stac-item
2021-07-12 11:46:16	ga_s2am_ard_3-2-1_50JMM_2021-07-12_final.stac-item
2021-10-16 10:27:10	ga_s2am_ard_3-2-1_53HPA_2021-10-16_final.stac-item
2021-11-06 11:31:46	ga_s2am_ard_3-2-1_51LXD_2021-11-06_final.stac-item
2021-11-16 11:35:20	ga_s2am_ard_3-2-1_51JWJ_2021-11-16_final.stac-item
2021-11-24 10:55:05	ga_s2am_ard_3-2-1_53JLJ_2021-11-24_final.stac-item
2021-12-06 11:31:17	ga_s2am_ard_3-2-1_52LBK_2021-12-06_final.stac-item
2021-12-20 11:11:38	ga_s2am_ard_3-2-1_52LDJ_2021-12-20_final.stac-item
2021-12-23 11:21:56	ga_s2am_ard_3-2-1_51LZC_2021-12-23_final.stac-item
2022-01-05 11:32:02	ga_s2am_ard_3-2-1_51LWC_2022-01-05_final.stac-item
2022-01-25 11:32:44	ga_s2am_ard_3-2-1_51KWV_2022-01-25_final.stac-item
2022-02-02 10:54:47	ga_s2am_ard_3-2-1_52JFR_2022-02-02_final.stac-item
2022-02-03 10:26:40	ga_s2am_ard_3-2-1_53HNC_2022-02-03_final.stac-item
2022-02-11 11:21:38	ga_s2am_ard_3-2-1_52LBJ_2022-02-11_final.stac-item
2022-02-17 11:43:19	ga_s2am_ard_3-2-1_51KTT_2022-02-17_final.stac-item
2022-03-03 11:23:24	ga_s2am_ard_3-2-1_51KYS_2022-03-03_final.stac-item
2022-03-31 10:46:26	ga_s2am_ard_3-2-1_53HLD_2022-03-31_final.stac-item
2022-05-05 11:33:07	ga_s2am_ard_3-2-1_51KYT_2022-05-05_final.stac-item
2022-05-18 11:44:46	ga_s2am_ard_3-2-1_51JUM_2022-05-18_final.stac-item
2022-07-07 11:46:54	ga_s2am_ard_3-2-1_50HMK_2022-07-07_final.stac-item
2022-07-13 12:06:08	ga_s2am_ard_3-2-1_50JKN_2022-07-13_final.stac-item
2022-08-10 11:26:52	ga_s2am_ard_3-2-1_51HWD_2022-08-10_final.stac-item
2022-09-09 11:25:06	ga_s2am_ard_3-2-1_51JXL_2022-09-09_final.stac-item
2022-10-13 11:04:19	ga_s2am_ard_3-2-1_52JFT_2022-10-13_final.stac-item
2022-10-13 11:04:34	ga_s2am_ard_3-2-1_52JFS_2022-10-13_final.stac-item
2022-10-29 11:24:22	ga_s2am_ard_3-2-1_52JBT_2022-10-29_final.stac-item
2022-11-21 11:33:57	ga_s2am_ard_3-2-1_51KWQ_2022-11-21_final.stac-item
2022-12-31 11:31:17	ga_s2am_ard_3-2-1_52LBK_2022-12-31_final.stac-item
2023-01-07 11:26:31	ga_s2am_ard_3-2-1_51HUE_2023-01-07_final.stac-item
2023-01-17 11:21:05	ga_s2am_ard_3-2-1_51LZF_2023-01-17_nrt.stac-item
2023-01-27 11:24:09	ga_s2am_ard_3-2-1_51KXP_2023-01-27_final.stac-item
2023-02-02 11:43:20	ga_s2am_ard_3-2-1_50KQC_2023-02-02_final
2023-02-26 11:21:36	ga_s2am_ard_3-2-1_52LBJ_2023-02-26_final
2023-03-03 10:36:47	ga_s2am_ard_3-2-1_53HNB_2023-03-03_final
2023-03-26 10:44:46	ga_s2am_ard_3-2-1_53JKL_2023-03-26_final
2023-04-04 11:14:23	ga_s2am_ard_3-2-1_52JBT_2023-04-04_final
2023-04-14 11:13:28	ga_s2am_ard_3-2-1_51KZS_2023-04-14_final
2023-06-03 11:16:26	ga_s2am_ard_3-2-1_51HYE_2023-06-03_final
2023-06-19 11:33:27	ga_s2am_ard_3-2-1_51KXS_2023-06-19_final
2023-07-12 11:47:15	ga_s2am_ard_3-2-1_50HMH_2023-07-12_final
2023-11-26 11:36:41	ga_s2am_ard_3-2-1_51HTD_2023-11-26_final
2023-12-10 11:11:45	ga_s2am_ard_3-2-1_52KGG_2023-12-10_final
2023-12-18 10:36:03	ga_s2am_ard_3-2-1_53HNE_2023-12-18_final
2024-01-08 11:43:11	ga_s2am_ard_3-2-1_50KQC_2024-01-08_final
2024-01-09 11:10:39	ga_s2am_ard_3-2-1_52LGM_2024-01-09_final
2024-01-22 11:23:03	ga_s2am_ard_3-2-1_51KYT_2024-01-22_final
2024-01-22 11:23:13	ga_s2am_ard_3-2-1_52KBB_2024-01-22_final
2024-02-23 10:26:34	ga_s2am_ard_3-2-1_53HPC_2024-02-23_final
2024-02-24 11:31:48	ga_s2am_ard_3-2-1_51LYC_2024-02-24_final
2024-03-08 11:44:17	ga_s2am_ard_3-2-1_50KRU_2024-03-08_final
2024-03-25 11:31:22	ga_s2am_ard_3-2-1_51LZE_2024-03-25_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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