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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_50JLN_2015-10-28_final.stac-item
2016-04-06 11:25:50	ga_s2am_ard_3-2-1_51KVV_2016-04-06_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_51JWL_2016-06-05_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50KRC_2016-06-11_final.stac-item
2016-08-04 11:32:03	ga_s2am_ard_3-2-1_51JTH_2016-08-04_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50JML_2016-09-09_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50HMJ_2016-10-29_final.stac-item
2016-11-16 11:11:49	ga_s2am_ard_3-2-1_51HWE_2016-11-16_final.stac-item
2017-01-08 11:18:08	ga_s2am_ard_3-2-1_51KYP_2017-01-08_final.stac-item
2017-01-18 11:19:51	ga_s2am_ard_3-2-1_51JVG_2017-01-18_final.stac-item
2017-01-31 11:26:14	ga_s2am_ard_3-2-1_51KXT_2017-01-31_final.stac-item
2017-02-09 12:02:43	ga_s2am_ard_3-2-1_49JGK_2017-02-09_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JKM_2017-06-26_final.stac-item
2017-08-09 11:36:05	ga_s2am_ard_3-2-1_50JQM_2017-08-09_final.stac-item
2017-12-24 11:22:03	ga_s2am_ard_3-2-1_51JXK_2017-12-24_final.stac-item
2018-01-13 11:19:15	ga_s2am_ard_3-2-1_51JVK_2018-01-13_final.stac-item
2018-01-13 11:19:15	ga_s2am_ard_3-2-1_51JYM_2018-01-13_final.stac-item
2018-04-03 11:23:03	ga_s2am_ard_3-2-1_51JVK_2018-04-03_final.stac-item
2018-04-10 11:16:00	ga_s2am_ard_3-2-1_51HWD_2018-04-10_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JNN_2018-06-18_final.stac-item
2018-08-07 11:46:07	ga_s2am_ard_3-2-1_50JNM_2018-08-07_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50JLM_2018-09-12_final.stac-item
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KXR_2018-10-10_final.stac-item
2018-12-21 12:03:15	ga_s2am_ard_3-2-1_50KMC_2018-12-21_final.stac-item
2019-01-01 11:33:59	ga_s2am_ard_3-2-1_51KXP_2019-01-01_final.stac-item
2019-01-24 11:43:15	ga_s2am_ard_3-2-1_51KTT_2019-01-24_final.stac-item
2019-04-13 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-04-13_final.stac-item
2019-06-06 11:57:11	ga_s2am_ard_3-2-1_50HLH_2019-06-06_final.stac-item
2019-06-26 11:55:57	ga_s2am_ard_3-2-1_50JMN_2019-06-26_final.stac-item
2019-06-26 11:56:34	ga_s2am_ard_3-2-1_50HNK_2019-06-26_final.stac-item
2019-07-13 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2019-07-13_final.stac-item
2019-07-13 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2019-07-13_final.stac-item
2020-01-02 11:53:05	ga_s2am_ard_3-2-1_50KRC_2020-01-02_final.stac-item
2020-01-09 11:43:56	ga_s2am_ard_3-2-1_51KTQ_2020-01-09_final.stac-item
2020-02-09 11:15:31	ga_s2am_ard_3-2-1_51JYH_2020-02-09_final.stac-item
2020-03-20 11:16:08	ga_s2am_ard_3-2-1_51JXF_2020-03-20_final.stac-item
2020-05-24 12:04:19	ga_s2am_ard_3-2-1_49KHQ_2020-05-24_final.stac-item
2020-05-25 11:34:31	ga_s2am_ard_3-2-1_51JWN_2020-05-25_final.stac-item
2020-06-10 11:56:06	ga_s2am_ard_3-2-1_50JKN_2020-06-10_final.stac-item
2020-06-26 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-06-26_final.stac-item
2020-06-30 11:57:14	ga_s2am_ard_3-2-1_50HLH_2020-06-30_final.stac-item
2020-08-03 11:36:40	ga_s2am_ard_3-2-1_50HQK_2020-08-03_final.stac-item
2020-08-06 11:45:27	ga_s2am_ard_3-2-1_50JPQ_2020-08-06_final.stac-item
2020-08-07 11:15:02	ga_s2am_ard_3-2-1_51JYL_2020-08-07_final.stac-item
2020-09-04 12:15:04	ga_s2am_ard_3-2-1_49JFM_2020-09-04_final.stac-item
2020-09-09 11:24:19	ga_s2am_ard_3-2-1_51KWP_2020-09-09_final.stac-item
2020-09-25 11:47:07	ga_s2am_ard_3-2-1_50HPH_2020-09-25_final.stac-item
2020-10-02 11:36:58	ga_s2am_ard_3-2-1_50HPJ_2020-10-02_final.stac-item
2020-10-22 11:36:34	ga_s2am_ard_3-2-1_51HUE_2020-10-22_final.stac-item
2020-11-18 11:25:12	ga_s2am_ard_3-2-1_51JXK_2020-11-18_final.stac-item
2020-11-18 11:25:37	ga_s2am_ard_3-2-1_51JYH_2020-11-18_final.stac-item
2020-12-11 11:34:57	ga_s2am_ard_3-2-1_51JUL_2020-12-11_final.stac-item
2020-12-28 11:24:01	ga_s2am_ard_3-2-1_51KWQ_2020-12-28_final.stac-item
2021-01-19 12:05:01	ga_s2am_ard_3-2-1_49JGM_2021-01-19_final.stac-item
2021-01-30 11:34:43	ga_s2am_ard_3-2-1_51JVM_2021-01-30_final.stac-item
2021-02-06 11:26:17	ga_s2am_ard_3-2-1_51JUF_2021-02-06_final.stac-item
2021-03-01 11:33:22	ga_s2am_ard_3-2-1_51KUT_2021-03-01_final.stac-item
2021-03-01 11:37:03	ga_s2am_ard_3-2-1_50HQH_2021-03-01_final.stac-item
2021-03-14 11:43:00	ga_s2am_ard_3-2-1_51KUU_2021-03-14_final.stac-item
2021-04-03 11:46:30	ga_s2am_ard_3-2-1_50HPK_2021-04-03_final.stac-item
2021-04-14 11:15:04	ga_s2am_ard_3-2-1_51JYK_2021-04-14_final.stac-item
2021-06-02 11:44:35	ga_s2am_ard_3-2-1_50JQT_2021-06-02_final.stac-item
2021-09-27 11:37:05	ga_s2am_ard_3-2-1_51HTC_2021-09-27_final.stac-item
2021-11-23 11:26:29	ga_s2am_ard_3-2-1_51HVE_2021-11-23_final.stac-item
2021-12-26 11:32:52	ga_s2am_ard_3-2-1_51KYU_2021-12-26_final.stac-item
2022-02-01 11:23:28	ga_s2am_ard_3-2-1_51KXS_2022-02-01_final.stac-item
2022-02-24 11:36:13	ga_s2am_ard_3-2-1_51JVF_2022-02-24_final.stac-item
2022-06-01 11:23:04	ga_s2am_ard_3-2-1_51KYU_2022-06-01_final.stac-item
2022-06-11 11:25:34	ga_s2am_ard_3-2-1_51JXJ_2022-06-11_final.stac-item
2022-07-08 11:16:54	ga_s2am_ard_3-2-1_51HXD_2022-07-08_final.stac-item
2022-07-30 11:55:12	ga_s2am_ard_3-2-1_50JPR_2022-07-30_final.stac-item
2022-08-03 11:36:16	ga_s2am_ard_3-2-1_50JQM_2022-08-03_final.stac-item
2022-08-26 11:43:34	ga_s2am_ard_3-2-1_50KQC_2022-08-26_final
2022-08-29 13:31:47	ga_s2am_ard_3-2-1_46LHN_2022-08-29_interim
2022-09-08 11:55:21	ga_s2am_ard_3-2-1_50JMR_2022-09-08_final.stac-item
2022-09-15 13:21:54	ga_s2am_ard_3-2-1_47LKG_2022-09-15_interim
2022-10-25 11:46:36	ga_s2am_ard_3-2-1_50HPK_2022-10-25_final.stac-item
2022-11-25 11:16:36	ga_s2am_ard_3-2-1_51HYD_2022-11-25_final.stac-item
2022-12-21 11:32:27	ga_s2am_ard_3-2-1_51KWA_2022-12-21_final.stac-item
2023-01-27 11:24:56	ga_s2am_ard_3-2-1_51JWL_2023-01-27_final.stac-item
2023-02-08 12:04:41	ga_s2am_ard_3-2-1_50JKT_2023-02-08_final
2023-03-30 12:04:55	ga_s2am_ard_3-2-1_50JKS_2023-03-30_final
2023-05-06 11:55:56	ga_s2am_ard_3-2-1_50JLN_2023-05-06_final
2023-06-02 11:43:47	ga_s2am_ard_3-2-1_51KUR_2023-06-02_final
2023-06-09 11:36:27	ga_s2am_ard_3-2-1_51HVE_2023-06-09_final
2023-06-19 11:33:05	ga_s2am_ard_3-2-1_51KVU_2023-06-19_final
2023-07-25 11:56:45	ga_s2am_ard_3-2-1_50HLK_2023-07-25_final
2023-08-11 11:46:30	ga_s2am_ard_3-2-1_50JML_2023-08-11_final
2023-08-12 11:16:27	ga_s2am_ard_3-2-1_51HYE_2023-08-12_final
2023-08-18 11:37:13	ga_s2am_ard_3-2-1_50HPH_2023-08-18_final
2023-10-21 11:16:37	ga_s2am_ard_3-2-1_51HYD_2023-10-21_final
2023-11-05 12:06:09	ga_s2am_ard_3-2-1_50JKM_2023-11-05_final
2023-12-10 11:16:35	ga_s2am_ard_3-2-1_51HXD_2023-12-10_final
2024-01-07 12:13:50	ga_s2am_ard_3-2-1_50KKA_2024-01-07_final
2024-01-15 11:34:04	ga_s2am_ard_3-2-1_51KWP_2024-01-15_final
2024-02-04 11:36:59	ga_s2am_ard_3-2-1_50HQH_2024-02-04_final
2024-02-24 11:32:30	ga_s2am_ard_3-2-1_51KVA_2024-02-24_final
2024-03-14 12:04:57	ga_s2am_ard_3-2-1_50JKS_2024-03-14_final
2024-04-07 11:42:40	ga_s2am_ard_3-2-1_51KVV_2024-04-07_final
2024-04-07 11:43:12	ga_s2am_ard_3-2-1_51KTT_2024-04-07_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