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
2015-12-03 10:41:05	ga_s2am_ard_3-2-1_53JMN_2015-12-03_final.stac-item
2016-04-06 11:33:21	ga_s2am_ard_3-2-1_51HTC_2016-04-06_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49JGM_2016-04-15_final.stac-item
2016-12-04 10:33:20	ga_s2am_ard_3-2-1_53HPA_2016-12-04_final.stac-item
2016-12-06 11:13:53	ga_s2am_ard_3-2-1_52JBP_2016-12-06_final.stac-item
2017-02-04 11:08:11	ga_s2am_ard_3-2-1_52KFF_2017-02-04_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49KGP_2017-07-09_final.stac-item
2017-07-17 11:20:58	ga_s2am_ard_3-2-1_51HVC_2017-07-17_final.stac-item
2017-07-23 11:45:09	ga_s2am_ard_3-2-1_50HPK_2017-07-23_final.stac-item
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_51LZD_2017-11-27_final.stac-item
2017-12-25 10:53:09	ga_s2am_ard_3-2-1_53JKK_2017-12-25_final.stac-item
2018-02-13 10:52:02	ga_s2am_ard_3-2-1_53JLL_2018-02-13_final.stac-item
2018-05-13 11:20:24	ga_s2am_ard_3-2-1_52KBF_2018-05-13_final.stac-item
2018-06-07 10:27:08	ga_s2am_ard_3-2-1_53JQK_2018-06-07_final.stac-item
2018-07-17 10:27:09	ga_s2am_ard_3-2-1_53HND_2018-07-17_final.stac-item
2018-08-23 10:17:05	ga_s2am_ard_3-2-1_53HQA_2018-08-23_final.stac-item
2018-10-27 11:07:09	ga_s2am_ard_3-2-1_52LDJ_2018-10-27_final.stac-item
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_51LUF_2018-11-05_final.stac-item
2019-01-08 11:23:01	ga_s2am_ard_3-2-1_52KBC_2019-01-08_final.stac-item
2019-01-23 10:34:22	ga_s2am_ard_3-2-1_53JNM_2019-01-23_final.stac-item
2019-01-31 11:31:36	ga_s2am_ard_3-2-1_51LYD_2019-01-31_final.stac-item
2019-03-01 12:05:36	ga_s2am_ard_3-2-1_50JKP_2019-03-01_final.stac-item
2019-03-24 12:15:09	ga_s2am_ard_3-2-1_49JGL_2019-03-24_final.stac-item
2019-04-01 11:33:24	ga_s2am_ard_3-2-1_51KXS_2019-04-01_final.stac-item
2019-04-03 10:35:56	ga_s2am_ard_3-2-1_53JMF_2019-04-03_final.stac-item
2019-05-15 11:11:05	ga_s2am_ard_3-2-1_52LFL_2019-05-15_final.stac-item
2019-05-18 11:22:30	ga_s2am_ard_3-2-1_51KYA_2019-05-18_final.stac-item
2019-06-10 11:33:33	ga_s2am_ard_3-2-1_51KVS_2019-06-10_final.stac-item
2019-06-19 10:25:09	ga_s2am_ard_3-2-1_53JQJ_2019-06-19_final.stac-item
2019-06-28 10:56:01	ga_s2am_ard_3-2-1_52JGL_2019-06-28_final.stac-item
2019-07-03 11:46:06	ga_s2am_ard_3-2-1_50JNM_2019-07-03_final.stac-item
2019-08-26 11:23:15	ga_s2am_ard_3-2-1_51KXT_2019-08-26_final.stac-item
2019-10-15 11:23:24	ga_s2am_ard_3-2-1_51KZS_2019-10-15_final.stac-item
2019-10-21 11:46:51	ga_s2am_ard_3-2-1_50HPJ_2019-10-21_final.stac-item
2019-12-20 11:43:37	ga_s2am_ard_3-2-1_51KUR_2019-12-20_final.stac-item
2020-01-07 11:00:25	ga_s2am_ard_3-2-1_52LHN_2020-01-07_final.stac-item
2020-01-13 11:22:50	ga_s2am_ard_3-2-1_51KYU_2020-01-13_final.stac-item
2020-02-03 10:54:04	ga_s2am_ard_3-2-1_52JHT_2020-02-03_final.stac-item
2020-02-28 11:46:29	ga_s2am_ard_3-2-1_50HPK_2020-02-28_final.stac-item
2020-03-04 10:55:23	ga_s2am_ard_3-2-1_52JGN_2020-03-04_final.stac-item
2020-05-22 11:23:34	ga_s2am_ard_3-2-1_51KXS_2020-05-22_final.stac-item
2020-06-03 12:03:50	ga_s2am_ard_3-2-1_50KKB_2020-06-03_final.stac-item
2020-06-21 11:23:49	ga_s2am_ard_3-2-1_51KXR_2020-06-21_final.stac-item
2020-08-01 10:55:22	ga_s2am_ard_3-2-1_52JFP_2020-08-01_final.stac-item
2020-08-03 11:34:16	ga_s2am_ard_3-2-1_51KWP_2020-08-03_final.stac-item
2020-09-01 12:06:00	ga_s2am_ard_3-2-1_50JKN_2020-09-01_final.stac-item
2020-10-15 11:42:42	ga_s2am_ard_3-2-1_51KVA_2020-10-15_final.stac-item
2020-11-09 10:55:46	ga_s2am_ard_3-2-1_52JGM_2020-11-09_final.stac-item
2020-11-15 11:12:21	ga_s2am_ard_3-2-1_52KEF_2020-11-15_final.stac-item
2020-11-20 12:05:54	ga_s2am_ard_3-2-1_50JLN_2020-11-20_final.stac-item
2021-01-01 11:06:24	ga_s2am_ard_3-2-1_52HBK_2021-01-01_final.stac-item
2021-01-10 11:33:31	ga_s2am_ard_3-2-1_51KVS_2021-01-10_final.stac-item
2021-01-14 11:11:13	ga_s2am_ard_3-2-1_52LGK_2021-01-14_final.stac-item
2021-01-16 11:53:51	ga_s2am_ard_3-2-1_50KPA_2021-01-16_final.stac-item
2021-01-19 12:04:29	ga_s2am_ard_3-2-1_50KKU_2021-01-19_final.stac-item
2021-02-06 11:24:26	ga_s2am_ard_3-2-1_51JXN_2021-02-06_final.stac-item
2021-02-08 10:27:04	ga_s2am_ard_3-2-1_53HPA_2021-02-08_final.stac-item
2021-02-18 12:03:22	ga_s2am_ard_3-2-1_50KMC_2021-02-18_final.stac-item
2021-02-22 11:43:17	ga_s2am_ard_3-2-1_51KTT_2021-02-22_final.stac-item
2021-04-08 10:55:59	ga_s2am_ard_3-2-1_52JEL_2021-04-08_final.stac-item
2021-05-06 11:56:06	ga_s2am_ard_3-2-1_50JMM_2021-05-06_final.stac-item
2021-05-20 11:34:11	ga_s2am_ard_3-2-1_51KWP_2021-05-20_final.stac-item
2021-06-22 11:41:34	ga_s2am_ard_3-2-1_51LUE_2021-06-22_final.stac-item
2021-11-05 10:25:09	ga_s2am_ard_3-2-1_53JQJ_2021-11-05_final.stac-item
2021-11-19 11:47:10	ga_s2am_ard_3-2-1_50HMH_2021-11-19_final.stac-item
2022-01-05 11:33:32	ga_s2am_ard_3-2-1_51KVS_2022-01-05_final.stac-item
2022-02-08 11:10:32	ga_s2am_ard_3-2-1_52LFN_2022-02-08_final
2022-02-13 12:03:52	ga_s2am_ard_3-2-1_50KMA_2022-02-13_final.stac-item
2022-02-21 11:22:06	ga_s2am_ard_3-2-1_52KCG_2022-02-21_final.stac-item
2022-03-20 11:13:58	ga_s2am_ard_3-2-1_52KBV_2022-03-20_final.stac-item
2022-03-29 11:43:06	ga_s2am_ard_3-2-1_50KRD_2022-03-29_final.stac-item
2022-06-13 10:26:50	ga_s2am_ard_3-2-1_53HNC_2022-06-13_final.stac-item
2022-07-21 11:26:49	ga_s2am_ard_3-2-1_51HWD_2022-07-21_final.stac-item
2022-09-04 12:14:06	ga_s2am_ard_3-2-1_50KKA_2022-09-04_final.stac-item
2022-09-12 11:34:10	ga_s2am_ard_3-2-1_51KVQ_2022-09-12_final.stac-item
2022-09-16 11:10:52	ga_s2am_ard_3-2-1_52LGM_2022-09-16_final.stac-item
2022-10-02 11:33:09	ga_s2am_ard_3-2-1_51KYT_2022-10-02_final.stac-item
2022-10-02 11:36:24	ga_s2am_ard_3-2-1_51JTF_2022-10-02_final.stac-item
2022-10-12 11:33:43	ga_s2am_ard_3-2-1_51KXR_2022-10-12_final.stac-item
2022-11-11 11:37:01	ga_s2am_ard_3-2-1_51HUC_2022-11-11_final.stac-item
2022-11-30 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-11-30_final.stac-item
2023-01-14 11:12:18	ga_s2am_ard_3-2-1_52KDF_2023-01-14_final.stac-item
2023-04-27 11:26:05	ga_s2am_ard_3-2-1_51JUG_2023-04-27_final
2023-05-23 11:43:32	ga_s2am_ard_3-2-1_51KUS_2023-05-23_final
2023-07-09 11:34:16	ga_s2am_ard_3-2-1_51KWP_2023-07-09_final
2023-07-18 10:26:45	ga_s2am_ard_3-2-1_53HNC_2023-07-18_final
2023-07-30 11:04:48	ga_s2am_ard_3-2-1_52JFR_2023-07-30_final
2023-08-22 11:11:08	ga_s2am_ard_3-2-1_52LFL_2023-08-22_final
2023-08-24 11:53:16	ga_s2am_ard_3-2-1_50KRC_2023-08-24_final
2023-08-27 12:04:48	ga_s2am_ard_3-2-1_49JHN_2023-08-27_final
2023-08-28 11:32:20	ga_s2am_ard_3-2-1_51KWB_2023-08-28_final
2023-09-08 11:04:48	ga_s2am_ard_3-2-1_52JFR_2023-09-08_final
2023-11-16 11:36:32	ga_s2am_ard_3-2-1_50HQK_2023-11-16_final
2023-11-21 10:44:17	ga_s2am_ard_3-2-1_53JNM_2023-11-21_final
2023-12-31 10:45:49	ga_s2am_ard_3-2-1_53JKG_2023-12-31_final
2024-01-28 11:42:59	ga_s2am_ard_3-2-1_50KRD_2024-01-28_final
2024-02-14 11:31:15	ga_s2am_ard_3-2-1_52LBK_2024-02-14_final
2024-02-16 12:15:08	ga_s2am_ard_3-2-1_49JGL_2024-02-16_final
2024-03-16 11:01:17	ga_s2am_ard_3-2-1_52LGK_2024-03-16_final
2024-03-21 11:56:45	ga_s2am_ard_3-2-1_50HLK_2024-03-21_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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