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
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_52LDJ_2015-12-25_final.stac-item
2016-04-14 10:51:39	ga_s2am_ard_3-2-1_52JFL_2016-04-14_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_51JYG_2016-05-10_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49JGL_2016-05-18_final.stac-item
2016-06-15 11:36:06	ga_s2am_ard_3-2-1_51JTG_2016-06-15_final.stac-item
2016-06-25 11:32:00	ga_s2am_ard_3-2-1_51KUS_2016-06-25_final
2016-08-28 11:12:16	ga_s2am_ard_3-2-1_51KZP_2016-08-28_final.stac-item
2016-09-14 10:57:41	ga_s2am_ard_3-2-1_52KGU_2016-09-14_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50HMJ_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JML_2016-10-09_final.stac-item
2016-11-02 11:26:18	ga_s2am_ard_3-2-1_51KXA_2016-11-02_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_51KYA_2016-11-22_final.stac-item
2016-12-03 11:00:41	ga_s2am_ard_3-2-1_52KEA_2016-12-03_final.stac-item
2017-01-14 11:34:53	ga_s2am_ard_3-2-1_51LWC_2017-01-14_final.stac-item
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_52LDJ_2017-01-25_final.stac-item
2017-02-04 11:08:11	ga_s2am_ard_3-2-1_52LGL_2017-02-04_final.stac-item
2017-02-09 12:02:43	ga_s2am_ard_3-2-1_50KLV_2017-02-09_final.stac-item
2017-02-17 11:23:12	ga_s2am_ard_3-2-1_51HUC_2017-02-17_final.stac-item
2017-03-06 11:07:05	ga_s2am_ard_3-2-1_52LGJ_2017-03-06_final.stac-item
2017-08-03 11:12:16	ga_s2am_ard_3-2-1_52KBC_2017-08-03_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49JGJ_2017-08-18_final.stac-item
2017-11-08 10:57:14	ga_s2am_ard_3-2-1_52KFD_2017-11-08_final.stac-item
2017-12-11 11:11:56	ga_s2am_ard_3-2-1_51JYM_2017-12-11_final.stac-item
2017-12-11 11:11:56	ga_s2am_ard_3-2-1_51KZQ_2017-12-11_final.stac-item
2018-01-10 11:12:06	ga_s2am_ard_3-2-1_52KEF_2018-01-10_final.stac-item
2018-02-19 11:07:09	ga_s2am_ard_3-2-1_51JYM_2018-02-19_final.stac-item
2018-02-19 11:07:09	ga_s2am_ard_3-2-1_52JBR_2018-02-19_final.stac-item
2018-03-07 11:30:40	ga_s2am_ard_3-2-1_51HVE_2018-03-07_final.stac-item
2018-05-10 11:07:15	ga_s2am_ard_3-2-1_52KFC_2018-05-10_final.stac-item
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_51JUH_2018-06-05_final.stac-item
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KWQ_2018-10-10_final.stac-item
2018-11-06 11:16:36	ga_s2am_ard_3-2-1_51HXD_2018-11-06_final.stac-item
2019-01-31 11:31:32	ga_s2am_ard_3-2-1_51LZD_2019-01-31_final.stac-item
2019-03-22 11:33:20	ga_s2am_ard_3-2-1_51KUT_2019-03-22_final.stac-item
2019-05-02 11:00:52	ga_s2am_ard_3-2-1_52LGM_2019-05-02_final.stac-item
2019-06-26 11:56:34	ga_s2am_ard_3-2-1_50HNK_2019-06-26_final.stac-item
2019-08-08 12:03:31	ga_s2am_ard_3-2-1_50KLC_2019-08-08_final.stac-item
2019-11-01 11:14:49	ga_s2am_ard_3-2-1_52JDR_2019-11-01_final.stac-item
2020-01-03 11:24:24	ga_s2am_ard_3-2-1_51JWN_2020-01-03_final.stac-item
2020-01-23 11:26:11	ga_s2am_ard_3-2-1_51JUF_2020-01-23_final.stac-item
2020-01-25 12:06:03	ga_s2am_ard_3-2-1_50JKM_2020-01-25_final.stac-item
2020-03-05 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2020-03-05_final.stac-item
2020-03-13 11:26:18	ga_s2am_ard_3-2-1_51HXE_2020-03-13_final.stac-item
2020-05-27 10:36:42	ga_s2am_ard_3-2-1_53HNC_2020-05-27_final.stac-item
2020-06-22 10:55:19	ga_s2am_ard_3-2-1_52JGP_2020-06-22_final.stac-item
2020-07-25 11:05:25	ga_s2am_ard_3-2-1_52JDP_2020-07-25_final.stac-item
2020-11-21 11:32:31	ga_s2am_ard_3-2-1_51KWA_2020-11-21_final.stac-item
2020-12-25 11:12:49	ga_s2am_ard_3-2-1_52KDD_2020-12-25_final.stac-item
2021-02-03 11:13:25	ga_s2am_ard_3-2-1_52KBB_2021-02-03_final.stac-item
2021-02-04 10:46:09	ga_s2am_ard_3-2-1_53HLE_2021-02-04_final.stac-item
2021-03-15 11:13:40	ga_s2am_ard_3-2-1_51KZR_2021-03-15_final.stac-item
2021-04-03 11:43:11	ga_s2am_ard_3-2-1_51KUT_2021-04-03_final.stac-item
2021-04-24 11:10:33	ga_s2am_ard_3-2-1_52LHM_2021-04-24_final.stac-item
2021-04-30 11:35:34	ga_s2am_ard_3-2-1_50JQP_2021-04-30_final.stac-item
2021-07-08 12:05:58	ga_s2am_ard_3-2-1_50JKN_2021-07-08_final.stac-item
2021-07-17 10:55:45	ga_s2am_ard_3-2-1_52JGM_2021-07-17_final.stac-item
2021-08-11 11:42:01	ga_s2am_ard_3-2-1_51LVC_2021-08-11_final.stac-item
2021-08-28 11:33:29	ga_s2am_ard_3-2-1_51KWS_2021-08-28_final.stac-item
2022-01-20 10:46:06	ga_s2am_ard_3-2-1_53HME_2022-01-20_final.stac-item
2022-01-29 11:14:09	ga_s2am_ard_3-2-1_52KBU_2022-01-29_final.stac-item
2022-02-24 11:36:08	ga_s2am_ard_3-2-1_50JQM_2022-02-24_final.stac-item
2022-03-04 10:55:35	ga_s2am_ard_3-2-1_52JFN_2022-03-04_final.stac-item
2022-04-05 11:36:15	ga_s2am_ard_3-2-1_51JUF_2022-04-05_final.stac-item
2022-04-18 11:42:32	ga_s2am_ard_3-2-1_51KVA_2022-04-18_final.stac-item
2022-05-22 11:26:47	ga_s2am_ard_3-2-1_51HWD_2022-05-22_final.stac-item
2022-05-29 11:13:56	ga_s2am_ard_3-2-1_52KDV_2022-05-29_final.stac-item
2022-07-10 11:55:19	ga_s2am_ard_3-2-1_50JNR_2022-07-10_final.stac-item
2022-07-30 11:54:58	ga_s2am_ard_3-2-1_50JPS_2022-07-30_final.stac-item
2022-08-11 10:53:40	ga_s2am_ard_3-2-1_52KHA_2022-08-11_final.stac-item
2022-08-13 11:33:28	ga_s2am_ard_3-2-1_51KVT_2022-08-13_final.stac-item
2022-09-05 11:45:12	ga_s2am_ard_3-2-1_50JPR_2022-09-05_final.stac-item
2022-09-15 11:46:03	ga_s2am_ard_3-2-1_50JNN_2022-09-15_final.stac-item
2022-10-02 11:35:05	ga_s2am_ard_3-2-1_51JVL_2022-10-02_final.stac-item
2022-10-11 12:04:51	ga_s2am_ard_3-2-1_49JGN_2022-10-11_final.stac-item
2022-11-25 11:13:39	ga_s2am_ard_3-2-1_51KZR_2022-11-25_final.stac-item
2022-12-29 10:53:27	ga_s2am_ard_3-2-1_52KHA_2022-12-29_final.stac-item
2023-01-01 11:02:39	ga_s2am_ard_3-2-1_52KHD_2023-01-01_final.stac-item
2023-01-17 11:25:53	ga_s2am_ard_3-2-1_51JWG_2023-01-17_final.stac-item
2023-02-11 12:15:18	ga_s2am_ard_3-2-1_49JGK_2023-02-11_final
2023-03-02 11:01:40	ga_s2am_ard_3-2-1_52LHH_2023-03-02_final
2023-04-20 11:31:04	ga_s2am_ard_3-2-1_51LZF_2023-04-20_final
2023-07-22 11:42:17	ga_s2am_ard_3-2-1_51KVB_2023-07-22_final
2023-09-01 11:13:59	ga_s2am_ard_3-2-1_51KZQ_2023-09-01_final
2023-09-06 12:06:15	ga_s2am_ard_3-2-1_50JKM_2023-09-06_final
2023-09-28 11:04:49	ga_s2am_ard_3-2-1_52JER_2023-09-28_final
2023-12-10 11:15:34	ga_s2am_ard_3-2-1_51JYH_2023-12-10_final
2023-12-19 11:43:29	ga_s2am_ard_3-2-1_51KVS_2023-12-19_final
2024-01-03 10:55:28	ga_s2am_ard_3-2-1_52JFN_2024-01-03_final
2024-01-09 11:12:42	ga_s2am_ard_3-2-1_52KED_2024-01-09_final
2024-01-12 11:26:27	ga_s2am_ard_3-2-1_51HUE_2024-01-12_final
2024-01-13 10:54:17	ga_s2am_ard_3-2-1_52JGS_2024-01-13_final
2024-02-23 12:03:39	ga_s2am_ard_3-2-1_50KLB_2024-02-23_final
2024-02-23 12:03:54	ga_s2am_ard_3-2-1_50KLA_2024-02-23_final
2024-03-05 11:36:43	ga_s2am_ard_3-2-1_51HUD_2024-03-05_final
2024-04-07 11:42:26	ga_s2am_ard_3-2-1_51KVA_2024-04-07_final
2024-04-11 11:25:14	ga_s2am_ard_3-2-1_51JWK_2024-04-11_final
2024-04-11 11:25:28	ga_s2am_ard_3-2-1_51JWJ_2024-04-11_final
2024-04-21 11:23:09	ga_s2am_ard_3-2-1_52KBC_2024-04-21_final
2024-04-30 11:56:39	ga_s2am_ard_3-2-1_50HMK_2024-04-30_final
2024-05-08 11:16:37	ga_s2am_ard_3-2-1_52HBJ_2024-05-08_nrt

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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