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
2016-04-07 11:02:08	ga_s2am_ard_3-2-1_52KEB_2016-04-07_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HLG_2016-06-11_final
2016-06-13 10:55:17	ga_s2am_ard_3-2-1_52JGM_2016-06-13_final.stac-item
2016-06-17 12:14:44	ga_s2am_ard_3-2-1_49JGM_2016-06-17_final.stac-item
2016-08-24 11:31:54	ga_s2am_ard_3-2-1_51JWJ_2016-08-24_final.stac-item
2016-09-20 11:22:33	ga_s2am_ard_3-2-1_51HUD_2016-09-20_final.stac-item
2017-01-02 11:02:35	ga_s2am_ard_3-2-1_52JFT_2017-01-02_final.stac-item
2017-02-13 11:37:46	ga_s2am_ard_3-2-1_50KRC_2017-02-13_final.stac-item
2017-06-14 11:11:51	ga_s2am_ard_3-2-1_52JCP_2017-06-14_final.stac-item
2017-08-16 11:26:10	ga_s2am_ard_3-2-1_51JVF_2017-08-16_final.stac-item
2018-03-04 11:22:24	ga_s2am_ard_3-2-1_52JBT_2018-03-04_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_50KNA_2018-03-06_final.stac-item
2018-05-03 11:21:11	ga_s2am_ard_3-2-1_51KXQ_2018-05-03_final.stac-item
2018-05-20 11:11:46	ga_s2am_ard_3-2-1_52KDA_2018-05-20_final.stac-item
2018-07-09 11:07:14	ga_s2am_ard_3-2-1_52KDA_2018-07-09_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_51KVS_2018-07-18_final.stac-item
2018-10-16 11:40:28	ga_s2am_ard_3-2-1_51KVU_2018-10-16_final.stac-item
2018-10-23 11:26:17	ga_s2am_ard_3-2-1_51KWS_2018-10-23_final.stac-item
2018-10-27 11:07:09	ga_s2am_ard_3-2-1_52KCD_2018-10-27_final.stac-item
2018-11-15 11:43:08	ga_s2am_ard_3-2-1_50KRC_2018-11-15_final.stac-item
2018-12-06 11:13:32	ga_s2am_ard_3-2-1_51KZR_2018-12-06_final.stac-item
2019-01-08 11:22:43	ga_s2am_ard_3-2-1_52KCD_2019-01-08_final.stac-item
2019-01-08 11:23:45	ga_s2am_ard_3-2-1_52KBV_2019-01-08_final.stac-item
2019-01-28 11:23:03	ga_s2am_ard_3-2-1_51KZT_2019-01-28_final.stac-item
2019-01-31 11:36:14	ga_s2am_ard_3-2-1_51JTF_2019-01-31_final.stac-item
2019-03-18 11:55:53	ga_s2am_ard_3-2-1_50JLN_2019-03-18_final.stac-item
2019-04-04 11:43:59	ga_s2am_ard_3-2-1_51KUQ_2019-04-04_final.stac-item
2019-05-31 11:32:33	ga_s2am_ard_3-2-1_51KYV_2019-05-31_final.stac-item
2019-06-06 11:56:13	ga_s2am_ard_3-2-1_50JLM_2019-06-06_final.stac-item
2019-06-27 11:23:58	ga_s2am_ard_3-2-1_51KYQ_2019-06-27_final.stac-item
2019-07-10 11:34:45	ga_s2am_ard_3-2-1_51JWM_2019-07-10_final.stac-item
2019-09-18 11:31:53	ga_s2am_ard_3-2-1_51LYC_2019-09-18_final.stac-item
2019-10-28 11:32:50	ga_s2am_ard_3-2-1_51KVV_2019-10-28_final.stac-item
2019-11-24 11:23:07	ga_s2am_ard_3-2-1_52KBC_2019-11-24_final.stac-item
2019-12-07 11:33:10	ga_s2am_ard_3-2-1_51KWT_2019-12-07_final.stac-item
2019-12-08 11:05:56	ga_s2am_ard_3-2-1_52JEL_2019-12-08_final.stac-item
2019-12-21 11:13:02	ga_s2am_ard_3-2-1_52KCC_2019-12-21_final.stac-item
2020-01-03 11:23:59	ga_s2am_ard_3-2-1_52KBU_2020-01-03_final.stac-item
2020-04-02 11:25:53	ga_s2am_ard_3-2-1_51JWG_2020-04-02_final.stac-item
2020-04-19 11:13:17	ga_s2am_ard_3-2-1_52KCB_2020-04-19_final.stac-item
2020-04-24 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2020-04-24_final.stac-item
2020-05-09 11:13:09	ga_s2am_ard_3-2-1_52KDC_2020-05-09_final.stac-item
2020-06-27 11:44:22	ga_s2am_ard_3-2-1_50KRU_2020-06-27_final.stac-item
2020-07-13 12:03:49	ga_s2am_ard_3-2-1_50KKB_2020-07-13_final.stac-item
2020-07-23 12:03:29	ga_s2am_ard_3-2-1_50KMC_2020-07-23_final.stac-item
2020-08-17 11:15:06	ga_s2am_ard_3-2-1_52JDQ_2020-08-17_final.stac-item
2020-09-16 11:13:41	ga_s2am_ard_3-2-1_52KCA_2020-09-16_final.stac-item
2020-10-03 11:04:27	ga_s2am_ard_3-2-1_52JDT_2020-10-03_final.stac-item
2020-11-04 11:43:02	ga_s2am_ard_3-2-1_51KVU_2020-11-04_final.stac-item
2020-11-25 11:13:53	ga_s2am_ard_3-2-1_52KCV_2020-11-25_final.stac-item
2021-01-07 11:23:07	ga_s2am_ard_3-2-1_51KZT_2021-01-07_final.stac-item
2021-01-31 11:05:16	ga_s2am_ard_3-2-1_52JEP_2021-01-31_final.stac-item
2021-02-02 11:44:16	ga_s2am_ard_3-2-1_50KRU_2021-02-02_final.stac-item
2021-03-04 11:46:15	ga_s2am_ard_3-2-1_50JQL_2021-03-04_final.stac-item
2021-03-28 11:22:21	ga_s2am_ard_3-2-1_51KZA_2021-03-28_final.stac-item
2021-04-07 11:23:17	ga_s2am_ard_3-2-1_51KZS_2021-04-07_final.stac-item
2021-07-18 12:05:18	ga_s2am_ard_3-2-1_49JGL_2021-07-18_final.stac-item
2021-08-28 11:37:19	ga_s2am_ard_3-2-1_50HQG_2021-08-28_final
2021-10-06 12:04:26	ga_s2am_ard_3-2-1_50KMU_2021-10-06_final.stac-item
2021-11-03 11:22:26	ga_s2am_ard_3-2-1_52KBF_2021-11-03_final.stac-item
2021-11-19 11:45:43	ga_s2am_ard_3-2-1_51JTH_2021-11-19_final.stac-item
2021-12-07 11:06:09	ga_s2am_ard_3-2-1_52JBL_2021-12-07_final.stac-item
2021-12-13 11:23:38	ga_s2am_ard_3-2-1_51KYR_2021-12-13_final.stac-item
2022-01-02 11:23:08	ga_s2am_ard_3-2-1_52KBC_2022-01-02_final.stac-item
2022-02-04 11:36:31	ga_s2am_ard_3-2-1_51HTE_2022-02-04_final.stac-item
2022-02-14 11:34:03	ga_s2am_ard_3-2-1_51KUQ_2022-02-14_final.stac-item
2022-03-29 11:46:56	ga_s2am_ard_3-2-1_50HQH_2022-03-29_final.stac-item
2022-03-30 11:15:21	ga_s2am_ard_3-2-1_52JCP_2022-03-30_final.stac-item
2022-04-04 12:04:00	ga_s2am_ard_3-2-1_50KKA_2022-04-04_final.stac-item
2022-04-14 12:04:45	ga_s2am_ard_3-2-1_49JHN_2022-04-14_final.stac-item
2022-04-26 11:06:15	ga_s2am_ard_3-2-1_52JBL_2022-04-26_final.stac-item
2022-05-05 11:34:30	ga_s2am_ard_3-2-1_51JWN_2022-05-05_final.stac-item
2022-05-14 12:04:37	ga_s2am_ard_3-2-1_49KHP_2022-05-14_final.stac-item
2022-06-07 11:44:24	ga_s2am_ard_3-2-1_50KRU_2022-06-07_final.stac-item
2022-06-17 11:43:29	ga_s2am_ard_3-2-1_50KRC_2022-06-17_final.stac-item
2022-07-14 11:33:03	ga_s2am_ard_3-2-1_51KYU_2022-07-14_final.stac-item
2022-08-02 12:06:06	ga_s2am_ard_3-2-1_50JKN_2022-08-02_final.stac-item
2022-09-25 11:43:04	ga_s2am_ard_3-2-1_51KVU_2022-09-25_final.stac-item
2022-10-01 12:04:50	ga_s2am_ard_3-2-1_50JKT_2022-10-01_final.stac-item
2022-10-15 11:43:15	ga_s2am_ard_3-2-1_51KVT_2022-10-15_final.stac-item
2023-01-14 12:50:56	ga_s2am_ard_3-2-1_48LXP_2023-01-14_interim
2023-01-30 11:31:40	ga_s2am_ard_3-2-1_51LXD_2023-01-30_final.stac-item
2023-02-16 11:24:12	ga_s2am_ard_3-2-1_51KWP_2023-02-16_final
2023-02-18 12:04:54	ga_s2am_ard_3-2-1_50JKS_2023-02-18_nrt.stac-item
2023-05-10 11:31:05	ga_s2am_ard_3-2-1_51LZF_2023-05-10_final
2023-05-27 11:25:59	ga_s2am_ard_3-2-1_51JWG_2023-05-27_final
2023-06-09 11:32:18	ga_s2am_ard_3-2-1_51KWB_2023-06-09_final
2023-08-04 11:57:18	ga_s2am_ard_3-2-1_50HKH_2023-08-04_nrt
2023-08-15 11:25:58	ga_s2am_ard_3-2-1_51JXG_2023-08-15_final
2023-08-21 11:47:08	ga_s2am_ard_3-2-1_50HPH_2023-08-21_final
2023-09-09 12:13:59	ga_s2am_ard_3-2-1_50KKA_2023-09-09_final
2023-09-11 11:14:51	ga_s2am_ard_3-2-1_52JDR_2023-09-11_final
2023-09-24 11:23:05	ga_s2am_ard_3-2-1_52KCC_2023-09-24_final
2023-11-06 11:34:10	ga_s2am_ard_3-2-1_51KWP_2023-11-06_final
2023-11-08 12:14:30	ga_s2am_ard_3-2-1_49KFP_2023-11-08_nrt
2024-02-14 11:33:57	ga_s2am_ard_3-2-1_51KVQ_2024-02-14_final
2024-03-01 11:53:38	ga_s2am_ard_3-2-1_50KMB_2024-03-01_final
2024-04-05 11:04:44	ga_s2am_ard_3-2-1_52JER_2024-04-05_final
2024-05-07 11:41:00	ga_s2am_ard_3-2-1_51LWG_2024-05-07_final
2024-05-14 11:33:25	ga_s2am_ard_3-2-1_51KUT_2024-05-14_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