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
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HMK_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51KVS_2016-01-20_final.stac-item
2016-07-22 11:22:31	ga_s2am_ard_3-2-1_51JYK_2016-07-22_final
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50JKP_2016-09-19_final.stac-item
2016-10-04 11:05:00	ga_s2am_ard_3-2-1_52HDK_2016-10-04_final
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_51KUV_2016-11-05_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_50KKB_2016-12-31_final.stac-item
2017-06-12 12:14:42	ga_s2am_ard_3-2-1_49JGM_2017-06-12_final.stac-item
2017-07-10 11:34:59	ga_s2am_ard_3-2-1_51HTD_2017-07-10_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50KNV_2017-07-16_final.stac-item
2017-08-13 11:12:03	ga_s2am_ard_3-2-1_51KZR_2017-08-13_final.stac-item
2017-09-09 11:02:57	ga_s2am_ard_3-2-1_52JEQ_2017-09-09_final.stac-item
2017-10-18 11:36:29	ga_s2am_ard_3-2-1_51HUC_2017-10-18_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_50HPK_2017-11-07_final.stac-item
2017-12-31 11:11:55	ga_s2am_ard_3-2-1_51KZS_2017-12-31_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50KQV_2018-01-12_final.stac-item
2018-01-26 11:29:50	ga_s2am_ard_3-2-1_51KXV_2018-01-26_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_51KWB_2018-02-08_final.stac-item
2018-02-15 11:34:02	ga_s2am_ard_3-2-1_51HTC_2018-02-15_final.stac-item
2018-02-25 11:27:26	ga_s2am_ard_3-2-1_51KXB_2018-02-25_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_51KVB_2018-03-10_final.stac-item
2018-04-19 11:40:43	ga_s2am_ard_3-2-1_51LWC_2018-04-19_final.stac-item
2018-05-06 11:26:23	ga_s2am_ard_3-2-1_51KYB_2018-05-06_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50JQM_2018-06-08_final.stac-item
2018-07-09 11:13:18	ga_s2am_ard_3-2-1_51KZR_2018-07-09_final.stac-item
2018-07-25 11:26:21	ga_s2am_ard_3-2-1_51KWU_2018-07-25_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HQK_2018-09-06_final.stac-item
2018-11-18 11:56:01	ga_s2am_ard_3-2-1_50JMM_2018-11-18_final.stac-item
2018-11-28 11:53:23	ga_s2am_ard_3-2-1_50KMC_2018-11-28_final.stac-item
2019-01-21 11:31:35	ga_s2am_ard_3-2-1_51LYD_2019-01-21_final.stac-item
2019-01-30 12:04:39	ga_s2am_ard_3-2-1_49JHN_2019-01-30_final.stac-item
2019-02-13 11:41:29	ga_s2am_ard_3-2-1_51LUE_2019-02-13_final.stac-item
2019-06-11 11:04:24	ga_s2am_ard_3-2-1_52JDT_2019-06-11_final.stac-item
2019-07-10 11:34:51	ga_s2am_ard_3-2-1_51JUM_2019-07-10_final.stac-item
2019-08-08 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2019-08-08_final.stac-item
2019-10-14 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2019-10-14_final.stac-item
2019-11-17 11:34:19	ga_s2am_ard_3-2-1_51KUP_2019-11-17_final.stac-item
2019-11-24 11:23:14	ga_s2am_ard_3-2-1_51KXT_2019-11-24_final.stac-item
2019-12-11 11:13:36	ga_s2am_ard_3-2-1_52KBA_2019-12-11_final.stac-item
2020-04-02 11:25:01	ga_s2am_ard_3-2-1_51JYK_2020-04-02_final.stac-item
2020-06-04 11:32:21	ga_s2am_ard_3-2-1_51KWB_2020-06-04_final.stac-item
2020-06-24 11:36:32	ga_s2am_ard_3-2-1_50JPL_2020-06-24_final.stac-item
2020-07-13 12:04:32	ga_s2am_ard_3-2-1_49KHP_2020-07-13_final.stac-item
2020-07-28 11:16:11	ga_s2am_ard_3-2-1_52JBL_2020-07-28_final.stac-item
2020-07-31 11:27:07	ga_s2am_ard_3-2-1_51HUC_2020-07-31_final.stac-item
2020-08-10 11:26:38	ga_s2am_ard_3-2-1_51HUE_2020-08-10_final.stac-item
2020-09-05 11:42:50	ga_s2am_ard_3-2-1_51KUV_2020-09-05_final.stac-item
2020-09-15 11:45:33	ga_s2am_ard_3-2-1_51JTJ_2020-09-15_final.stac-item
2020-09-29 11:23:01	ga_s2am_ard_3-2-1_51KYU_2020-09-29_final.stac-item
2020-10-05 11:41:24	ga_s2am_ard_3-2-1_51LUF_2020-10-05_final.stac-item
2020-10-25 11:45:52	ga_s2am_ard_3-2-1_50JQN_2020-10-25_final.stac-item
2020-12-04 11:41:31	ga_s2am_ard_3-2-1_51LUE_2020-12-04_final.stac-item
2020-12-20 12:04:38	ga_s2am_ard_3-2-1_50JLT_2020-12-20_final.stac-item
2020-12-25 11:13:53	ga_s2am_ard_3-2-1_51KZQ_2020-12-25_final.stac-item
2021-01-14 11:16:41	ga_s2am_ard_3-2-1_51HXD_2021-01-14_final.stac-item
2021-03-01 11:32:22	ga_s2am_ard_3-2-1_51KYA_2021-03-01_final.stac-item
2021-03-01 11:34:54	ga_s2am_ard_3-2-1_51JWL_2021-03-01_final.stac-item
2021-03-11 11:32:25	ga_s2am_ard_3-2-1_51KXA_2021-03-11_final.stac-item
2021-08-14 11:53:13	ga_s2am_ard_3-2-1_50KRC_2021-08-14_final.stac-item
2021-09-15 10:55:29	ga_s2am_ard_3-2-1_52JGN_2021-09-15_final.stac-item
2021-11-16 11:32:30	ga_s2am_ard_3-2-1_51KWA_2021-11-16_final.stac-item
2021-11-19 11:43:22	ga_s2am_ard_3-2-1_50KQC_2021-11-19_final.stac-item
2021-12-03 11:23:13	ga_s2am_ard_3-2-1_51KXT_2021-12-03_final.stac-item
2021-12-03 11:23:57	ga_s2am_ard_3-2-1_51KXQ_2021-12-03_final.stac-item
2022-01-12 11:22:53	ga_s2am_ard_3-2-1_51KZU_2022-01-12_final.stac-item
2022-02-10 11:53:23	ga_s2am_ard_3-2-1_50KNC_2022-02-10_final.stac-item
2022-02-24 11:32:17	ga_s2am_ard_3-2-1_51KWB_2022-02-24_final.stac-item
2022-03-13 11:23:30	ga_s2am_ard_3-2-1_51KZS_2022-03-13_final.stac-item
2022-05-12 11:24:18	ga_s2am_ard_3-2-1_51KWP_2022-05-12_final.stac-item
2022-06-21 11:24:31	ga_s2am_ard_3-2-1_51JZN_2022-06-21_final.stac-item
2022-07-21 11:23:04	ga_s2am_ard_3-2-1_51KZU_2022-07-21_final.stac-item
2022-08-10 11:22:06	ga_s2am_ard_3-2-1_51LZC_2022-08-10_final.stac-item
2022-08-13 11:34:26	ga_s2am_ard_3-2-1_51KVP_2022-08-13_final.stac-item
2022-10-26 11:13:42	ga_s2am_ard_3-2-1_52KBA_2022-10-26_final.stac-item
2022-11-14 11:43:03	ga_s2am_ard_3-2-1_51KUU_2022-11-14_final.stac-item
2022-12-03 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-12-03_final.stac-item
2023-01-04 11:16:05	ga_s2am_ard_3-2-1_52JBL_2023-01-04_final.stac-item
2023-03-14 11:43:15	ga_s2am_ard_3-2-1_51KTT_2023-03-14_final
2023-04-25 10:46:00	ga_s2am_ard_3-2-1_52JGL_2023-04-25_final
2023-05-20 11:36:16	ga_s2am_ard_3-2-1_51JUF_2023-05-20_final
2023-05-28 10:54:51	ga_s2am_ard_3-2-1_52JFR_2023-05-28_final
2023-06-02 11:42:49	ga_s2am_ard_3-2-1_51KUV_2023-06-02_final
2023-06-06 11:25:17	ga_s2am_ard_3-2-1_51JWK_2023-06-06_final
2023-06-23 11:15:11	ga_s2am_ard_3-2-1_52JBQ_2023-06-23_final
2023-06-25 11:57:23	ga_s2am_ard_3-2-1_50HMG_2023-06-25_final
2023-07-19 11:32:33	ga_s2am_ard_3-2-1_51KWA_2023-07-19_final
2023-07-28 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2023-07-28_final
2023-07-29 11:37:12	ga_s2am_ard_3-2-1_50HPH_2023-07-29_final
2023-08-08 11:36:31	ga_s2am_ard_3-2-1_50JPL_2023-08-08_final
2023-08-21 11:43:50	ga_s2am_ard_3-2-1_51KUR_2023-08-21_final
2023-10-10 11:43:43	ga_s2am_ard_3-2-1_51KUR_2023-10-10_final
2023-10-14 11:23:26	ga_s2am_ard_3-2-1_51KXS_2023-10-14_final
2023-10-17 11:32:39	ga_s2am_ard_3-2-1_51KXV_2023-10-17_final
2023-10-17 11:36:56	ga_s2am_ard_3-2-1_51HUC_2023-10-17_final
2023-10-30 11:42:21	ga_s2am_ard_3-2-1_51KWA_2023-10-30_final
2024-03-09 11:14:24	ga_s2am_ard_3-2-1_52JBT_2024-03-09_final
2024-04-21 11:21:29	ga_s2am_ard_3-2-1_51LZE_2024-04-21_final
2024-05-21 11:26:59	ga_s2am_ard_3-2-1_51HVC_2024-05-21_nrt
2024-05-23 12:05:14	ga_s2am_ard_3-2-1_49JGL_2024-05-23_nrt
2024-05-30 11:56:43	ga_s2am_ard_3-2-1_50HLK_2024-05-30_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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