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
2016-01-08 11:03:33	ga_s2am_ard_3-2-1_52KGC_2016-01-08_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51KXU_2016-05-16_final.stac-item
2017-01-08 11:18:08	ga_s2am_ard_3-2-1_51KYQ_2017-01-08_final.stac-item
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_50KNC_2017-03-11_final.stac-item
2017-04-21 11:34:59	ga_s2am_ard_3-2-1_51JVJ_2017-04-21_final.stac-item
2017-08-09 11:36:05	ga_s2am_ard_3-2-1_51HVE_2017-08-09_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51JVF_2017-09-28_final.stac-item
2017-10-06 10:53:13	ga_s2am_ard_3-2-1_52JFS_2017-10-06_final.stac-item
2017-10-11 11:40:47	ga_s2am_ard_3-2-1_50HMH_2017-10-11_final.stac-item
2017-12-30 11:37:45	ga_s2am_ard_3-2-1_51KWB_2017-12-30_final.stac-item
2017-12-31 11:11:55	ga_s2am_ard_3-2-1_52JBN_2017-12-31_final.stac-item
2018-02-08 11:45:59	ga_s2am_ard_3-2-1_50HNK_2018-02-08_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50HMH_2018-02-21_final.stac-item
2018-03-08 10:57:12	ga_s2am_ard_3-2-1_52LGM_2018-03-08_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_50HNK_2018-03-10_final.stac-item
2018-03-14 11:21:15	ga_s2am_ard_3-2-1_51HXD_2018-03-14_final.stac-item
2018-03-21 11:11:51	ga_s2am_ard_3-2-1_52KDV_2018-03-21_final.stac-item
2018-03-27 11:26:19	ga_s2am_ard_3-2-1_51KYA_2018-03-27_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_51KXB_2018-05-06_final.stac-item
2018-05-07 10:57:18	ga_s2am_ard_3-2-1_52KEA_2018-05-07_final.stac-item
2018-05-10 11:12:54	ga_s2am_ard_3-2-1_51HXD_2018-05-10_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_51JTJ_2018-06-18_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51KXQ_2018-08-14_final.stac-item
2018-09-13 11:26:17	ga_s2am_ard_3-2-1_51KXT_2018-09-13_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50HMJ_2018-09-26_final.stac-item
2018-09-30 11:16:55	ga_s2am_ard_3-2-1_52KBA_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HVE_2018-09-30_final.stac-item
2018-10-08 10:37:24	ga_s2am_ard_3-2-1_53JKG_2018-10-08_final.stac-item
2018-11-06 11:15:35	ga_s2am_ard_3-2-1_51JYH_2018-11-06_final.stac-item
2019-01-14 11:43:20	ga_s2am_ard_3-2-1_51KVS_2019-01-14_final.stac-item
2019-01-25 11:15:04	ga_s2am_ard_3-2-1_52JBQ_2019-01-25_final.stac-item
2019-02-17 11:23:46	ga_s2am_ard_3-2-1_51KZQ_2019-02-17_final.stac-item
2019-04-17 11:57:08	ga_s2am_ard_3-2-1_50HMH_2019-04-17_final.stac-item
2019-04-28 11:27:05	ga_s2am_ard_3-2-1_51HUC_2019-04-28_final.stac-item
2019-07-14 11:13:53	ga_s2am_ard_3-2-1_52KDV_2019-07-14_final.stac-item
2019-07-14 11:16:42	ga_s2am_ard_3-2-1_51HYD_2019-07-14_final.stac-item
2019-08-02 11:43:05	ga_s2am_ard_3-2-1_51KUU_2019-08-02_final.stac-item
2019-09-12 11:13:20	ga_s2am_ard_3-2-1_52KCB_2019-09-12_final.stac-item
2019-09-18 11:34:28	ga_s2am_ard_3-2-1_51JVN_2019-09-18_final.stac-item
2020-01-16 11:32:16	ga_s2am_ard_3-2-1_51KYA_2020-01-16_final.stac-item
2020-02-11 11:55:11	ga_s2am_ard_3-2-1_50JPQ_2020-02-11_final.stac-item
2020-03-05 12:04:38	ga_s2am_ard_3-2-1_50JKT_2020-03-05_final.stac-item
2020-04-19 11:14:09	ga_s2am_ard_3-2-1_52KBU_2020-04-19_final.stac-item
2020-06-22 10:55:40	ga_s2am_ard_3-2-1_52JEN_2020-06-22_final.stac-item
2020-07-21 11:24:07	ga_s2am_ard_3-2-1_51KWQ_2020-07-21_final.stac-item
2020-08-09 11:57:12	ga_s2am_ard_3-2-1_50HMH_2020-08-09_final.stac-item
2020-10-16 11:14:43	ga_s2am_ard_3-2-1_52JBS_2020-10-16_final.stac-item
2021-01-30 11:32:29	ga_s2am_ard_3-2-1_51KWA_2021-01-30_final.stac-item
2021-02-12 11:44:15	ga_s2am_ard_3-2-1_51KTP_2021-02-12_final.stac-item
2021-04-12 10:36:30	ga_s2am_ard_3-2-1_53HNC_2021-04-12_final.stac-item
2021-05-03 11:47:19	ga_s2am_ard_3-2-1_50HNG_2021-05-03_final
2021-06-06 11:23:28	ga_s2am_ard_3-2-1_52KCA_2021-06-06_final.stac-item
2021-06-15 11:56:18	ga_s2am_ard_3-2-1_50JNL_2021-06-15_final.stac-item
2021-06-23 11:13:49	ga_s2am_ard_3-2-1_52KDV_2021-06-23_final.stac-item
2021-08-11 11:47:27	ga_s2am_ard_3-2-1_50HMG_2021-08-11_final
2021-09-04 11:24:05	ga_s2am_ard_3-2-1_52KBU_2021-09-04_final.stac-item
2021-09-14 11:24:16	ga_s2am_ard_3-2-1_51KWP_2021-09-14_final.stac-item
2021-11-22 11:55:53	ga_s2am_ard_3-2-1_50JMN_2021-11-22_final.stac-item
2021-11-23 11:23:21	ga_s2am_ard_3-2-1_52KBB_2021-11-23_final.stac-item
2021-12-14 10:55:16	ga_s2am_ard_3-2-1_52JFP_2021-12-14_final.stac-item
2022-01-25 11:34:25	ga_s2am_ard_3-2-1_51JWN_2022-01-25_final.stac-item
2022-05-12 11:23:53	ga_s2am_ard_3-2-1_51KZQ_2022-05-12_final.stac-item
2022-07-27 11:44:11	ga_s2am_ard_3-2-1_51KTQ_2022-07-27_final.stac-item
2022-09-16 11:16:17	ga_s2am_ard_3-2-1_51JYF_2022-09-16_final.stac-item
2022-09-22 11:34:12	ga_s2am_ard_3-2-1_51KXP_2022-09-22_final.stac-item
2022-10-12 11:36:29	ga_s2am_ard_3-2-1_51HVE_2022-10-12_final.stac-item
2022-11-20 12:03:24	ga_s2am_ard_3-2-1_50KMC_2022-11-20_final.stac-item
2022-12-12 11:04:18	ga_s2am_ard_3-2-1_52JET_2022-12-12_final.stac-item
2022-12-18 11:22:55	ga_s2am_ard_3-2-1_51KYU_2022-12-18_final.stac-item
2022-12-24 11:46:17	ga_s2am_ard_3-2-1_50JPL_2022-12-24_final.stac-item
2023-01-23 11:43:54	ga_s2am_ard_3-2-1_51KUQ_2023-01-23_final.stac-item
2023-01-24 12:50:57	ga_s2am_ard_3-2-1_48LWP_2023-01-24_final
2023-01-27 11:21:18	ga_s2am_ard_3-2-1_52LCK_2023-01-27_final
2023-02-02 11:43:28	ga_s2am_ard_3-2-1_51KUS_2023-02-02_final
2023-02-22 11:45:06	ga_s2am_ard_3-2-1_50JNR_2023-02-22_nrt.stac-item
2023-03-02 11:02:18	ga_s2am_ard_3-2-1_52KGF_2023-03-02_final
2023-03-28 11:25:32	ga_s2am_ard_3-2-1_51JYH_2023-03-28_final
2023-04-30 11:33:34	ga_s2am_ard_3-2-1_51KUS_2023-04-30_final
2023-05-17 11:27:00	ga_s2am_ard_3-2-1_51HVC_2023-05-17_final
2023-06-03 11:13:08	ga_s2am_ard_3-2-1_52KDC_2023-06-03_final
2023-06-06 11:26:51	ga_s2am_ard_3-2-1_51HUD_2023-06-06_final
2023-06-19 11:35:37	ga_s2am_ard_3-2-1_51JTJ_2023-06-19_final
2023-06-27 10:54:23	ga_s2am_ard_3-2-1_52JGT_2023-06-27_final
2023-07-11 12:14:36	ga_s2am_ard_3-2-1_49KFP_2023-07-11_nrt
2023-07-20 11:03:38	ga_s2am_ard_3-2-1_52KEA_2023-07-20_final
2023-07-20 11:05:41	ga_s2am_ard_3-2-1_52JCN_2023-07-20_final
2023-09-07 11:36:43	ga_s2am_ard_3-2-1_50HPK_2023-09-07_final
2023-11-02 11:55:50	ga_s2am_ard_3-2-1_50JKP_2023-11-02_final
2023-12-10 11:15:48	ga_s2am_ard_3-2-1_51JYG_2023-12-10_final
2024-01-02 11:23:24	ga_s2am_ard_3-2-1_52KCA_2024-01-02_final
2024-01-02 11:26:15	ga_s2am_ard_3-2-1_51JUF_2024-01-02_final
2024-01-16 11:01:35	ga_s2am_ard_3-2-1_52LHH_2024-01-16_final
2024-01-16 11:05:31	ga_s2am_ard_3-2-1_52JFM_2024-01-16_final
2024-01-22 11:21:46	ga_s2am_ard_3-2-1_52LBH_2024-01-22_final
2024-01-24 12:03:27	ga_s2am_ard_3-2-1_50KNB_2024-01-24_final
2024-03-02 11:22:34	ga_s2am_ard_3-2-1_52KCE_2024-03-02_final
2024-03-15 11:36:02	ga_s2am_ard_3-2-1_51JTG_2024-03-15_final
2024-03-25 11:34:15	ga_s2am_ard_3-2-1_51KVP_2024-03-25_final
2024-03-28 11:41:56	ga_s2am_ard_3-2-1_51LWC_2024-03-28_final
2024-04-11 11:24:45	ga_s2am_ard_3-2-1_51JWM_2024-04-11_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

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