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
2015-09-23 11:10:40	ga_s2am_ard_3-2-1_52LFL_2015-09-23_final.stac-item
2016-01-21 11:14:09	ga_s2am_ard_3-2-1_52KCF_2016-01-21_final.stac-item
2016-01-31 11:12:11	ga_s2am_ard_3-2-1_52KCE_2016-01-31_final.stac-item
2016-02-04 10:53:14	ga_s2am_ard_3-2-1_52KGA_2016-02-04_final.stac-item
2016-03-02 10:44:00	ga_s2am_ard_3-2-1_53JLN_2016-03-02_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50KKA_2016-03-16_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50JNR_2016-03-20_final.stac-item
2016-03-28 11:01:10	ga_s2am_ard_3-2-1_52KEB_2016-03-28_final.stac-item
2016-03-29 10:28:49	ga_s2am_ard_3-2-1_53HME_2016-03-29_final.stac-item
2016-03-29 10:28:49	ga_s2am_ard_3-2-1_53JMJ_2016-03-29_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JMS_2016-04-02_final.stac-item
2016-04-06 11:25:50	ga_s2am_ard_3-2-1_52LBK_2016-04-06_final.stac-item
2016-04-10 11:07:07	ga_s2am_ard_3-2-1_52KCD_2016-04-10_final.stac-item
2016-04-14 10:51:39	ga_s2am_ard_3-2-1_52JEN_2016-04-14_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49JGM_2016-04-15_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51LZE_2016-04-23_final.stac-item
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51KWQ_2016-05-03_final.stac-item
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51KXS_2016-05-03_final.stac-item
2016-05-04 10:52:08	ga_s2am_ard_3-2-1_52JEN_2016-05-04_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50KQB_2016-05-09_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_51JXH_2016-05-10_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_52KCF_2016-05-10_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50HPJ_2016-05-16_final.stac-item
2016-05-27 11:02:16	ga_s2am_ard_3-2-1_52KDV_2016-05-27_final.stac-item
2016-05-28 10:34:29	ga_s2am_ard_3-2-1_53JMG_2016-05-28_final.stac-item
2016-05-28 10:34:29	ga_s2am_ard_3-2-1_53JNK_2016-05-28_final.stac-item
2016-05-30 11:11:45	ga_s2am_ard_3-2-1_52KBU_2016-05-30_final.stac-item
2016-06-03 10:52:21	ga_s2am_ard_3-2-1_52KGV_2016-06-03_final.stac-item
2016-06-06 10:58:03	ga_s2am_ard_3-2-1_52LHN_2016-06-06_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_51LUE_2016-06-18_final.stac-item
2016-07-26 11:02:15	ga_s2am_ard_3-2-1_52KFA_2016-07-26_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_52KHA_2016-10-31_final.stac-item
2017-01-12 11:02:04	ga_s2am_ard_3-2-1_52KGD_2017-01-12_final.stac-item
2017-02-27 11:22:43	ga_s2am_ard_3-2-1_51HUC_2017-02-27_final.stac-item
2017-03-30 10:52:12	ga_s2am_ard_3-2-1_52KHF_2017-03-30_final.stac-item
2017-09-19 11:02:07	ga_s2am_ard_3-2-1_52KGE_2017-09-19_final.stac-item
2017-11-08 10:57:14	ga_s2am_ard_3-2-1_52KHB_2017-11-08_final.stac-item
2018-01-18 10:32:26	ga_s2am_ard_3-2-1_53JNN_2018-01-18_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50HMJ_2018-02-01_final.stac-item
2018-05-23 11:17:08	ga_s2am_ard_3-2-1_51KYS_2018-05-23_final.stac-item
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_50KKU_2018-06-04_final.stac-item
2018-09-25 10:27:03	ga_s2am_ard_3-2-1_53JNM_2018-09-25_final.stac-item
2019-02-05 10:44:10	ga_s2am_ard_3-2-1_53JLN_2019-02-05_final.stac-item
2019-02-09 12:05:45	ga_s2am_ard_3-2-1_50JKN_2019-02-09_final.stac-item
2019-02-16 11:57:06	ga_s2am_ard_3-2-1_50HLH_2019-02-16_final.stac-item
2019-02-22 10:34:18	ga_s2am_ard_3-2-1_53JPM_2019-02-22_final.stac-item
2019-03-17 10:44:00	ga_s2am_ard_3-2-1_53JNN_2019-03-17_final.stac-item
2019-04-03 10:34:26	ga_s2am_ard_3-2-1_53JNM_2019-04-03_final.stac-item
2019-04-30 12:05:59	ga_s2am_ard_3-2-1_50JKN_2019-04-30_final.stac-item
2019-06-17 11:27:05	ga_s2am_ard_3-2-1_51HUC_2019-06-17_final.stac-item
2019-07-19 12:03:49	ga_s2am_ard_3-2-1_50KKB_2019-07-19_final.stac-item
2019-09-03 10:44:03	ga_s2am_ard_3-2-1_53JPN_2019-09-03_final.stac-item
2019-09-19 11:02:18	ga_s2am_ard_3-2-1_52KHE_2019-09-19_final.stac-item
2019-10-01 11:41:33	ga_s2am_ard_3-2-1_51LUE_2019-10-01_final.stac-item
2019-11-13 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2019-11-13_final.stac-item
2019-11-13 11:57:08	ga_s2am_ard_3-2-1_50HMH_2019-11-13_final.stac-item
2020-01-18 10:34:01	ga_s2am_ard_3-2-1_53JPN_2020-01-18_final.stac-item
2020-03-13 11:25:17	ga_s2am_ard_3-2-1_51JYJ_2020-03-13_final.stac-item
2020-04-07 10:36:47	ga_s2am_ard_3-2-1_53HNB_2020-04-07_final.stac-item
2020-04-09 11:13:37	ga_s2am_ard_3-2-1_52KBA_2020-04-09_final.stac-item
2020-06-07 11:43:31	ga_s2am_ard_3-2-1_51KVS_2020-06-07_final.stac-item
2020-06-21 11:23:27	ga_s2am_ard_3-2-1_51KZS_2020-06-21_final.stac-item
2020-07-11 11:23:11	ga_s2am_ard_3-2-1_51KZT_2020-07-11_final.stac-item
2020-07-13 10:26:37	ga_s2am_ard_3-2-1_53HQC_2020-07-13_final.stac-item
2020-07-23 12:06:09	ga_s2am_ard_3-2-1_50JLM_2020-07-23_final.stac-item
2020-09-30 10:52:25	ga_s2am_ard_3-2-1_52KHF_2020-09-30_final.stac-item
2020-12-18 11:26:34	ga_s2am_ard_3-2-1_51HXD_2020-12-18_final.stac-item
2021-02-09 11:36:32	ga_s2am_ard_3-2-1_51HVD_2021-02-09_final.stac-item
2021-03-08 11:25:56	ga_s2am_ard_3-2-1_51JWG_2021-03-08_final.stac-item
2021-03-24 11:41:31	ga_s2am_ard_3-2-1_51LUE_2021-03-24_final.stac-item
2021-03-27 11:52:18	ga_s2am_ard_3-2-1_50KQG_2021-03-27_final
2021-04-12 12:14:22	ga_s2am_ard_3-2-1_49KGP_2021-04-12_final.stac-item
2021-05-08 10:55:55	ga_s2am_ard_3-2-1_52JGL_2021-05-08_final.stac-item
2021-06-06 11:23:28	ga_s2am_ard_3-2-1_52KCA_2021-06-06_final.stac-item
2021-09-27 11:34:14	ga_s2am_ard_3-2-1_51KWP_2021-09-27_final.stac-item
2021-09-28 11:04:28	ga_s2am_ard_3-2-1_52JGS_2021-09-28_final.stac-item
2022-04-01 11:55:51	ga_s2am_ard_3-2-1_50JLN_2022-04-01_final.stac-item
2022-04-02 11:25:36	ga_s2am_ard_3-2-1_51JYH_2022-04-02_final.stac-item
2022-04-02 11:25:40	ga_s2am_ard_3-2-1_51JXH_2022-04-02_final.stac-item
2022-07-20 11:55:18	ga_s2am_ard_3-2-1_50JNR_2022-07-20_final.stac-item
2022-08-03 11:36:28	ga_s2am_ard_3-2-1_51JTF_2022-08-03_final.stac-item
2022-09-04 12:14:10	ga_s2am_ard_3-2-1_49KGR_2022-09-04_final.stac-item
2022-09-07 10:44:32	ga_s2am_ard_3-2-1_53JNM_2022-09-07_final.stac-item
2022-09-23 11:05:05	ga_s2am_ard_3-2-1_52JFQ_2022-09-23_final.stac-item
2022-09-30 10:54:31	ga_s2am_ard_3-2-1_53JLM_2022-09-30_final.stac-item
2022-10-02 11:32:07	ga_s2am_ard_3-2-1_51LWC_2022-10-02_final.stac-item
2022-10-28 11:50:33	ga_s2am_ard_3-2-1_51LUJ_2022-10-28_nrt.stac-item
2022-11-01 11:34:19	ga_s2am_ard_3-2-1_51JXN_2022-11-01_final.stac-item
2022-11-15 11:11:29	ga_s2am_ard_3-2-1_52LGJ_2022-11-15_final.stac-item
2022-12-11 11:31:28	ga_s2am_ard_3-2-1_51LXE_2022-12-11_final
2023-01-26 11:57:03	ga_s2am_ard_3-2-1_50HMH_2023-01-26_final.stac-item
2023-04-05 10:44:06	ga_s2am_ard_3-2-1_53JNN_2023-04-05_final
2023-06-03 11:16:38	ga_s2am_ard_3-2-1_52HBJ_2023-06-03_nrt
2023-06-15 10:16:56	ga_s2am_ard_3-2-1_53HQB_2023-06-15_final
2023-06-22 11:46:41	ga_s2am_ard_3-2-1_50HNK_2023-06-22_final
2023-07-12 11:41:23	ga_s2am_ard_3-2-1_51LUF_2023-07-12_final
2023-07-18 12:06:08	ga_s2am_ard_3-2-1_50JLM_2023-07-18_final
2023-08-07 10:26:55	ga_s2am_ard_3-2-1_53HPB_2023-08-07_final
2023-08-21 11:41:24	ga_s2am_ard_3-2-1_51LUF_2023-08-21_final
2023-09-08 11:05:03	ga_s2am_ard_3-2-1_52JFQ_2023-09-08_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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