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
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50HMJ_2015-11-14_final.stac-item
2016-04-06 11:25:50	ga_s2am_ard_3-2-1_51KVT_2016-04-06_final.stac-item
2016-04-06 11:33:21	ga_s2am_ard_3-2-1_50HQK_2016-04-06_final.stac-item
2016-04-06 11:33:21	ga_s2am_ard_3-2-1_51JTG_2016-04-06_final.stac-item
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51JVK_2016-05-03_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49KHS_2016-05-15_final
2016-05-23 11:22:44	ga_s2am_ard_3-2-1_51HWC_2016-05-23_final
2016-05-25 12:04:47	ga_s2am_ard_3-2-1_49JGL_2016-05-25_final.stac-item
2016-05-30 11:11:45	ga_s2am_ard_3-2-1_51JXJ_2016-05-30_final.stac-item
2016-06-25 11:32:00	ga_s2am_ard_3-2-1_51KWS_2016-06-25_final
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JNM_2016-07-21_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_51KTU_2016-11-05_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51KVU_2016-12-15_final.stac-item
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50JLM_2017-05-27_final.stac-item
2017-05-31 11:28:39	ga_s2am_ard_3-2-1_51KUT_2017-05-31_final.stac-item
2017-09-08 11:29:54	ga_s2am_ard_3-2-1_51KWB_2017-09-08_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51JWL_2017-09-28_final.stac-item
2017-10-08 11:36:06	ga_s2am_ard_3-2-1_51JTF_2017-10-08_final.stac-item
2017-10-15 11:26:08	ga_s2am_ard_3-2-1_51HUE_2017-10-15_final.stac-item
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_50KKA_2017-11-29_final.stac-item
2017-12-26 12:04:47	ga_s2am_ard_3-2-1_49JGL_2017-12-26_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51KUP_2018-01-06_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_51KUU_2018-02-08_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50KKU_2018-04-25_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50KMC_2018-04-25_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JKT_2018-05-25_final.stac-item
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_51KVQ_2018-06-15_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_51KVS_2018-06-28_final.stac-item
2018-07-05 11:35:08	ga_s2am_ard_3-2-1_51HUC_2018-07-05_final.stac-item
2018-08-04 11:32:40	ga_s2am_ard_3-2-1_51KVS_2018-08-04_final.stac-item
2018-10-23 11:26:17	ga_s2am_ard_3-2-1_51KVT_2018-10-23_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_51KVV_2018-10-26_final.stac-item
2018-11-15 11:42:51	ga_s2am_ard_3-2-1_51KVU_2018-11-15_final.stac-item
2018-11-22 11:33:17	ga_s2am_ard_3-2-1_51KVT_2018-11-22_final.stac-item
2018-11-22 11:33:19	ga_s2am_ard_3-2-1_51KUS_2018-11-22_final.stac-item
2019-01-01 11:33:36	ga_s2am_ard_3-2-1_51KWR_2019-01-01_final.stac-item
2019-01-07 11:57:01	ga_s2am_ard_3-2-1_50HMH_2019-01-07_final.stac-item
2019-05-11 11:33:01	ga_s2am_ard_3-2-1_51KWU_2019-05-11_final.stac-item
2019-06-20 11:33:26	ga_s2am_ard_3-2-1_51KUT_2019-06-20_final.stac-item
2019-07-23 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2019-07-23_final.stac-item
2019-10-28 11:33:01	ga_s2am_ard_3-2-1_51KWU_2019-10-28_final.stac-item
2019-12-27 11:33:57	ga_s2am_ard_3-2-1_51KUQ_2019-12-27_final.stac-item
2019-12-27 11:34:12	ga_s2am_ard_3-2-1_51KUP_2019-12-27_final.stac-item
2020-01-26 11:33:49	ga_s2am_ard_3-2-1_51KWQ_2020-01-26_final.stac-item
2020-03-18 12:14:52	ga_s2am_ard_3-2-1_49JGM_2020-03-18_final.stac-item
2020-09-22 11:36:38	ga_s2am_ard_3-2-1_51HVD_2020-09-22_final.stac-item
2020-10-11 12:06:01	ga_s2am_ard_3-2-1_50JKN_2020-10-11_final.stac-item
2020-10-28 11:52:39	ga_s2am_ard_3-2-1_50KQF_2020-10-28_final
2020-11-11 11:34:07	ga_s2am_ard_3-2-1_51KUQ_2020-11-11_final.stac-item
2020-11-14 11:43:28	ga_s2am_ard_3-2-1_51KVS_2020-11-14_final.stac-item
2021-01-03 11:42:57	ga_s2am_ard_3-2-1_51KVU_2021-01-03_final.stac-item
2021-01-20 11:33:17	ga_s2am_ard_3-2-1_51KVT_2021-01-20_final.stac-item
2021-02-05 11:57:05	ga_s2am_ard_3-2-1_50HMH_2021-02-05_final.stac-item
2021-02-18 12:06:09	ga_s2am_ard_3-2-1_50JKM_2021-02-18_final.stac-item
2021-02-19 11:33:41	ga_s2am_ard_3-2-1_51KWR_2021-02-19_final.stac-item
2021-03-01 11:33:22	ga_s2am_ard_3-2-1_51KUT_2021-03-01_final.stac-item
2021-04-03 11:47:03	ga_s2am_ard_3-2-1_50HNH_2021-04-03_final.stac-item
2021-04-20 11:36:56	ga_s2am_ard_3-2-1_51HTC_2021-04-20_final.stac-item
2021-05-07 11:24:14	ga_s2am_ard_3-2-1_51KWP_2021-05-07_final.stac-item
2021-05-09 12:03:43	ga_s2am_ard_3-2-1_49KHS_2021-05-09_final
2021-06-05 11:53:18	ga_s2am_ard_3-2-1_50KQC_2021-06-05_final.stac-item
2021-06-22 11:47:18	ga_s2am_ard_3-2-1_50HPG_2021-06-22_final
2021-07-22 11:46:51	ga_s2am_ard_3-2-1_50HPJ_2021-07-22_final.stac-item
2021-07-22 11:47:10	ga_s2am_ard_3-2-1_50HNH_2021-07-22_final.stac-item
2021-08-11 11:42:19	ga_s2am_ard_3-2-1_51KUB_2021-08-11_final
2021-08-27 12:03:46	ga_s2am_ard_3-2-1_49KHS_2021-08-27_final
2021-11-23 11:27:02	ga_s2am_ard_3-2-1_51HUC_2021-11-23_final.stac-item
2021-11-26 11:32:58	ga_s2am_ard_3-2-1_51KWU_2021-11-26_final.stac-item
2021-11-26 11:34:17	ga_s2am_ard_3-2-1_51KUP_2021-11-26_final.stac-item
2021-12-26 11:33:17	ga_s2am_ard_3-2-1_51KVT_2021-12-26_final.stac-item
2021-12-29 11:42:47	ga_s2am_ard_3-2-1_51KUV_2021-12-29_final.stac-item
2022-01-25 11:33:01	ga_s2am_ard_3-2-1_51KVU_2022-01-25_final.stac-item
2022-02-03 12:05:55	ga_s2am_ard_3-2-1_50JKN_2022-02-03_final.stac-item
2022-03-16 11:33:49	ga_s2am_ard_3-2-1_51KVR_2022-03-16_final.stac-item
2022-04-02 11:25:45	ga_s2am_ard_3-2-1_51JYG_2022-04-02_final.stac-item
2022-08-06 11:42:28	ga_s2am_ard_3-2-1_51KUB_2022-08-06_final
2022-08-13 11:34:08	ga_s2am_ard_3-2-1_51KWQ_2022-08-13_final.stac-item
2022-08-26 11:43:17	ga_s2am_ard_3-2-1_50KRD_2022-08-26_final
2022-09-02 11:33:39	ga_s2am_ard_3-2-1_51KWS_2022-09-02_final.stac-item
2022-09-02 11:36:22	ga_s2am_ard_3-2-1_51JVF_2022-09-02_final.stac-item
2022-09-12 11:33:55	ga_s2am_ard_3-2-1_51KVR_2022-09-12_final.stac-item
2022-09-12 11:36:21	ga_s2am_ard_3-2-1_51JVF_2022-09-12_final.stac-item
2022-09-22 11:33:29	ga_s2am_ard_3-2-1_51KUT_2022-09-22_final.stac-item
2022-10-25 11:43:27	ga_s2am_ard_3-2-1_51KVS_2022-10-25_final.stac-item
2022-11-04 11:42:32	ga_s2am_ard_3-2-1_51KVA_2022-11-04_final.stac-item
2022-12-11 11:33:45	ga_s2am_ard_3-2-1_51KVR_2022-12-11_final.stac-item
2022-12-24 11:43:16	ga_s2am_ard_3-2-1_51KTT_2022-12-24_final.stac-item
2022-12-31 11:33:00	ga_s2am_ard_3-2-1_51KVU_2022-12-31_final.stac-item
2023-02-22 11:43:16	ga_s2am_ard_3-2-1_50KRC_2023-02-22_final
2023-02-25 11:53:22	ga_s2am_ard_3-2-1_50KNC_2023-02-25_final
2023-04-10 11:32:47	ga_s2am_ard_3-2-1_51KVV_2023-04-10_final
2023-07-02 11:43:16	ga_s2am_ard_3-2-1_51KVT_2023-07-02_final
2023-07-02 11:43:34	ga_s2am_ard_3-2-1_51KUS_2023-07-02_final
2023-08-01 11:43:24	ga_s2am_ard_3-2-1_50KRC_2023-08-01_final
2023-08-08 11:33:35	ga_s2am_ard_3-2-1_51KVS_2023-08-08_final
2023-08-15 11:24:07	ga_s2am_ard_3-2-1_51KWQ_2023-08-15_final
2023-08-28 11:33:47	ga_s2am_ard_3-2-1_51KWR_2023-08-28_final
2023-10-10 11:43:24	ga_s2am_ard_3-2-1_51KVS_2023-10-10_final
2023-10-30 11:43:24	ga_s2am_ard_3-2-1_51KVS_2023-10-30_final
2023-11-12 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2023-11-12_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