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
2016-03-07 11:32:50	ga_s2am_ard_3-2-1_51HUC_2016-03-07_final.stac-item
2016-03-07 11:32:50	ga_s2am_ard_3-2-1_50HPJ_2016-03-07_final.stac-item
2016-03-07 11:32:50	ga_s2am_ard_3-2-1_50HQJ_2016-03-07_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HLH_2016-03-20_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HNH_2016-03-20_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HNJ_2016-03-20_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HPJ_2016-03-20_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HQJ_2016-03-20_final.stac-item
2016-05-03 11:17:04	ga_s2am_ard_3-2-1_51LZC_2016-05-03_final.stac-item
2016-05-03 11:17:04	ga_s2am_ard_3-2-1_51LZD_2016-05-03_final.stac-item
2016-05-06 11:36:08	ga_s2am_ard_3-2-1_50HQK_2016-05-06_final.stac-item
2016-05-06 11:36:08	ga_s2am_ard_3-2-1_50JPL_2016-05-06_final.stac-item
2016-05-06 11:36:08	ga_s2am_ard_3-2-1_50JQL_2016-05-06_final.stac-item
2016-05-06 11:36:08	ga_s2am_ard_3-2-1_51HUE_2016-05-06_final.stac-item
2016-05-06 11:36:08	ga_s2am_ard_3-2-1_51HVE_2016-05-06_final.stac-item
2016-05-06 11:36:08	ga_s2am_ard_3-2-1_50JQM_2016-05-06_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_51LUC_2016-05-09_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_51LVE_2016-05-09_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_51LWE_2016-05-09_final.stac-item
2016-05-16 11:26:26	ga_s2am_ard_3-2-1_51KYA_2016-05-16_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51KVA_2016-05-16_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51KYV_2016-05-16_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50KMA_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50KNU_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50KQA_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50KLU_2016-05-22_final.stac-item
2016-05-25 12:04:47	ga_s2am_ard_3-2-1_50JLQ_2016-05-25_final.stac-item
2016-05-25 12:04:47	ga_s2am_ard_3-2-1_49JGK_2016-05-25_final.stac-item
2016-05-27 11:02:16	ga_s2am_ard_3-2-1_52JDT_2016-05-27_final.stac-item
2016-05-27 11:02:16	ga_s2am_ard_3-2-1_52JET_2016-05-27_final.stac-item
2016-05-27 11:02:16	ga_s2am_ard_3-2-1_52JFT_2016-05-27_final.stac-item
2016-05-27 11:02:16	ga_s2am_ard_3-2-1_52JGT_2016-05-27_final.stac-item
2016-05-27 11:02:16	ga_s2am_ard_3-2-1_52KEC_2016-05-27_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50KMA_2016-07-01_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50KNU_2016-07-01_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50KQA_2016-07-01_final.stac-item
2016-07-09 11:09:03	ga_s2am_ard_3-2-1_52KCU_2016-07-09_final.stac-item
2016-07-13 10:52:20	ga_s2am_ard_3-2-1_52KGA_2016-07-13_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KHR_2016-07-14_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50KKA_2016-07-14_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50KLU_2016-07-14_final.stac-item
2016-07-16 10:57:59	ga_s2am_ard_3-2-1_52KEC_2016-07-16_final.stac-item
2016-07-16 10:57:59	ga_s2am_ard_3-2-1_52KGG_2016-07-16_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50KNU_2016-07-21_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50KQA_2016-07-21_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50KLU_2016-07-21_final.stac-item
2016-07-22 11:22:31	ga_s2am_ard_3-2-1_51HUC_2016-07-22_final.stac-item
2016-07-22 11:22:31	ga_s2am_ard_3-2-1_51HXC_2016-07-22_final.stac-item
2016-07-22 11:22:31	ga_s2am_ard_3-2-1_51KWQ_2016-07-22_final.stac-item
2016-07-22 11:22:31	ga_s2am_ard_3-2-1_52KBU_2016-07-22_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_49JGL_2016-07-24_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_50JKT_2016-07-24_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_50JLT_2016-07-24_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_50JMR_2016-07-24_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_49JGM_2016-07-24_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_49JHN_2016-07-24_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_50JKR_2016-07-24_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_50JKS_2016-07-24_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_50JLS_2016-07-24_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_51KTR_2016-07-28_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_51KUQ_2016-07-28_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_50KMC_2016-08-03_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_50KNC_2016-08-03_final.stac-item
2016-08-04 11:32:03	ga_s2am_ard_3-2-1_51JTM_2016-08-04_final.stac-item
2016-08-04 11:32:03	ga_s2am_ard_3-2-1_51JUM_2016-08-04_final.stac-item
2016-08-04 11:32:03	ga_s2am_ard_3-2-1_51JWL_2016-08-04_final.stac-item
2016-08-12 10:48:11	ga_s2am_ard_3-2-1_52JFT_2016-08-12_final.stac-item
2016-08-12 10:48:11	ga_s2am_ard_3-2-1_52JGR_2016-08-12_final.stac-item
2016-08-12 10:48:11	ga_s2am_ard_3-2-1_52JGT_2016-08-12_final.stac-item
2016-08-12 10:48:11	ga_s2am_ard_3-2-1_52JHS_2016-08-12_final.stac-item
2016-08-12 10:48:11	ga_s2am_ard_3-2-1_52KGA_2016-08-12_final.stac-item
2016-08-16 12:14:44	ga_s2am_ard_3-2-1_49JGL_2016-08-16_final.stac-item
2016-08-17 11:40:15	ga_s2am_ard_3-2-1_51LUC_2016-08-17_final.stac-item
2016-08-25 10:57:17	ga_s2am_ard_3-2-1_52KEC_2016-08-25_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KGP_2016-08-26_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KGQ_2016-08-26_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KHR_2016-08-26_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_50KKA_2016-08-26_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49JGM_2016-08-26_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KHQ_2016-08-26_final.stac-item
2016-08-31 11:22:38	ga_s2am_ard_3-2-1_51KXS_2016-08-31_final.stac-item
2016-08-31 11:22:38	ga_s2am_ard_3-2-1_51KYT_2016-08-31_final.stac-item
2016-08-31 11:22:38	ga_s2am_ard_3-2-1_52KCC_2016-08-31_final.stac-item
2023-01-06 11:50:32	ga_s2am_ard_3-2-1_51LTJ_2023-01-06_nrt.stac-item
2023-01-06 11:50:47	ga_s2am_ard_3-2-1_51LTH_2023-01-06_nrt.stac-item
2023-01-06 11:51:01	ga_s2am_ard_3-2-1_51LTG_2023-01-06_nrt.stac-item
2023-01-06 11:51:16	ga_s2am_ard_3-2-1_51LTF_2023-01-06_nrt.stac-item
2023-01-06 11:51:30	ga_s2am_ard_3-2-1_51LTE_2023-01-06_nrt.stac-item
2023-01-06 11:52:15	ga_s2am_ard_3-2-1_50KRG_2023-01-06_nrt.stac-item
2023-01-06 11:52:27	ga_s2am_ard_3-2-1_50KNG_2023-01-06_nrt.stac-item
2023-01-06 11:52:29	ga_s2am_ard_3-2-1_50KRF_2023-01-06_nrt.stac-item
2023-01-06 11:52:40	ga_s2am_ard_3-2-1_50KNF_2023-01-06_nrt.stac-item
2023-01-06 11:52:44	ga_s2am_ard_3-2-1_50KRE_2023-01-06_nrt.stac-item
2023-01-06 11:52:54	ga_s2am_ard_3-2-1_50KNE_2023-01-06_nrt.stac-item
2023-01-06 11:53:09	ga_s2am_ard_3-2-1_50KND_2023-01-06_nrt.stac-item
2023-01-06 11:56:28	ga_s2am_ard_3-2-1_50JKL_2023-01-06_nrt.stac-item
2023-01-06 11:56:32	ga_s2am_ard_3-2-1_49JGF_2023-01-06_nrt.stac-item
2023-01-06 11:57:21	ga_s2am_ard_3-2-1_49HFC_2023-01-06_nrt.stac-item
2023-01-06 11:57:24	ga_s2am_ard_3-2-1_49HGB_2023-01-06_nrt.stac-item
2023-01-06 11:57:27	ga_s2am_ard_3-2-1_49HFB_2023-01-06_nrt.stac-item

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