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:

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First 100 results (query limit)

Time (local)	Label
2022-04-23 10:50:28	ga_s2am_ard_3-2-1_53LNH_2022-04-23_final
2022-04-23 10:50:32	ga_s2am_ard_3-2-1_53LMH_2022-04-23_final
2022-04-23 10:50:43	ga_s2am_ard_3-2-1_53LNG_2022-04-23_final.stac-item
2022-04-23 10:50:46	ga_s2am_ard_3-2-1_53LMG_2022-04-23_final.stac-item
2022-04-23 10:50:52	ga_s2am_ard_3-2-1_53LLG_2022-04-23_final.stac-item
2022-04-23 10:50:58	ga_s2am_ard_3-2-1_53LNF_2022-04-23_final.stac-item
2022-04-23 10:51:01	ga_s2am_ard_3-2-1_53LMF_2022-04-23_final.stac-item
2022-04-23 10:51:04	ga_s2am_ard_3-2-1_53LLF_2022-04-23_final.stac-item
2022-04-23 10:51:12	ga_s2am_ard_3-2-1_53LNE_2022-04-23_final.stac-item
2022-04-23 10:51:15	ga_s2am_ard_3-2-1_53LME_2022-04-23_final.stac-item
2022-04-23 10:51:18	ga_s2am_ard_3-2-1_53LLE_2022-04-23_final.stac-item
2022-04-23 10:51:23	ga_s2am_ard_3-2-1_53LPD_2022-04-23_final.stac-item
2022-04-23 10:51:27	ga_s2am_ard_3-2-1_53LND_2022-04-23_final.stac-item
2022-04-23 10:51:30	ga_s2am_ard_3-2-1_53LMD_2022-04-23_final.stac-item
2022-04-23 10:51:33	ga_s2am_ard_3-2-1_53LLD_2022-04-23_final.stac-item
2022-04-23 10:51:36	ga_s2am_ard_3-2-1_53LPC_2022-04-23_final.stac-item
2022-04-23 10:51:41	ga_s2am_ard_3-2-1_53LNC_2022-04-23_final.stac-item
2022-04-23 10:51:44	ga_s2am_ard_3-2-1_53LMC_2022-04-23_final.stac-item
2022-04-23 10:51:46	ga_s2am_ard_3-2-1_53KPB_2022-04-23_final.stac-item
2022-04-23 10:51:48	ga_s2am_ard_3-2-1_53LLC_2022-04-23_final.stac-item
2022-04-23 10:51:55	ga_s2am_ard_3-2-1_53KNB_2022-04-23_final.stac-item
2022-04-23 10:51:59	ga_s2am_ard_3-2-1_53KMB_2022-04-23_final.stac-item
2022-04-23 10:52:02	ga_s2am_ard_3-2-1_53KLB_2022-04-23_final.stac-item
2022-04-23 10:52:06	ga_s2am_ard_3-2-1_53KKB_2022-04-23_final.stac-item
2022-04-23 10:52:10	ga_s2am_ard_3-2-1_53KNA_2022-04-23_final.stac-item
2022-04-23 10:52:13	ga_s2am_ard_3-2-1_53KMA_2022-04-23_final.stac-item
2022-04-23 10:52:17	ga_s2am_ard_3-2-1_53KLA_2022-04-23_final.stac-item
2022-04-23 10:52:20	ga_s2am_ard_3-2-1_53KKA_2022-04-23_final.stac-item
2022-04-23 10:52:24	ga_s2am_ard_3-2-1_52KHF_2022-04-23_final.stac-item
2022-04-23 10:52:25	ga_s2am_ard_3-2-1_53KNV_2022-04-23_final.stac-item
2022-04-23 10:52:28	ga_s2am_ard_3-2-1_53KMV_2022-04-23_final.stac-item
2022-04-23 10:52:31	ga_s2am_ard_3-2-1_53KLV_2022-04-23_final.stac-item
2022-04-23 10:52:34	ga_s2am_ard_3-2-1_53KKV_2022-04-23_final.stac-item
2022-04-23 10:52:36	ga_s2am_ard_3-2-1_52KHE_2022-04-23_final.stac-item
2022-04-23 10:52:38	ga_s2am_ard_3-2-1_53KNU_2022-04-23_final.stac-item
2022-04-23 10:52:42	ga_s2am_ard_3-2-1_53KMU_2022-04-23_final.stac-item
2022-04-23 10:52:46	ga_s2am_ard_3-2-1_53KLU_2022-04-23_final.stac-item
2022-04-23 10:52:49	ga_s2am_ard_3-2-1_53KKU_2022-04-23_final.stac-item
2022-04-23 10:52:49	ga_s2am_ard_3-2-1_52KHD_2022-04-23_final.stac-item
2022-04-23 10:52:50	ga_s2am_ard_3-2-1_53KNT_2022-04-23_final.stac-item
2022-04-23 10:52:57	ga_s2am_ard_3-2-1_53KMT_2022-04-23_final.stac-item
2022-04-23 10:53:00	ga_s2am_ard_3-2-1_53KLT_2022-04-23_final.stac-item
2022-04-23 10:53:04	ga_s2am_ard_3-2-1_53KKT_2022-04-23_final.stac-item
2022-04-23 10:53:04	ga_s2am_ard_3-2-1_52KHC_2022-04-23_final.stac-item
2022-04-23 10:53:11	ga_s2am_ard_3-2-1_53KMS_2022-04-23_final.stac-item
2022-04-23 10:53:15	ga_s2am_ard_3-2-1_53KLS_2022-04-23_final.stac-item
2022-04-23 10:53:18	ga_s2am_ard_3-2-1_53KKS_2022-04-23_final.stac-item
2022-04-23 10:53:19	ga_s2am_ard_3-2-1_52KHB_2022-04-23_final.stac-item
2022-04-23 10:53:25	ga_s2am_ard_3-2-1_52KGB_2022-04-23_final.stac-item
2022-04-23 10:53:26	ga_s2am_ard_3-2-1_53KMR_2022-04-23_final.stac-item
2022-04-23 10:53:30	ga_s2am_ard_3-2-1_53KLR_2022-04-23_final.stac-item
2022-04-23 10:53:33	ga_s2am_ard_3-2-1_53KKR_2022-04-23_final.stac-item
2022-04-23 10:53:33	ga_s2am_ard_3-2-1_52KHA_2022-04-23_final.stac-item
2022-04-23 10:53:37	ga_s2am_ard_3-2-1_52KGA_2022-04-23_final.stac-item
2022-04-23 10:53:41	ga_s2am_ard_3-2-1_53KMQ_2022-04-23_final.stac-item
2022-04-23 10:53:44	ga_s2am_ard_3-2-1_53KLQ_2022-04-23_final.stac-item
2022-04-23 10:53:47	ga_s2am_ard_3-2-1_53KKQ_2022-04-23_final.stac-item
2022-04-23 10:53:47	ga_s2am_ard_3-2-1_52KHV_2022-04-23_final.stac-item
2022-04-23 10:53:51	ga_s2am_ard_3-2-1_52KGV_2022-04-23_final.stac-item
2022-04-23 10:53:54	ga_s2am_ard_3-2-1_53KMP_2022-04-23_final.stac-item
2022-04-23 10:53:58	ga_s2am_ard_3-2-1_53KLP_2022-04-23_final.stac-item
2022-04-23 10:54:02	ga_s2am_ard_3-2-1_53KKP_2022-04-23_final.stac-item
2022-04-23 10:54:02	ga_s2am_ard_3-2-1_52KHU_2022-04-23_final.stac-item
2022-04-23 10:54:04	ga_s2am_ard_3-2-1_53JMN_2022-04-23_final.stac-item
2022-04-23 10:54:06	ga_s2am_ard_3-2-1_52KGU_2022-04-23_final.stac-item
2022-04-23 10:54:13	ga_s2am_ard_3-2-1_53JLN_2022-04-23_final.stac-item
2022-04-23 10:54:16	ga_s2am_ard_3-2-1_52JHT_2022-04-23_final.stac-item
2022-04-23 10:54:17	ga_s2am_ard_3-2-1_53JKN_2022-04-23_final.stac-item
2022-04-23 10:54:20	ga_s2am_ard_3-2-1_52JGT_2022-04-23_final.stac-item
2022-04-23 10:54:26	ga_s2am_ard_3-2-1_52JFT_2022-04-23_final.stac-item
2022-04-23 10:54:28	ga_s2am_ard_3-2-1_53JLM_2022-04-23_final.stac-item
2022-04-23 10:54:31	ga_s2am_ard_3-2-1_52JHS_2022-04-23_final.stac-item
2022-04-23 10:54:31	ga_s2am_ard_3-2-1_53JKM_2022-04-23_final.stac-item
2022-04-23 10:54:34	ga_s2am_ard_3-2-1_52JGS_2022-04-23_final.stac-item
2022-04-23 10:54:38	ga_s2am_ard_3-2-1_52JFS_2022-04-23_final.stac-item
2022-04-23 10:54:42	ga_s2am_ard_3-2-1_53JLL_2022-04-23_final.stac-item
2022-04-23 10:54:46	ga_s2am_ard_3-2-1_53JKL_2022-04-23_final.stac-item
2022-04-23 10:54:49	ga_s2am_ard_3-2-1_52JGR_2022-04-23_final.stac-item
2022-04-23 10:54:52	ga_s2am_ard_3-2-1_52JFR_2022-04-23_final.stac-item
2022-04-23 10:54:57	ga_s2am_ard_3-2-1_53JLK_2022-04-23_final.stac-item
2022-04-23 10:55:00	ga_s2am_ard_3-2-1_53JKK_2022-04-23_final.stac-item
2022-04-23 10:55:03	ga_s2am_ard_3-2-1_52JGQ_2022-04-23_final.stac-item
2022-04-23 10:55:07	ga_s2am_ard_3-2-1_52JFQ_2022-04-23_final.stac-item
2022-04-23 10:55:10	ga_s2am_ard_3-2-1_53JLJ_2022-04-23_final.stac-item
2022-04-23 10:55:15	ga_s2am_ard_3-2-1_53JKJ_2022-04-23_final.stac-item
2022-04-23 10:55:18	ga_s2am_ard_3-2-1_52JGP_2022-04-23_final.stac-item
2022-04-23 10:55:20	ga_s2am_ard_3-2-1_53JLH_2022-04-23_final.stac-item
2022-04-23 10:55:21	ga_s2am_ard_3-2-1_52JFP_2022-04-23_final.stac-item
2022-04-23 10:55:27	ga_s2am_ard_3-2-1_52JEP_2022-04-23_final.stac-item
2022-04-23 10:55:29	ga_s2am_ard_3-2-1_53JKH_2022-04-23_final.stac-item
2022-04-23 10:55:32	ga_s2am_ard_3-2-1_52JGN_2022-04-23_final.stac-item
2022-04-23 10:55:36	ga_s2am_ard_3-2-1_52JFN_2022-04-23_final.stac-item
2022-04-23 10:55:39	ga_s2am_ard_3-2-1_52JEN_2022-04-23_final.stac-item
2022-04-23 10:55:44	ga_s2am_ard_3-2-1_53JKG_2022-04-23_final.stac-item
2022-04-23 10:55:47	ga_s2am_ard_3-2-1_52JGM_2022-04-23_final.stac-item
2022-04-23 10:55:50	ga_s2am_ard_3-2-1_52JFM_2022-04-23_final.stac-item
2022-04-23 10:55:54	ga_s2am_ard_3-2-1_52JEM_2022-04-23_final.stac-item
2022-04-23 10:55:59	ga_s2am_ard_3-2-1_53JKF_2022-04-23_final.stac-item
2022-04-23 10:56:01	ga_s2am_ard_3-2-1_52JGL_2022-04-23_final.stac-item
2022-04-23 10:56:05	ga_s2am_ard_3-2-1_52JFL_2022-04-23_final.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