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
2023-02-07 10:50:34	ga_s2am_ard_3-2-1_53LPG_2023-02-07_final
2023-02-07 10:50:37	ga_s2am_ard_3-2-1_53LNG_2023-02-07_final
2023-02-07 10:50:46	ga_s2am_ard_3-2-1_53LLG_2023-02-07_final
2023-02-07 10:50:48	ga_s2am_ard_3-2-1_53LPF_2023-02-07_final
2023-02-07 10:50:58	ga_s2am_ard_3-2-1_53LLF_2023-02-07_final
2023-02-07 10:51:10	ga_s2am_ard_3-2-1_53LME_2023-02-07_final
2023-02-07 10:51:12	ga_s2am_ard_3-2-1_53LLE_2023-02-07_final
2023-02-07 10:51:17	ga_s2am_ard_3-2-1_53LPD_2023-02-07_final
2023-02-07 10:51:24	ga_s2am_ard_3-2-1_53LMD_2023-02-07_final
2023-02-07 10:51:27	ga_s2am_ard_3-2-1_53LLD_2023-02-07_final
2023-02-07 10:51:30	ga_s2am_ard_3-2-1_53LPC_2023-02-07_final
2023-02-07 10:51:39	ga_s2am_ard_3-2-1_53LMC_2023-02-07_final
2023-02-07 10:51:42	ga_s2am_ard_3-2-1_53LLC_2023-02-07_final
2023-02-07 10:51:53	ga_s2am_ard_3-2-1_53KMB_2023-02-07_final
2023-02-07 10:52:00	ga_s2am_ard_3-2-1_53KKB_2023-02-07_final
2023-02-07 10:52:04	ga_s2am_ard_3-2-1_53KNA_2023-02-07_final
2023-02-07 10:52:08	ga_s2am_ard_3-2-1_53KMA_2023-02-07_final
2023-02-07 10:52:14	ga_s2am_ard_3-2-1_53KKA_2023-02-07_final
2023-02-07 10:52:18	ga_s2am_ard_3-2-1_52KHF_2023-02-07_final
2023-02-07 10:52:23	ga_s2am_ard_3-2-1_53KKV_2023-02-07_final
2023-02-07 10:52:27	ga_s2am_ard_3-2-1_53KMV_2023-02-07_final
2023-02-07 10:52:29	ga_s2am_ard_3-2-1_53KLV_2023-02-07_final
2023-02-07 10:52:31	ga_s2am_ard_3-2-1_52KHE_2023-02-07_final
2023-02-07 10:52:37	ga_s2am_ard_3-2-1_53KMU_2023-02-07_final
2023-02-07 10:52:40	ga_s2am_ard_3-2-1_53KLU_2023-02-07_final
2023-02-07 10:52:43	ga_s2am_ard_3-2-1_53KKU_2023-02-07_final
2023-02-07 10:52:44	ga_s2am_ard_3-2-1_52KHD_2023-02-07_final
2023-02-07 10:52:51	ga_s2am_ard_3-2-1_53KMT_2023-02-07_final
2023-02-07 10:52:55	ga_s2am_ard_3-2-1_53KLT_2023-02-07_final
2023-02-07 10:52:58	ga_s2am_ard_3-2-1_53KKT_2023-02-07_final
2023-02-07 10:53:06	ga_s2am_ard_3-2-1_53KMS_2023-02-07_final
2023-02-07 10:53:09	ga_s2am_ard_3-2-1_53KLS_2023-02-07_final
2023-02-07 10:53:12	ga_s2am_ard_3-2-1_53KKS_2023-02-07_final
2023-02-07 10:53:19	ga_s2am_ard_3-2-1_52KGB_2023-02-07_final
2023-02-07 10:53:20	ga_s2am_ard_3-2-1_53KMR_2023-02-07_final
2023-02-07 10:53:24	ga_s2am_ard_3-2-1_53KLR_2023-02-07_final
2023-02-07 10:53:27	ga_s2am_ard_3-2-1_53KKR_2023-02-07_final
2023-02-07 10:53:27	ga_s2am_ard_3-2-1_52KHA_2023-02-07_final
2023-02-07 10:53:31	ga_s2am_ard_3-2-1_52KGA_2023-02-07_final
2023-02-07 10:53:35	ga_s2am_ard_3-2-1_53KMQ_2023-02-07_final
2023-02-07 10:53:38	ga_s2am_ard_3-2-1_53KLQ_2023-02-07_final
2023-02-07 10:53:42	ga_s2am_ard_3-2-1_53KKQ_2023-02-07_final
2023-02-07 10:53:42	ga_s2am_ard_3-2-1_52KHV_2023-02-07_final
2023-02-07 10:53:45	ga_s2am_ard_3-2-1_52KGV_2023-02-07_final
2023-02-07 10:53:48	ga_s2am_ard_3-2-1_53KMP_2023-02-07_final
2023-02-07 10:53:53	ga_s2am_ard_3-2-1_53KLP_2023-02-07_final
2023-02-07 10:53:56	ga_s2am_ard_3-2-1_53KKP_2023-02-07_final
2023-02-07 10:53:56	ga_s2am_ard_3-2-1_52KHU_2023-02-07_final
2023-02-07 10:53:58	ga_s2am_ard_3-2-1_53JMN_2023-02-07_final
2023-02-07 10:54:00	ga_s2am_ard_3-2-1_52KGU_2023-02-07_final
2023-02-07 10:54:07	ga_s2am_ard_3-2-1_53JLN_2023-02-07_final
2023-02-07 10:54:11	ga_s2am_ard_3-2-1_52JHT_2023-02-07_final
2023-02-07 10:54:11	ga_s2am_ard_3-2-1_53JKN_2023-02-07_final
2023-02-07 10:54:14	ga_s2am_ard_3-2-1_52JGT_2023-02-07_final
2023-02-07 10:54:20	ga_s2am_ard_3-2-1_52JFT_2023-02-07_final
2023-02-07 10:54:22	ga_s2am_ard_3-2-1_53JLM_2023-02-07_final
2023-02-07 10:54:25	ga_s2am_ard_3-2-1_52JHS_2023-02-07_final
2023-02-07 10:54:25	ga_s2am_ard_3-2-1_53JKM_2023-02-07_final
2023-02-07 10:54:29	ga_s2am_ard_3-2-1_52JGS_2023-02-07_final
2023-02-07 10:54:32	ga_s2am_ard_3-2-1_52JFS_2023-02-07_final
2023-02-07 10:54:37	ga_s2am_ard_3-2-1_53JLL_2023-02-07_final
2023-02-07 10:54:40	ga_s2am_ard_3-2-1_53JKL_2023-02-07_final
2023-02-07 10:54:43	ga_s2am_ard_3-2-1_52JGR_2023-02-07_final
2023-02-07 10:54:46	ga_s2am_ard_3-2-1_52JFR_2023-02-07_final
2023-02-07 10:54:51	ga_s2am_ard_3-2-1_53JLK_2023-02-07_final
2023-02-07 10:54:54	ga_s2am_ard_3-2-1_53JKK_2023-02-07_final
2023-02-07 10:54:57	ga_s2am_ard_3-2-1_52JGQ_2023-02-07_final
2023-02-07 10:54:59	ga_s2am_ard_3-2-1_52JFQ_2023-02-07_final
2023-02-07 10:55:01	ga_s2am_ard_3-2-1_53JLJ_2023-02-07_final
2023-02-07 10:55:03	ga_s2am_ard_3-2-1_53JKK_2023-02-07_final
2023-02-07 10:55:03	ga_s2am_ard_3-2-1_53JKJ_2023-02-07_final
2023-02-07 10:55:04	ga_s2am_ard_3-2-1_52JGP_2023-02-07_final
2023-02-07 10:55:04	ga_s2am_ard_3-2-1_52JGQ_2023-02-07_final
2023-02-07 10:55:06	ga_s2am_ard_3-2-1_52JFQ_2023-02-07_final
2023-02-07 10:55:06	ga_s2am_ard_3-2-1_53JLJ_2023-02-07_final
2023-02-07 10:55:10	ga_s2am_ard_3-2-1_53JKJ_2023-02-07_final
2023-02-07 10:55:12	ga_s2am_ard_3-2-1_52JGP_2023-02-07_final
2023-02-07 10:55:14	ga_s2am_ard_3-2-1_53JLH_2023-02-07_final
2023-02-07 10:55:16	ga_s2am_ard_3-2-1_52JFP_2023-02-07_final
2023-02-07 10:55:21	ga_s2am_ard_3-2-1_52JEP_2023-02-07_final
2023-02-07 10:55:23	ga_s2am_ard_3-2-1_53JKH_2023-02-07_final
2023-02-07 10:55:26	ga_s2am_ard_3-2-1_52JGN_2023-02-07_final
2023-02-07 10:55:30	ga_s2am_ard_3-2-1_52JFN_2023-02-07_final
2023-02-07 10:55:33	ga_s2am_ard_3-2-1_52JEN_2023-02-07_final
2023-02-07 10:55:38	ga_s2am_ard_3-2-1_53JKG_2023-02-07_final
2023-02-07 10:55:41	ga_s2am_ard_3-2-1_52JGM_2023-02-07_final
2023-02-07 10:55:45	ga_s2am_ard_3-2-1_52JFM_2023-02-07_final
2023-02-07 10:55:48	ga_s2am_ard_3-2-1_52JEM_2023-02-07_final
2023-02-07 10:55:53	ga_s2am_ard_3-2-1_53JKF_2023-02-07_final
2023-02-07 10:55:55	ga_s2am_ard_3-2-1_52JGL_2023-02-07_final
2023-02-07 10:55:59	ga_s2am_ard_3-2-1_52JFL_2023-02-07_final
2023-02-07 10:56:03	ga_s2am_ard_3-2-1_52JEL_2023-02-07_final
2023-02-07 10:56:07	ga_s2am_ard_3-2-1_53HKE_2023-02-07_final
2023-02-07 10:56:09	ga_s2am_ard_3-2-1_52HGK_2023-02-07_final
2023-02-07 10:56:14	ga_s2am_ard_3-2-1_52HFK_2023-02-07_nrt.stac-item
2023-02-07 10:56:17	ga_s2am_ard_3-2-1_52HEK_2023-02-07_final
2023-02-07 10:56:18	ga_s2am_ard_3-2-1_53HKD_2023-02-07_final
2023-02-07 10:56:20	ga_s2am_ard_3-2-1_52HGJ_2023-02-07_nrt.stac-item
2023-02-07 10:56:21	ga_s2am_ard_3-2-1_52HDK_2023-02-07_final
2023-02-07 10:56:22	ga_s2am_ard_3-2-1_52HFJ_2023-02-07_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