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
2022-08-09 11:56:08	ga_s2am_ard_3-2-1_50JLN_2022-08-09_final.stac-item
2022-08-09 11:56:11	ga_s2am_ard_3-2-1_50JKN_2022-08-09_final.stac-item
2022-08-09 11:56:16	ga_s2am_ard_3-2-1_50JNM_2022-08-09_final.stac-item
2022-08-09 11:56:19	ga_s2am_ard_3-2-1_50JMM_2022-08-09_final.stac-item
2022-08-09 11:56:23	ga_s2am_ard_3-2-1_50JLM_2022-08-09_final.stac-item
2022-08-09 11:56:26	ga_s2am_ard_3-2-1_50JKM_2022-08-09_final.stac-item
2022-08-09 11:56:30	ga_s2am_ard_3-2-1_50JNL_2022-08-09_final.stac-item
2022-08-09 11:56:34	ga_s2am_ard_3-2-1_50JML_2022-08-09_final.stac-item
2022-08-09 11:56:37	ga_s2am_ard_3-2-1_50JLL_2022-08-09_final.stac-item
2022-08-09 11:56:41	ga_s2am_ard_3-2-1_50HNK_2022-08-09_final.stac-item
2022-08-09 11:56:48	ga_s2am_ard_3-2-1_50HMK_2022-08-09_final.stac-item
2022-08-09 11:56:52	ga_s2am_ard_3-2-1_50HLK_2022-08-09_final.stac-item
2022-08-09 11:57:03	ga_s2am_ard_3-2-1_50HMJ_2022-08-09_final.stac-item
2022-08-09 11:57:06	ga_s2am_ard_3-2-1_50HLJ_2022-08-09_final.stac-item
2022-08-09 11:57:17	ga_s2am_ard_3-2-1_50HMH_2022-08-09_final.stac-item
2022-08-09 11:57:21	ga_s2am_ard_3-2-1_50HLH_2022-08-09_final.stac-item
2022-08-10 09:41:35	ga_s2am_ard_3-2-1_56KMG_2022-08-10_final
2022-08-10 09:41:39	ga_s2am_ard_3-2-1_56KLG_2022-08-10_final
2022-08-10 09:41:41	ga_s2am_ard_3-2-1_56KKG_2022-08-10_final
2022-08-10 09:41:44	ga_s2am_ard_3-2-1_55KHB_2022-08-10_final
2022-08-10 09:41:50	ga_s2am_ard_3-2-1_56KMF_2022-08-10_final
2022-08-10 09:41:53	ga_s2am_ard_3-2-1_56KLF_2022-08-10_final.stac-item
2022-08-10 09:41:56	ga_s2am_ard_3-2-1_56KKF_2022-08-10_final.stac-item
2022-08-10 09:42:04	ga_s2am_ard_3-2-1_56KME_2022-08-10_final
2022-08-10 09:42:08	ga_s2am_ard_3-2-1_56KLE_2022-08-10_final.stac-item
2022-08-10 09:42:16	ga_s2am_ard_3-2-1_56KMD_2022-08-10_final
2022-08-10 09:42:18	ga_s2am_ard_3-2-1_56KLD_2022-08-10_final.stac-item
2022-08-10 09:46:45	ga_s2am_ard_3-2-1_55HFB_2022-08-10_final.stac-item
2022-08-10 09:46:47	ga_s2am_ard_3-2-1_55HEB_2022-08-10_final.stac-item
2022-08-10 09:46:48	ga_s2am_ard_3-2-1_55HDB_2022-08-10_final.stac-item
2022-08-10 09:46:51	ga_s2am_ard_3-2-1_55HCB_2022-08-10_final.stac-item
2022-08-10 09:46:54	ga_s2am_ard_3-2-1_55HFA_2022-08-10_final.stac-item
2022-08-10 09:46:57	ga_s2am_ard_3-2-1_55HEA_2022-08-10_final.stac-item
2022-08-10 09:47:01	ga_s2am_ard_3-2-1_55HDA_2022-08-10_final.stac-item
2022-08-10 09:47:04	ga_s2am_ard_3-2-1_55HCA_2022-08-10_final.stac-item
2022-08-10 09:47:08	ga_s2am_ard_3-2-1_55HFV_2022-08-10_final.stac-item
2022-08-10 09:47:12	ga_s2am_ard_3-2-1_55HEV_2022-08-10_final.stac-item
2022-08-10 09:47:16	ga_s2am_ard_3-2-1_55HDV_2022-08-10_final.stac-item
2022-08-10 09:47:19	ga_s2am_ard_3-2-1_55HCV_2022-08-10_final.stac-item
2022-08-10 09:47:26	ga_s2am_ard_3-2-1_55HEU_2022-08-10_final.stac-item
2022-08-10 09:47:30	ga_s2am_ard_3-2-1_55HDU_2022-08-10_final.stac-item
2022-08-10 09:47:34	ga_s2am_ard_3-2-1_55HCU_2022-08-10_final.stac-item
2022-08-10 09:47:41	ga_s2am_ard_3-2-1_55HET_2022-08-10_final.stac-item
2022-08-10 09:47:41	ga_s2am_ard_3-2-1_55HBU_2022-08-10_final.stac-item
2022-08-10 09:47:45	ga_s2am_ard_3-2-1_55HDT_2022-08-10_final.stac-item
2022-08-10 09:47:48	ga_s2am_ard_3-2-1_55HCT_2022-08-10_final.stac-item
2022-08-10 09:47:52	ga_s2am_ard_3-2-1_55HBT_2022-08-10_final.stac-item
2022-08-10 09:47:55	ga_s2am_ard_3-2-1_55HES_2022-08-10_final.stac-item
2022-08-10 09:47:56	ga_s2am_ard_3-2-1_54HYC_2022-08-10_final.stac-item
2022-08-10 09:47:59	ga_s2am_ard_3-2-1_55HDS_2022-08-10_final.stac-item
2022-08-10 09:48:02	ga_s2am_ard_3-2-1_55HCS_2022-08-10_final.stac-item
2022-08-10 09:48:06	ga_s2am_ard_3-2-1_55HBS_2022-08-10_final.stac-item
2022-08-10 09:48:07	ga_s2am_ard_3-2-1_54HYB_2022-08-10_final.stac-item
2022-08-10 09:48:10	ga_s2am_ard_3-2-1_55GER_2022-08-10_final.stac-item
2022-08-10 09:48:14	ga_s2am_ard_3-2-1_55GDR_2022-08-10_final.stac-item
2022-08-10 09:48:17	ga_s2am_ard_3-2-1_55GCR_2022-08-10_final.stac-item
2022-08-10 09:48:20	ga_s2am_ard_3-2-1_55GBR_2022-08-10_final.stac-item
2022-08-10 09:48:20	ga_s2am_ard_3-2-1_54GYA_2022-08-10_final.stac-item
2022-08-10 09:48:23	ga_s2am_ard_3-2-1_55GEQ_2022-08-10_final.stac-item
2022-08-10 09:48:28	ga_s2am_ard_3-2-1_55GDQ_2022-08-10_final.stac-item
2022-08-10 09:48:32	ga_s2am_ard_3-2-1_55GCQ_2022-08-10_final.stac-item
2022-08-10 09:48:34	ga_s2am_ard_3-2-1_55GEP_2022-08-10_final.stac-item
2022-08-10 09:48:42	ga_s2am_ard_3-2-1_55GDP_2022-08-10_final.stac-item
2022-08-10 09:48:46	ga_s2am_ard_3-2-1_55GCP_2022-08-10_final.stac-item
2022-08-10 09:48:57	ga_s2am_ard_3-2-1_55GDN_2022-08-10_final.stac-item
2022-08-10 09:49:01	ga_s2am_ard_3-2-1_55GCN_2022-08-10_final.stac-item
2022-08-10 11:21:37	ga_s2am_ard_3-2-1_51LZE_2022-08-10_final.stac-item
2022-08-10 11:21:52	ga_s2am_ard_3-2-1_51LZD_2022-08-10_final.stac-item
2022-08-10 11:22:05	ga_s2am_ard_3-2-1_52LBH_2022-08-10_final.stac-item
2022-08-10 11:22:06	ga_s2am_ard_3-2-1_51LZC_2022-08-10_final.stac-item
2022-08-10 11:22:11	ga_s2am_ard_3-2-1_51LYC_2022-08-10_final.stac-item
2022-08-10 11:22:12	ga_s2am_ard_3-2-1_52KDG_2022-08-10_final.stac-item
2022-08-10 11:22:16	ga_s2am_ard_3-2-1_52KCG_2022-08-10_final.stac-item
2022-08-10 11:22:20	ga_s2am_ard_3-2-1_52KBG_2022-08-10_final.stac-item
2022-08-10 11:22:21	ga_s2am_ard_3-2-1_51KZB_2022-08-10_final.stac-item
2022-08-10 11:22:24	ga_s2am_ard_3-2-1_51KYB_2022-08-10_final.stac-item
2022-08-10 11:22:24	ga_s2am_ard_3-2-1_52KDF_2022-08-10_final.stac-item
2022-08-10 11:22:31	ga_s2am_ard_3-2-1_52KCF_2022-08-10_final.stac-item
2022-08-10 11:22:34	ga_s2am_ard_3-2-1_52KBF_2022-08-10_final.stac-item
2022-08-10 11:22:35	ga_s2am_ard_3-2-1_51KZA_2022-08-10_final.stac-item
2022-08-10 11:22:39	ga_s2am_ard_3-2-1_51KYA_2022-08-10_final.stac-item
2022-08-10 11:22:45	ga_s2am_ard_3-2-1_52KCE_2022-08-10_final.stac-item
2022-08-10 11:22:49	ga_s2am_ard_3-2-1_52KBE_2022-08-10_final.stac-item
2022-08-10 11:22:50	ga_s2am_ard_3-2-1_51KZV_2022-08-10_final.stac-item
2022-08-10 11:22:53	ga_s2am_ard_3-2-1_51KYV_2022-08-10_final.stac-item
2022-08-10 11:23:00	ga_s2am_ard_3-2-1_52KCD_2022-08-10_final.stac-item
2022-08-10 11:23:03	ga_s2am_ard_3-2-1_52KBD_2022-08-10_final.stac-item
2022-08-10 11:23:04	ga_s2am_ard_3-2-1_51KZU_2022-08-10_final.stac-item
2022-08-10 11:23:08	ga_s2am_ard_3-2-1_51KYU_2022-08-10_final.stac-item
2022-08-10 11:23:12	ga_s2am_ard_3-2-1_51KXU_2022-08-10_final.stac-item
2022-08-10 11:23:15	ga_s2am_ard_3-2-1_52KCC_2022-08-10_final.stac-item
2022-08-10 11:23:18	ga_s2am_ard_3-2-1_52KBC_2022-08-10_final.stac-item
2022-08-10 11:23:18	ga_s2am_ard_3-2-1_51KZT_2022-08-10_final.stac-item
2022-08-10 11:23:22	ga_s2am_ard_3-2-1_51KYT_2022-08-10_final.stac-item
2022-08-10 11:23:25	ga_s2am_ard_3-2-1_51KXT_2022-08-10_final.stac-item
2022-08-10 11:23:28	ga_s2am_ard_3-2-1_52KCB_2022-08-10_final.stac-item
2022-08-10 11:23:32	ga_s2am_ard_3-2-1_52KBB_2022-08-10_final.stac-item
2022-08-10 11:23:33	ga_s2am_ard_3-2-1_51KZS_2022-08-10_final.stac-item
2022-08-10 11:23:37	ga_s2am_ard_3-2-1_51KYS_2022-08-10_final.stac-item
2022-08-10 11:23:39	ga_s2am_ard_3-2-1_52KCA_2022-08-10_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