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
2023-04-09 10:20:28	ga_s2am_ard_3-2-1_54LXM_2023-04-09_final
2023-04-09 10:20:36	ga_s2am_ard_3-2-1_54LZL_2023-04-09_final
2023-04-09 10:20:49	ga_s2am_ard_3-2-1_54LZK_2023-04-09_final
2023-04-09 10:21:00	ga_s2am_ard_3-2-1_54LWK_2023-04-09_final
2023-04-09 10:21:08	ga_s2am_ard_3-2-1_54LYJ_2023-04-09_final
2023-04-09 10:21:21	ga_s2am_ard_3-2-1_54LVJ_2023-04-09_final
2023-04-09 10:21:22	ga_s2am_ard_3-2-1_54LYH_2023-04-09_final
2023-04-09 10:21:33	ga_s2am_ard_3-2-1_54LVH_2023-04-09_final
2023-04-09 10:21:34	ga_s2am_ard_3-2-1_54KYG_2023-04-09_final
2023-04-09 10:21:38	ga_s2am_ard_3-2-1_54KWG_2023-04-09_final
2023-04-09 10:21:38	ga_s2am_ard_3-2-1_54LVH_2023-04-09_final
2023-04-09 10:21:41	ga_s2am_ard_3-2-1_54KYG_2023-04-09_final
2023-04-09 10:21:44	ga_s2am_ard_3-2-1_54KWG_2023-04-09_final
2023-04-09 10:22:09	ga_s2am_ard_3-2-1_54KXE_2023-04-09_final
2023-04-09 10:22:13	ga_s2am_ard_3-2-1_54KYD_2023-04-09_final
2023-04-09 10:22:16	ga_s2am_ard_3-2-1_54KVE_2023-04-09_final
2023-04-09 10:22:24	ga_s2am_ard_3-2-1_54KXD_2023-04-09_final
2023-04-09 10:22:35	ga_s2am_ard_3-2-1_54KUD_2023-04-09_final
2023-04-09 10:23:11	ga_s2am_ard_3-2-1_54KWA_2023-04-09_final
2023-04-09 10:23:14	ga_s2am_ard_3-2-1_54KVA_2023-04-09_final
2023-04-09 10:23:18	ga_s2am_ard_3-2-1_54KUA_2023-04-09_final
2023-04-09 10:23:25	ga_s2am_ard_3-2-1_54KWV_2023-04-09_final
2023-04-09 10:23:29	ga_s2am_ard_3-2-1_54KVV_2023-04-09_final
2023-04-09 10:23:32	ga_s2am_ard_3-2-1_54KUV_2023-04-09_final
2023-04-09 10:23:55	ga_s2am_ard_3-2-1_54JWT_2023-04-09_final
2023-04-09 10:24:04	ga_s2am_ard_3-2-1_53JRN_2023-04-09_final
2023-04-09 10:24:13	ga_s2am_ard_3-2-1_54JVS_2023-04-09_final
2023-04-09 10:24:27	ga_s2am_ard_3-2-1_54JVR_2023-04-09_final
2023-04-09 10:24:34	ga_s2am_ard_3-2-1_54JTR_2023-04-09_final
2023-04-09 10:24:45	ga_s2am_ard_3-2-1_54JUQ_2023-04-09_final
2023-04-09 10:24:51	ga_s2am_ard_3-2-1_53JQK_2023-04-09_final
2023-04-09 10:25:00	ga_s2am_ard_3-2-1_54JUP_2023-04-09_final
2023-04-09 10:25:03	ga_s2am_ard_3-2-1_54JTP_2023-04-09_final
2023-04-09 10:25:24	ga_s2am_ard_3-2-1_54JVM_2023-04-09_final
2023-04-09 10:25:35	ga_s2am_ard_3-2-1_53JQG_2023-04-09_final
2023-04-09 10:25:40	ga_s2am_ard_3-2-1_53JPG_2023-04-09_final
2023-04-09 10:25:43	ga_s2am_ard_3-2-1_54JUL_2023-04-09_final
2023-04-09 10:25:52	ga_s2am_ard_3-2-1_53JPF_2023-04-09_final
2023-04-09 10:26:22	ga_s2am_ard_3-2-1_53HPD_2023-04-09_final
2023-04-09 10:26:30	ga_s2am_ard_3-2-1_54HTH_2023-04-09_final
2023-04-09 10:26:40	ga_s2am_ard_3-2-1_54HUG_2023-04-09_final
2023-04-09 10:26:50	ga_s2am_ard_3-2-1_53HPB_2023-04-09_final
2023-04-09 10:26:51	ga_s2am_ard_3-2-1_54HUF_2023-04-09_final
2023-04-09 10:26:54	ga_s2am_ard_3-2-1_53HNB_2023-04-09_final
2023-04-09 10:27:01	ga_s2am_ard_3-2-1_53HQA_2023-04-09_final
2023-04-09 10:27:12	ga_s2am_ard_3-2-1_54HTE_2023-04-09_final
2023-04-09 10:27:13	ga_s2am_ard_3-2-1_53HQV_2023-04-09_final
2023-04-09 12:03:27	ga_s2am_ard_3-2-1_50KLC_2023-04-09_final
2023-04-09 12:03:38	ga_s2am_ard_3-2-1_50KMB_2023-04-09_final
2023-04-09 12:03:41	ga_s2am_ard_3-2-1_50KLB_2023-04-09_final
2023-04-09 12:03:45	ga_s2am_ard_3-2-1_49KHS_2023-04-09_final
2023-04-09 12:03:56	ga_s2am_ard_3-2-1_50KLA_2023-04-09_final
2023-04-09 12:03:59	ga_s2am_ard_3-2-1_49KHR_2023-04-09_final
2023-04-09 12:04:07	ga_s2am_ard_3-2-1_50KMV_2023-04-09_final
2023-04-09 12:04:14	ga_s2am_ard_3-2-1_49KHQ_2023-04-09_final
2023-04-09 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2023-04-09_final
2023-04-09 12:04:27	ga_s2am_ard_3-2-1_50KKU_2023-04-09_final
2023-04-09 12:04:29	ga_s2am_ard_3-2-1_49KGP_2023-04-09_final
2023-04-09 12:04:34	ga_s2am_ard_3-2-1_50KKU_2023-04-09_final
2023-04-09 12:04:34	ga_s2am_ard_3-2-1_50JKT_2023-04-09_final
2023-04-09 12:04:35	ga_s2am_ard_3-2-1_49KGP_2023-04-09_final
2023-04-09 12:04:42	ga_s2am_ard_3-2-1_49JHN_2023-04-09_final
2023-04-09 12:04:43	ga_s2am_ard_3-2-1_50JKT_2023-04-09_final
2023-04-09 12:04:58	ga_s2am_ard_3-2-1_50JMR_2023-04-09_final
2023-04-09 12:05:01	ga_s2am_ard_3-2-1_49JGM_2023-04-09_final
2023-04-09 12:05:08	ga_s2am_ard_3-2-1_50JLR_2023-04-09_final
2023-04-09 12:05:15	ga_s2am_ard_3-2-1_49JGL_2023-04-09_final
2023-04-09 12:05:26	ga_s2am_ard_3-2-1_50JKQ_2023-04-09_final
2023-04-09 12:05:38	ga_s2am_ard_3-2-1_50JLP_2023-04-09_final
2023-04-09 12:05:41	ga_s2am_ard_3-2-1_50JKP_2023-04-09_final
2023-04-09 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2023-04-09_final
2023-04-09 12:05:52	ga_s2am_ard_3-2-1_50JLN_2023-04-09_final
2023-04-09 12:05:58	ga_s2am_ard_3-2-1_49JGH_2023-04-09_final
2023-04-09 12:06:10	ga_s2am_ard_3-2-1_50JKM_2023-04-09_final
2023-04-09 12:06:14	ga_s2am_ard_3-2-1_50JLL_2023-04-09_final
2023-04-20 09:52:01	ga_s2am_ard_3-2-1_55KFV_2023-04-20_nrt
2023-04-20 11:30:25	ga_s2am_ard_3-2-1_51LYJ_2023-04-20_nrt
2023-04-20 11:30:34	ga_s2am_ard_3-2-1_52LBN_2023-04-20_nrt
2023-04-20 11:30:54	ga_s2am_ard_3-2-1_51LYG_2023-04-20_nrt
2023-04-20 11:37:22	ga_s2am_ard_3-2-1_50HQF_2023-04-20_nrt
2023-04-20 11:37:26	ga_s2am_ard_3-2-1_51HTA_2023-04-20_nrt
2023-04-20 11:37:27	ga_s2am_ard_3-2-1_50HQF_2023-04-20_nrt
2023-04-21 09:22:51	ga_s2am_ard_3-2-1_56KPA_2023-04-20_nrt
2023-04-21 09:23:20	ga_s2am_ard_3-2-1_56KPU_2023-04-20_nrt
2023-04-21 09:25:16	ga_s2am_ard_3-2-1_56JPL_2023-04-20_nrt
2023-04-21 09:25:31	ga_s2am_ard_3-2-1_56HPK_2023-04-20_nrt
2023-04-21 09:25:49	ga_s2am_ard_3-2-1_56HNJ_2023-04-20_nrt
2023-04-21 09:26:01	ga_s2am_ard_3-2-1_56HNH_2023-04-20_nrt
2023-04-21 09:26:06	ga_s2am_ard_3-2-1_56HPH_2023-04-20_nrt
2023-04-21 09:26:07	ga_s2am_ard_3-2-1_56HPG_2023-04-20_nrt
2023-04-21 09:26:32	ga_s2am_ard_3-2-1_56HNF_2023-04-20_nrt
2023-04-21 09:26:47	ga_s2am_ard_3-2-1_56HNE_2023-04-20_nrt
2023-04-21 09:27:01	ga_s2am_ard_3-2-1_56HND_2023-04-20_nrt
2023-04-21 09:27:13	ga_s2am_ard_3-2-1_56HNC_2023-04-20_nrt
2023-04-21 09:27:41	ga_s2am_ard_3-2-1_56HKB_2023-04-20_nrt
2023-04-21 09:27:49	ga_s2am_ard_3-2-1_56GMA_2023-04-20_nrt
2023-04-21 09:28:03	ga_s2am_ard_3-2-1_56GMV_2023-04-20_nrt
2023-04-21 09:28:07	ga_s2am_ard_3-2-1_56GLV_2023-04-20_nrt
2023-04-21 09:28:21	ga_s2am_ard_3-2-1_56GLU_2023-04-20_nrt
2023-04-21 09:28:36	ga_s2am_ard_3-2-1_56GLT_2023-04-20_nrt

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