Search ga_s2am_ard_3 on 15th March 2022

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2022-03-15 10:19:42	ga_s2am_ard_3-2-1_54LZQ_2022-03-15_final
2022-03-15 10:19:48	ga_s2am_ard_3-2-1_54LXQ_2022-03-15_final
2022-03-15 10:19:56	ga_s2am_ard_3-2-1_54LZP_2022-03-15_final
2022-03-15 10:20:17	ga_s2am_ard_3-2-1_54LXN_2022-03-15_final
2022-03-15 10:20:25	ga_s2am_ard_3-2-1_54LZM_2022-03-15_final
2022-03-15 10:20:28	ga_s2am_ard_3-2-1_54LYM_2022-03-15_final
2022-03-15 10:20:32	ga_s2am_ard_3-2-1_54LXM_2022-03-15_final
2022-03-15 10:21:04	ga_s2am_ard_3-2-1_54LWK_2022-03-15_final
2022-03-15 10:21:15	ga_s2am_ard_3-2-1_54LXJ_2022-03-15_final
2022-03-15 10:21:26	ga_s2am_ard_3-2-1_54LYH_2022-03-15_final
2022-03-15 10:21:59	ga_s2am_ard_3-2-1_54KXF_2022-03-15_final
2022-03-15 10:22:28	ga_s2am_ard_3-2-1_54KXD_2022-03-15_final
2022-03-15 10:22:31	ga_s2am_ard_3-2-1_54KWD_2022-03-15_final
2022-03-15 10:22:35	ga_s2am_ard_3-2-1_54KVD_2022-03-15_final
2022-03-15 10:22:39	ga_s2am_ard_3-2-1_54KUD_2022-03-15_final
2022-03-15 10:23:41	ga_s2am_ard_3-2-1_54KTV_2022-03-15_final
2022-03-15 10:23:51	ga_s2am_ard_3-2-1_54KUU_2022-03-15_final
2022-03-15 10:24:08	ga_s2am_ard_3-2-1_54JTT_2022-03-15_final
2022-03-15 10:24:12	ga_s2am_ard_3-2-1_54JWS_2022-03-15_final
2022-03-15 10:24:16	ga_s2am_ard_3-2-1_54JVS_2022-03-15_final
2022-03-15 10:24:23	ga_s2am_ard_3-2-1_54JTS_2022-03-15_final
2022-03-15 10:24:25	ga_s2am_ard_3-2-1_54JWR_2022-03-15_final
2022-03-15 10:24:31	ga_s2am_ard_3-2-1_54JVR_2022-03-15_final
2022-03-15 10:24:34	ga_s2am_ard_3-2-1_54JUR_2022-03-15_final
2022-03-15 10:24:38	ga_s2am_ard_3-2-1_54JTR_2022-03-15_final
2022-03-15 10:24:44	ga_s2am_ard_3-2-1_53JQL_2022-03-15_final
2022-03-15 10:24:45	ga_s2am_ard_3-2-1_54JVQ_2022-03-15_final
2022-03-15 10:24:49	ga_s2am_ard_3-2-1_54JUQ_2022-03-15_final
2022-03-15 10:24:52	ga_s2am_ard_3-2-1_54JTQ_2022-03-15_final
2022-03-15 10:24:55	ga_s2am_ard_3-2-1_53JQK_2022-03-15_final
2022-03-15 10:25:00	ga_s2am_ard_3-2-1_54JVP_2022-03-15_final
2022-03-15 10:25:03	ga_s2am_ard_3-2-1_54JUP_2022-03-15_final
2022-03-15 10:25:07	ga_s2am_ard_3-2-1_54JTP_2022-03-15_final
2022-03-15 10:25:09	ga_s2am_ard_3-2-1_53JQJ_2022-03-15_final
2022-03-15 10:25:15	ga_s2am_ard_3-2-1_54JVN_2022-03-15_final
2022-03-15 10:25:18	ga_s2am_ard_3-2-1_54JUN_2022-03-15_final
2022-03-15 10:25:21	ga_s2am_ard_3-2-1_54JTN_2022-03-15_final
2022-03-15 10:25:24	ga_s2am_ard_3-2-1_53JQH_2022-03-15_final
2022-03-15 10:25:28	ga_s2am_ard_3-2-1_54JVM_2022-03-15_final
2022-03-15 10:25:32	ga_s2am_ard_3-2-1_54JUM_2022-03-15_final
2022-03-15 10:25:36	ga_s2am_ard_3-2-1_54JTM_2022-03-15_final
2022-03-15 10:25:38	ga_s2am_ard_3-2-1_53JQG_2022-03-15_final
2022-03-15 10:25:39	ga_s2am_ard_3-2-1_54JVL_2022-03-15_final
2022-03-15 10:25:44	ga_s2am_ard_3-2-1_53JPG_2022-03-15_final
2022-03-15 10:25:47	ga_s2am_ard_3-2-1_54JUL_2022-03-15_final
2022-03-15 10:25:50	ga_s2am_ard_3-2-1_54JTL_2022-03-15_final
2022-03-15 10:25:53	ga_s2am_ard_3-2-1_53JQF_2022-03-15_final
2022-03-15 10:25:56	ga_s2am_ard_3-2-1_53JPF_2022-03-15_final
2022-03-15 10:26:01	ga_s2am_ard_3-2-1_54HUK_2022-03-15_final
2022-03-15 10:26:05	ga_s2am_ard_3-2-1_54HTK_2022-03-15_final
2022-03-15 10:26:07	ga_s2am_ard_3-2-1_53HQE_2022-03-15_final
2022-03-15 10:26:11	ga_s2am_ard_3-2-1_53HPE_2022-03-15_final
2022-03-15 10:26:16	ga_s2am_ard_3-2-1_54HUJ_2022-03-15_final
2022-03-15 10:26:26	ga_s2am_ard_3-2-1_53HPD_2022-03-15_final
2022-03-15 10:26:31	ga_s2am_ard_3-2-1_54HUH_2022-03-15_final
2022-03-15 10:26:34	ga_s2am_ard_3-2-1_54HTH_2022-03-15_final
2022-03-15 10:26:36	ga_s2am_ard_3-2-1_53HQC_2022-03-15_final
2022-03-15 10:26:40	ga_s2am_ard_3-2-1_53HPC_2022-03-15_final
2022-03-15 10:26:44	ga_s2am_ard_3-2-1_54HUG_2022-03-15_final
2022-03-15 10:26:44	ga_s2am_ard_3-2-1_53HNC_2022-03-15_final
2022-03-15 10:26:49	ga_s2am_ard_3-2-1_54HTG_2022-03-15_final
2022-03-15 10:26:50	ga_s2am_ard_3-2-1_53HQB_2022-03-15_final
2022-03-15 10:26:54	ga_s2am_ard_3-2-1_53HPB_2022-03-15_final
2022-03-15 10:26:55	ga_s2am_ard_3-2-1_54HUF_2022-03-15_final
2022-03-15 10:26:58	ga_s2am_ard_3-2-1_53HNB_2022-03-15_final
2022-03-15 10:27:03	ga_s2am_ard_3-2-1_54HTF_2022-03-15_final
2022-03-15 10:27:05	ga_s2am_ard_3-2-1_53HQA_2022-03-15_final
2022-03-15 10:27:09	ga_s2am_ard_3-2-1_53HPA_2022-03-15_final
2022-03-15 10:27:16	ga_s2am_ard_3-2-1_54HTE_2022-03-15_final.stac-item
2022-03-15 10:27:17	ga_s2am_ard_3-2-1_53HQV_2022-03-15_final.stac-item
2022-03-15 10:27:19	ga_s2am_ard_3-2-1_53HPV_2022-03-15_final.stac-item
2022-03-15 12:03:30	ga_s2am_ard_3-2-1_50KLC_2022-03-15_final
2022-03-15 12:03:42	ga_s2am_ard_3-2-1_50KMB_2022-03-15_final
2022-03-15 12:04:17	ga_s2am_ard_3-2-1_50KKV_2022-03-15_final
2022-03-15 12:04:29	ga_s2am_ard_3-2-1_50KLU_2022-03-15_final
2022-03-15 12:04:32	ga_s2am_ard_3-2-1_50KKU_2022-03-15_final
2022-03-15 12:04:50	ga_s2am_ard_3-2-1_49JGN_2022-03-15_final
2022-03-15 12:04:52	ga_s2am_ard_3-2-1_50JMS_2022-03-15_final
2022-03-15 12:05:01	ga_s2am_ard_3-2-1_50JKS_2022-03-15_final
2022-03-15 12:05:02	ga_s2am_ard_3-2-1_50JMR_2022-03-15_final
2022-03-15 12:05:04	ga_s2am_ard_3-2-1_49JGM_2022-03-15_final
2022-03-15 12:05:12	ga_s2am_ard_3-2-1_50JLR_2022-03-15_final
2022-03-15 12:05:12	ga_s2am_ard_3-2-1_49JFM_2022-03-15_final
2022-03-15 12:05:16	ga_s2am_ard_3-2-1_50JKR_2022-03-15_final
2022-03-15 12:05:19	ga_s2am_ard_3-2-1_49JGL_2022-03-15_final
2022-03-15 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2022-03-15_final
2022-03-15 12:05:30	ga_s2am_ard_3-2-1_50JKQ_2022-03-15_final
2022-03-15 12:05:33	ga_s2am_ard_3-2-1_49JGK_2022-03-15_final
2022-03-15 12:05:38	ga_s2am_ard_3-2-1_50JLP_2022-03-15_final
2022-03-15 12:05:39	ga_s2am_ard_3-2-1_50JKP_2022-03-15_final
2022-03-15 12:05:41	ga_s2am_ard_3-2-1_49JGK_2022-03-15_final
2022-03-15 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2022-03-15_final
2022-03-15 12:05:44	ga_s2am_ard_3-2-1_50JLP_2022-03-15_final
2022-03-15 12:05:46	ga_s2am_ard_3-2-1_50JKP_2022-03-15_final
2022-03-15 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2022-03-15_final
2022-03-15 12:05:55	ga_s2am_ard_3-2-1_50JLN_2022-03-15_final
2022-03-15 12:05:59	ga_s2am_ard_3-2-1_50JKN_2022-03-15_final
2022-03-15 12:06:02	ga_s2am_ard_3-2-1_49JGH_2022-03-15_final.stac-item
2022-03-15 12:06:08	ga_s2am_ard_3-2-1_50JLM_2022-03-15_final
2022-03-15 12:06:14	ga_s2am_ard_3-2-1_50JKM_2022-03-15_final

Return to ga_s2am_ard_3 on 15th March 2022 overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2022

March

15th