Search ga_s2bm_ard_3 across May 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 s2cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s2cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s2cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s2cloudless 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
2022-05-01 11:04:08	ga_s2bm_ard_3-2-1_52JDT_2022-05-01_final
2022-05-01 11:04:10	ga_s2bm_ard_3-2-1_52JGT_2022-05-01_final
2022-05-01 11:04:12	ga_s2bm_ard_3-2-1_52JFT_2022-05-01_final
2022-05-01 11:04:14	ga_s2bm_ard_3-2-1_52JET_2022-05-01_final
2022-05-01 11:04:16	ga_s2bm_ard_3-2-1_52JDT_2022-05-01_final
2022-05-01 11:04:18	ga_s2bm_ard_3-2-1_52JGS_2022-05-01_final
2022-05-01 11:04:23	ga_s2bm_ard_3-2-1_52JFS_2022-05-01_final
2022-05-01 11:04:26	ga_s2bm_ard_3-2-1_52JES_2022-05-01_final
2022-05-01 11:04:29	ga_s2bm_ard_3-2-1_52JGR_2022-05-01_final
2022-05-01 11:04:30	ga_s2bm_ard_3-2-1_52JDS_2022-05-01_final
2022-05-01 11:04:37	ga_s2bm_ard_3-2-1_52JFR_2022-05-01_final
2022-05-01 11:04:41	ga_s2bm_ard_3-2-1_52JER_2022-05-01_final
2022-05-01 11:04:44	ga_s2bm_ard_3-2-1_52JDR_2022-05-01_final
2022-05-01 11:04:50	ga_s2bm_ard_3-2-1_52JCR_2022-05-01_final
2022-05-01 11:04:51	ga_s2bm_ard_3-2-1_52JFQ_2022-05-01_final
2022-05-01 11:04:55	ga_s2bm_ard_3-2-1_52JEQ_2022-05-01_final
2022-05-01 11:04:59	ga_s2bm_ard_3-2-1_52JDQ_2022-05-01_final
2022-05-01 11:05:02	ga_s2bm_ard_3-2-1_52JCQ_2022-05-01_final
2022-05-01 11:05:06	ga_s2bm_ard_3-2-1_52JFP_2022-05-01_final
2022-05-01 11:05:10	ga_s2bm_ard_3-2-1_52JEP_2022-05-01_final
2022-05-01 11:05:13	ga_s2bm_ard_3-2-1_52JDP_2022-05-01_final
2022-05-01 11:05:16	ga_s2bm_ard_3-2-1_52JCP_2022-05-01_final
2022-05-01 11:05:20	ga_s2bm_ard_3-2-1_52JFN_2022-05-01_final
2022-05-01 11:05:24	ga_s2bm_ard_3-2-1_52JEN_2022-05-01_final
2022-05-01 11:05:28	ga_s2bm_ard_3-2-1_52JDN_2022-05-01_final
2022-05-01 11:05:31	ga_s2bm_ard_3-2-1_52JCN_2022-05-01_final
2022-05-01 11:05:32	ga_s2bm_ard_3-2-1_52JFM_2022-05-01_final
2022-05-01 11:05:39	ga_s2bm_ard_3-2-1_52JEM_2022-05-01_final
2022-05-01 11:05:42	ga_s2bm_ard_3-2-1_52JDM_2022-05-01_final
2022-05-01 11:05:46	ga_s2bm_ard_3-2-1_52JCM_2022-05-01_final
2022-05-01 11:05:52	ga_s2bm_ard_3-2-1_52JBM_2022-05-01_final
2022-05-01 11:05:53	ga_s2bm_ard_3-2-1_52JEL_2022-05-01_final
2022-05-01 11:05:57	ga_s2bm_ard_3-2-1_52JDL_2022-05-01_final
2022-05-01 11:06:00	ga_s2bm_ard_3-2-1_52JCL_2022-05-01_final
2022-05-01 11:06:04	ga_s2bm_ard_3-2-1_52JBL_2022-05-01_final
2022-05-01 11:06:11	ga_s2bm_ard_3-2-1_52HDK_2022-05-01_final
2022-05-01 11:06:15	ga_s2bm_ard_3-2-1_52HCK_2022-05-01_final
2022-05-01 11:06:18	ga_s2bm_ard_3-2-1_52HBK_2022-05-01_final
2022-05-01 11:06:30	ga_s2bm_ard_3-2-1_51HYD_2022-05-01_final
2022-05-02 10:29:34	ga_s2bm_ard_3-2-1_54LXQ_2022-05-02_final
2022-05-02 10:29:37	ga_s2bm_ard_3-2-1_54LWQ_2022-05-02_final
2022-05-02 10:29:48	ga_s2bm_ard_3-2-1_54LXP_2022-05-02_final
2022-05-02 10:29:52	ga_s2bm_ard_3-2-1_54LWP_2022-05-02_final
2022-05-02 10:30:02	ga_s2bm_ard_3-2-1_54LXN_2022-05-02_final
2022-05-02 10:30:06	ga_s2bm_ard_3-2-1_54LWN_2022-05-02_final
2022-05-02 10:30:12	ga_s2bm_ard_3-2-1_54LXM_2022-05-02_final
2022-05-02 10:30:20	ga_s2bm_ard_3-2-1_54LWM_2022-05-02_final
2022-05-02 10:30:24	ga_s2bm_ard_3-2-1_54LVM_2022-05-02_final
2022-05-02 10:30:35	ga_s2bm_ard_3-2-1_54LWL_2022-05-02_final
2022-05-02 10:30:39	ga_s2bm_ard_3-2-1_54LVL_2022-05-02_final
2022-05-02 10:30:50	ga_s2bm_ard_3-2-1_54LWK_2022-05-02_final
2022-05-02 10:30:53	ga_s2bm_ard_3-2-1_54LVK_2022-05-02_final
2022-05-02 10:31:04	ga_s2bm_ard_3-2-1_54LWJ_2022-05-02_final
2022-05-02 10:31:08	ga_s2bm_ard_3-2-1_54LVJ_2022-05-02_final
2022-05-02 10:31:11	ga_s2bm_ard_3-2-1_54LUJ_2022-05-02_final
2022-05-02 10:31:17	ga_s2bm_ard_3-2-1_54LWH_2022-05-02_final
2022-05-02 10:31:22	ga_s2bm_ard_3-2-1_54LVH_2022-05-02_final
2022-05-02 10:31:25	ga_s2bm_ard_3-2-1_54LUH_2022-05-02_final
2022-05-02 10:31:26	ga_s2bm_ard_3-2-1_54KWG_2022-05-02_final
2022-05-02 10:31:36	ga_s2bm_ard_3-2-1_54KVG_2022-05-02_final
2022-05-02 10:31:40	ga_s2bm_ard_3-2-1_54KUG_2022-05-02_final
2022-05-02 10:31:43	ga_s2bm_ard_3-2-1_54KTG_2022-05-02_final
2022-05-02 10:31:44	ga_s2bm_ard_3-2-1_53KRB_2022-05-02_final
2022-05-02 10:31:51	ga_s2bm_ard_3-2-1_54KVF_2022-05-02_final
2022-05-02 10:31:54	ga_s2bm_ard_3-2-1_54KUF_2022-05-02_final
2022-05-02 10:31:58	ga_s2bm_ard_3-2-1_54KTF_2022-05-02_final
2022-05-02 10:31:59	ga_s2bm_ard_3-2-1_53KRA_2022-05-02_final
2022-05-02 10:32:05	ga_s2bm_ard_3-2-1_53KQA_2022-05-02_final
2022-05-02 10:32:06	ga_s2bm_ard_3-2-1_54KVE_2022-05-02_final
2022-05-02 10:32:09	ga_s2bm_ard_3-2-1_54KUE_2022-05-02_final
2022-05-02 10:32:12	ga_s2bm_ard_3-2-1_54KTE_2022-05-02_final
2022-05-02 10:32:13	ga_s2bm_ard_3-2-1_53KRV_2022-05-02_final
2022-05-03 11:43:16	ga_s2bm_ard_3-2-1_50KQC_2022-05-03_final
2022-05-03 11:43:28	ga_s2bm_ard_3-2-1_50KRB_2022-05-03_final
2022-05-03 11:43:31	ga_s2bm_ard_3-2-1_50KQB_2022-05-03_final
2022-05-03 11:43:42	ga_s2bm_ard_3-2-1_50KRA_2022-05-03_final
2022-05-03 11:43:46	ga_s2bm_ard_3-2-1_50KQA_2022-05-03_final
2022-05-03 11:44:05	ga_s2bm_ard_3-2-1_50KPV_2022-05-03_final
2022-05-03 11:44:11	ga_s2bm_ard_3-2-1_50KRU_2022-05-03_final
2022-05-03 11:44:14	ga_s2bm_ard_3-2-1_50KQU_2022-05-03_final
2022-05-03 11:44:18	ga_s2bm_ard_3-2-1_50KPU_2022-05-03_final
2022-05-03 11:44:25	ga_s2bm_ard_3-2-1_50JRT_2022-05-03_final
2022-05-03 11:44:29	ga_s2bm_ard_3-2-1_50JQT_2022-05-03_final
2022-05-03 11:44:32	ga_s2bm_ard_3-2-1_50JPT_2022-05-03_final
2022-05-03 11:44:40	ga_s2bm_ard_3-2-1_50JRS_2022-05-03_final
2022-05-03 11:44:43	ga_s2bm_ard_3-2-1_50JQS_2022-05-03_final
2022-05-03 11:44:47	ga_s2bm_ard_3-2-1_50JPS_2022-05-03_final
2022-05-03 11:44:58	ga_s2bm_ard_3-2-1_50JQR_2022-05-03_final
2022-05-03 11:45:01	ga_s2bm_ard_3-2-1_50JPR_2022-05-03_final
2022-05-03 11:45:06	ga_s2bm_ard_3-2-1_50JNR_2022-05-03_final
2022-05-03 11:45:12	ga_s2bm_ard_3-2-1_50JQQ_2022-05-03_final
2022-05-03 11:45:16	ga_s2bm_ard_3-2-1_50JPQ_2022-05-03_final
2022-05-03 11:45:19	ga_s2bm_ard_3-2-1_50JNQ_2022-05-03_final
2022-05-03 11:45:27	ga_s2bm_ard_3-2-1_50JQP_2022-05-03_final
2022-05-03 11:45:31	ga_s2bm_ard_3-2-1_50JPP_2022-05-03_final
2022-05-03 11:45:34	ga_s2bm_ard_3-2-1_50JNP_2022-05-03_final
2022-05-03 11:45:38	ga_s2bm_ard_3-2-1_50JQN_2022-05-03_final
2022-05-03 11:45:40	ga_s2bm_ard_3-2-1_50JPN_2022-05-03_final
2022-05-03 11:45:41	ga_s2bm_ard_3-2-1_50JNP_2022-05-03_final
2022-05-03 11:45:41	ga_s2bm_ard_3-2-1_50JNN_2022-05-03_final

Return to ga_s2bm_ard_3 across May 2022 overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

GA Collection 3

USGS Products

Collection 2 NBAR

Collection 2 NBAR Tiled

Pixel Quality

Collection 2 Level1

Tidal

Water Observations

Fractional Cover

Sentinel 2

Ingested Pixel Quality

Geomedians

TMAD

Telemetry data

Summary

Other Products

2022

May

All days