NOAA ERDDAP
Easier access to scientific data

Brought to you by NOAA NMFS SWFSC ERD    

ERDDAP > tabledap > Subset ?

Dataset Title:  ud_476-20220412T1700 Real-Time Raw Trajectory Subscribe RSS
Institution:  University of Delaware   (Dataset ID: ud_476-20220412T1700-trajectory-raw-rt)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 94)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    trajectory ?  =  1 option: ud_476-20220412T1700
    source_file ?  =  94 options

View:      Map of All Related Data ?      Distinct Data Counts ?     Distinct Data ?      Related Data Counts ?     Related Data ?

 
Map of All Related Data ?   (Refine the map and/or download the image)

To view the map, check View : Map of All Related Data above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.
 


Distinct Data Counts ?

To view the counts of distinct combinations of the variables listed above,
check View : Distinct Data Counts above and select a value for one of the variables above.

 


Distinct Data ?   (Metadata)    (Refine the data subset and/or download the data)  

trajectory source_file
 
ud_476-20220412T1700 ud_476-2022-101-3-1-sbd(01840001)
ud_476-20220412T1700 ud_476-2022-101-3-2-sbd(01840002)
ud_476-20220412T1700 ud_476-2022-101-3-3-sbd(01840003)
ud_476-20220412T1700 ud_476-2022-101-3-4-sbd(01840004)
ud_476-20220412T1700 ud_476-2022-101-3-5-sbd(01840005)
ud_476-20220412T1700 ud_476-2022-101-3-6-sbd(01840006)
ud_476-20220412T1700 ud_476-2022-101-4-0-sbd(01850000)
ud_476-20220412T1700 ud_476-2022-101-4-1-sbd(01850001)
ud_476-20220412T1700 ud_476-2022-101-4-10-sbd(01850010)
ud_476-20220412T1700 ud_476-2022-101-4-11-sbd(01850011)
ud_476-20220412T1700 ud_476-2022-101-4-12-sbd(01850012)
ud_476-20220412T1700 ud_476-2022-101-4-13-sbd(01850013)
ud_476-20220412T1700 ud_476-2022-101-4-14-sbd(01850014)
ud_476-20220412T1700 ud_476-2022-101-4-15-sbd(01850015)
ud_476-20220412T1700 ud_476-2022-101-4-16-sbd(01850016)
ud_476-20220412T1700 ud_476-2022-101-4-17-sbd(01850017)
ud_476-20220412T1700 ud_476-2022-101-4-18-sbd(01850018)
ud_476-20220412T1700 ud_476-2022-101-4-19-sbd(01850019)
ud_476-20220412T1700 ud_476-2022-101-4-2-sbd(01850002)
ud_476-20220412T1700 ud_476-2022-101-4-20-sbd(01850020)
ud_476-20220412T1700 ud_476-2022-101-4-21-sbd(01850021)
ud_476-20220412T1700 ud_476-2022-101-4-22-sbd(01850022)
ud_476-20220412T1700 ud_476-2022-101-4-23-sbd(01850023)
ud_476-20220412T1700 ud_476-2022-101-4-24-sbd(01850024)
ud_476-20220412T1700 ud_476-2022-101-4-25-sbd(01850025)
ud_476-20220412T1700 ud_476-2022-101-4-26-sbd(01850026)
ud_476-20220412T1700 ud_476-2022-101-4-27-sbd(01850027)
ud_476-20220412T1700 ud_476-2022-101-4-28-sbd(01850028)
ud_476-20220412T1700 ud_476-2022-101-4-29-sbd(01850029)
ud_476-20220412T1700 ud_476-2022-101-4-3-sbd(01850003)
ud_476-20220412T1700 ud_476-2022-101-4-30-sbd(01850030)
ud_476-20220412T1700 ud_476-2022-101-4-31-sbd(01850031)
ud_476-20220412T1700 ud_476-2022-101-4-32-sbd(01850032)
ud_476-20220412T1700 ud_476-2022-101-4-33-sbd(01850033)
ud_476-20220412T1700 ud_476-2022-101-4-34-sbd(01850034)
ud_476-20220412T1700 ud_476-2022-101-4-35-sbd(01850035)
ud_476-20220412T1700 ud_476-2022-101-4-36-sbd(01850036)
ud_476-20220412T1700 ud_476-2022-101-4-37-sbd(01850037)
ud_476-20220412T1700 ud_476-2022-101-4-38-sbd(01850038)
ud_476-20220412T1700 ud_476-2022-101-4-39-sbd(01850039)
ud_476-20220412T1700 ud_476-2022-101-4-4-sbd(01850004)
ud_476-20220412T1700 ud_476-2022-101-4-40-sbd(01850040)
ud_476-20220412T1700 ud_476-2022-101-4-41-sbd(01850041)
ud_476-20220412T1700 ud_476-2022-101-4-42-sbd(01850042)
ud_476-20220412T1700 ud_476-2022-101-4-43-sbd(01850043)
ud_476-20220412T1700 ud_476-2022-101-4-44-sbd(01850044)
ud_476-20220412T1700 ud_476-2022-101-4-45-sbd(01850045)
ud_476-20220412T1700 ud_476-2022-101-4-46-sbd(01850046)
ud_476-20220412T1700 ud_476-2022-101-4-47-sbd(01850047)
ud_476-20220412T1700 ud_476-2022-101-4-48-sbd(01850048)
ud_476-20220412T1700 ud_476-2022-101-4-49-sbd(01850049)
ud_476-20220412T1700 ud_476-2022-101-4-5-sbd(01850005)
ud_476-20220412T1700 ud_476-2022-101-4-50-sbd(01850050)
ud_476-20220412T1700 ud_476-2022-101-4-51-sbd(01850051)
ud_476-20220412T1700 ud_476-2022-101-4-52-sbd(01850052)
ud_476-20220412T1700 ud_476-2022-101-4-53-sbd(01850053)
ud_476-20220412T1700 ud_476-2022-101-4-54-sbd(01850054)
ud_476-20220412T1700 ud_476-2022-101-4-55-sbd(01850055)
ud_476-20220412T1700 ud_476-2022-101-4-56-sbd(01850056)
ud_476-20220412T1700 ud_476-2022-101-4-57-sbd(01850057)
ud_476-20220412T1700 ud_476-2022-101-4-58-sbd(01850058)
ud_476-20220412T1700 ud_476-2022-101-4-59-sbd(01850059)
ud_476-20220412T1700 ud_476-2022-101-4-6-sbd(01850006)
ud_476-20220412T1700 ud_476-2022-101-4-60-sbd(01850060)
ud_476-20220412T1700 ud_476-2022-101-4-61-sbd(01850061)
ud_476-20220412T1700 ud_476-2022-101-4-62-sbd(01850062)
ud_476-20220412T1700 ud_476-2022-101-4-63-sbd(01850063)
ud_476-20220412T1700 ud_476-2022-101-4-64-sbd(01850064)
ud_476-20220412T1700 ud_476-2022-101-4-65-sbd(01850065)
ud_476-20220412T1700 ud_476-2022-101-4-66-sbd(01850066)
ud_476-20220412T1700 ud_476-2022-101-4-67-sbd(01850067)
ud_476-20220412T1700 ud_476-2022-101-4-68-sbd(01850068)
ud_476-20220412T1700 ud_476-2022-101-4-69-sbd(01850069)
ud_476-20220412T1700 ud_476-2022-101-4-7-sbd(01850007)
ud_476-20220412T1700 ud_476-2022-101-4-70-sbd(01850070)
ud_476-20220412T1700 ud_476-2022-101-4-71-sbd(01850071)
ud_476-20220412T1700 ud_476-2022-101-4-72-sbd(01850072)
ud_476-20220412T1700 ud_476-2022-101-4-73-sbd(01850073)
ud_476-20220412T1700 ud_476-2022-101-4-74-sbd(01850074)
ud_476-20220412T1700 ud_476-2022-101-4-75-sbd(01850075)
ud_476-20220412T1700 ud_476-2022-101-4-76-sbd(01850076)
ud_476-20220412T1700 ud_476-2022-101-4-77-sbd(01850077)
ud_476-20220412T1700 ud_476-2022-101-4-78-sbd(01850078)
ud_476-20220412T1700 ud_476-2022-101-4-79-sbd(01850079)
ud_476-20220412T1700 ud_476-2022-101-4-8-sbd(01850008)
ud_476-20220412T1700 ud_476-2022-101-4-80-sbd(01850080)
ud_476-20220412T1700 ud_476-2022-101-4-81-sbd(01850081)
ud_476-20220412T1700 ud_476-2022-101-4-82-sbd(01850082)
ud_476-20220412T1700 ud_476-2022-101-4-83-sbd(01850083)
ud_476-20220412T1700 ud_476-2022-101-4-84-sbd(01850084)
ud_476-20220412T1700 ud_476-2022-101-4-85-sbd(01850085)
ud_476-20220412T1700 ud_476-2022-101-4-86-sbd(01850086)
ud_476-20220412T1700 ud_476-2022-101-4-87-sbd(01850087)
ud_476-20220412T1700 ud_476-2022-101-4-9-sbd(01850009)

In total, there are 94 rows of distinct combinations of the variables listed above. All of the rows are shown above.
To change the maximum number of rows displayed, change View : Distinct Data above.
 


Related Data Counts ?

To view the related data counts,
check View : Related Data Counts above and select a value for one of the variables above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.
 


Related Data ?   (Metadata)    (Refine the data subset and/or download the data)

To view the related data, change View : Related Data above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.


 
ERDDAP, Version 2.22
Disclaimers | Privacy Policy | Contact