Simulating Locational Error in Field-Based Measurements of Reflectance

Author(s):  
P. M. Atkinson
Keyword(s):  
1989 ◽  
Vol 67 (5) ◽  
pp. 1122-1124 ◽  
Author(s):  
Patricia E. Reynolds

An experimental satellite collar was tested on a captive bull muskox (Ovibos moschatus) and a wild cow muskox in north-eastern Alaska. The animals had no observed problems carrying the 2.2-kg collar. The satellite collar provided frequent data on location and activity of the muskox as well as internal temperature of the collar canister. During a 12-month period, 329 locations were obtained from the wild cow muskox with a locational error ranging from 0.28 to 2.46 km. Fewer locations were obtained in winter than summer, but amounts of data received on activity and temperature were relatively consistent year-round. A counter that recorded closure of a mercury tip switch at 1-min intervals for 30 min was useful for determining if the animal was active or resting. Home range size, movements, and activity of the satellite-collared cow muskox were all reduced in winter.


2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
J. L. Sadd ◽  
E. S. Hall ◽  
M. Pastor ◽  
R. A. Morello-Frosch ◽  
D. Lowe-Liang ◽  
...  

Researchers and government regulators have developed numerous tools to screen areas and populations for cumulative impacts and vulnerability to environmental hazards and risk. These tools all rely on secondary data maintained by government agencies as part of the regulatory and permitting process. Stakeholders interested in cumulative impacts screening results have consistently questioned the accuracy and completeness of some of these datasets. In this study, three cumulative impacts screening tools used in California were compared, and ground-truth validation was used to determine the effect database inaccuracy. Ground-truthing showed substantial locational inaccuracy and error in hazardous facility databases and statewide air toxics emission inventories of up to 10 kilometers. These errors resulted in significant differences in cumulative impact screening scores generated by one screening tool, the Environmental Justice Screening Method.


2018 ◽  
Vol 56 (4) ◽  
pp. 928-937
Author(s):  
Henry Ndaimani ◽  
Amon Murwira ◽  
Mhosisi Masocha

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