Oblique ionogram features associated with off-great circle HF propagation at high and sub-auroral latitudes

2003 ◽  
Vol 150 (4) ◽  
pp. 295 ◽  
Author(s):  
N.C. Rogers ◽  
E.M. Warrington ◽  
T.B. Jones
Keyword(s):  
Great Circle ◽  
Hf Propagation

Measurements of the extent to which round-the-world HF propagation follows a great circle

1964 ◽  
Vol 52 (4) ◽  
pp. 418-419 ◽  
Author(s):  
R.B. Fenwick ◽  
O.G. Villard ◽  
E.C. Hayden ◽  
R. Bredek
Keyword(s):  
Great Circle ◽  
Hf Propagation ◽  
The World

scholarly journals A ray-tracing model to account for off-great circle HF propagation over northerly paths

Radio Science ◽  
2005 ◽  
Vol 40 (4) ◽  
pp. n/a-n/a ◽  
Author(s):  
N. Y. Zaalov ◽  
E. M. Warrington ◽  
A. J. Stocker
Keyword(s):  
Ray Tracing ◽  
Great Circle ◽  
Hf Propagation ◽  
Ray Tracing Model

Charts for Great Circle Sailing

1885 ◽  
Vol 20 (501supp) ◽  
pp. 7991-7991
Author(s):  
Richard A. Proctor
Keyword(s):  
Great Circle

From Littoral to Ozone: On Mike Pearson’s Contributions to Indian Ocean History

2019 ◽  
Vol 2 (1) ◽  
pp. 12-24
Author(s):  
Edward A. Alpers
Keyword(s):  
New York ◽  
Indian Ocean ◽  
Great Circle ◽  
Historical Scholarship ◽  
The Indian Ocean ◽  
Seminal Article

In this article I examine two of Michael Pearson’s most important contributions to our understanding of Indian Ocean history: the concept of the littoral, which he first articulated in his seminal article on “Littoral society: the case for the coast” in The Great Circle 7, no. 1 (1985): 1-8, and his comment in The Indian Ocean (London and New York: Routledge, 2003, p. 9) that “I want it to have a whiff of ozone.” Accordingly, I review Pearson’s publications to see how he has written about these two notions and how they have influenced historical scholarship about the Indian Ocean.

Empirical Estimation of Shortest Route Length along U.S. Interstate Highways Based on Great Circle Distance

2021 ◽  
pp. 036119812110152
Author(s):  
Nawei Liu ◽  
Fei Xie ◽  
Zhenhong Lin ◽  
Mingzhou Jin
Keyword(s):  
Linear Regression ◽  
State Level ◽  
Distance Matrix ◽  
Great Circle ◽  
The State ◽  
Empirical Estimation ◽  
Interstate Highways ◽  
Shortest Route ◽  
Route Length ◽  
Great Circle Distance

In this study, 98 regression models were specified for easily estimating shortest distances based on great circle distances along the U.S. interstate highways nationwide and for each of the continental 48 states. This allows transportation professionals to quickly generate distance, or even distance matrix, without expending significant efforts on complicated shortest path calculations. For simple usage by all professionals, all models are present in the simple linear regression form. Only one explanatory variable, the great circle distance, is considered to calculate the route distance. For each geographic scope (i.e., the national or one of the states), two different models were considered, with and without the intercept. Based on the adjusted R-squared, it was observed that models without intercepts generally have better fitness. All these models generally have good fitness with the linear regression relationship between the great circle distance and route distance. At the state level, significant variations in the slope coefficients between the state-level models were also observed. Furthermore, a preliminary analysis of the effect of highway density on this variation was conducted.

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