User:Ab3080888/数学沙盒

排队网络是一种由多个单独队列通过路由网络互连形成的复杂系统。在相关示意图中，我们用圆形符号表示服务台，用连续的矩形表示队列，用箭头标示路由网络。虽然排队网络研究的主要目标是确定网络的平衡分布状态，但在实际应用中，对系统瞬态特性的研究往往更具有基础性意义。

排队论（英語：Queueing theory）是一门研究等待现象的数学理论。 它通过建立数学模型来预测排队长度和等待时间。 由于其研究成果对服务资源配置的决策具有重要指导意义，排队论已成为運籌學中的重要分支学科。

这门学科可以追溯到阿格纳·克拉鲁普·厄兰的开创性研究。他最初为解决哥本哈根电话交换公司的来电问题建立了理论模型。 这些理论不仅为电信流量工程奠定了基础，还逐步拓展到电信、交通、计算机、项目管理等众多领域。目前，排队论在工业工程领域应用尤为广泛，已成为工厂、商店、办公室和医院等场所规划设计的重要工具。

描述

排队论是管理科學领域中的重要研究方向之一。管理科学为企业提供了多种科学和数学方法来解决各类问题。 排队分析主要研究等待队列的概率特性，因此其分析结果（即运行特征）具有概率性而非确定性。这些运行特征包括：系统内顾客数量的概率分布、系统内平均顾客数、队列中平均等待人数、顾客在系统内的平均停留时间、顾客的平均等待时间，以及服务台忙碌或空闲的概率等。 排队分析的核心目标是通过计算现有系统的这些特征，并测试各种可能的改进方案。通过对比当前系统与替代方案的运行特征，管理者可以清晰地评估每个方案的利弊得失。这些分析能够帮助管理者做出最终决策，实现成本节约、缩短等待时间、提升效率等目标。常用的排队模型主要包括单服务台和多服务台两种基本类型，具体会在后文详细讨论。这些模型还可以根据服务时间是否固定、队列长度是否受限、源群体是否有限等因素进行细分。

单排队节点

排队系统可以简单理解为一个近似的黑盒模型。任务（在不同场景中也称为顾客或请求）进入系统后，可能需要等待，接受处理，最后离开系统。

A black box. Jobs arrive to, and depart from, the queue.

不过，这个系统并不是一个完全的黑盒，因为我们需要了解它的一些内部运作机制。系统中设有一个或多个服务窗口（server），每个窗口都可以受理一个新到达的任务。当某个任务处理完毕离开后，对应的服务窗口就能继续接待下一个任务。

A queueing node with 3 servers. Server a is idle, and thus an arrival is given to it to process. Server b is currently busy and will take some time before it can complete service of its job. Server c has just completed service of a job and thus will be next to receive an arriving job.

举个常见的例子：超市收银台就是一个典型的排队系统（虽然还有其他例子，但这个是文献中最常用的）。顾客来到超市，在收银台办理结账，然后离开。由于每个收银员同一时间只能服务一位顾客，所以这是一个单服务窗口的排队系统。如果规定顾客看到收银员正忙就直接离开，这种情况就是无等待空间的排队系统；如果设置了可容纳 n 位顾客的等候区，则称为具有 n 个等待空间的排队系统。

出生-死亡过程

单个队列（也称为排队节点）的行为可以用出生-死亡過程来描述。该过程刻画了队列中任务的到达和离开动态，以及系统中实时的任务数量。如果用 k 表示系统中的任务数量（包括正在处理的和在缓冲区等待的），那么每当有新任务到达时 k 值加1，任务完成离开时 k 值减1。

系统通过“出生”和“死亡”两种事件在不同的 k 值之间转换。对于每个任务$i$，这些转换分别以到达率$\lambda _{i}$和离开率$\mu _{i}$发生。在队列系统中，这些速率通常被认为是稳定的，不会随队列中任务数量的变化而改变，因此我们可以采用单位时间内的平均到达率和离开率。基于这一假设，该过程的平均到达率$\lambda ={\text{avg}}(\lambda _{1},\lambda _{2},\dots ,\lambda _{k})$，平均离开率$\mu ={\text{avg}}(\mu _{1},\mu _{2},\dots ,\mu _{k})$。

A birth–death process. The values in the circles represent the state of the system, which evolves based on arrival rates λ_i and departure rates μ_i.

A queue with 1 server, arrival rate λ and departure rate μ

Balance equations

The steady state equations for the birth-and-death process, known as the balance equations, are as follows. Here $P_{n}$ denotes the steady state probability to be in state n.

$\mu _{1}P_{1}=\lambda _{0}P_{0}$

$\lambda _{0}P_{0}+\mu _{2}P_{2}=(\lambda _{1}+\mu _{1})P_{1}$

$\lambda _{n-1}P_{n-1}+\mu _{n+1}P_{n+1}=(\lambda _{n}+\mu _{n})P_{n}$

The first two equations imply

$P_{1}={\frac {\lambda _{0}}{\mu _{1}}}P_{0}$

and

$P_{2}={\frac {\lambda _{1}}{\mu _{2}}}P_{1}+{\frac {1}{\mu _{2}}}(\mu _{1}P_{1}-\lambda _{0}P_{0})={\frac {\lambda _{1}}{\mu _{2}}}P_{1}={\frac {\lambda _{1}\lambda _{0}}{\mu _{2}\mu _{1}}}P_{0}$.

By mathematical induction,

$P_{n}={\frac {\lambda _{n-1}\lambda _{n-2}\cdots \lambda _{0}}{\mu _{n}\mu _{n-1}\cdots \mu _{1}}}P_{0}=P_{0}\prod _{i=0}^{n-1}{\frac {\lambda _{i}}{\mu _{i+1}}}$.

The condition $\sum _{n=0}^{\infty }P_{n}=P_{0}+P_{0}\sum _{n=1}^{\infty }\prod _{i=0}^{n-1}{\frac {\lambda _{i}}{\mu _{i+1}}}=1$ leads to

$P_{0}={\frac {1}{1+\sum _{n=1}^{\infty }\prod _{i=0}^{n-1}{\frac {\lambda _{i}}{\mu _{i+1}}}}}$

which, together with the equation for $P_{n}$ $(n\geq 1)$, fully describes the required steady state probabilities.

Kendall's notation

主条目：Kendall's notation

Single queueing nodes are usually described using Kendall's notation in the form A/S/c where A describes the distribution of durations between each arrival to the queue, S the distribution of service times for jobs, and c the number of servers at the node. For an example of the notation, the M/M/1 queue is a simple model where a single server serves jobs that arrive according to a Poisson process (where inter-arrival durations are exponentially distributed) and have exponentially distributed service times (the M denotes a Markov process). In an M/G/1 queue, the G stands for "general" and indicates an arbitrary probability distribution for service times.

Example analysis of an M/M/1 queue

Consider a queue with one server and the following characteristics:

• $\lambda$: the arrival rate (the reciprocal of the expected time between each customer arriving, e.g. 10 customers per second)
• $\mu$: the reciprocal of the mean service time (the expected number of consecutive service completions per the same unit time, e.g. per 30 seconds)
• n: the parameter characterizing the number of customers in the system
• $P_{n}$: the probability of there being n customers in the system in steady state

Further, let $E_{n}$ represent the number of times the system enters state n, and $L_{n}$ represent the number of times the system leaves state n. Then $\left\vert E_{n}-L_{n}\right\vert \in \{0,1\}$ for all n. That is, the number of times the system leaves a state differs by at most 1 from the number of times it enters that state, since it will either return into that state at some time in the future ($E_{n}=L_{n}$) or not ($\left\vert E_{n}-L_{n}\right\vert =1$).

When the system arrives at a steady state, the arrival rate should be equal to the departure rate.

Thus the balance equations

$\mu P_{1}=\lambda P_{0}$

$\lambda P_{0}+\mu P_{2}=(\lambda +\mu )P_{1}$

$\lambda P_{n-1}+\mu P_{n+1}=(\lambda +\mu )P_{n}$

imply

$P_{n}={\frac {\lambda }{\mu }}P_{n-1},\ n=1,2,\ldots$

The fact that $P_{0}+P_{1}+\cdots =1$ leads to the geometric distribution formula

$P_{n}=(1-\rho )\rho ^{n}$

where $\rho ={\frac {\lambda }{\mu }}<1$.

Simple two-equation queue

A common basic queueing system is attributed to Erlang and is a modification of Little's Law. Given an arrival rate λ, a dropout rate σ, and a departure rate μ, length of the queue L is defined as:

$L={\frac {\lambda -\sigma }{\mu }}$.

Assuming an exponential distribution for the rates, the waiting time W can be defined as the proportion of arrivals that are served. This is equal to the exponential survival rate of those who do not drop out over the waiting period, giving:

${\frac {\mu }{\lambda }}=e^{-W{\mu }}$

The second equation is commonly rewritten as:

$W={\frac {1}{\mu }}\mathrm {ln} {\frac {\lambda }{\mu }}$

The two-stage one-box model is common in epidemiology.

History

In 1909, Agner Krarup Erlang, a Danish engineer who worked for the Copenhagen Telephone Exchange, published the first paper on what would now be called queueing theory. He modeled the number of telephone calls arriving at an exchange by a Poisson process and solved the M/D/1 queue in 1917 and M/D/k queueing model in 1920. In Kendall's notation:

• M stands for "Markov" or "memoryless", and means arrivals occur according to a Poisson process
• D stands for "deterministic", and means jobs arriving at the queue require a fixed amount of service
• k describes the number of servers at the queueing node (k = 1, 2, 3, ...)

If the node has more jobs than servers, then jobs will queue and wait for service.

The M/G/1 queue was solved by Felix Pollaczek in 1930, a solution later recast in probabilistic terms by Aleksandr Khinchin and now known as the Pollaczek–Khinchine formula.

After the 1940s, queueing theory became an area of research interest to mathematicians. In 1953, David George Kendall solved the GI/M/k queue and introduced the modern notation for queues, now known as Kendall's notation. In 1957, Pollaczek studied the GI/G/1 using an integral equation. John Kingman gave a formula for the mean waiting time in a G/G/1 queue, now known as Kingman's formula.

Leonard Kleinrock worked on the application of queueing theory to message switching in the early 1960s and packet switching in the early 1970s. His initial contribution to this field was his doctoral thesis at the Massachusetts Institute of Technology in 1962, published in book form in 1964. His theoretical work published in the early 1970s underpinned the use of packet switching in the ARPANET, a forerunner to the Internet.

The matrix geometric method and matrix analytic methods have allowed queues with phase-type distributed inter-arrival and service time distributions to be considered.

Systems with coupled orbits are an important part in queueing theory in the application to wireless networks and signal processing.

Modern day application of queueing theory concerns among other things product development where (material) products have a spatiotemporal existence, in the sense that products have a certain volume and a certain duration.

Problems such as performance metrics for the M/G/k queue remain an open problem.

Service disciplines

Various scheduling policies can be used at queueing nodes:

First in, first out

First in first out (FIFO) queue example

Also called first-come, first-served (FCFS), this principle states that customers are served one at a time and that the customer that has been waiting the longest is served first.

Last in, first out

This principle also serves customers one at a time, but the customer with the shortest waiting time will be served first. Also known as a stack.

Processor sharing

Service capacity is shared equally between customers.

Priority

Customers with high priority are served first. Priority queues can be of two types: non-preemptive (where a job in service cannot be interrupted) and preemptive (where a job in service can be interrupted by a higher-priority job). No work is lost in either model.

Shortest job first

The next job to be served is the one with the smallest size.

Preemptive shortest job first

The next job to be served is the one with the smallest original size.

Shortest remaining processing time

The next job to serve is the one with the smallest remaining processing requirement.

Service facility

• Single server: customers line up and there is only one server
• Several parallel servers (single queue): customers line up and there are several servers
• Several parallel servers (several queues): there are many counters and customers can decide for which to queue

Unreliable server

Server failures occur according to a stochastic (random) process (usually Poisson) and are followed by setup periods during which the server is unavailable. The interrupted customer remains in the service area until server is fixed.

Customer waiting behavior

• Balking: customers decide not to join the queue if it is too long
• Jockeying: customers switch between queues if they think they will get served faster by doing so
• Reneging: customers leave the queue if they have waited too long for service

Arriving customers not served (either due to the queue having no buffer, or due to balking or reneging by the customer) are also known as dropouts. The average rate of dropouts is a significant parameter describing a queue.

排队网络

Queue networks are systems in which multiple queues are connected by customer routing. When a customer is serviced at one node, it can join another node and queue for service, or leave the network.

For networks of m nodes, the state of the system can be described by an m–dimensional vector (x₁, x₂, ..., x_m) where x_i represents the number of customers at each node.

The simplest non-trivial networks of queues are called tandem queues. The first significant results in this area were Jackson networks, for which an efficient product-form stationary distribution exists and the mean value analysis (which allows average metrics such as throughput and sojourn times) can be computed. If the total number of customers in the network remains constant, the network is called a closed network and has been shown to also have a product–form stationary distribution by the Gordon–Newell theorem. This result was extended to the BCMP network, where a network with very general service time, regimes, and customer routing is shown to also exhibit a product–form stationary distribution. The normalizing constant can be calculated with the Buzen's algorithm, proposed in 1973.

Networks of customers have also been investigated, such as Kelly networks, where customers of different classes experience different priority levels at different service nodes. Another type of network are G-networks, first proposed by Erol Gelenbe in 1993: these networks do not assume exponential time distributions like the classic Jackson network.

Routing algorithms

参见：Stochastic scheduling

In discrete-time networks where there is a constraint on which service nodes can be active at any time, the max-weight scheduling algorithm chooses a service policy to give optimal throughput in the case that each job visits only a single-person service node. In the more general case where jobs can visit more than one node, backpressure routing gives optimal throughput. A network scheduler must choose a queueing algorithm, which affects the characteristics of the larger network.

Mean-field limits

Mean-field models consider the limiting behaviour of the empirical measure (proportion of queues in different states) as the number of queues m approaches infinity. The impact of other queues on any given queue in the network is approximated by a differential equation. The deterministic model converges to the same stationary distribution as the original model.

Heavy traffic/diffusion approximations

主条目：Heavy traffic approximation

In a system with high occupancy rates (utilisation near 1), a heavy traffic approximation can be used to approximate the queueing length process by a reflected Brownian motion, Ornstein–Uhlenbeck process, or more general diffusion process. The number of dimensions of the Brownian process is equal to the number of queueing nodes, with the diffusion restricted to the non-negative orthant.

Fluid limits

主条目：Fluid limit

Fluid models are continuous deterministic analogs of queueing networks obtained by taking the limit when the process is scaled in time and space, allowing heterogeneous objects. This scaled trajectory converges to a deterministic equation which allows the stability of the system to be proven. It is known that a queueing network can be stable but have an unstable fluid limit.

Queueing Applications

Queueing theory finds widespread application in computer science and information technology. In networking, for instance, queues are integral to routers and switches, where packets queue up for transmission. By applying queueing theory principles, designers can optimize these systems, ensuring responsive performance and efficient resource utilization. Beyond the technological realm, queueing theory is relevant to everyday experiences. Whether waiting in line at a supermarket or for public transportation, understanding the principles of queueing theory provides valuable insights into optimizing these systems for enhanced user satisfaction. At some point, everyone will be involved in an aspect of queuing. What some may view to be an inconvenience could possibly be the most effective method. Queueing theory, a discipline rooted in applied mathematics and computer science, is a field dedicated to the study and analysis of queues, or waiting lines, and their implications across a diverse range of applications. This theoretical framework has proven instrumental in understanding and optimizing the efficiency of systems characterized by the presence of queues. The study of queues is essential in contexts such as traffic systems, computer networks, telecommunications, and service operations. Queueing theory delves into various foundational concepts, with the arrival process and service process being central. The arrival process describes the manner in which entities join the queue over time, often modeled using stochastic processes like Poisson processes. The efficiency of queueing systems is gauged through key performance metrics. These include the average queue length, average wait time, and system throughput. These metrics provide insights into the system's functionality, guiding decisions aimed at enhancing performance and reducing wait times. References: Gross, D., & Harris, C. M. (1998). Fundamentals of Queueing Theory. John Wiley & Sons. Kleinrock, L. (1976). Queueing Systems: Volume I - Theory. Wiley. Cooper, B. F., & Mitrani, I. (1985). Queueing Networks: A Fundamental Approach. John Wiley & Sons

See also

• Ehrenfest model
• Erlang unit
• Line management
• Network simulation
• Project production management
• Queue area
• Queueing delay
• Queue management system
• Queuing Rule of Thumb
• Random early detection
• Renewal theory
• Throughput
• Scheduling (computing)
• Traffic jam
• Traffic generation model
• Flow network

Further reading

• Gross, Donald; Carl M. Harris. Fundamentals of Queueing Theory. Wiley. 1998. ISBN 978-0-471-32812-4.  Online
• Zukerman, Moshe. Introduction to Queueing Theory and Stochastic Teletraffic Models (PDF). 2013. arXiv:1307.2968 . 
• Deitel, Harvey M. An introduction to operating systems revisited first. Addison-Wesley. 1984: 673. ISBN 978-0-201-14502-1.  chap.15, pp. 380–412
• Gelenbe, Erol; Isi Mitrani. Analysis and Synthesis of Computer Systems. World Scientific 2nd Edition. 2010. ISBN 978-1-908978-42-4. 
• Newell, Gordron F. Applications of Queueing Theory. Chapman and Hall. 1 June 1971. 
• Leonard Kleinrock, Information Flow in Large Communication Nets, (MIT, Cambridge, May 31, 1961) Proposal for a Ph.D. Thesis
• Leonard Kleinrock. Information Flow in Large Communication Nets (RLE Quarterly Progress Report, July 1961)
• Leonard Kleinrock. Communication Nets: Stochastic Message Flow and Delay (McGraw-Hill, New York, 1964)
• Kleinrock, Leonard. Queueing Systems: Volume I – Theory. New York: Wiley Interscience. 2 January 1975: 417. ISBN 978-0-471-49110-1.  含有內容需登入查看的頁面 (link)
• Kleinrock, Leonard. Queueing Systems: Volume II – Computer Applications. New York: Wiley Interscience. 22 April 1976: 576. ISBN 978-0-471-49111-8. 
• Lazowska, Edward D.; John Zahorjan; G. Scott Graham; Kenneth C. Sevcik. Quantitative System Performance: Computer System Analysis Using Queueing Network Models. Prentice-Hall, Inc. 1984. ISBN 978-0-13-746975-8. 
• Jon Kleinberg; Éva Tardos. Algorithm Design. Pearson. 30 June 2013. ISBN 978-1-292-02394-6. 

External links

• Teknomo's Queueing theory tutorial and calculators
• Virtamo's Queueing Theory Course
• Myron Hlynka's Queueing Theory Page
• LINE: a general-purpose engine to solve queueing models

Template:Queueing theory

A geodesic on an oblate ellipsoid

The study of geodesics on an ellipsoid arose in connection with geodesy specifically with the solution of triangulation networks. The figure of the Earth is well approximated by an oblate ellipsoid, a slightly flattened sphere. A geodesic is the shortest path between two points on a curved surface, i.e., the analogue of a straight line on a plane surface. The solution of a triangulation network on an ellipsoid is therefore a set of exercises in spheroidal trigonometry (Euler 1755).

Isaac Newton

Leonhard Euler

If the Earth is treated as a sphere, the geodesics are great circles (all of which are closed) and the problems reduce to ones in spherical trigonometry. However, Newton (1687) showed that the effect of the rotation of the Earth results in its resembling a slightly oblate ellipsoid and, in this case, the equator and the meridians are the only closed geodesics. Furthermore, the shortest path between two points on the equator does not necessarily run along the equator. Finally, if the ellipsoid is further perturbed to become a triaxial ellipsoid (with three distinct semi-axes), then only three geodesics are closed and one of these is unstable.

The problems in geodesy are usually reduced to two main cases: the direct problem, given a starting point and an initial heading, find the position after traveling a certain distance along the geodesic; and the inverse problem, given two points on the ellipsoid find the connecting geodesic and hence the shortest distance between them. Because the flattening of the Earth is small, the geodesic distance between two points on the Earth is well approximated by the great-circle distance using the mean Earth radius—the relative error is less than 1%. However, the course of the geodesic can differ dramatically from that of the great circle. As an extreme example, consider two points on the equator with a longitude difference of 179°59′; while the connecting great circle follows the equator, the shortest geodesics pass within 180 km of either pole (the flattening makes two symmetric paths passing close to the poles shorter than the route along the equator).

Aside from their use in geodesy and related fields such as navigation, terrestrial geodesics arise in the study of the propagation of signals which are confined (approximately) to the surface of the Earth, for example, sound waves in the ocean (Munk & Forbes 1989) and the radio signals from lightning (Casper & Bent 1991). Geodesics are used to define some maritime boundaries, which in turn determine the allocation of valuable resources as such oil and mineral rights. Ellipsoidal geodesics also arise in other applications; for example, the propagation of radio waves along the fuselage of an aircraft, which can be roughly modeled as a prolate (elongated) ellipsoid (Kim & Burnside 1986).

Geodesics are an important intrinsic characteristic of curved surfaces. The sequence of progressively more complex surfaces, the sphere, an ellipsoid of revolution, and a triaxial ellipsoid, provide a useful family of surfaces for investigating the general theory of surfaces. Indeed, Gauss's work on the survey of Hanover, which involved geodesics on an oblate ellipsoid, was a key motivation for his study of surfaces (Gauss 1828). Similarly, the existence of three closed geodesics on a triaxial ellipsoid turns out to be a general property of closed, simply connected surfaces; this was conjectured by Poincaré (1905) and proved by Lyusternik & Schnirelmann (1929) (Klingenberg 1982，§3.7).

Geodesics on an ellipsoid of revolution

There are several ways of defining geodesics (Hilbert & Cohn-Vossen 1952，第220–221頁). A simple definition is as the shortest path between two points on a surface. However, it is frequently more useful to define them as paths with zero geodesic curvature—i.e., the analogue of straight lines on a curved surface. This definition encompasses geodesics traveling so far across the ellipsoid's surface (somewhat less than half the circumference) that other distinct routes require less distance. Locally, these geodesics are still identical to the shortest distance between two points.

By the end of the 18th century, an ellipsoid of revolution (the term spheroid is also used) was a well-accepted approximation to the figure of the Earth. The adjustment of triangulation networks entailed reducing all the measurements to a reference ellipsoid and solving the resulting two-dimensional problem as an exercise in spheroidal trigonometry (Bomford 1952，Chap. 3).

Fig. 1. A geodesic AB on an ellipsoid of revolution. N is the north pole and EFH lie on the equator.

It is possible to reduce the various geodesic problems into one of two types. Consider two points: A at latitude φ₁ and longitude λ₁ and B at latitude φ₂ and longitude λ₂ (see Fig. 1). The connecting geodesic (from A to B) is AB, of length s₁₂, which has azimuths α₁ and α₂ at the two endpoints. The two geodesic problems usually considered are:

1. the direct geodesic problem or first geodesic problem, given A, α₁, and s₁₂, determine B and α₂;
2. the inverse geodesic problem or second geodesic problem, given A and B, determine s₁₂, α₁, and α₂.

As can be seen from Fig. 1, these problems involve solving the triangle NAB given one angle, α₁ for the direct problem and λ₁₂ = λ₂ − λ₁ for the inverse problem, and its two adjacent sides. In the course of the 18th century these problems were elevated (especially in literature in the German language) to the principal geodesic problems (Hansen 1865，第69頁).

For a sphere the solutions to these problems are simple exercises in spherical trigonometry, whose solution is given by formulas for solving a spherical triangle. (See the article on great-circle navigation.)

Alexis Clairaut

Barnaba Oriani

For an ellipsoid of revolution, the characteristic constant defining the geodesic was found by Clairaut (1735). A systematic solution for the paths of geodesics was given by Legendre (1806) and Oriani (1806) (and subsequent papers in 1808 and 1810). The full solution for the direct problem (complete with computational tables and a worked out example) is given by Bessel (1825).

Much of the early work on these problems was carried out by mathematicians—for example, Legendre, Bessel, and Gauss—who were also heavily involved in the practical aspects of surveying. Beginning in about 1830, the disciplines diverged: those with an interest in geodesy concentrated on the practical aspects such as approximations suitable for field work, while mathematicians pursued the solution of geodesics on a triaxial ellipsoid, the analysis of the stability of closed geodesics, etc.

During the 18th century geodesics were typically referred to as "shortest lines". The term "geodesic line" was coined by Laplace (1799b):

Nous désignerons cette ligne sous le nom de ligne géodésique [We will call this line the geodesic line].

This terminology was introduced into English either as "geodesic line" or as "geodetic line", for example (Hutton 1811),

A line traced in the manner we have now been describing, or deduced from trigonometrical measures, by the means we have indicated, is called a geodetic or geodesic line: it has the property of being the shortest which can be drawn between its two extremities on the surface of the Earth; and it is therefore the proper itinerary measure of the distance between those two points.

In its adoption by other fields "geodesic line", frequently shortened, to "geodesic", was preferred.

This section treats the problem on an ellipsoid of revolution (both oblate and prolate). The problem on a triaxial ellipsoid is covered in the next section.

When determining distances on the earth, various approximate methods are frequently used; some of these are described in the article on geographical distance.

Equations for a geodesic

Friedrich Bessel

Fig. 2. Differential element of a meridian ellipse.

Fig. 3. Differential element of a geodesic on an ellipsoid.

Here the equations for a geodesic are developed; these allow the geodesics of any length to be computed accurately. The following derivation closely follows that of Bessel (1825). Bagratuni (1962，§15), Krakiwsky & Thomson (1974，§4), Rapp (1993，§1.2), and Borre & Strang (2012) also provide derivations of these equations.

Consider an ellipsoid of revolution with equatorial radius a and polar semi-axis b. Define the flattening f = (a − b)/a, the eccentricity e² = f(2 − f), and the second eccentricity e′ = e/(1 − f). (In most applications in geodesy, the ellipsoid is taken to be oblate, a > b; however, the theory applies without change to prolate ellipsoids, a < b, in which case f, e², and e′² are negative.)

Let an elementary segment of a path on the ellipsoid have length ds. From Figs. 2 and 3, we see that if its azimuth is α, then ds is related to dφ and dλ by

(1)${\color {white}.}\qquad \cos \alpha \,ds=\rho \,d\phi =-dR/\sin \phi ,\quad \sin \alpha \,ds=R\,d\lambda ,$

where ρ is the meridional radius of curvature, R = ν cosφ is the radius of the circle of latitude φ, and ν is the normal radius of curvature. The elementary segment is therefore given by

$ds^{2}=\rho ^{2}\,d\phi ^{2}+R^{2}\,d\lambda ^{2}$

or

${\begin{aligned}ds&={\sqrt {\rho ^{2}\phi '^{2}+R^{2}}}\,d\lambda \\&\equiv L(\phi ,\phi ')\,d\lambda ,\end{aligned}}$

where φ′ = dφ/dλ and L depends on φ through ρ(φ) and R(φ). The length of an arbitrary path between (φ₁, λ₁) and (φ₂, λ₂) is given by

$s_{12}=\int _{\lambda _{1}}^{\lambda _{2}}L(\phi ,\phi ')\,d\lambda ,$

where φ is a function of λ satisfying φ(λ₁) = φ₁ and φ(λ₂) = φ₂. The shortest path or geodesic entails finding that function φ(λ) which minimizes s₁₂. This is an exercise in the calculus of variations and the minimizing condition is given by the Beltrami identity,

$L-\phi '{\frac {\partial L}{\partial \phi '}}={\text{const.}}$

Fig. 4. The geometric construction for parametric latitude, β. A point P at latitude φ on the meridian (red) is mapped to a point P′ on a sphere of radius a (shown as a blue circle) by keeping the radius R constant.

Substituting for L and using Eqs. (1) gives

$R\sin \alpha ={\text{const.}}$

Clairaut (1735) first found this relation, using a geometrical construction; a similar derivation is presented by Lyusternik (1964，§10). Differentiating this relation and manipulating the result gives (Jekeli 2012，Eq. (2.95))

$d\alpha =\sin \phi \,d\lambda .$

This, together with Eqs. (1), leads to a system of ordinary differential equations for a geodesic (Borre & Strang 2012，Eqs. (11.71) and (11.76))

(2)${\color {white}.}\qquad \displaystyle {\frac {d\phi }{ds}}={\frac {\cos \alpha }{\rho }};\quad {\frac {d\lambda }{ds}}={\frac {\sin \alpha }{\nu \cos \phi }};\quad {\frac {d\alpha }{ds}}={\frac {\tan \phi \sin \alpha }{\nu }}.$

We can express R in terms of the parametric latitude, β, using

$R=a\cos \beta$

(see Fig. 4 for the geometrical construction), and Clairaut's relation then becomes

$\sin \alpha _{1}\cos \beta _{1}=\sin \alpha _{2}\cos \beta _{2}.$

Fig. 5. Geodesic problem mapped to the auxiliary sphere.

Fig. 6. The elementary geodesic problem on the auxiliary sphere.

This is the sine rule of spherical trigonometry relating two sides of the triangle NAB (see Fig. 5), NA = ½π − β₁, and NB = ½π − β₂ and their opposite angles B = π − α₂ and A = α₁.

In order to find the relation for the third side AB = σ₁₂, the spherical arc length, and included angle N = ω₁₂, the spherical longitude, it is useful to consider the triangle NEP representing a geodesic starting at the equator; see Fig. 6. In this figure, the variables referred to the auxiliary sphere are shown with the corresponding quantities for the ellipsoid shown in parentheses. Quantities without subscripts refer to the arbitrary point P; E, the point at which the geodesic crosses the equator in the northward direction, is used as the origin for σ, s and ω.

Fig. 7. Differential element of a geodesic on a sphere.

If the side EP is extended by moving P infinitesimally (see Fig. 7), we obtain

(3)${\color {white}.}\qquad \cos \alpha \,d\sigma =d\beta ,\quad \sin \alpha \,d\sigma =\cos \beta \,d\omega .$

Combining Eqs. (1) and (3) gives differential equations for s and λ

${\frac {1}{a}}{\frac {ds}{d\sigma }}={\frac {d\lambda }{d\omega }}={\frac {\sin \beta }{\sin \phi }}.$

Up to this point, we have not made use of the specific equations for an ellipsoid, and indeed the derivation applies to an arbitrary surface of revolution. Bessel now specializes to an ellipsoid in which R and Z are related by

${\frac {R^{2}}{a^{2}}}+{\frac {Z^{2}}{b^{2}}}=1,$

where Z is the height above the equator (see Fig. 4). Differentiating this and setting dR/dZ = −sinφ/cosφ gives

${\frac {R\sin \phi }{a^{2}}}-{\frac {Z\cos \phi }{b^{2}}}=0;$

eliminating Z from these equations, we obtain

${\frac {R}{a}}=\cos \beta ={\frac {\cos \phi }{\sqrt {1-e^{2}\sin ^{2}\phi }}}.$

This relation between β and φ can be written as

$\tan \beta ={\sqrt {1-e^{2}}}\tan \phi =(1-f)\tan \phi ,$

which is the normal definition of the parametric latitude on an ellipsoid. Furthermore, we have

${\frac {\sin \beta }{\sin \phi }}={\sqrt {1-e^{2}\cos ^{2}\beta }},$

so that the differential equations for the geodesic become

${\frac {1}{a}}{\frac {ds}{d\sigma }}={\frac {d\lambda }{d\omega }}={\sqrt {1-e^{2}\cos ^{2}\beta }}.$

The last step is to use σ as the independent parameter in both of these differential equations and thereby to express s and λ as integrals. Applying the sine rule to the vertices E and G in the spherical triangle EGP in Fig. 6 gives

$\sin \beta =\sin \beta (\sigma ;\alpha _{0})=\cos \alpha _{0}\sin \sigma ,$

where α₀ is the azimuth at E. Substituting this into the equation for ds/dσ and integrating the result gives

(4)${\color {white}.}\qquad {\begin{aligned}{\frac {s}{b}}&=\int _{0}^{\sigma }{\frac {\sqrt {1-e^{2}\cos ^{2}\beta (\sigma ';\alpha _{0})}}{1-f}}\,d\sigma '\\&=\int _{0}^{\sigma }{\sqrt {1+k^{2}\sin ^{2}\sigma '}}\,d\sigma ',\end{aligned}}$

where

$k=e'\cos \alpha _{0},$

and the limits on the integral are chosen so that s(σ = 0) = 0. Legendre (1811，第180頁) pointed out that the equation for s is the same as the equation for the arc on an ellipse with semi-axes b(1 + e′² cos²α₀)^1/2 and b. In order to express the equation for λ in terms of σ, we write

$d\omega ={\frac {\sin \alpha _{0}}{\cos ^{2}\beta }}\,d\sigma ,$

which follows from Eq. (3) and Clairaut's relation. This yields

(5)${\color {white}.}\qquad {\begin{aligned}\lambda -\lambda _{0}&=(1-f)\sin \alpha _{0}\int _{0}^{\sigma }{\frac {\sqrt {1+k^{2}\sin ^{2}\sigma '}}{1-\cos ^{2}\alpha _{0}\sin ^{2}\sigma '}}\,d\sigma '\\&=\omega -\sin \alpha _{0}\int _{0}^{\sigma }{\frac {e^{2}}{1+{\sqrt {1-e^{2}\cos ^{2}\beta (\sigma ';\alpha _{0})}}}}\,d\sigma '\\&=\omega -f\sin \alpha _{0}\int _{0}^{\sigma }{\frac {2-f}{1+(1-f){\sqrt {1+k^{2}\sin ^{2}\sigma '}}}}\,d\sigma ',\end{aligned}}$

and the limits on the integrals are chosen so that λ = λ₀ at the equator crossing, σ = 0.

In using these integral relations, we allow σ to increase continuously (not restricting it to a range [−π, π], for example) as the great circle, resp. geodesic, encircles the auxiliary sphere, resp. ellipsoid. The quantities ω, λ, and s are likewise allowed to increase without limit. Once the problem is solved, λ can be reduced to the conventional range.

This completes the solution of the path of a geodesic using the auxiliary sphere. By this device a great circle can be mapped exactly to a geodesic on an ellipsoid of revolution. However, because the equations for s and λ in terms of the spherical quantities depend on α₀, the mapping is not a consistent mapping of the surface of the sphere to the ellipsoid or vice versa; instead, it should be viewed merely as a convenient tool for solving for a particular geodesic.

There are also several ways of approximating geodesics on an ellipsoid which usually apply for sufficiently short lines (Rapp 1991，§6); however, these are typically comparable in complexity to the method for the exact solution given above (Jekeli 2012，§2.1.4).

Behavior of geodesics

Fig. 8. Meridians and the equator are the only closed geodesics. (For the very flattened ellipsoids, there are other closed geodesics; see Figs. 13 and 14).

Geodesic on an oblate ellipsoid (f = 1/50) with α₀ = 45°.

Fig. 9. Latitude as a function of longitude for a single cycle of the geodesic from one northward equatorial crossing to the next.

Fig. 10. Following the geodesic on the ellipsoid for about 5 circuits.

Fig. 11. The same geodesic after about 70 circuits.

Fig. 12. Geodesic on a prolate ellipsoid (f = −1/50) with α₀ = 45°. Compare with Fig. 10.

Before solving for the geodesics, it is worth reviewing their behavior. Fig. 8 shows the simple closed geodesics which consist of the meridians (green) and the equator (red). (Here the qualification "simple" means that the geodesic closes on itself without an intervening self-intersection.) This follows from the equations for the geodesics given in the previous section.

For meridians, we have α₀ = 0 and Eq. (5) becomes λ = ω + λ₀, i.e., the longitude will vary the same way as for a sphere, jumping by π each time the geodesic crosses the pole. The distance, Eq. (4), reduces to the length of an arc of an ellipse with semi-axes a and b (as expected), expressed in terms of parametric latitude, β.

The equator (β = 0 on the auxiliary sphere, φ = 0 on the ellipsoid) corresponds to α₀ = ½π. The distance reduces to the arc of a circle of radius b (and not a), s = bσ, while the longitude simplifies to λ = (1 − f)σ + λ₀. A geodesic that is nearly equatorial will intersect the equator at intervals of πb. As a consequence, the maximum length of a equatorial geodesic which is also a shortest path is πb on an oblate ellipsoid (on a prolate ellipsoid, the maximum length is πa).

All other geodesics are typified by Figs. 9 to 11. Figure 9 shows latitude as a function of longitude for a geodesic starting on the equator with α₀ = 45°. A full cycle of the geodesic, from one northward crossing of the equator to the next, is shown. The equatorial crossings are called nodes and the points of maximum or minimum latitude are called vertices; the vertex latitudes are given by |β| = ±(½π − |α₀|). The latitude is an odd, resp. even, function of the longitude about the nodes, resp. vertices. The geodesic completes one full oscillation in latitude before the longitude has increased by 360°. Thus, on each successive northward crossing of the equator (see Fig. 10), λ falls short of a full circuit of the equator by approximately 2π f sinα₀ (for a prolate ellipsoid, this quantity is negative and λ completes more that a full circuit; see Fig. 12). For nearly all values of α₀, the geodesic will fill that portion of the ellipsoid between the two vertex latitudes (see Fig. 11).

Two additional closed geodesics for the oblate ellipsoid, b/a = 2/7.

Fig. 13. Side view.

Fig. 14. Top view.

If the ellipsoid is sufficiently oblate, i.e., b/a < ½, another class of simple closed geodesics is possible (Klingenberg 1982，§3.5.19). Two such geodesics are illustrated in Figs. 13 and 14. Here b/a = 2/7 and the equatorial azimuth, α₀, for the green (resp. blue) geodesic is chosen to be 53.175° (resp. 75.192°), so that the geodesic completes 2 (resp. 3) complete oscillations about the equator on one circuit of the ellipsoid.

Evaluation of the integrals

Solving the geodesic problems entails evaluating the integrals for the distance, s, and the longitude, λ, Eqs. (4) and (5). In geodetic applications, where f is small, the integrals are typically evaluated as a series; for this purpose, the second form of the longitude integral is preferred (since it avoids the near singular behavior of the first form when geodesics pass close to a pole). In both integrals, the integrand is an even periodic function of period π. Furthermore, the term dependent on σ is multiplied by a small quantity k² = O(f). As a consequence, the integrals can both be written in the form

$I=B_{0}\sigma +\sum _{j=1}^{\infty }B_{j}\sin 2j\sigma$

where B₀ = 1 + O(f) and B_j = O(f ^j). Series expansions for B_j can readily be found and the result truncated so that only terms which are O(f ^J) and larger are retained. (Because the longitude integral is multiplied by f, it is typically only necessary to retain terms up to O(f ^J−1) in that integral.) This prescription is followed by many authors (Legendre 1806) (Oriani 1806) (Bessel 1825) (Helmert 1880) (Rainsford 1955) (Rapp 1993). Vincenty (1975a) uses J = 3 which provides an accuracy of about 0.1 mm for the WGS84 ellipsoid. Karney (2013) gives expansions carried out for J = 6 which suffices to provide full double precision accuracy for |f| ≤ 1/50. Trigonometric series of this type can be conveniently summed using Clenshaw summation.

In order to solve the direct geodesic problem, it is necessary to find σ given s. Since the integrand in the distance integral is positive, this problem has a unique root, which may be found using Newton's method, noting that the required derivative is just the integrand of the distance integral. Oriani (1833) instead uses series reversion so that σ can be found without iteration; Helmert (1880) gives a similar series. The reverted series converges somewhat slower that the direct series and, if |f| > 1/100, Karney (2013，addenda) supplements the reverted series with one step of Newton's method to maintain accuracy. Vincenty (1975a) instead relies on a simpler (but slower) function iteration to solve for σ.

It is also possible to evaluate the integrals (4) and (5) by numerical quadrature (Saito 1970) (Saito 1979) (Sjöberg & Shirazian 2012) or to apply numerical techniques for the solution of the ordinary differential equations, Eqs. (2) (Kivioja 1971) (Thomas & Featherstone 2005) (Panou et al. 2013). Such techniques can be used for arbitrary flattening f. However, if f is small, e.g., |f| ≤ 1/50, they do not offer the speed and accuracy of the series expansions described above. Furthermore, for arbitrary f, the evaluation of the integrals in terms of elliptic integrals (see below) also provides a fast and accurate solution. On the other hand, Mathar (2007) has tackled the more complex problem of geodesics on the surface at a constant altitude, h, above the ellipsoid by solving the corresponding ordinary differential equations, Eqs. (2) with [ρ, ν] replaced by [ρ + h, ν + h].

A. M. Legendre

Arthur Cayley

Geodesics on an ellipsoid was an early application of elliptic integrals. In particular, Legendre (1811) writes the integrals, Eqs. (4) and (5), as

(6)${\color {white}.}\qquad \displaystyle {\frac {s}{b}}=E(\sigma ,ik),$

(7)${\color {white}.}\qquad {\begin{aligned}\lambda &=(1-f)\sin \alpha _{0}G(\sigma ,\cos ^{2}\alpha _{0},ik)\\&=\chi -{\frac {e'^{2}}{\sqrt {1+e'^{2}}}}\sin \alpha _{0}H(\sigma ,-e'^{2},ik),\\\end{aligned}}$

where

$\tan \chi ={\sqrt {\frac {1+e'^{2}}{1+k^{2}\sin ^{2}\sigma }}}\tan \omega ,$

and

${\begin{aligned}G(\phi ,\alpha ^{2},k)&=\int _{0}^{\phi }{\frac {\sqrt {1-k^{2}\sin ^{2}\theta }}{1-\alpha ^{2}\sin ^{2}\theta }}\,d\theta \\&={\frac {k^{2}}{\alpha ^{2}}}F(\phi ,k)+{\biggl (}1-{\frac {k^{2}}{\alpha ^{2}}}{\biggr )}\Pi (\phi ,\alpha ^{2},k),\\H(\phi ,\alpha ^{2},k)&=\int _{0}^{\phi }{\frac {\cos ^{2}\theta }{(1-\alpha ^{2}\sin ^{2}\theta ){\sqrt {1-k^{2}\sin ^{2}\theta }}}}\,d\theta \\&={\frac {1}{\alpha ^{2}}}F(\phi ,k)+{\biggl (}1-{\frac {1}{\alpha ^{2}}}{\biggr )}\Pi (\phi ,\alpha ^{2},k),\end{aligned}}$

and F(φ, k), E(φ, k), and Π(φ, α², k), are incomplete elliptic integrals in the notation of DLMF (2010，§19.2(ii)). The first formula for the longitude in Eq. (7) follows directly from the first form of Eq. (5). The second formula in Eq. (7), due to Cayley (1870), is more convenient for calculation since the elliptic integral appears in a small term. The equivalence of the two forms follows from DLMF (2010，Eq. (19.7.8)). Fast algorithms for computing elliptic integrals are given by Carlson (1995) in terms of symmetric elliptic integrals. Equation (6) is conveniently inverted using Newton's method. The use of elliptic integrals provides a good method of solving the geodesic problem for |f| > 1/50.

Solution of the direct problem

The basic strategy for solving the geodesic problems on the ellipsoid is to map the problem onto the auxiliary sphere by converting φ, λ, and s, to β, ω and σ, to solve the corresponding great-circle problem on the sphere, and to transfer the results back to the ellipsoid.

In implementing this program, we will frequently need to solve the "elementary" spherical triangle for NEP in Fig. 6 with P replaced by either A (subscript 1) or B (subscript 2). For this purpose, we can apply Napier's rules for quadrantal triangles to the triangle NEP on the auxiliary sphere which give

${\begin{aligned}\sin \alpha _{0}&=\sin \alpha \cos \beta =\tan \omega \cot \sigma ,\\\cos \sigma &=\cos \beta \cos \omega =\tan \alpha _{0}\cot \alpha ,\\\cos \alpha &=\cos \omega \cos \alpha _{0}=\cot \sigma \tan \beta ,\\\sin \beta &=\cos \alpha _{0}\sin \sigma =\cot \alpha \tan \omega ,\\\sin \omega &=\sin \sigma \sin \alpha =\tan \beta \tan \alpha _{0}.\end{aligned}}$

We can also stipulate that cosβ ≥ 0 and cosα₀ ≥ 0. Implementing this plan for the direct problem is straightforward. We are given φ₁, α₁, and s₁₂. From φ₁ we obtain β₁ (using the formula for the parametric latitude). We now solve the triangle problem with P = A and β₁ and α₁ given to find α₀, σ₁, and ω₁. Use the distance and longitude equations, Eqs. (4) and (5), together with the known value of λ₁, to find s₁ and λ₀. Determine s₂ = s₁ + s₁₂ and invert the distance equation to find σ₂. Solve the triangle problem with P = B and α₀ and σ₂ given to find β₂, ω₂, and α₂. Convert β₂ to φ₂ and substitute σ₂ and ω₂ into the longitude equation to give λ₂.

The overall method follows the procedure for solving the direct problem on a sphere. It is essentially the program laid out by Bessel (1825), Helmert (1880，§5.9), and most subsequent authors.

Intermediate points, way-points, on a geodesic can be found by holding φ₁ and α₁ fixed and solving the direct problem for several values of s₁₂. Once the first waypoint is found, only the last portion of the solution (starting with the determination of s₂) needs to be repeated for each new value of s₁₂.

Solution of the inverse problem

The ease with which the direct problem can be solved results from the fact that given φ₁ and α₁, we can immediately find α₀, the parameter in the distance and longitude integrals, Eqs. (4) and (5). In the case of the inverse problem, we are given λ₁₂, but we cannot easily relate this to the equivalent spherical angle ω₁₂ because α₀ is unknown. Thus, the solution of the problem requires that α₀ be found iteratively. Before tackling this, it is worth understanding better the behavior of geodesics, this time, keeping the starting point fixed and varying the azimuth.

Geodesics from a single point (f = 1/10, φ₁ = −30°)

Fig. 15. Geodesics, geodesic circles, and the cut locus.

Fig. 16. The geodesics shown on a plate carrée projection.

Fig. 17. λ₁₂ as a function of α₁ for φ₁ = −30° and φ₂ = 20°.

Suppose point A in the inverse problem has φ₁ = −30° and λ₁ = 0°. Fig. 15 shows geodesics (in blue) emanating A with α₁ a multiple of 15° up to the point at which they cease to be shortest paths. (The flattening has been increased to 1/10 in order to accentuate the ellipsoidal effects.) Also shown (in green) are curves of constant s₁₂, which are the geodesic circles centered A. Gauss (1828) showed that, on any surface, geodesics and geodesic circle intersect at right angles. The red line is the cut locus, the locus of points which have multiple (two in this case) shortest geodesics from A. On a sphere, the cut locus is a point. On an oblate ellipsoid (shown here), it is a segment of the circle of latitude centered on the point antipodal to A, φ = −φ₁. The longitudinal extent of cut locus is approximately λ₁₂ ∈ [π − f π cosφ₁, π + f π cosφ₁]. If A lies on the equator, φ₁ = 0, this relation is exact and as a consequence the equator is only a shortest geodesic if |λ₁₂| ≤ (1 − f)π. For a prolate ellipsoid, the cut locus is a segment of the anti-meridian centered on the point antipodal to A, λ₁₂ = π, and this means that meridional geodesics stop being shortest paths before the antipodal point is reached.

The solution of the inverse problem involves determining, for a given point B with latitude φ₂ and longitude λ₂ which blue and green curves it lies on; this determines α₁ and s₁₂ respectively. In Fig. 16, the ellipsoid has been "rolled out" onto a plate carrée projection. Suppose φ₂ = 20°, the green line in the figure. Then as α₁ is varied between 0° and 180°, the longitude at which the geodesic intersects φ = φ₂ varies between 0° and 180° (see Fig. 17). This behavior holds provided that |φ₂| ≤ |φ₁| (otherwise the geodesic does not reach φ₂ for some values of α₁). Thus, the inverse problem may be solved by determining the value α₁ which results in the given value of λ₁₂ when the geodesic intersects the circle φ = φ₂.

This suggests the following strategy for solving the inverse problem (Karney 2013). Assume that the points A and B satisfy

(8)${\color {white}.}\qquad \phi _{1}\leq 0,\quad \left|\phi _{2}\right|\leq \left|\phi _{1}\right|,\quad 0\leq \lambda _{12}\leq \pi .$

(There is no loss of generality in this assumption, since the symmetries of the problem can be used to generate any configuration of points from such configurations.)

1. First treat the "easy" cases, geodesics which lie on a meridian or the equator. Otherwise...
2. Guess a value of α₁.
3. Solve the so-called hybrid geodesic problem, given φ₁, φ₂, and α₁ find λ₁₂, s₁₂, and α₂, corresponding to the first intersection of the geodesic with the circle φ = φ₂.
4. Compare the resulting λ₁₂ with the desired value and adjust α₁ until the two values agree. This completes the solution.

Each of these steps requires some discussion.

1. For an oblate ellipsoid, the shortest geodesic lies on a meridian if either point lies on a pole or if λ₁₂ = 0 or ±π. The shortest geodesic follows the equator if φ₁ = φ₂ = 0 and |λ₁₂| ≤ (1 − f)π. For a prolate ellipsoid, the meridian is no longer the shortest geodesic if λ₁₂ = ±π and the points are close to antipodal (this will be discussed in the next section). There is no longitudinal restriction on equatorial geodesics.

2. In most cases a suitable starting value of α₁ is found by solving the spherical inverse problem

$\tan \alpha _{1}={\frac {\cos \beta _{2}\sin \omega _{12}}{\cos \beta _{1}\sin \beta _{2}-\sin \beta _{1}\cos \beta _{2}\cos \omega _{12}}},$

with ω₁₂ = λ₁₂. This may be a bad approximation if A and B are nearly antipodal (both the numerator and denominator in the formula above become small); however, this may not matter (depending on how step 4 is handled).

3. The solution of the hybrid geodesic problem is as follows. It starts the same way as the solution of the direct problem, solving the triangle NEP with P = A to find α₀, σ₁, ω₁, and λ₀. Now find α₂ from sinα₂ = sinα₀/cosβ₂, taking cosα₂ ≥ 0 (corresponding to the first, northward, crossing of the circle φ = φ₂). Next, σ₂ is given by tanσ₂ = tanβ₂/cosα₂ and ω₂ by tanω₂ = tanσ₂/sinα₀. Finally, use the distance and longitude equations, Eqs. (4) and (5), to find s₁₂ and λ₁₂.

4. In order to discuss how α₁ is updated, let us define the root-finding problem in more detail. The curve in Fig. 17 shows λ₁₂(α₁; φ₁, φ₂) where we regard φ₁ and φ₂ as parameters and α₁ as the independent variable. We seek the value of α₁ which is the root of

$g(\alpha _{1})\equiv \lambda _{12}(\alpha _{1};\phi _{1},\phi _{2})-\lambda _{12}=0,$

where g(0) ≤ 0 and g(π) ≥ 0. In fact, there is a unique root in the interval α₁ ∈ [0, π]. Any of a number of root-finding algorithms can be used to solve such an equation. Karney (2013) uses Newton's method, which requires a good starting guess; however it may be supplemented by a fail-safe method, such as the bisection method, to guarantee convergence.

F. R. Helmert

An alternative method for solving the inverse problem is given by Helmert (1880，§5.13). Let us rewrite the Eq. (5) as

${\begin{aligned}\lambda _{12}&=\omega _{12}-f\sin \alpha _{0}\int _{\sigma _{1}}^{\sigma _{2}}{\frac {2-f}{1+(1-f){\sqrt {1+k^{2}\sin ^{2}\sigma '}}}}\,d\sigma '\\&=\omega _{12}-f\sin \alpha _{0}I(\sigma _{1},\sigma _{2};\alpha _{0}).\end{aligned}}$

Helmert's method entails assuming that ω₁₂ = λ₁₂, solving the resulting problem on auxiliary sphere, and obtaining an updated estimate of ω₁₂ using

$\omega _{12}=\lambda _{12}+f\sin \alpha _{0}I(\sigma _{1},\sigma _{2};\alpha _{0}).$

This fixed point iteration is repeated until convergence. Rainsford (1955) advocates this method and Vincenty (1975a) adopted it in his solution of the inverse problem. The drawbacks of this method are that convergence is slower than obtained using Newton's method (as described above) and, more seriously, that the process fails to converge at all for nearly antipodal points. In a subsequent report, Vincenty (1975b) attempts to cure this defect; but he is only partially successful—the NGS (2012) implementation still includes Vincenty's fix still fails to converge in some cases. Lee (2011) has compared 17 methods for solving the inverse problem against the method given by Karney (2013).

The shortest distance returned by the solution of the inverse problem is (obviously) uniquely defined. However, if B lies on the cut locus of A there are multiple azimuths which yield the same shortest distance. Here is a catalog of those cases:

• φ₁ = −φ₂ (with neither point at a pole). If α₁ = α₂, the geodesic is unique. Otherwise there are two geodesics and the second one is obtained by interchanging α₁ and α₂. (This occurs when λ₁₂ ≈ ±π for oblate ellipsoids.)
• λ₁₂ = ±π (with neither point at a pole). If α₁ = 0 or ±π, the geodesic is unique. Otherwise there are two geodesics and the second one is obtained by negating α₁ and α₂. (This occurs when φ₁ + φ₂ ≈ 0 for prolate ellipsoids.)
• A and B are at opposite poles. There are infinitely many geodesics which can be generated by varying the azimuths so as to keep α₁ + α₂ constant. (For spheres, this prescription applies when A and B are antipodal.)

Differential behavior of geodesics

C. F. Gauss

E. B. Christoffel

Various problems involving geodesics require knowing their behavior when they are perturbed. This is useful in trigonometric adjustments (Ehlert 1993), determining the physical properties of signals which follow geodesics, etc. Consider a reference geodesic, parameterized by s the length from the northward equator crossing, and a second geodesic a small distance t(s) away from it. Gauss (1828) showed that t(s) obeys the Gauss-Jacobi equation

(9)${\color {white}.}\qquad \displaystyle {\frac {d^{2}t(s)}{ds^{2}}}=K(s)t(s),$

Fig. 18. Definition of reduced length and geodesic scale.

where K(s) is the Gaussian curvature at s. The solution may be expressed as the sum of two independent solutions

$t(s_{2})=Cm(s_{1},s_{2})+DM(s_{1},s_{2})$

where

${\begin{aligned}m(s_{1},s_{1})&=0,\quad \left.{\frac {dm(s_{1},s_{2})}{ds_{2}}}\right|_{s_{2}=s_{1}}=1,\\M(s_{1},s_{1})&=1,\quad \left.{\frac {dM(s_{1},s_{2})}{ds_{2}}}\right|_{s_{2}=s_{1}}=0.\end{aligned}}$

We shall abbreviate m(s₁, s₂) = m₁₂, the so-called reduced length, and M(s₁, s₂) = M₁₂, the geodesic scale. Their basic definitions are illustrated in Fig. 18. Christoffel (1869) made an extensive study of their properties. The reduced length obeys a reciprocity relation,

$m_{12}+m_{21}=0.$

Their derivatives are

${\begin{aligned}{\frac {dm_{12}}{ds_{2}}}&=M_{21},\\{\frac {dM_{12}}{ds_{2}}}&=-{\frac {1-M_{12}M_{21}}{m_{12}}}.\end{aligned}}$

Assuming that points 1, 2, and 3, lie on the same geodesic, then the following addition rules apply (Karney 2013),

${\begin{aligned}m_{13}&=m_{12}M_{23}+m_{23}M_{21},\\M_{13}&=M_{12}M_{23}-(1-M_{12}M_{21}){\frac {m_{23}}{m_{12}}},\\M_{31}&=M_{32}M_{21}-(1-M_{23}M_{32}){\frac {m_{12}}{m_{23}}}.\end{aligned}}$

The reduced length and the geodesic scale are components of the Jacobi field.

The Gaussian curvature for an ellipsoid of revolution is

$K={\frac {1}{\rho \nu }}={\frac {(1-e^{2}\sin ^{2}\phi )^{2}}{b^{2}}}={\frac {b^{2}}{a^{4}(1-e^{2}\cos ^{2}\beta )^{2}}}.$

Helmert (1880，Eq. (6.5.1.)) solved the Gauss-Jacobi equation for this case obtaining

${\begin{aligned}m_{12}/b&={\sqrt {1+k^{2}\sin ^{2}\sigma _{2}}}\,\cos \sigma _{1}\sin \sigma _{2}-{\sqrt {1+k^{2}\sin ^{2}\sigma _{1}}}\,\sin \sigma _{1}\cos \sigma _{2}\\&\quad -\cos \sigma _{1}\cos \sigma _{2}{\bigl (}J(\sigma _{2})-J(\sigma _{1}){\bigr )},\\M_{12}&=\cos \sigma _{1}\cos \sigma _{2}+{\frac {\sqrt {1+k^{2}\sin ^{2}\sigma _{2}}}{\sqrt {1+k^{2}\sin ^{2}\sigma _{1}}}}\sin \sigma _{1}\sin \sigma _{2}\\&\quad -{\frac {\sin \sigma _{1}\cos \sigma _{2}{\bigl (}J(\sigma _{2})-J(\sigma _{1}){\bigr )}}{\sqrt {1+k^{2}\sin ^{2}\sigma _{1}}}},\end{aligned}}$

where

${\begin{aligned}J(\sigma )&=\int _{0}^{\sigma }{\frac {k^{2}\sin ^{2}\sigma '}{\sqrt {1+k^{2}\sin ^{2}\sigma '}}}\,d\sigma '\\&=E(\sigma ,ik)-F(\sigma ,ik).\end{aligned}}$

As we see from Fig. 18 (top sub-figure), the separation of two geodesics starting at the same point with azimuths differing by dα₁ is m₁₂ dα₁. On a closed surface such as an ellipsoid, we expect m₁₂ to oscillate about zero. Indeed, if the starting point of a geodesic is a pole, φ₁ = ½π, then the reduced length is the radius of the circle of latitude, m₁₂ = a cosβ₂ = a sinσ₁₂. Similarly, for a meridional geodesic starting on the equator, φ₁ = α₁ = 0, we have M₁₂ = cosσ₁₂. In the typical case, these quantities oscillate with a period of about 2π in σ₁₂ and grow linearly with distance at a rate proportional to f. In trigonometric adjustments over small areas, it may be possible to approximate K(s) in Eq. (9) by a constant K. In this limit, the solutions for m₁₂ and M₁₂ are the same as for a sphere of radius 1/√K, namely,

$m_{12}=\sin({\sqrt {K}}s_{12})/{\sqrt {K}},\quad M_{12}=\cos({\sqrt {K}}s_{12}).$

To simplify the discussion of shortest paths in this paragraph we consider only geodesics with s₁₂ > 0. The point at which m₁₂ becomes zero is the point conjugate to the starting point. In order for a geodesic between A and B, of length s₁₂, to be a shortest path it must satisfy the Jacobi condition (Jacobi 1837) (Jacobi 1866，§6) (Forsyth 1927，§§26–27) (Bliss 1916), that there is no point conjugate to A between A and B. If this condition is not satisfied, then there is a nearby path (not necessarily a geodesic) which is shorter. Thus, the Jacobi condition is a local property of the geodesic and is only a necessary condition for the geodesic being a global shortest path. Necessary and sufficient conditions for a geodesic being the shortest path are:

• for an oblate ellipsoid, |σ₁₂| ≤ π;
• for a prolate ellipsoid, |λ₁₂| ≤ π, if α₀ ≠ 0; if α₀ = 0, the supplemental condition m₁₂ ≥ 0 is required if |λ₁₂| = π.

The latter condition above can be used to determine whether the shortest path is a meridian in the case of a prolate ellipsoid with |λ₁₂| = π. The derivative required to solve the inverse method using Newton's method, ∂λ₁₂(α₁; φ₁, φ₂) / ∂α₁, is given in terms of the reduced length (Karney 2013，Eq. (46)).

Geodesic map projections

Two map projections are defined in terms of geodesics. They are based on polar and rectangular geodesic coordinates on the surface (Gauss 1828). The polar coordinate system (r, θ) is centered on some point A. The coordinates of another point B are given by r = s₁₂ and θ = ½π − α₁ and these coordinates are used to find the projected coordinates on a plane map, x = r cosθ and y = r sinθ. The result is the familiar azimuthal equidistant projection; in the field of the differential geometry of surfaces, it is called the exponential map. Due to the basic properties of geodesics (Gauss 1828), lines of constant r and lines of constant θ intersect at right angles on the surface. The scale of the projection in the radial direction is unity, while the scale in the azimuthal direction is s₁₂/m₁₂.

The rectangular coordinate system (x, y) uses a reference geodesic defined by A and α₁ as the x axis. The point (x, y) is found by traveling a distance s₁₃ = x from A along the reference geodesic to an intermediate point C and then turning ½π counter-clockwise and traveling along a geodesic a distance s₃₂ = y. If A is on the equator and α₁ = ½π, this gives the equidistant cylindrical projection. If α₁ = 0, this gives the Cassini-Soldner projection. Cassini's map of France placed A at the Paris Observatory. Due to the basic properties of geodesics (Gauss 1828), lines of constant x and lines of constant y intersect at right angles on the surface. The scale of the projection in the y direction is unity, while the scale in the x direction is 1/M₃₂.

The gnomonic projection is a projection of the sphere where all geodesics (i.e., great circles) map to straight lines (making it a convenient aid to navigation). Such a projection is only possible for surfaces of constant Gaussian curvature (Beltrami 1865). Thus a projection in which geodesics map to straight lines is not possible for an ellipsoid. However, it is possible to construct an ellipsoidal gnomonic projection in which this property approximately holds (Karney 2013，§8). On the sphere, the gnomonic projection is the limit of a doubly azimuthal projection, a projection preserving the azimuths from two points A and B, as B approaches A. Carrying out this limit in the case of a general surface yields an azimuthal projection in which the distance from the center of projection is given by ρ = m₁₂/M₁₂. Even though geodesics are only approximately straight in this projection, all geodesics through the center of projection are straight. The projection can then be used to give an iterative but rapidly converging method of solving some problems involving geodesics, in particular, finding the intersection of two geodesics and finding the shortest path from a point to a geodesic.

The Hammer retroazimuthal projection is a variation of the azimuthal equidistant projection (Hammer 1910). A geodesic is constructed from a central point A to some other point B. The polar coordinates of the projection of B are r = s₁₂ and θ = ½π − α₂ (which depends on the azimuth at B, instead of at A). This can be used to determine the direction from an arbitrary point to some fixed center. Hinks (1929) suggested another application: if the central point A is a beacon, such as the Rugby Clock, then at an unknown location B the range and the bearing to A can be measured and the projection can be used to estimate the location of B.

Envelope of geodesics

Geodesics from a single point (f = 1/10, φ₁ = −30°)

Fig. 19. The envelope of geodesics from a point A at φ₁ = −30°.

Fig. 20. The four geodesics connecting A and a point B, φ₂ = 26°, λ₁₂ = 175°.

The geodesics from a particular point A if continued past the cut locus form an envelope illustrated in Fig. 19. Here the geodesics for which α₁ is a multiple of 3° are shown in light blue. (The geodesics are only shown for their first passage close to the antipodal point, not for subsequent ones.) Some geodesic circles are shown in green; these form cusps on the envelope. The cut locus is shown in red. The envelope is the locus of points which are conjugate to A; points on the envelope may be computed by finding the point at which m₁₂ = 0 on a geodesic (and Newton's method can be used to find this point). Jacobi (1891) calls this star-like figure produced by the envelope an astroid.

Outside the astroid two geodesics intersect at each point; thus there are two geodesics (with a length approximately half the circumference of the ellipsoid) between A and these points. This corresponds to the situation on the sphere where there are "short" and "long" routes on a great circle between two points. Inside the astroid four geodesics intersect at each point. Four such geodesics are shown in Fig. 20 where the geodesics are numbered in order of increasing length. (This figure uses the same position for A as Fig. 15 and is drawn in the same projection.) The two shorter geodesics are stable, i.e., m₁₂ > 0, so that there is no nearby path connecting the two points which is shorter; the other two are unstable. Only the shortest line (the first one) has σ₁₂ ≤ π. All the geodesics are tangent to the envelope which is shown in green in the figure. A similar set of geodesics for the WGS84 ellipsoid is given in this table (Karney 2011，Table 1):

Geodesics for φ₁ = −30°, φ₂ = 29.9°, λ₁₂ = 179.8° (WGS84)

No.	α1 (°)	α2 (°)	s12 (m)	σ12 (°)	m12 (m)
1	161.890524736	18.090737246	19989832.8276	179.894971388	57277.3769
2	30.945226882	149.089121757	20010185.1895	180.116378785	24240.7062
3	68.152072881	111.990398904	20011886.5543	180.267429871	−22649.2935
4	−81.075605986	−99.282176388	20049364.2525	180.630976969	−68796.1679

The approximate shape of the astroid is given by

$x^{2/3}+y^{2/3}=1$

or, in parametric form,

$x=\cos ^{3}\theta ,\quad y=\sin ^{3}\theta .$

The astroid is also the envelope of the family of lines

${\frac {x}{\cos \gamma }}+{\frac {y}{\sin \gamma }}=1,$

where γ is a parameter. (These are generated by the rod of the trammel of Archimedes.) This aids in finding a good starting guess for α₁ for Newton's method for in inverse problem in the case of nearly antipodal points (Karney 2013，§5).

The astroid is the (exterior) evolute of the geodesic circles centered at A. Likewise, the geodesic circles are involutes of the astroid.

Area of a geodesic polygon

A geodesic polygon is a polygon whose sides are geodesics. The area of such a polygon may be found by first computing the area between a geodesic segment and the equator, i.e., the area of the quadrilateral AFHB in Fig. 1 (Danielsen 1989). Once this area is known, the area of a polygon may be computed by summing the contributions from all the edges of the polygon.

Here we develop the formula for the area S₁₂ of AFHB following Sjöberg (2006). The area of any closed region of the ellipsoid is

$T=\int dT=\int {\frac {1}{K}}\cos \phi \,d\phi \,d\lambda ,$

where dT is an element of surface area and K is the Gaussian curvature. Now the Gauss–Bonnet theorem applied to a geodesic polygon states

$\Gamma =\int K\,dT=\int \cos \phi \,d\phi \,d\lambda ,$

where

$\Gamma =2\pi -\sum _{j}\theta _{j}$

is the geodesic excess and θ_j is the exterior angle at vertex j. Multiplying the equation for Γ by R₂², where R₂ is the authalic radius, and subtracting this from the equation for T gives

${\begin{aligned}T&=R_{2}^{2}\,\Gamma +\int {\biggl (}{\frac {1}{K}}-R_{2}^{2}{\biggr )}\cos \phi \,d\phi \,d\lambda \\&=R_{2}^{2}\,\Gamma +\int {\biggl (}{\frac {b^{2}}{(1-e^{2}\sin ^{2}\phi )^{2}}}-R_{2}^{2}{\biggr )}\cos \phi \,d\phi \,d\lambda ,\end{aligned}}$

where the value of K for an ellipsoid has been substituted. Applying this formula to the quadrilateral AFHB, noting that Γ = α₂ − α₁, and performing the integral over φ gives

$S_{12}=R_{2}^{2}(\alpha _{2}-\alpha _{1})+b^{2}\int _{\lambda _{1}}^{\lambda _{2}}{\biggl (}{\frac {1}{2(1-e^{2}\sin ^{2}\phi )}}+{\frac {\tanh ^{-1}(e\sin \phi )}{2e\sin \phi }}-{\frac {R_{2}^{2}}{b^{2}}}{\biggr )}\sin \phi \,d\lambda ,$

where the integral is over the geodesic line (so that φ is implicitly a function of λ). Converting this into an integral over σ, we obtain

$S_{12}=R_{2}^{2}E_{12}-e^{2}a^{2}\cos \alpha _{0}\sin \alpha _{0}\int _{\sigma _{1}}^{\sigma _{2}}{\frac {t(e'^{2})-t(k^{2}\sin ^{2}\sigma )}{e'^{2}-k^{2}\sin ^{2}\sigma }}{\frac {\sin \sigma }{2}}\,d\sigma ,$

where

$t(x)=1+x+{\sqrt {1+x}}{\frac {\sinh ^{-1}\!{\sqrt {x}}}{\sqrt {x}}},$

and the notation E₁₂ = α₂ − α₁ is used for the geodesic excess. The integral can be expressed as a series valid for small f (Danielsen 1989) (Karney 2013，§6 and addendum).

The area of a geodesic polygon is given by summing S₁₂ over its edges. This result holds provided that the polygon does not include a pole; if it does 2π R₂² must be added to the sum. If the edges are specified by their vertices, then a convenient expression for E₁₂ is

$\tan {\frac {E_{12}}{2}}={\frac {\sin {\tfrac {1}{2}}(\beta _{2}+\beta _{1})}{\cos {\tfrac {1}{2}}(\beta _{2}-\beta _{1})}}\tan {\frac {\omega _{12}}{2}}.$

This result follows from one of Napier's analogies.

Software implementations

An implementation of Vincenty's algorithm in Fortran is provided by NGS (2012). Version 3.0 includes Vincenty's treatment of nearly antipodal points (Vincenty 1975b). Vincenty's original formulas are used in many geographic information systems. Except for nearly antipodal points (where the inverse method fails to converge), this method is accurate to about 0.1 mm for the WGS84 ellipsoid (Karney 2011，§9).

The algorithms given in Karney (2013) are included in GeographicLib (Karney 2014). These are accurate to about 15 nanometers for the WGS84 ellipsoid. Implementations in several languages (C++, C, Fortran, Java, JavaScript, Python, Matlab, and Maxima) are provided. In addition to solving the basic geodesic problem, this library can return m₁₂, M₁₂, M₂₁, and S₁₂. The library includes a command-line utility, GeodSolve, for geodesic calculations. As of version 4.9.1, the PROJ.4 library for cartographic projections uses the C implementation for geodesic calculations. This is exposed in the command-line utility, geod, and in the library itself.

The solution of the geodesic problems in terms of elliptic integrals is included in GeographicLib (in C++ only), e.g., via the -E option to GeodSolve. This method of solution is about 2–3 times slower than using series expansions; however it provides accurate solutions for ellipsoids of revolution with b/a ∈ [0.01, 100] (Karney 2013，addenda).

Geodesics on a triaxial ellipsoid

Solving the geodesic problem for an ellipsoid of revolution is, from the mathematical point of view, relatively simple: because of symmetry, geodesics have a constant of the motion, given by Clairaut's relation allowing the problem to be reduced to quadrature. By the early 19th century (with the work of Legendre, Oriani, Bessel, et al.), there was a complete understanding of the properties of geodesics on an ellipsoid of revolution.

On the other hand, geodesics on a triaxial ellipsoid (with 3 unequal axes) have no obvious constant of the motion and thus represented a challenging "unsolved" problem in the first half of the 19th century. In a remarkable paper, Jacobi (1839) discovered a constant of the motion allowing this problem to be reduced to quadrature also (Klingenberg 1982，§3.5).

Triaxial coordinate systems

Gaspard Monge

Charles Dupin

The key to the solution is expressing the problem in the "right" coordinate system. Consider the ellipsoid defined by

$h={\frac {X^{2}}{a^{2}}}+{\frac {Y^{2}}{b^{2}}}+{\frac {Z^{2}}{c^{2}}}=1,$

where (X,Y,Z) are Cartesian coordinates centered on the ellipsoid and, without loss of generality, a ≥ b ≥ c > 0. A point on the surface is specified by a latitude and longitude. The geographical latitude and longitude (φ, λ) are defined by

${\frac {\nabla h}{\left|\nabla h\right|}}=\left({\begin{array}{c}\cos \phi \cos \lambda \\\cos \phi \sin \lambda \\\sin \phi \end{array}}\right).$

The parametric latitude and longitude (φ′, λ′) are defined by

${\begin{aligned}X&=a\cos \phi '\cos \lambda ',\\Y&=b\cos \phi '\sin \lambda ',\\Z&=c\sin \phi '.\end{aligned}}$

Jacobi (1866，§§26–27) employed the ellipsoidal latitude and longitude (β, ω) defined by

Fig. 21. Ellipsoidal coordinates.

${\begin{aligned}X&=a\cos \omega {\frac {\sqrt {a^{2}-b^{2}\sin ^{2}\beta -c^{2}\cos ^{2}\beta }}{\sqrt {a^{2}-c^{2}}}},\\Y&=b\cos \beta \sin \omega ,\\Z&=c\sin \beta {\frac {\sqrt {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega -c^{2}}}{\sqrt {a^{2}-c^{2}}}}.\end{aligned}}$

In the limit b → a, β becomes the parametric latitude for an oblate ellipsoid, so the use of the symbol β is consistent with the previous sections. However, ω is different from the spherical longitude defined above.

Grid lines of constant β (in blue) and ω (in green) are given in Fig. 21. In contrast to (φ, λ) and (φ′, λ′), (β, ω) is an orthogonal coordinate system: the grid lines intersect at right angles. The principal sections of the ellipsoid, defined by X = 0 and Z = 0 are shown in red. The third principal section, Y = 0, is covered by the lines β = ±90° and ω = 0° or ±180°. These lines meet at four umbilical points (two of which are visible in this figure) where the principal radii of curvature are equal. Here and in the other figures in this section the parameters of the ellipsoid are a:b:c = 1.01:1:0.8, and it is viewed in an orthographic projection from a point above φ = 40°, λ = 30°.

The grid lines of the ellipsoidal coordinates may be interpreted in three different ways

1. They are "lines of curvature" on the ellipsoid, i.e., they are parallel to the directions of principal curvature (Monge 1796).
2. They are also intersections of the ellipsoid with confocal systems of hyperboloids of one and two sheets (Dupin 1813，Part 5).
3. Finally they are geodesic ellipses and hyperbolas defined using two adjacent umbilical points (Hilbert & Cohn-Vossen 1952，第188頁). For example, the lines of constant β in Fig. 21 can be generated with the familiar string construction for ellipses with the ends of the string pinned to the two umbilical points.

Conversions between these three types of latitudes and longitudes and the Cartesian coordinates are simple algebraic exercises.

The element of length on the ellipsoid in ellipsoidal coordinates is given by

${\begin{aligned}{\frac {ds^{2}}{(a^{2}-b^{2})\sin ^{2}\omega +(b^{2}-c^{2})\cos ^{2}\beta }}&={\frac {b^{2}\sin ^{2}\beta +c^{2}\cos ^{2}\beta }{a^{2}-b^{2}\sin ^{2}\beta -c^{2}\cos ^{2}\beta }}d\beta ^{2}\\&\qquad +{\frac {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega }{a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega -c^{2}}}d\omega ^{2}\end{aligned}}$

and the differential equations for a geodesic are

${\begin{aligned}{\frac {d\beta }{ds}}&={\frac {1}{\sqrt {(a^{2}-b^{2})\sin ^{2}\omega +(b^{2}-c^{2})\cos ^{2}\beta }}}{\frac {\sqrt {a^{2}-b^{2}\sin ^{2}\beta -c^{2}\cos ^{2}\beta }}{\sqrt {b^{2}\sin ^{2}\beta +c^{2}\cos ^{2}\beta }}}\cos \alpha ,\\{\frac {d\omega }{ds}}&={\frac {1}{\sqrt {(a^{2}-b^{2})\sin ^{2}\omega +(b^{2}-c^{2})\cos ^{2}\beta }}}{\frac {\sqrt {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega -c^{2}}}{\sqrt {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega }}}\sin \alpha ,\\{\frac {d\alpha }{ds}}&={\frac {1}{((a^{2}-b^{2})\sin ^{2}\omega +(b^{2}-c^{2})\cos ^{2}\beta )^{3/2}}}\times \\&\quad {\biggl (}{\frac {(a^{2}-b^{2})\cos \omega \sin \omega {\sqrt {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega -c^{2}}}}{\sqrt {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega }}}\cos \alpha \\&\qquad +{\frac {(b^{2}-c^{2})\cos \beta \sin \beta {\sqrt {a^{2}-b^{2}\sin ^{2}\beta -c^{2}\cos ^{2}\beta }}}{\sqrt {b^{2}\sin ^{2}\beta +c^{2}\cos ^{2}\beta }}}\sin \alpha {\biggr )}.\end{aligned}}$

Jacobi's solution

C. G. J. Jacobi

Joseph Liouville

J. G. Darboux

Jacobi showed that the geodesic equations, expressed in ellipsoidal coordinates, are separable. Here is how he recounted his discovery to his friend and neighbor Bessel (Jacobi 1839，Letter to Bessel),

The day before yesterday, I reduced to quadrature the problem of geodesic lines on an ellipsoid with three unequal axes. They are the simplest formulas in the world, Abelian integrals, which become the well known elliptic integrals if 2 axes are set equal.

Königsberg, 28th Dec. '38.

The solution given by Jacobi (Jacobi 1839) (Jacobi 1866，§28) is

${\begin{aligned}\delta &=\int {\frac {{\sqrt {b^{2}\sin ^{2}\beta +c^{2}\cos ^{2}\beta }}\,d\beta }{{\sqrt {a^{2}-b^{2}\sin ^{2}\beta -c^{2}\cos ^{2}\beta }}{\sqrt {(b^{2}-c^{2})\cos ^{2}\beta -\gamma }}}}\\&\quad -\int {\frac {{\sqrt {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega }}\,d\omega }{{\sqrt {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega -c^{2}}}{\sqrt {(a^{2}-b^{2})\sin ^{2}\omega +\gamma }}}}.\end{aligned}}$

As Jacobi notes "a function of the angle β equals a function of the angle ω. These two functions are just Abelian integrals..." Two constants δ and γ appear in the solution. Typically δ is zero if the lower limits of the integrals are taken to be the starting point of the geodesic and the direction of the geodesics is determined by γ. However, for geodesics that start at an umbilical points, we have γ = 0 and δ determines the direction at the umbilical point. The constant γ may be expressed as

$\gamma =(b^{2}-c^{2})\cos ^{2}\beta \sin ^{2}\alpha -(a^{2}-b^{2})\sin ^{2}\omega \cos ^{2}\alpha ,$

where α is the angle the geodesic makes with lines of constant ω. In the limit b → a, this reduces to sinα cosβ = const., the familiar Clairaut relation. A nice derivation of Jacobi's result is given by Darboux (1894，§§583–584) where he gives the solution found by Liouville (1846) for general quadratic surfaces. In this formulation, the distance along the geodesic, s, is found using

${\begin{aligned}{\frac {ds}{(a^{2}-b^{2})\sin ^{2}\omega +(b^{2}-c^{2})\cos ^{2}\beta }}&={\frac {{\sqrt {b^{2}\sin ^{2}\beta +c^{2}\cos ^{2}\beta }}\,d\beta }{{\sqrt {a^{2}-b^{2}\sin ^{2}\beta -c^{2}\cos ^{2}\beta }}{\sqrt {(b^{2}-c^{2})\cos ^{2}\beta -\gamma }}}}\\&={\frac {{\sqrt {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega }}\,d\omega }{{\sqrt {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega -c^{2}}}{\sqrt {(a^{2}-b^{2})\sin ^{2}\omega +\gamma }}}}.\end{aligned}}$

An alternative expression for the distance is

${\begin{aligned}ds&={\frac {{\sqrt {b^{2}\sin ^{2}\beta +c^{2}\cos ^{2}\beta }}{\sqrt {(b^{2}-c^{2})\cos ^{2}\beta -\gamma }}\,d\beta }{\sqrt {a^{2}-b^{2}\sin ^{2}\beta -c^{2}\cos ^{2}\beta }}}\\&\quad {}+{\frac {{\sqrt {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega }}{\sqrt {(a^{2}-b^{2})\sin ^{2}\omega +\gamma }}\,d\omega }{\sqrt {a^{2}\sin ^{2}\omega +b^{2}\cos ^{2}\omega -c^{2}}}}.\end{aligned}}$

Survey of triaxial geodesics

Circumpolar geodesics, ω₁ = 0°, α₁ = 90°.

Fig. 22. β₁ = 45.1°.

Fig. 23. β₁ = 87.48°.

On a triaxial ellipsoid, there are only 3 simple closed geodesics, the three principal sections of the ellipsoid given by X = 0, Y = 0, and Z = 0. To survey the other geodesics, it is convenient to consider geodesics which intersect the middle principal section, Y = 0, at right angles. Such geodesics are shown in Figs. 22–26, which use the same ellipsoid parameters and the same viewing direction as Fig. 21. In addition, the three principal ellipses are shown in red in each of these figures.

If the starting point is β₁ ∈ (−90°, 90°), ω₁ = 0, and α₁ = 90°, then γ > 0 and the geodesic encircles the ellipsoid in a "circumpolar" sense. The geodesic oscillates north and south of the equator; on each oscillation it completes slightly less that a full circuit around the ellipsoid resulting, in the typical case, in the geodesic filling the area bounded by the two latitude lines β = ±β₁. Two examples are given in Figs. 22 and 23. Figure 22 shows practically the same behavior as for an oblate ellipsoid of revolution (because a ≈ b); compare to Fig. 11. However, if the starting point is at a higher latitude (Fig. 22) the distortions resulting from a ≠ b are evident. All tangents to a circumpolar geodesic touch the confocal single-sheeted hyperboloid which intersects the ellipsoid at β = β₁ (Chasles 1846) (Hilbert & Cohn-Vossen 1952，第223–224頁).

Transpolar geodesics, β₁ = 90°, α₁ = 180°.

Fig. 24. ω₁ = 39.9°.

Fig. 25. ω₁ = 9.966°.

If the starting point is β₁ = 90°, ω₁ ∈ (0°, 180°), and α₁ = 180°, then γ < 0 and the geodesic encircles the ellipsoid in a "transpolar" sense. The geodesic oscillates east and west of the ellipse X = 0; on each oscillation it completes slightly more that a full circuit around the ellipsoid resulting, in the typical case, in the geodesic filling the area bounded by the two longitude lines ω = ω₁ and ω = 180° − ω₁. If a = b, all meridians are geodesics; the effect of a ≠ b causes such geodesics to oscillate east and west. Two examples are given in Figs. 24 and 25. The constriction of the geodesic near the pole disappears in the limit b → c; in this case, the ellipsoid becomes a prolate ellipsoid and Fig. 24 would resemble Fig. 12 (rotated on its side). All tangents to a transpolar geodesic touch the confocal double-sheeted hyperboloid which intersects the ellipsoid at ω = ω₁.

Fig. 26. An umbilical geodesic, β₁ = 90°, ω₁ = 0°, α₁ = 135°.

If the starting point is β₁ = 90°, ω₁ = 0° (an umbilical point), and α₁ = 135° (the geodesic leaves the ellipse Y = 0 at right angles), then γ = 0 and the geodesic repeatedly intersects the opposite umbilical point and returns to its starting point. However, on each circuit the angle at which it intersects Y = 0 becomes closer to 0° or 180° so that asymptotically the geodesic lies on the ellipse Y = 0 (Hart 1849) (Arnold 1989，第265頁). This is shown in Fig. 26. Note that a single geodesic does not fill an area on the ellipsoid. All tangents to umbilical geodesics touch the confocal hyperbola which intersects the ellipsoid at the umbilic points.

Umbilical geodesic enjoy several interesting properties.

• Through any point on the ellipsoid, there are two umbilical geodesics.
• The geodesic distance between opposite umbilical points is the same regardless of the initial direction of the geodesic.
• Whereas the closed geodesics on the ellipses X = 0 and Z = 0 are stable (an geodesic initially close to and nearly parallel to the ellipse remains close to the ellipse), the closed geodesic on the ellipse Y = 0, which goes through all 4 umbilical points, is exponentially unstable. If it is perturbed, it will swing out of the plane Y = 0 and flip around before returning to close to the plane. (This behavior may repeat depending on the nature of the initial perturbation.)

If the starting point A of a geodesic is not an umbilical point, then its envelope is an astroid with two cusps lying on β = −β₁ and the other two on ω = ω₁ + π (Sinclair 2003). The cut locus for A is the portion of the line β = −β₁ between the cusps (Itoh & Kiyohara 2004).

(Panou 2013) gives a method for solving the inverse problem for a triaxial ellipsoid by directly integrating the system of ordinary differential equations for a geodesic. (Thus, it does not utilize Jacobi's solution.)

Applications

Karl Weierstrass

Henri Poincaré

The direct and inverse geodesic problems no longer play the central role in geodesy that they once did. Instead of solving adjustment of geodetic networks as a two-dimensional problem in spheroidal trigonometry, these problem are now solved by three-dimensional methods (Vincenty & Bowring 1978). Nevertheless, terrestrial geodesics still play an important role in several areas:

• for measuring distances and areas in geographic information systems;
• the definition of maritime boundaries (UNCLOS 2006);
• in the rules of the Federal Aviation Administration for area navigation (RNAV 2007);
• the method of measuring distances in the FAI Sporting Code (FAI 2013).

By the principle of least action, many problems in physics can be formulated as a variational problem similar to that for geodesics. Indeed, the geodesic problem is equivalent to the motion of a particle constrained to move on the surface, but otherwise subject to no forces (Laplace 1799a) (Hilbert & Cohn-Vossen 1952，第222頁). For this reason, geodesics on simple surfaces such as ellipsoids of revolution or triaxial ellipsoids are frequently used as "test cases" for exploring new methods. Examples include:

• the development of elliptic integrals (Legendre 1811) and elliptic functions (Weierstrass 1861);
• the development of differential geometry (Gauss 1828) (Christoffel 1869);
• methods for solving systems of differential equations by a change of independent variables (Jacobi 1839);
• the study of caustics (Jacobi 1891);
• investigations into the number and stability of periodic orbits (Poincaré 1905);
• in the limit c → 0, geodesics on a triaxial ellipsoid reduce to a case of dynamical billiards;
• extensions to an arbitrary number of dimensions (Knörrer 1980);
• geodesic flow on a surface (Berger 2010，Chap. 12).

See also

• Geographical distance
• Great-circle navigation
• Geodesics
• Geodesy
• Meridian arc
• Rhumb line
• Vincenty's formulae

References

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External links

• Online geodesic bibliography, approximately 180 books and articles on geodesics on ellipsoids together with links to online copies.
• Implementations of Vincenty (1975a) for oblate ellipsoids:
  • NGS implementation, includes modifications described in Vincenty (1975b).
  • NGS online tools.
  • Online calculator from Geoscience Australia.
  • Javascript implementations of solutions to direct problem and inverse problem.
• Implementation of Karney (2013) for ellipsoids of revolution in Geographiclib (Karney 2014):
  • GeographicLib web site for downloading library and documentation.
  • GeodSolve(1), man page for a utility for geodesic calculations.
  • An online version of GeodSolve.
  • Planimeter(1), man page for a utility for calculating the area of geodesic polygons.
  • An online version of Planimeter.
  • geod(1), man page for the PROJ.4 utility for geodesic calculations.
  • Javascript utility for direct and inverse problems and area calculations.
  • Drawing geodesics on Google Maps.
  • Matlab implementation of the geodesic routines (used for the figures for geodesics on ellipsoids of revolution in this article).
  • The first description of the geodesic algorithms from (Karney 2009).
• Geodesics on a triaxial ellipsoid:
  • Additional notes about Jacobi's solution.
  • Caustics on an ellipsoid.