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Length
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| Length | |
|---|---|
Common symbols | l |
| SI unit | metre (m) |
Other units | see unit of length |
| Extensive? | yes |
| Dimension | |
Length is a measure of distance. In the International System of Quantities, length is a quantity with dimension distance. In most systems of measurement a base unit for length is chosen, from which all other units are derived. In the International System of Units (SI) system, the base unit for length is the metre.[1]
Length is commonly understood to mean the most extended dimension of a fixed object.[1] However, this is not always the case and may depend on the position the object is in.
Various terms for the length of a fixed object are used, and these include height, which is vertical length or vertical extent, width, breadth, and depth. Height is used when there is a base from which vertical measurements can be taken. Width and breadth usually refer to a shorter dimension than length. Depth is used for the measure of a third dimension.[2]
Length is the measure of one spatial dimension, whereas area is a measure of two dimensions (length squared) and volume is a measure of three dimensions (length cubed).
History
[edit]Measurement has been important ever since humans settled from nomadic lifestyles and started using building materials, occupying land and trading with neighbours. As trade between different places increased, the need for standard units of length increased. And later, as society has become more technologically oriented, much higher accuracy of measurement is required in an increasingly diverse set of fields, from micro-electronics to interplanetary ranging.[3]
Under Einstein's special relativity, length can no longer be thought of as being constant in all reference frames. Thus a ruler that is one metre long in one frame of reference will not be one metre long in a reference frame that is moving relative to the first frame. This means the length of an object varies depending on the speed of the observer.
Use in mathematics
[edit]Euclidean geometry
[edit]In Euclidean geometry, length is measured along straight lines unless otherwise specified and refers to segments on them. Pythagoras's theorem relating the length of the sides of a right triangle is one of many applications in Euclidean geometry. Length may also be measured along other types of curves and is referred to as arclength.
In a triangle, the length of an altitude, a line segment drawn from a vertex perpendicular to the side not passing through the vertex (referred to as a base of the triangle), is called the height of the triangle.
The area of a rectangle is defined to be length × width of the rectangle. If a long thin rectangle is stood up on its short side then its area could also be described as its height × width.
The volume of a solid rectangular box (such as a plank of wood) is often described as length × height × depth.
The perimeter of a polygon is the sum of the lengths of its sides.
The circumference of a circular disk is the length of the boundary (a circle) of that disk.
Other geometries
[edit]In other geometries, length may be measured along possibly curved paths, called geodesics. The Riemannian geometry used in general relativity is an example of such a geometry. In spherical geometry, length is measured along the great circles on the sphere and the distance between two points on the sphere is the shorter of the two lengths on the great circle, which is determined by the plane through the two points and the center of the sphere.
Graph theory
[edit]In an unweighted graph, the length of a cycle, path, or walk is the number of edges it uses.[4] In a weighted graph, it may instead be the sum of the weights of the edges that it uses.[5]
Length is used to define the shortest path, girth (shortest cycle length), and longest path between two vertices in a graph.
Measure theory
[edit]In measure theory, length is most often generalized to general sets of via the Lebesgue measure. In the one-dimensional case, the Lebesgue outer measure of a set is defined in terms of the lengths of open intervals. Concretely, the length of an open interval is first defined as
so that the Lebesgue outer measure of a general set may then be defined as[6]
Computer science
[edit]In computer science, the length of a string is the number of characters that comprise the string. For example, the bit string has length 11.[7]
Many programming languages have a string data type with a method for length to retrieve the length of a string.
String s = "Hello, world!";
int len = s.length(); // len = 13
The "length" of a sequential data structure, such as a dynamic array, can be described as the number of elements contained in it.
import java.util.List;
int[] a = {1, 2, 3, 4, 5};
int len = a.length; // len = 5
List<Integer> list = List.of(1, 2, 3, 4, 5, 6, 7, 8);
int len = list.size(); // len = 8
Units
[edit]In the physical sciences and engineering, when one speaks of units of length, the word length is synonymous with distance. There are several units that are used to measure length. Historically, units of length may have been derived from the lengths of human body parts, the distance travelled in a number of paces, the distance between landmarks or places on the Earth, or arbitrarily on the length of some common object.
In the International System of Units (SI), the base unit of length is the metre (symbol, m), now defined in terms of the speed of light (about 300 million metres per second). The millimetre (mm), centimetre (cm) and the kilometre (km), derived from the metre, are also commonly used units. In U.S. customary units, English or imperial system of units, commonly used units of length are the inch (in), the foot (ft), the yard (yd), and the mile (mi). A unit of length used in navigation is the nautical mile (nmi).[8]
1.609344 km = 1 miles
Units used to denote distances in the vastness of space, as in astronomy, are much longer than those typically used on Earth (metre or kilometre) and include the astronomical unit (au), the light-year, and the parsec (pc).
Units used to denote sub-atomic distances, as in nuclear physics, are much smaller than the millimetre. Examples include the fermi (fm).
See also
[edit]References
[edit]- ^ a b "Length". WordNet. Archived from the original on 25 September 2016. Retrieved 15 March 2020.
- ^ "Measurement: Length, width, height, depth". Think Math!. Archived from the original on 24 February 2020. Retrieved 15 March 2020.
- ^ History of Length Measurement, National Physical Laboratory Archived 2013-11-26 at the Wayback Machine
- ^ Caldwell, Chris K. (1995). "Graph Theory Glossary". Archived from the original on 2022-10-22. Retrieved 2020-03-18.
- ^ Cheung, Shun Yan. "Weighted graphs and path length". Archived from the original on 2020-01-09. Retrieved 2020-03-18.
- ^ Le, Dung. "Lebesgue Measure" (PDF). Archived (PDF) from the original on 2010-11-30.
- ^ John E. Hopcroft, Jeffrey D. Ullman (1979). Introduction to Automata Theory, Languages, and Computation. Addison-Wesley. ISBN 0-201-02988-X. Here: sect.1.1, p.1
- ^ Cardarelli, François (2003). Encyclopaedia of Scientific Units, Weights, and Measures: Their SI Equivalences and Origins. Springer. ISBN 9781852336820.
Length
View on GrokipediaFundamentals
Definition and Concept
Length is a fundamental quantity that measures the one-dimensional extent between two points or along a continuous path in space. Intuitively, it represents the separation between objects, such as the distance across a room or the height of a building, providing a basic sense of spatial scale in everyday observations.[9] In physical contexts, length is defined as a basic property independent of other quantities, capturing the spatial interval without inherent direction.[10] Formally, in mathematical terms, length corresponds to the separation between elements in a metric space, where a distance function quantifies the "length" between points and , adhering to axioms such as non-negativity (), identity of indiscernibles ( if and only if ), symmetry, and the triangle inequality.[11] This concept extends to higher dimensions while remaining one-dimensional in nature, as it evaluates extent along a single axis or direction within the space. Length thus operates as a scalar value, yielding a non-negative real number that describes magnitude without vectorial components.[12] While related, length differs from distance in that the latter typically denotes the shortest straight-line separation (geodesic distance) between points, whereas length can refer to the total extent along any specified path, such as a curve. It also contrasts with broader notions of size, which encompass multi-dimensional measures like area or volume, focusing instead on linear extension. In vector spaces, length manifests as the norm of a vector, a scalar that quantifies its magnitude, reinforcing its role in abstract geometric structures.[13]Basic Properties
In Euclidean geometry, the length of a line segment is characterized by several fundamental properties that ensure its consistency and utility as a measure of extent. These properties include additivity for collinear segments, invariance under rigid transformations, positivity, homogeneity under scaling, and the triangle inequality. They form the basis for defining length as a metric function on the space, applicable prior to more advanced geometric constructions. Additivity states that for any three collinear points A, B, and C, with B between A and C, the length of segment AC equals the sum of the lengths of AB and BC, expressed as . This property arises from the order axioms in foundational systems, allowing the continuous extension of segments along a line. It ensures that length behaves like a one-dimensional measure along straight paths. Length is invariant under rigid transformations, such as translations and rotations, in Euclidean space. Specifically, if T is a rigid motion (isometry), then for any points A and B, . This preservation follows from the congruence axioms, which equate segments that can be superimposed by such motions without distortion. Positivity requires that the length of any segment is non-negative, with for distinct points A and B, and only if A coincides with B. This axiom establishes length as a strict measure of separation, excluding negative or zero values for non-degenerate segments. Homogeneity implies that scaling a figure by a positive factor k proportionally affects its lengths, so . Derived from the correspondence between geometric segments and real numbers in axiomatic frameworks, this property supports similarity transformations and dimensional analysis. The triangle inequality provides that for any points A, B, and C, , with equality holding if and only if B lies on the segment AC. As a derived theorem from the metric properties and order axioms, it bounds the direct extent between points by indirect paths, foundational for path minimization in geometry.Historical Development
Ancient and Pre-Modern Measures
In ancient Mesopotamia, length measurements were primarily empirical and derived from body parts, with the cubit (known as kush) serving as a fundamental unit equivalent to approximately 0.5 meters, based on the length of the forearm from elbow to fingertip.[14] This unit was subdivided into smaller components, such as the shu-si (finger, about 1.67 cm) and she (barleycorn, roughly 0.28 cm), and scaled up to larger measures like the nindan (rod, about 6 meters), facilitating applications in construction, agriculture, and land surveying.[14] Similarly, in ancient Egypt, the cubit was a core unit, with the royal cubit standardized at around 52.3 cm—slightly longer than the common cubit to account for the pharaoh's forearm plus a hand span—and used extensively for building monuments and surveying Nile floodplains.[3] Variations in the royal cubit appeared in practical artifacts, such as New Kingdom jars with circumferences ranging from 48.6 to 59.8 cm, reflecting regional adaptations while maintaining a base of 28 fingers (each about 1.87 cm).[15] Greek metrology built on these traditions, introducing units tied to athletics and architecture, notably the stadion—a track length of approximately 185 meters, or 600 Greek feet (each foot around 0.308 meters)—which defined the shortest sprint race at events like the Olympics and Pythian Games.[16] This measure varied slightly by locale, with the Olympic stadion measured at 192.27 meters and the Delphic at about 177.65 meters, underscoring early inconsistencies in foot lengths across city-states. Hero of Alexandria advanced metrology in the first century CE through his work Metrica and Dioptra, describing anthropometric systems that proportioned units like the finger (daktylos, ~1.9 cm), palm (4 fingers), and foot (16 fingers, ~30.8 cm) to the human body, while devising instruments for precise surveying of lengths in engineering and astronomy.[17] These contributions emphasized proportional relationships, such as the cubit as 18 inches or 24 fingers, aiding in the measurement of distances for trade routes and public works.[18] The Romans adapted Greek and earlier systems into a more militaristic framework, with the pes (foot) standardized at about 29.6 cm—derived from an average adult foot—and serving as the base for engineering feats like roads and aqueducts.[19] Larger distances were reckoned in paces (passus, two steps or 1.48 meters) and miles (mille passus, 1,000 paces or roughly 1,480 meters), enabling efficient legionary marches and territorial mapping.[3] Into the medieval period, these body-based units persisted across Europe but with growing inconsistencies; the foot varied from 25 to 35 cm by region (e.g., shorter in England at ~30.5 cm post-Norman Conquest, longer in parts of Germany), the hand (palm width, 7-10 cm) differed by occupation, and the pace (step length, 70-80 cm) fluctuated with terrain and individual gait, complicating trade and leading to disputes among merchants.[20] Such variability arose from local customs and the absence of durable standards, as measures were often calibrated against rulers' bodies or common tools rather than fixed artifacts.[21] Efforts toward standardization emerged in ancient trade contexts, particularly in Greece, where the Attic foot (approximately 29.5 cm) was promoted for consistency in commerce and architecture, as evidenced by its use in Athenian markets and temples to align measurements with imported goods from across the Mediterranean.[22] This unit, described by Plutarch as derived from proportional divisions of the human form, helped mitigate discrepancies in exchanges but remained one of many local variants until later reforms.[23]Modern Standardization
The modern standardization of length measurement began during the French Revolution, when the French Academy of Sciences proposed a universal unit based on natural phenomena to replace disparate local standards. On March 26, 1791, the French National Assembly adopted the metre as one ten-millionth of the distance from the North Pole to the equator along the meridian passing through Paris, a definition intended to be both rational and invariant. This initial prototype, known as the Mètre des Archives, was crafted from brass in 1799, but its reliance on a specific survey introduced inaccuracies due to measurement errors in the meridian arc.[24] To achieve international consensus and reproducibility, the Metre Convention was signed on May 20, 1875, by representatives of 17 nations in Paris, establishing the International Bureau of Weights and Measures (BIPM) in Sèvres, France, as the custodian of metric standards. The 1st General Conference on Weights and Measures (CGPM) in 1889 formalized the metre as the distance between two engraved lines on a platinum-iridium bar (the International Prototype Metre) maintained at 0°C, marking a shift to a durable artifact standard while preserving the original intent. However, this artifact-based definition faced challenges, including gradual instability from surface wear, contamination, and thermal expansion variations, which complicated precise replication across laboratories without direct access to the prototype.[25][26] Advancements in spectroscopy prompted further refinements for greater universality. At the 11th CGPM in 1960, the metre was redefined as exactly 1,650,763.73 wavelengths in vacuum of the orange-red radiation from the transition between the 2p₁₀ and 5d₅ energy levels of krypton-86 atoms, enabling atomic-scale reproducibility independent of physical artifacts. This spectral standard was superseded in 1983 by the 17th CGPM, which defined the metre as the distance light travels in vacuum in 1/299,792,458 of a second, tying length directly to the speed of light (c) and the second, thus addressing prior reproducibility issues by leveraging fundamental constants. The 26th CGPM in 2019 completed this evolution through the SI redefinition, fixing c at exactly 299,792,458 m/s alongside other constants like the caesium hyperfine frequency for the second, ensuring the metre's definition remains stable and universally accessible via advanced interferometry without reliance on variable measurements.[27][28][29]Mathematical Applications
Euclidean Geometry
In Euclidean geometry, length is treated as a primitive concept through the framework of line segments, as established in Euclid's Elements. A straight line is defined as a breadthless length, and a line segment is the finite portion between two points on that line. Equality of lengths, equivalent to modern congruence, is assumed in the common notions, such as "things which coincide with one another are equal to one another," allowing segments to be compared by superposition.[30] These foundations enable the rigorous treatment of lengths without numerical measurement, emphasizing geometric equality.[31] The Pythagorean theorem exemplifies the role of length in right triangles, stating that if a right angle is formed by sides of lengths and , then the hypotenuse satisfies . Euclid proves this in Book I, Proposition 47, by constructing squares on each side and showing via area rearrangements (using prior propositions on parallelograms) that the area on the hypotenuse equals the sum of the areas on the legs. An outline of an alternative proof using similar triangles proceeds by drawing the altitude from the right angle to the hypotenuse, dividing the original triangle into two smaller right triangles; each is similar to the original by AA criterion (sharing angles), yielding proportions and , where , which multiply to .[32][33] Circle properties further illustrate length applications, where the circumference is given by , with as the fixed ratio of circumference to diameter, approximately 3.14159. Euclid does not compute explicitly but demonstrates in Book III, Propositions 26–28, that in equal circles, equal central angles subtend equal arcs, and arc lengths are proportional to the central angles via inscribed angles and sector divisions. This proportion underpins the arc length formula , where is the central angle in radians (defined such that a full circle is ), derived by limiting polygonal approximations.[34] Geometric constructions with compass and straightedge, as per Euclid's first three postulates, allow precise manipulation of lengths without scales. For instance, Proposition I.3 enables copying a given segment to subtract equal lengths from a longer one, while Proposition I.10 bisects a segment by constructing perpendiculars and equal circles to find the midpoint. Proposition I.1 constructs an equilateral triangle on a given segment, ensuring all sides equal the base length through circle intersections. These methods preserve length equality, forming the basis for all Euclidean constructions.[31] Congruence and similarity criteria rely heavily on length equalities or proportions. For congruence, the side-angle-side (SAS) criterion (Book I, Proposition 4) states that if two sides and the included angle of one triangle equal those of another, the triangles are congruent, implying equal third sides and angles. The side-side-side (SSS) criterion (Book I, Proposition 8) follows: if all three sides of one triangle equal those of another, the triangles are congruent. For similarity, proportional lengths under equal angles (Book VI) extend these, such as SSS similarity where corresponding sides are proportional.[35]Non-Euclidean Geometries
In non-Euclidean geometries, the concept of length deviates from the Euclidean framework due to constant nonzero curvature, leading to modified distance measurements along geodesics, the shortest paths between points. Hyperbolic geometry, characterized by negative curvature, exhibits exponential growth in lengths along geodesics; for instance, the circumference of a circle of radius is , which expands exponentially with increasing , contrasting the linear growth in Euclidean space.[36] This property arises because parallel geodesics diverge, causing distances between them to increase exponentially, as seen in models like the upper half-plane where the distance between two vertical geodesics separated by a fixed horizontal distance grows with height.[37] Elliptic geometry, with positive curvature, features finite spaces where all geodesics intersect, and lengths are measured along elliptic lines, modeled by great circles on a sphere with antipodal points identified (real projective plane). The shortest path between two points is the minor arc of the elliptic line connecting them, with distances bounded— in this model from the unit sphere, the maximum distance is , corresponding to a quarter of the great circle circumference of .[38] These paths are longer than the straight-line distances in the embedding Euclidean space, reflecting the geometry's curvature and compactness. The Gauss-Bonnet theorem connects this curvature to boundary lengths: for a region with boundary, the integral of Gaussian curvature over the area equals times the Euler characteristic minus the sum of interior angles and the integral of geodesic curvature along the boundary, where the latter term involves the total length scaled by curvature.[39] In hyperbolic settings with constant negative curvature , this implies defect angles in polygons relate directly to areas, indirectly influencing perimeter lengths through geodesic properties.[40] Metric tensors formalize these length elements. In Euclidean geometry, the line element is , yielding straight-line distances. In the Poincaré disk model of hyperbolic geometry, it becomes , distorting lengths such that points near the boundary appear farther apart, with geodesics as circular arcs orthogonal to the unit circle.[41] For elliptic geometry on the unit sphere (before quotient), the metric is , where great-circle distances are given by . The ratio of a circle's circumference to its diameter varies with radius in both geometries, unlike the constant in Euclidean space; in hyperbolic geometry, it exceeds and grows without bound, while in elliptic geometry, the analogue is less than and decreases toward 2 as radius approaches .[42] The foundations of non-Euclidean geometries were established independently by Nikolai Lobachevsky, who published his work on hyperbolic geometry in 1829, and János Bolyai, who developed similar ideas around 1832 without prior knowledge of Lobachevsky's results. These discoveries challenged Euclid's parallel postulate and paved the way for modern differential geometry.[43][44]Graph Theory and Discrete Structures
In graph theory, the concept of length manifests in discrete structures through path metrics, where paths consist of edges connecting vertices. In unweighted graphs, the distance between two vertices is defined as the minimum number of edges in any path connecting them, providing a combinatorial measure of separation. The graph diameter extends this notion as the maximum such distance over all pairs of vertices, quantifying the overall "spread" or worst-case connectivity in the structure. These definitions, foundational to discrete mathematics, enable analysis of network efficiency and reachability without invoking continuous measures. Weighted graphs introduce edge lengths as non-negative real numbers assigned to edges, representing costs such as time, capacity, or resources. The length of a path in such a graph is the sum of its edge weights, and the shortest path between vertices is the one with minimal total length. This framework generalizes unweighted distances, where each edge implicitly has weight 1, and supports optimization in combinatorial problems. Seminal work established efficient computation of these lengths, emphasizing their role in modeling real-world discrete systems. Dijkstra's algorithm computes shortest paths from a source vertex to all others in weighted graphs with non-negative edge weights. It operates by maintaining a priority queue of tentative distances, initializing the source with distance zero and others with infinity. Iteratively, it extracts the vertex with the smallest tentative distance, marks it as permanently settled, and relaxes the distances to its adjacent vertices by checking if routing through the settled vertex yields a shorter path. This greedy process continues until all vertices are settled, yielding exact shortest lengths in O((V + E) log V) time with efficient priority queues, where V is the number of vertices and E the number of edges. The algorithm's correctness relies on the non-negativity of weights, ensuring no shorter paths are missed after settlement. In computer networks, graph lengths model routing efficiency, with vertices as routers and edges weighted by hops (edge count) or latency (propagation delay). Protocols like RIP use hop counts as lengths to find minimal-hop paths via distance-vector methods, limiting diameters to 15 to prevent infinite loops. More advanced link-state protocols, such as OSPF, employ Dijkstra's algorithm on latency-weighted graphs to compute global shortest paths, adapting to topology changes for low-latency routing. These applications demonstrate how discrete length optimization minimizes data transmission delays in large-scale networks. Hamiltonian paths, which visit each vertex exactly once, relate to length optimization in the traveling salesman problem (TSP), where the goal is to find the minimal total edge weight of such a path forming a cycle. TSP, NP-hard in general, models discrete routing challenges like logistics, with edge lengths as distances or costs. Early exact methods used cutting-plane techniques on integer programs to solve large instances, establishing benchmarks for approximation and heuristic approaches in combinatorial optimization.Measure Theory
In measure theory, the concept of length is rigorously formalized through the Lebesgue measure on the real line , providing a foundation for measuring subsets in a way that extends classical notions while handling more general sets. The Lebesgue outer measure , introduced by Henri Lebesgue, assigns to any subset the value where denotes the length of the interval .[45] This definition ensures that the outer measure is subadditive and translation-invariant, capturing the intuitive idea of length via coverings while applying to all sets. For bounded intervals, the Lebesgue outer measure coincides with the classical length: the closed interval has measure , and open or half-open intervals of the same endpoints share this value. The Lebesgue measure is then the restriction of to the -algebra of Lebesgue measurable sets, defined via Carathéodory's criterion, where a set is measurable if for all . On measurable sets, exhibits countable additivity: if are disjoint measurable sets, then . This contrasts with Jordan measurability, which requires approximation by finite unions of intervals and applies only to sets of finite perimeter, excluding more irregular sets that Lebesgue measure accommodates. However, not all subsets of are Lebesgue measurable; the existence of non-measurable sets was demonstrated by Giuseppe Vitali, who constructed the Vitali set by selecting one representative from each equivalence class of within using the axiom of choice.[46] The countable disjoint union of translates for covers up to measure zero, implying and simultaneously if measurable, a contradiction. To generalize length beyond one-dimensional Euclidean space and irregular sets, Felix Hausdorff introduced the Hausdorff measure, which extends Lebesgue measure to fractal-like structures in metric spaces.[47] For a subset of a metric space and dimension parameter , the -dimensional Hausdorff outer measure is defined as where the infimum is over coverings by sets of diameter at most .[48] In , the one-dimensional Hausdorff measure recovers the Lebesgue measure on measurable sets, but for fractals, the Hausdorff dimension quantifies roughness, generalizing length to non-integer dimensions where traditional length fails.[48][47] In the context of paths and curves, length is expressed via integration with respect to the arc length element , where the total length of a rectifiable path is given by , or more abstractly as the one-dimensional Hausdorff measure of the image .[49] This formulation aligns with Lebesgue integration, ensuring that lengths of non-smooth but measurable paths are well-defined through the underlying measure structure.[49]Measurement and Units
SI and Metric Units
The meter (m) is the SI base unit of length, defined as the distance traveled by light in vacuum in 1/299792458 of a second, with the speed of light fixed at exactly 299792458 meters per second (c = 299792458 m/s).[50] This definition, adopted in 1983 and made exact in the 2019 revision of the International System of Units (SI), ensures the meter's value is invariant and universal, independent of time, location, or experimental conditions, as it relies on fundamental physical constants rather than physical artifacts. In practice, the meter is realized using high-precision optical methods, such as iodine-stabilized helium-neon lasers operating at a wavelength of 633 nm or femtosecond laser frequency combs that link optical frequencies to the cesium-based second, achieving uncertainties below 10^{-11} in relative length measurements.[51] These techniques allow national metrology institutes to disseminate the meter standard with traceability to the SI definition. The metric system employs decimal prefixes to form coherent multiples and submultiples of the meter, facilitating measurements across vast scales. Common prefixes include kilo- (10^3 m) for kilometers (km), used in road distances, and milli- (10^{-3} m) for millimeters (mm), applied in precision engineering. The full range extends from quecto- (10^{-30} m) for subatomic scales to quetta- (10^{30} m) for cosmological distances, with the complete list standardized by the International Bureau of Weights and Measures (BIPM).[52]| Prefix | Symbol | Power of 10 | Example Unit |
|---|---|---|---|
| quetta- | Q | 10^{30} | Qm (quettameter) |
| ronna- | R | 10^{27} | Rm (ronnameter) |
| yotta- | Y | 10^{24} | Ym (yottameter) |
| ... | ... | ... | ... |
| yocto- | y | 10^{-24} | ym (yoctometer) |
| ronto- | r | 10^{-27} | rm (rontometer) |
| quecto- | q | 10^{-30} | qm (quectometer) |
Non-Metric Units and Conversions
Non-metric units of length, primarily from the imperial and US customary systems, persist in various applications despite the global adoption of the metric system. These units trace their roots to historical British standards formalized in the 19th century, with the inch serving as the base unit defined exactly as 25.4 millimeters since an international agreement in 1959. The foot equals 12 inches, the yard comprises 3 feet, and the mile measures 5,280 feet, reflecting a hierarchical structure suited to everyday and large-scale measurements in countries like the United States.[54][55] The nautical mile, essential for maritime and aviation navigation, is defined internationally as exactly 1,852 meters, a standardization adopted at the First International Extraordinary Hydrographic Conference in Monaco in 1929 and implemented in the United States in 1954. This unit originates from the average length of one minute of latitude along the Earth's surface, approximating one-sixtieth of a degree of longitude at the equator.[56] Historical units like the furlong and chain highlight specialized applications in agriculture and surveying. The furlong, equivalent to 660 feet, derives from the medieval English practice of plowing, representing the length of a furrow that a team of oxen could complete in one go without resting, and remains in use today for horse racing distances. Gunter's chain, invented in 1620 by English mathematician Edmund Gunter, measures 66 feet and consists of 100 iron links, facilitating precise land measurements by aligning with the rod (16.5 feet) and acre calculations in early surveying.[57][58] Conversion between these non-metric units and the metric system relies on exact factors established by international bodies. Key conversions include:| Unit | Definition in Larger Unit | Exact Metric Equivalent |
|---|---|---|
| Inch (in) | 1/12 foot | 25.4 mm (or 0.0254 m) |
| Foot (ft) | 1/3 yard | 0.3048 m |
| Yard (yd) | 3/1760 mile | 0.9144 m |
| Mile (mi) | 5280 feet | 1.609344 km |
| Nautical mile (nmi) | - | 1.852 km |
| Furlong (fur) | 660 feet | 201.168 m |
| Chain (ch) | 66 feet | 20.1168 m |
