NDLI: Formulas for precisely and efficiently estimating the bias and variance of the length measurements

Content Provider	Springer Nature Link
Author	Xue, Shuqiang Yang, Yuanxi Dang, Yamin
Copyright Year	2016
Abstract	Error analysis in length measurements is an important problem in geographic information system and cartographic operations. The distance between two random points—i.e., the length of a random line segment—may be viewed as a nonlinear mapping of the coordinates of the two points. In real-world applications, an unbiased length statistic may be expected in high-precision contexts, but the variance of the unbiased statistic is of concern in assessing the quality. This paper suggesting the use of a k-order bias correction formula and a nonlinear error propagation approach to the distance equation provides a useful way to describe the length of a line. The study shows that the bias is determined by the relative precision of the random line segment, and that the use of the higher-order bias correction is only needed for short-distance applications.
Starting Page	399
Ending Page	415
Page Count	17
File Format	PDF
ISSN	14355930
Journal	Journal of Geographical Systems
Volume Number	18
Issue Number	4
e-ISSN	14355949
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-09-14
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Length Bias correction Variance estimation Nonlinear error propagation Regional/Spatial Science Geographical Information Systems/Cartography Computer Application in Social and Behavioral Sciences Landscape/Regional and Urban Planning Geography Simulation and Modeling
Content Type	Text
Resource Type	Article
Subject	Earth-Surface Processes Geography, Planning and Development Economics and Econometrics

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