Natural neighbors interpolation method for correcting IDW

Jia Li; Jiatian Li; Xiaoqing Zuo; Ping Duan

doi:10.1117/12.838426

16 October 2009 Natural neighbors interpolation method for correcting IDW

Jia Li, Jiatian Li, Xiaoqing Zuo, Ping Duan

Author Affiliations +

Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 74925E (2009) https://doi.org/10.1117/12.838426
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China

Abstract

Digital Elevation Model (DEM) interpolation is one of basic functions for spatial description and spatial analysis in GIS and related spatial information fields. Interpolation can be viewed as a function for estimating the heights of unknown points using a set of proper known data. It is a key problem of DEM. Inverse distance weighting (IDW) interpolation is the most commonly used in DEM. The reference points selected by IDW might not be well distributed in space. This leads to the discontinuity problem of interpolated DEM surface and some artifacts might be generated. In order to solve the problem caused by ill-distribution of the number and position of reference points in searching process, this paper put forward a new surface interpolation model about first-order natural neighbor interpolation. The use of first-order natural neighbor interpolation based on TIN can adapt well to poor data distributions because inserting into a point generates a well-defined set of neighbors. In the fitting process, according to range of influence composed by first-order natural neighbor points and the triangle area as weight base of the known point, a non-linear fitting equation can be constructed. Comparative experiments show that this method has higher precision and more practical application value.

Citation Download Citation

Jia Li, Jiatian Li, Xiaoqing Zuo, and Ping Duan "Natural neighbors interpolation method for correcting IDW", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74925E (16 October 2009); https://doi.org/10.1117/12.838426

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE