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A Method of DTM Construction Based on Quadrangular Irregular Networks and Related Error Analysis.

Kang M, Wang M, Du Q - PLoS ONE (2015)

Bottom Line: The results indicate that the QIN method is the most accurate method tested.The difference in accuracy rank seems to be caused by the locations of the data points sampled.Although the QIN method has drawbacks, it is an alternative method for DTM construction.

View Article: PubMed Central - PubMed

Affiliation: School of Resource and Environment Science, Wuhan University, Wuhan 430079, China; Key laboratory of Geographic Information System, Ministry of Education, Wuhan University, Wuhan 430079, China.

ABSTRACT
A new method of DTM construction based on quadrangular irregular networks (QINs) that considers all the original data points and has a topological matrix is presented. A numerical test and a real-world example are used to comparatively analyse the accuracy of QINs against classical interpolation methods and other DTM representation methods, including SPLINE, KRIGING and triangulated irregular networks (TINs). The numerical test finds that the QIN method is the second-most accurate of the four methods. In the real-world example, DTMs are constructed using QINs and the three classical interpolation methods. The results indicate that the QIN method is the most accurate method tested. The difference in accuracy rank seems to be caused by the locations of the data points sampled. Although the QIN method has drawbacks, it is an alternative method for DTM construction.

No MeSH data available.


Comparisons between simulation results and observed data.(a) SPLINE, (b) KRIGING, (c) TIN and (d) QIN.
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pone.0127592.g012: Comparisons between simulation results and observed data.(a) SPLINE, (b) KRIGING, (c) TIN and (d) QIN.

Mentions: Fig 12 shows the relationship between the heights of the interpolated points and the corresponding observed heights of the points. This analysis indicates that the QIN method has the highest interpolation accuracy. The results from the SPLINE simulation appear more discrete and are lower than the line y = x overall. The KRIGING method has fewer points than SPLINE and tends to overestimate the elevations of lower check points. The TIN method has very few discrete simulation points and overestimates the elevations of lower check points even more than the KRIGING method does. The QIN method has the best result, but there are also some discrete simulation points.


A Method of DTM Construction Based on Quadrangular Irregular Networks and Related Error Analysis.

Kang M, Wang M, Du Q - PLoS ONE (2015)

Comparisons between simulation results and observed data.(a) SPLINE, (b) KRIGING, (c) TIN and (d) QIN.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4440715&req=5

pone.0127592.g012: Comparisons between simulation results and observed data.(a) SPLINE, (b) KRIGING, (c) TIN and (d) QIN.
Mentions: Fig 12 shows the relationship between the heights of the interpolated points and the corresponding observed heights of the points. This analysis indicates that the QIN method has the highest interpolation accuracy. The results from the SPLINE simulation appear more discrete and are lower than the line y = x overall. The KRIGING method has fewer points than SPLINE and tends to overestimate the elevations of lower check points. The TIN method has very few discrete simulation points and overestimates the elevations of lower check points even more than the KRIGING method does. The QIN method has the best result, but there are also some discrete simulation points.

Bottom Line: The results indicate that the QIN method is the most accurate method tested.The difference in accuracy rank seems to be caused by the locations of the data points sampled.Although the QIN method has drawbacks, it is an alternative method for DTM construction.

View Article: PubMed Central - PubMed

Affiliation: School of Resource and Environment Science, Wuhan University, Wuhan 430079, China; Key laboratory of Geographic Information System, Ministry of Education, Wuhan University, Wuhan 430079, China.

ABSTRACT
A new method of DTM construction based on quadrangular irregular networks (QINs) that considers all the original data points and has a topological matrix is presented. A numerical test and a real-world example are used to comparatively analyse the accuracy of QINs against classical interpolation methods and other DTM representation methods, including SPLINE, KRIGING and triangulated irregular networks (TINs). The numerical test finds that the QIN method is the second-most accurate of the four methods. In the real-world example, DTMs are constructed using QINs and the three classical interpolation methods. The results indicate that the QIN method is the most accurate method tested. The difference in accuracy rank seems to be caused by the locations of the data points sampled. Although the QIN method has drawbacks, it is an alternative method for DTM construction.

No MeSH data available.