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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.


Check points error distribution of simulations.(a) QIN, (b) SPLINE, (c) KRIGING, (d) TIN.
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pone.0127592.g008: Check points error distribution of simulations.(a) QIN, (b) SPLINE, (c) KRIGING, (d) TIN.

Mentions: Hessing IDW performs the worst in the first step, but this does not mean that the QIN method has a higher error, because this accuracy analysis is just about the new data points in the first step. With these new data points, the QIN meshes were constructed completely and the bicubic surface can be constructed based on the meshes. As Table 2 shows, the QIN method actually delivers the second best accuracy. SPLINE has the highest accuracy, and TIN performs the worst. Therefore, the overall accuracy ranking is different from that of the first step. With the increased number of points involved in the interpolation calculation, the accuracy of both the SPLINE and QIN methods improve. Fig 8 shows that the accuracy of QINs is greatly affected in areas with steep slopes; the Peaks surface has four such areas of high error. SPLINE and KRIGING show a concentrated area of high error, and overall, the simulated z value is lower than the true value. TIN also has a region of high error, but in other areas the result is closer to the true value.


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

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

Check points error distribution of simulations.(a) QIN, (b) SPLINE, (c) KRIGING, (d) TIN.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0127592.g008: Check points error distribution of simulations.(a) QIN, (b) SPLINE, (c) KRIGING, (d) TIN.
Mentions: Hessing IDW performs the worst in the first step, but this does not mean that the QIN method has a higher error, because this accuracy analysis is just about the new data points in the first step. With these new data points, the QIN meshes were constructed completely and the bicubic surface can be constructed based on the meshes. As Table 2 shows, the QIN method actually delivers the second best accuracy. SPLINE has the highest accuracy, and TIN performs the worst. Therefore, the overall accuracy ranking is different from that of the first step. With the increased number of points involved in the interpolation calculation, the accuracy of both the SPLINE and QIN methods improve. Fig 8 shows that the accuracy of QINs is greatly affected in areas with steep slopes; the Peaks surface has four such areas of high error. SPLINE and KRIGING show a concentrated area of high error, and overall, the simulated z value is lower than the true value. TIN also has a region of high error, but in other areas the result is closer to the true value.

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.