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A hybrid model for DTM generation fr...

Lee, Hyun Seung.

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A hybrid model for DTM generation from LIDAR data.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A hybrid model for DTM generation from LIDAR data./
Author:	Lee, Hyun Seung.
Description:	102 p.
Notes:	Source: Dissertation Abstracts International, Volume: 65-10, Section: B, page: 5310.
Contained By:	Dissertation Abstracts International65-10B.
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3151544
ISBN:	0496115057

A hybrid model for DTM generation from LIDAR data.
Lee, Hyun Seung.

A hybrid model for DTM generation from LIDAR data. - 102 p.

Source: Dissertation Abstracts International, Volume: 65-10, Section: B, page: 5310.

Thesis (Ph.D.)--Mississippi State University, 2004.

This dissertation introduces an innovative technique to extract ground elevation models using small-footprint LIDAR data. This technique consists of a preprocessing step, ground modeling, and interpolation. In the preprocessing step, much of the non-terrain points are eliminated using a histogram-based clustering technique. Then, in the ground modeling stage, the information such as elevation and slope between nearest neighbor points is extracted. This step corresponds to an outlier detection process. In this stage, residuals and gradient indices for elevation and slope, are introduced. These indices are investigated for a constructed 95% confidence interval to discard the remaining non-terrain points. Finally, using spline interpolation, a smooth ground surface is generated. Simulation results show a significant improvement over existing techniques. Furthermore, the possibility of using a ground trend model developed from specific tree height measurements is investigated. For this analysis, a statistical regression analysis model is used. Performing this analysis, a 0.63 R-squared value is obtained. This result indicates that the LIDAR ground surface obtained from the presented algorithm is related to the true ground surface.

ISBN: 0496115057Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

A hybrid model for DTM generation from LIDAR data.
LDR:02126nmm 2200277 4500 001 1819154
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020 $a 0496115057
035 $a (UnM)AAI3151544
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040 $a UnM $c UnM
100 1 $a Lee, Hyun Seung. $3 1908451
245 1 2 $a A hybrid model for DTM generation from LIDAR data.
300 $a 102 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-10, Section: B, page: 5310.
500 $a Major Professor: Nicholas H. Younan.
502 $a Thesis (Ph.D.)--Mississippi State University, 2004.
520 $a This dissertation introduces an innovative technique to extract ground elevation models using small-footprint LIDAR data. This technique consists of a preprocessing step, ground modeling, and interpolation. In the preprocessing step, much of the non-terrain points are eliminated using a histogram-based clustering technique. Then, in the ground modeling stage, the information such as elevation and slope between nearest neighbor points is extracted. This step corresponds to an outlier detection process. In this stage, residuals and gradient indices for elevation and slope, are introduced. These indices are investigated for a constructed 95% confidence interval to discard the remaining non-terrain points. Finally, using spline interpolation, a smooth ground surface is generated. Simulation results show a significant improvement over existing techniques. Furthermore, the possibility of using a ground trend model developed from specific tree height measurements is investigated. For this analysis, a statistical regression analysis model is used. Performing this analysis, a 0.63 R-squared value is obtained. This result indicates that the LIDAR ground surface obtained from the presented algorithm is related to the true ground surface.
590 $a School code: 0132.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Remote Sensing. $3 1018559
690 $a 0544
690 $a 0799
710 2 0 $a Mississippi State University. $3 1017550
773 0 $t Dissertation Abstracts International $g 65-10B.
790 1 0 $a Younan, Nicholas H., $e advisor
790 $a 0132
791 $a Ph.D.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3151544