Comparison of Horizontal Accuracy, Shape Similarity and Cost of Three Different Road Mapping Techniques

Kweon, Hyeongkeun; Kim, Myeongjun; Lee, Dong Kun; Seo, Jung Il; Rhee, Hakjun

doi:10.3390/f10050452

Cited by 7 publications

(9 citation statements)

References 18 publications

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“…The results showed that the VIM-V presented a high level of reliability in detecting the perturbations. • Kweon et al (2019) applied the SBOM to assessing the positional accuracy of three different road-mapping techniques (CAD file conversion, image warping and GNSS mapping). The XL lines were composed of five routes of about 6 km.…”

Section: Applications and Resultsmentioning

confidence: 99%

Positional quality assessment based on linear elements

Mozas‐Calvache¹

2021

rcarto

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This study describes the current state of the art related to the assessment of the positional accuracy of spatial databases based on lines. The use of this type of element of spatial databases has increased in recent years because of the current possibilities of acquisition and sharing data of routes, roads, etc. Nowadays, users are also contributors and this supposes that the spatial quality of data acquired and shared by non-experts must be assessed as is the case with data produced by institutions and enterprises. In this context, several methods based on lines have been developed up to this time for several purposes. This study reviews these methods, analyzing their characteristics, measures, etc. In addition, more than 30 applications of these methods are also summarized. These applications include control of generalized and digitized lines, control of spatial databases, analysis of the displacement of lines between dates, etc

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Section: Applications and Resultsmentioning

confidence: 99%

Positional quality assessment based on linear elements

Mozas‐Calvache¹

2021

rcarto

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“…Three methods were used to assess the results of geometry of footprint building extraction, which were segment of line comparison, shape index similarity (Veltkamp and Hagedoorn, 2000;Veltkamp, 2011b;Kweon et al, 2019), and edge point-correspondence (Ramirez and Ali, 2003;Kweon et al, 2019). The segment of line comparison was used to evaluate the number of sections of every line resulted from samples against reference dataset.…”

Section: Building Extraction Analysismentioning

confidence: 99%

A Simple But Effective Approach of Building Footprint Extraction in Topographic Mapping Acceleration

Susetyo¹,

Rizaldy²,

Hariyono³

et al. 2021

Indonesian J. Geosci.

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Topographic mapping using stereo plotting is not effective, because it takes much time and labour-intensive. Thus, this research was conducted to find the effective way to extract building footprint for mapping acceleration from LiDAR data. Building extraction method in this process comprises four steps: ground/non-ground filtering, building classification, segmentation, and building extraction. Classification of ground and non-ground classes was performed using Adaptive-TIN Surface algorithm. Non-ground points from filtering process were classified as building with the algorithm based on multiscale local dimensionality to separate points at the maximum separability plane. Segmentation using segment growing was used to separate each building, so boundary detection could be conducted for each segment to create boundary of each building. Lastly, building extraction was conducted through three steps: boundary point detection, building delineation, and building regularization. With ten samples and step 0.5, classification resulted in quality and miss factor of 0.597 and 0.524, respectively. The quality was improved by segmentation process to 0.604, while miss factor was getting worse to 0.561. Meanwhile, on the average shape index value from extracted building had 0.02 difference, and the number of errors was 30% for the line segment comparison. Regarding positional accuracy using centroid accuracy assessment, this method could produce RMSE of 1.169 m.

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“…If the shape is circular, the shape index is 1 (i.e., the smallest perimeter in a given internal area). If the shape is a square, the shape index is 1.13 [16]. The shape index can be expressed by Equation (2).…”

Section: Factors Affecting the Forest Road Circuitymentioning

confidence: 99%

“…However, in the case of non-urbanized areas, the deviation may be large [1,15]. In particular, forest roads, which provide infrastructure for sustainable forest management [16], are affected by their route alignments due to mountainous terrain; thus, most of the route is composed of complex linear shapes, and the circuity factors deviate considerably from region to region [11,15]. To estimate the actual road distance for planning a road network or forest operation, estimating the network distance and calculating the circuity factor of the forest road network are necessary.…”

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confidence: 99%

Comparisons of Estimated Circuity Factor of Forest Roads with Different Vertical Heights in Mountainous Areas, Republic of Korea

Kweon

2019

Forests

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Distance is one of the important factors in determining transportation cost and travel time, and it can be easily estimated by measuring the circuity of road networks. This study calculated the circuity factors to estimate the network distance for 27 forest roads (about 105 km) in South Korea. For this purpose, ridge, mid-slope, and valley roads were classified according to the construction location of the mountain slope, and the weighted and unweighted circuity factor (each 500-m section) were calculated. The average value of weighted circuity was 1.55: mid-slope roads (2.09), ridge roads (1.36), and valley roads (1.09). The average unweighted circuity factors were 1.61 for mid-slope roads, 1.21 for ridge roads, and 1.07 for valley roads. This study found that the circuity of the forest road network was most affected by the mountain terrain. In addition, the circuity factor increased with increasing network distance in the mid-slope roads but was not affected by the network distance in ridges and valleys. To improve the efficiency of transportation in the forest road network, it is important to locate the ladings and properly connect with the public road network.

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Comparison of Horizontal Accuracy, Shape Similarity and Cost of Three Different Road Mapping Techniques

Cited by 7 publications

References 18 publications

Positional quality assessment based on linear elements

Positional quality assessment based on linear elements

A Simple But Effective Approach of Building Footprint Extraction in Topographic Mapping Acceleration

Comparisons of Estimated Circuity Factor of Forest Roads with Different Vertical Heights in Mountainous Areas, Republic of Korea

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