Algorithm for Estimating Mountainous Surface Area Based on GPS Data

Song, Guopeng; Chen, Yifan; Zhou, Yunfeng

doi:10.1007/978-3-642-35567-7_82

Cited by 1 publication

(1 citation statement)

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“…Since TIN data is stored in a vector format, it can be used for accurate measurements and cutting. Therefore, TIN-based surface area calculations are generally considered to have a high accuracy [9,14]. However, due to the different parameters used in the generation process (such as the number of vertices and the elevation threshold), different TIN datasets will be generated.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Vector-Raster Overlay Algorithm for High-Accuracy and High-Efficiency Surface Area Calculations of Irregularly Shaped Land Use Patches

Xie

Liu

et al. 2017

IJGI

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The Earth's surface is uneven, and conventional area calculation methods are based on the assumption that the projection plane area can be obtained without considering the actual undulation of the Earth's surface and by simplifying the Earth's shape to be a standard ellipsoid. However, the true surface area is important for investigating and evaluating land resources. In this study, the authors propose a new method based on an efficient vector-raster overlay algorithm (VROA-based method) to calculate the surface areas of irregularly shaped land use patches. In this method, a surface area raster file is first generated based on the raster-based digital elevation model (raster-based DEM). Then, a vector-raster overlay algorithm (VROA) is used that considers the precise clipping of raster cells using the vector polygon boundary. Xiantao City, Luotian County, and the Shennongjia Forestry District, which are representative of a plain landform, a hilly topography, and a mountain landscape, respectively, are selected to calculate the surface area. Compared with a traditional method based on triangulated irregular networks (TIN-based method), our method significantly reduces the processing time. In addition, our method effectively improves the accuracy compared with another traditional method based on raster-based DEM (raster-based method). Therefore, the method satisfies the requirements of large-scale engineering applications.

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Section: Introductionmentioning

confidence: 99%