![]() ![]() Indeed, the scale and level of detail required in an individual project will determine the spatial resolution and accuracy of the DEM required and so the suitable methodology to be followed. Each data type has its methodology however, each methodology has its advantages and challenges. Besides the digitized contour lines method, DEMs can be generated from various data sources ground surveys, photogrammetric stereo methods, satellite images, laser scanning, radar interferometry, and Global Positioning System (GPS) (Wang, Holland, and Gudmundsson 2018 Soni et al. DEM generation with various data sources has attracted a lot of attention in the research community (Shen, Meng, and Zhang 2016 Zhou and Zhu 2013 Kamel, Miky, and El Shouny 2020 Bhushan et al. 2010 Xu and Dong 2021), and agriculture applications (Tijskens, Ramon, and De Baerdemaeker 2003 Chidi et al. 2017), disaster analysis (Demirkesen et al. 2021 Ricchetti 2001 Yang, Meng, and Zhang 2011), hydrological modeling (Hopkinson, Hayashi, and Peddle 2008 Le Coz et al. It is considered as the most prevalent and widespread model that can be used in many civil and environmental applications, such as geological studies (Liu et al. Applying the methodology, experimental results indicate that the developed approach provides a significant advantage in terrain modeling enhancement, generates DEMs smoothly and effectively from contours, mitigates problems and reduces uncertainties.ĭigital Elevation Model (DEM) is an array representation of squared pixels each pixel has associated with its elevation data. The convergence probabilities between extracted and original flow lines for the same regions were 96.91%, 94.93%, and 84.03%. Adding four contour lines, the Root Mean Square Error (RMSE) of examining points were 0.26 m, 0.29 m, and 0.05 m for hilly, undulated, and plain samples, respectively, and the Mean Absolute Error (MAE) were 0.50 m, 0.48 m, and 0.17 m. The precision of the extracted GRID model increases as the number of added contours increases. The proposed methodology was tested using a variety of terrain patterns in terms of intensity: hilly, undulated, and plain (1:25,000 topographic map, 5 m contour interval). In this paper, an approach for improving the digital terrain modeling based on contour line densification and Delaunay triangulation is presented to acquire a more suitable DEM for hydrographic modeling and its applications. Although there are different algorithms and technologies for interpolation in between contour lines, DEMs extracted solely from contours still suffer from poor terrain quality representation, which in turn negatively affects the quality of analytical applications results. Compared with other data sources, contour lines are still the cheapest and more common data source becausethey cover all areas, at different scales, in most countries. Generally, DEMs can be generated from various data sources, such as ground surveys, photogrammetric stereo methods, satellite images, laser scanning, and digitized contour lines. Digital Elevation Models (DEMs) play a crucial role in civil and environmental applications, such as hydrologic and geologic analyses, hazard monitoring, natural resources exploration, etc. ![]()
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