Terrain Surface, Visualization Modeling

There are many different types of the terrain visualization techniques, which are the result of the evolution over time and the development of technological innovations. Earth’s surface roughness plays a key role in controlling surface and the Earth's atmosphere processes. This relationship is so strong that understanding the nature of the terrain topography can directly lead to clarity in understanding of these processes, both analytically and computationally. Therefore, the analysis and visualization of the terrain topography has provided significant applications in many of the activities of the Geographic Information System and environmental Modeling. Geomorphologists and cartographers both use information derived from digital elevation models to quantify the shape and structure of the Earth's topographic surfaces. Cartographic purpose of terrain relief visualization is to display landforms and features of the earth’s surface which is done through drawing hachures and other methods that lead to more realistic terrain surface visualization. Cartographers have used a variety of mechanisms, including colors and shades to create a 3-dimensional appearance of topographical surface in 2-dimensional surface of the maps. The recent study tries to present different ideas and models in the section of terrain topography visualization. For this purpose, vector (point and line) and raster data structure, Digital elevation model with respecting to the concepts of geomorphometry and digital terrain modeling had been used. And python programming has been widely used to design and automating the algorithms of the models.

In the first part, the raster database was prepared and arranged. The raster database contains elevation data that includes digital surface model. Which is currently the most accurate elevation data on a free, global scale. digital Surface model released by the Japan Space Agency in May and October 2015 with a horizontal resolution of about 23 meters were used to model the visualization of terrain topography surfaces. This data is obtained from the ALOS satellite images which is extracted from a five-meter grid data with global coverage which is now the most accurate elevation data in the global scale. In the next step, slope calculated using four slope algorithms on a digital surface model grid structure. The aspect was calculated in the same way. The aspect layer with the results of these four slope algorithms, averaged and standard hill shade calculated using common formula in the geographic information system. Then, the visualization modeling of the terrain topographic surfaces followed in two parts. In the vector modeling section, the hachure modeling of the terrain surface carried out which the results in the field of linear hachure drawing includes: Max-Center-Min, Max-Min, Random Point – Min and multi-sector aspect hachuring models which coded in the python programming environment. In the Point hachure section, two random point models with slope weight and random point model with curvature as a weight were modeled, coded and executed. In the raster modeling section, three model approaches were considered. In the first approach, blended shading was followed, which included combining standard hill shading model with a variety of terrain curvature, radiation models (Morphoradiation), and ridgeline effect models.14 types of terrain curvature were used and combined with standard hill shading to create new models for visualization of terrain surface topography. In the second part, radiation models including direct radiation, direct radiation duration, diffuse radiation and global radiation were combined with standard hill shading to create new models. To add the effect of the ridgelines in the display of the terrain surface topography, the method provided by Solhi and Seif (1399) was used to identify the ridges of the terrain topography.

Various models were prepared and presented in the terrain surface topography visualization. Part of the modeling is related to the vector data structures and the other part is related to the raster data structures. In the vector modeling section, four algorithms including: Max-Center-Min, Max-Min, Random point-Min and Multi-Sector Aspect hachuring were configured and presented. These four algorithms have the ability to create linear hachures on the terrain topography surfaces in order to create a spatial dimension of the digital elevation model. All four algorithms are performed using the moving window technique and automatically apply linear hachuring with using digital elevation model. The second part is related to raster data structures, which includes hybrid models (combining standard hill shade with different terrain curvatures types, radiation models and ridgeline effect), hypsometric tinting, contour maquette, and colored contour maquette.

Terrain surface topography visualization has wide applications and plays important role in the cartography and preparation of base-maps, geological maps and topographic maps as well as thematic maps such as geomorphological maps and many other maps. Modeling terrain surface topography, using different ideas, methods, and techniques, can be effective in improving and the visualization of terrain surfaces in different applications. In this research, with emphasis on the subject of terrain visualization modeling, different methods and models were presented both in the section of vector data structures (linear and dotted) and raster data structures. Various methods and models have been proposed that can be used in a wide range of environmental studies as well as cartographic methods and techniques. The presented models are practiced only from the digital elevation model and do not require field and special data, which are considered as features and strengths of these models. Future researchers are advised to develop and evolve the models, methods and techniques of this field of study and try to create practical and creative models. The field of digital terrain modeling, in the analytical and demonstration sections, creates a suitable platform for environmental science studies and in the form of basic and fundamental research can lead to scientific creation and dynamism in this field.