Optical Morphology and its Application in Geomorphology

Optical Morphology and its Application in Geomorphology Geomorphologists use different models to illustrate topography and geomorphic features which, one of these common model is hillshading, that is a effective tool to detect and represent morphological shape of the terrain. This model uses a light source to make a contrast between bright sections and the parts that fall in the shadows. Many researchers have worked on the hillshade modelling. Some of them work on the azimuthal and zenithal angle of light source illumination on the earth surfaces. Some others focus on the direction and the gradient of the earth and their effect on the quality of the shadows and bright areas representations. In this research new concepts named optical morphology introduced which is considerred as a set of methods, models and technics, for representing geomorphologic and topographic features more accurate and visible. 14 terrain curvature models and 6 models regarding to azimuthal and zenithal angle adjustmernt performed. For running these models, Digital Surface Model (DSM) extracted from ALOS satellite data, was used in the large varieties of Iran geomorphological landforms. Then, these models scripted in the python programming language and graphical user interface (GUI) designed, using using Python Tkinter library. A GIS-Based toolkit named Optical Morphology prepared for calculating all introduced models in the form of raster file format. Finally, numerical analysis (Including statistical, morphological,directional and contrast analysis) run on the all model outputs and then, performances and some general applications of these models are describe in the field of geomorphology. In this research Digital Surface Model, published by Japan Aerospace Exploration Agency (JAXA), with a spatial resolution near 23m, is used. The data is obtained from ALOS satellite image. The database is based on the global 3-D topographical DSM, which is currently the most accurate elevation data on the global scale. Several hill-shade modeling is used to enhance terrain feature’s representation. For this purpose, Python programming is used for preparing all these models.
Main local terrain descriptors such as slope and aspect used to enhance terrain morphology appearance. 6 models run based on changing azimuthal and zenithal angles of light source position which are included Aspect Frequency Distribution Analysis (AFDA), Un-weighted Multi-Directional Light Source (UMDLS), Weighed Multi-Directional Light Source (WMDLS), Vertical Light Source Illumination (VLSI), Slope Shading Model (SSM), and Sinusoidal Light Source Fluctuation (SLSF). 14 models run according to the terrain curvatures which are included Profile Curvature Shading Model (PCSM), Tangential Curvature Shading Model (TCSM), Plan Curvature Shading Model (PCSM), Un-sphericity Curvature Shading Model (UCSM), Mean Curvature Shading Model (MCSM), Differential Curvature Shading Model (DCSM), Maximal Curvature Shading Model (MaCSM), Minimal Curvature Shading Model (MiCSM), Horizontal Excess Curvature Shading Model (HECSM), Vertical Excess Curvature Shading Model (VECSM), Total Gaussian Curvature Shading Model (TGCSM), Total Accumulation Curvature Shading Model (TACSM), Flowlines Curvature Shading Model (FCSM), Total Ring Curvature Shading Model (TRCSM). All these models programmed using python (V.2.7 and Tkinter for GUI programming). In this research optical morphology of terrain performmed, using basic geographic information system concepts. Python programming used to execute different hillshade models. Some topographical factors such as terrain slope and aspect considered with regards to light source directions (Azimuthal and zenithal directions). In general 20 different shading models programmed for calculating optical morphology and prepared as GIS toolkit named Optical Morphology. This tool could be able to uses Digital Elevation Model as an input, process and analysis its raster structure and then store results as an ASCII file format. Finally, results, applications, advantages and disadvantages of these models explained. light source direction modeling combining to the geomorphological attributes, is a powerful tool for recognizing and detecting landforms more accurate and could help geomorphologist in different field of studies. In this research, optical morphology modeling was done using Python programming language to enhance representation of the geomorphological terrain features. The results of these efforts are abstracted in the GIS-based toolkit which is applicable in the quantitative geomorphology area. These models have different approaches against local topographic properties, local conditions of each place and aims of shading. Some geomorphological factors such as slope and aspect, topographic characteristics, terrain curvatures and, pixel distribution was considering in running and performing suitable and adjusting model.
Keywords: Optical Morphology, Geomorphology, Python Programming, Analytical Hill-shading