فهرست مطالب سینا صلحی

The diversity and broadness of applied research in the field of geomorphology has led to a semantic and conceptual disconnection between such a research and the theoretical foundations and intellectual ideas that support them. Today, there is a need for a clearer relationship between applied research in the field of geomorphology and the schools of thought that support them, which justifies the need for current research. Samadzadeh et al. (1400) have proposed a new definition of morphological structure in the science of geomorphology. This study emphasizes the importance of fundamental studies, so that changes in the basic and theoretical concepts of science, create the opportunity for new attitudes and the creation of new theoretical ideas in a scientific discipline. Hence, they have explained a hierarchical structure of morphology defined in seven levels, including: land-concept, land-space, land-context, landscape, land-form, land-feature and land-object. Prior to this, Ramesht (2005), in her book Symbols and images in geomorphology, has dealt with the principles of morphology in geomorphology and declared hierarchical theories as a basis for the form units’ classifications in geomorphology. This research, which is a kind of link between a fundamental research in presenting the new structure of morphology and its practical application in geomorphology, it tries to act by quantifying the basic ideas for the improvement of geomorphological science in the field of morphological classification systems.

 Landform refers to any physical feature of the surface with a recognizable structure and shape. Landform elements and structural forms of the terrain surface could, directly and indirectly, drive many other environmental variables. Numerical representation of the surface and uneven pattern of the earth is a common topic in geographical, geomorphological, geological, and geophysical hazard mapping as well as sea-bed exploration. The combination of the earth and computer science with mathematics and geomorphometric engineering interacts with discrete and continuous landforms. Geomorphometry dates back to about 150 years ago and the work of Alexander von Humboldt and geomorphologists, and today with the revolution in computer science and especially digital computer models is developing rapidly. Detection and classification of landforms are of interest to GIS developers, geoscientists, and geomorphometry researchers. In this way, the desired work units are extracted with higher speed and accuracy and used in the form of vector and raster maps. Existing approaches are mainly based on height, terrain derivative, gradient, curvature, flow direction, slope position, morphometric indices, and the like. Also, less attention has been paid to the challenge of matching the diagnostic scale with the Landform scale, and most models have this shortcoming. On the other hand, less attention has been paid to the possibility of vectorization output results and also to the analysis of sensitivity and temporal response algorithms to machine processing. In this research, we attempted to recover and resolve the mentioned shortcoming and problems in the previous works. In this research, using basic algorithms of raster analysis and coding, new methods and algorithms for the automatic detection of landforms have been developed. Focal raster analysis is also emphasized and the moving window technique is used to implement the algorithms. Facing the scale challenge, sensitivity analysis, and the response algorithms to input changes as well as accuracy assessment are other aspects that have been addressed in this research.

 In this study, the Digital Surface Model (DSM) published by the Japan Space Agency in May and October 2015 with a horizontal resolution of about 30 meters was used to work on the topography of the region. These data are obtained from ALOS satellite images. This database is based on DSM data (5m network version) 3D topography, one of the most accurate elevation data on a global scale. The digital elevation model was transformed into a matrix structure using a Python coding environment. Then, raster analysis was implemented using the moving window technique. The moving window algorithm was coded in a way that the dimensions of the moving window could be freely determined and changed. In proportion to the size of the moving window, some adaptive algorithms are implemented to automatically correct and organize the edge effect in proportion to the size of the moving window. In this study, automatic landform detection was performed using spatial analysis of kernel patterns in the raster grid of digital elevation models and the results were presented in the form of three algorithms applied in the detection of topographic peaks and ridges. These algorithms include Multilevel Mean Summit Recognition Algorithm (MLMSR), Complex Multilevel Summit Recognition Algorithm (CMLSR), and Single Point Summit Recognition (SPSR). Each of these three algorithms was first conceptually designed and then coded and executed using the Python programming language. In the next step, the sources of error and specific scenarios of the algorithms were examined. The sensitivity of each algorithm related to the dimensions of the moving window, the resolution, and the size of the raster file, was evaluated, and finally, the accuracy and validation of the three models, using reference layers that were manually prepared and plotted, were assessed. All the procedures were designed in a way that could easily be implemented in an official software and were completely compatible with the structure of machinery processing. Also, being automatic and working on different platforms where one of our priorities.

 In the automatic detection of peaks and ridges using a digital terrain model, kernel spatial pattern analysis was used. In this regard, three proposed algorithms in this field were designed, coded, and executed. The output results of each of the algorithms were presented in the form of a raster and vector data model. Accuracy and sensitivity assessments were performed by considering changes in moving window size, resolution, and raster grid size (row x column) for each of the algorithms. The MLMSR algorithm tends to be in a more binary result in the lower dimensions of the moving window, while the CMLSR and SPSR algorithms do not. In all algorithms, increasing the size of the moving window causes a more generalization ratio. CMLSR and SPSR algorithms are more suitable for cartographic and visual purposes due to the higher degree of grading in the results. Regarding the temporal performance (Runtime) or sensitivity to input changes, the SPSR algorithm performs better. This is especially important when the input file size (number of rows and columns) is large. According to the results of validation and accuracy evaluation, MLMSR and SPSR had better performance than, the CMLSR algorithm. Python programming language has been widely used in the design and implementation of all algorithms, as well as in the field of sensitivity evaluation and validation. Totally more than 500 lines of codes were done for this purpose. All algorithms are automated and are able to execute and store results in raster and vector format using machine processing.

 The results show that the MLMSR algorithm in smaller dimensions of the moving window is tending to more binary results, which is problematic in some graphical and cartographic applications, but the CMLSR and SPSR algorithms showed more gradual trends in their outputs and so, they performed better in this respect. Researchers who intend to study and develop in this field are advised to focus on adaptive algorithms and optimize the dimensions of the moving window in relation to the volume of input information and so, in this way, they increase the flexibility of algorithms in relation to input changes.

The importance of words and their role in drawing the intellectual space is not hidden from anyone. Changes in the basic and theoretical concepts of science create the opportunity for new attitudes and the creation of new theoretical concepts in a scientific order. On the other hand, changing the basic concepts requires changing the terminology to prevent the mentality of the scientific community from interfering and overlapping with the previous concepts. The creation of new concepts that are the result of scientific advances in various fields requires a redefinition of the terminology system in that branch of science. Due to the current situation of research in the field of geomorphology, which is mainly focused on the applied sectors and less development of the basic principles has been done, fundamental research and terminological development and the development of the fundamentals of this branch of science are felt. In this research, with the aim of terminological development and development of theoretical roots of geomorphology in the form of a basic research and in general order to provide a redefinition of the hierarchical structure of morphology in the field of geomorphology, the research has been planned. Different branches of science face different phases during their growth and development. In this study, two main phases that affect scientific networks in different periods called static terminological phase and dynamic terminological phase are explained. From a brief overview of the research trends governing the science of geomorphology, infertility in the creation of new concepts and meanings can be inferred that can be attributed to the terms of the static phase of terminology. Coming out of static terminological conditions and entering dynamic conditions requires more attention to fundamental studies and redefining pre-existing concepts in the form of new terminology. In this regard, the basic morphological structure in geomorphology (including 7 levels: Land concept, Land space, Landscape, Landform, Land Feature, Land Object), relationship structures (Hierarchical or non-hierarchical relationships, intra and inter-level relationships, one-way and two-way relationship), scale levels (including: universal, global, regional, zonal, focal, local, pointwise), and flow of energy are explained.

Different branches of science face different phases during their growth and development. Two main phases that affect scientific networks in different periods, in this research, are named and explained Dynamic Terminological Phase (DTP) and Static Terminological Phase (STP). Given that the theoretical development of different branches of science is associated with terminological development and this relationship is a kind of interrelated relationship, in the dynamic phase of terminology, different branches of science, are more dynamic which this would be reflected in the terminological production volume. In the other phase, the volume of terminological production is reduced and is a kind of response to scientific stagnation, which is called the static phase of terminology, and is an indicator of fundamental stagnation and scientific development in that branch of science. Formerly, form units in geomorphology have been considered based on units of landscape, land view, land form and land feature (Ramesht, 1384, 15). In the classification presented in this research, the resolution of the classification system and their leveling is presented in a different way. The distinctive feature of the recently proposed structure is its higher resolution as well as its semantic nature.In this hierarchical system, each form unit can contain a number of sub-units. From the combination of seven hierarchical units of form, the structure of modern morphology in geomorphology is formulated, the largest unit of morphology unit in this structure is land concept and the smallest unit is land-object. In this structure the land concept, land space, land context, landscape, landform, land feature, land object, have universal, global, regional, zonal, focal, local, and point-wise scales, respectively. The scale levels are also classified into four Major classes: Mega, Macro, Meso, and Micro. In the proposed formulation structure, 10 different types of interaction and relationship that are related to the structure of this structure, are explained. These relationships can be hierarchical or non-hierarchical, intra-level or inter-level, one-way or two-way. From the combination of the above states, ten relations are created. morphic relations in this form structure can be divided and classified into two main groups: vertical and horizontal.

The nature of the current space governing the science of geomorphology, which is itself a function of the space of the scientific community as a whole, indicates a stagnation in the birth of concepts and being in a static terminological phase. Such conditions justify the need for such fundamental studies in order to open new spaces. With this explanation, monitoring the content and semantic space of geomorphology, it seems that this science, like many other sciences, is in a static phase of terminology. This issue can, over time, damage the meaning and spirit of a scientific discipline. In this research, the solution to get out of this space and try to enter the dynamic terminological phase, through the design of new meanings in the form of new terminology has been considered. In this regard, the basic formulation system that was proposed in geomorphology with a completely new structure and different hierarchical levels, has been configured and developed in the form of a new terminological design. This new system of morphology is presented in 7 different levels, including: Land Concept, Land Space, Land Context, Land scape, Land form, Land feature and Land object is Provided.In the proposed morphological structure, 10 different types of relationships and the relationship that these relationships have with the morphological structure are explained.Scale The studies at each of the hierarchical levels of the proposed morphological system are explained on a universal, global, regional, zonal, focal, local and point scale, respectively.

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.

Part of the studies of geomorphology is dedicated to the automated, semi-automated identification, segmentation and classification of landscapes and landforms at different scales. Each of the landscape classification systems, includes a number of smaller units or landforms. Some methods have been used to identify and recognize Landforms, while others have been dedicated to the landscape classifications. Landscape classification is applicable in a wide range of geomorphological studies such as, mapping geomorphological maps, zonation and environmental potential in the field of ecotourism, environmental exploitation and sustainable development, and also in the field of economic geography, natural hazard assessment and arranging the land use planning documents of the country and many other fields which is directly and indirectly applicable. In this study, an attempt has been made to present a new system in the landscape classification which be able to recognize and classify, landscapes of the terrain surface using, digital elevation models considering the ease and simplicity of the procedures. For this purpose, tangential, plan and profile curvature and slope extracted from digital elevation model, these three curvature combined together to get mean curvature and these factors including elevation, slope and mean curvature used to classify landscapes of the terrain. In the next step, each of the three components of the above-mentioned was divided into two parts based on 5 methods of thresholding, including: geometrical interval, quantile, natural breaks, standard deviation and weighted average. Finally, all three components have been coded and named with a special system and the area of the Iran, was classified into 8 landscapes units and the results were presented as a color map

The area covered by snow (SC) and land surface temperature (LST) and their fluctuations in different altitudes of a mountain unit are important in climatic, hydrological and water and ecological resources management. In this study, the relationship between SC and LST in this mountainous unit was examined in monthly, seasonal and annual intervals. For this purpose, Terra and Aqua Satellite image data which are carrying Modis sensor, used in temporal range of 2003-2018.In all time periods studied, a clear relationship between elevation and SC, was observed in the Central Alborz highlands. The relationship between these two environmental indicators are direct, although the rate of change varies on different altitudes. Two specific height thresholds were observed in Central Alborz, the first threshold being at an altitude of 1000 meters and the other at 4000 meters. So that the SC rises to a height of 1000 meters with increasing altitude. After an altitude of 4,000 meters, the slope changes again and starts to decrease. LST variations are the opposite of SC. In general, increasing the height leads to a decrease in LST, but, up to 1000m is an exception to this rule, and increasing the height will increase the LST.

The area covered by snow (SC) and land surface temperature (LST) and their fluctuations in different altitudes of a mountain unit are important in climatic, hydrological and water and ecological resources management. Snow cover and land surface tempratue distribuations on different elevational class would be important from the view point of environmental systems and ecosystems observations and management. One of the major mountainous unit in Iran, which is supplying many human population, is the Central Alborz mountain, located in the northern boundary of Iran.

In this study, the relationship between SC and LST in this mountainous unit was examined in monthly, seasonal and annual intervals. For this purpose, Terra and Aqua Satellite image data with spatial resolusion of 50m which are carrying Modis sensor, used in temporal range of 2003-2018. Digital Surface Model released by the Japan Aerospace Exploration Agency (JAXA) deployed the Advanced Land Observing Satellite (ALOS) between January 2006 and May 2011, used in this research. This data have spatial resolusion of 1 arc secound (~30m) and a vertical RMSE of 4.4 m. and now is one of the most accurate dataset with global coverage and free of charge.

In all time periods studied, a clear relationship between elevation and SC, was observed in the central Alborz highlands. The relationship between these two environmental indicators are direct, although the rate of change varies on different altitudes. Two specific height thresholds were observed in Central Alborz, the first threshold being at an altitude of 1000 meters and the other at 4000 meters. So that the SC rises to a height of 1000 meters with increasing altitude. After an altitude of 4,000 meters, the slope changes again and starts to decrease. LST changes are the opposite of SC changes, in general, increasing the height leads to a decrease in LST of course, up to 1000 meters is an exception to this rule, and increasing the height will increase the LST. This is due to the cooling effect of the Caspian Sea and high humidity at altitudes below 1000 meters and also decreasing vegatation coveabdr density up to 1000m, which mainly includes the northern slopes of Alborz. Forests, forest-steppes and grasslands, are absorbing the sunrays energy and consume it in the process of photosynthesis, and so they prevents, the land surface temperature to be increased. In the highland of central Alborz (the elevation up to almost 1000m) lower humidity and vegetation cover in addition to the rocky surfaces, leads to the higher LSTs. From an altitude of 1000 meters and above, the general trend of increasing altitude leads to a decrease in LST in Central Alborz. Another environmental indicator was defined in this study, which was called the Equilibrium Line Altitude of Land surface Temperature and Snow Cover (ELALS). ELALS is a height at which LST and SC reach equilibrium. The annual average of this environmental index is in the hight of 2,800 meters during the study period in the Central Alborz highlands. The minimum level of ELALS in winter is 1740 meters above sea level. This environmental index tends to reach low altitudes in cold seasons and months and tends to higher altitudes in warmer periods of the year.

Finally, this environmental index can be used in geomorphological studies of glaciers, climates, water resources, hydrological management of basins and ecological studies of mountainous landscapes.

Terrain morphology, provides a lot information for researchers in the field of environmental science. One of the goals in geomorphology is identification, and analyzing terrain landforms. In the past, the identification of landforms was performing field-based or using topographical maps. Manually, which was time-consuming and difficult, and in vast areas, it was facing many problems. In this article we had attempted to identify glacial and sub glacial landforms including: glacial cirque, glacial sinkhole (Tarn Lake), summit, saddle, ridgeline, drainage line, and sedimentary fans. For recognizing these landforms, two modelling approaches have followed. First is a conceptual modeling, which uses kernel pattern modeling. This modeling level, provides the condition in which, terrain morphology compares to the reference pattern. Second is an object-based modeling, which uses reference object to recognize landforms. Above mentioned landforms, considered in this research, recognizes, using both modeling approaches, and the results represents in the form of maps. Some typical landforms considered to make accuracy assessment and performance control, for each model output possible. To automate modeling procedures, Python programming language used widely. Eventually, all codes and scripts prepared in the build-in Graphical User Interface (GUI) programming environment of python (Tkinter), and the software, named: Landform Detector V.1 prepared. Accuracy assessment, shows that landform recognition process had performed with 60% in average, which respect to the landform complexity, is acceptable. Average accuracy of the considered models are equal to 51.58 % and 50.60 % for conceptual and object-based approaches, respectively. In result, object-based approach had a better performance overall.

The area, covered by snow or snow-cover variations, is one of the important factor in climatologic and hydrologic studies, that could be also useful and applicable in water management and environmental studies, specifically when it is combined with topographic characteristics. In this research Land Surface Temperature (LST) and snow-cover interactions were considered. These environmental indicators interactions, combined with focal topographic characteristics such as slope, play a major role in snow-cover persistency. As a result, the influences of these factors had taken into account in central Alborz mountainous belt in Iran northern boundary. To achieve this goal, snow-cover (SC) and land surface temperature (LST) obtained from Aqua and Terra satellite images that are carrying Modis sensor, used in a the temporal range of 2003 up to 2018. Snow cover data with spatial resolusion of 500m analyzied using python programming language. The analysis performed related to the aspect as a major topographic characteristic in the scope of terrain modeling with using moving window and cell by cell raster analysis thechniques. The result, shows a strong relationship between terrain aspect and snow coverage in the central sector of Alborz Mountains. Land surface temperature and snow-cover had an inverse trend, specifically during winter and fall seasons. June LST (Khordad) was high according to the higher zenith angle of the sun in this period of year. There is a clear gap between the LST values of northern and southern aspects of central Alborz that could be result of mountain orientations to the sun rays, higher humidity levels and denser vegetation cover in the northern part. Southward areas, show higher temperature in almost all months. Directional analysis of LST, demonstrated, that maximum levels of LST are observed in the south-faced and specifically southeastward area and the minimum levels observed in northeastward and specifically northward area during all months. Southward area of the alborz mountainous wall, located at the latitude band of 36N, experienced a higher sun ray incident angle and thus having higher LSTs in southern and southeastern parts. Finally in almost all temporal periods (including month, season and year) higher LSTs in southern aspects (South, Southeast and southwest) in compared to northern one (North, Northeast and northwest) has been observed.

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

Freezing Level Height (FLH), Permafrost Edge Altitude (PEA), Equilibrium Line Altitude (ELA) and Snow-Cover Percentage (SC) are considered as important components of assessing and investigating the status of water resources. Environmental Lapse-Rate (ELR) was used to calculate these parameters. Regarding to the problem of using Land-Based climatological stations data, gridded radiosonde data were used as a replacement. This database has a higher and proper spatial and temporal resolution. In the first stage, raw data were processed in the Python programming environment, and then the ELR ratios on the lower part of troposphere were estimated up to 6000m in order to be used in FLH calculation during 2008 to 2016 time period, FLH and ELR were together used to calculate PEA at Sabalan mountainous area. The results are presented in the form of diagrams, maps and tables. Snow-Cover status at the Sabalan heights was obtained from Terra and Aqua Modis images, during the same period and they were analyzed and presented on the basis of monthly, seasonaly and annually time interval. The SC levels and the FLH altitudes were analyzed and compared. The FLH position, and hypsometrical distribution interactions, can be used for investigation of water resources future, and the establishment of appropriate water management scenarios. The comparison of SC percentage and the FLH level pointed out more differences during warm-months and the less during cold and wet months of the year. Winterly FLH level of Sabalan mountain lies at the elevation classes of 1200-1700, 1700-2200 and 2200-2700m which shows a normal, semi-critical and critical state of water resources respectively that could affect water resources management policies.

Longitudinal profile morphometry of the mountain valleys, provide a numerical and quantitative indicators for researchers of geomorphology to draw form-processes conclusions from the morphological evolutionary state of mountainous units. Morphological Behavior of the valley’s longitudinal profile, could be a sign of predominant processes and their interactions with topography.13 valley’s basins in mountainous area of Sahand (Western Azarbayejan,Iran) were delimited with a homogenouse lithology.To homogenize criteria in different valleys, each basin outlet was bounded at the absolute height of 1800m. In each valley, main drainage paths, were drawn using Arc Hydro Model (V.2). Coordinates of the location of each point on these paths (Longitudinal profile) were extracted from digital elevation model and python programming languge was used to make it automate. In this research five Low-level (Geometric, Topologic), twenty Mid-level (Statistic, Topographic), and four High-level (2L-3L.R[1], P.C.I[2], C.C.I[3], E.R.R[4]) morphometrical indices were used and run.The Percent of profile concavity (P.C.I), shows that longitudinal sections which are located in the northeast hillside of Sahand mountain has a higher level so that is a sign of more concavity ratio and thus more profile evolution.The profile concavity index (C.C.I) has also similar trends. Elevation Relief Ratio (E.R.R) and 2D to 3D length ratio (2L-3L.R) shows a higher levels in the southwest hillside. Eventually, under consideration of these four morphometric models, it’s possible to observe clear differences in the evolution of longitudinal profiles which are located in the north to northeast hillsides of Sahand mountain in comparison with south to southwest part of this mountainous unit, which is corresponded perfectly with sunny hillside and slopes located in the shade.
Introduction Geomorphometry is a scientific branch on the basis of measurements, computational geometry, topography and morphology of the earth's surface and their temporal deformation. Geomorphometry is a quantitative analysis of the earth's surface. Geomorphometry is a quantitative analysis of the earth's surface (Pike,1995,2000a: Rasemman et al., 2004). Digital Elevation Model (DEM) is used as an input for many geomorphometric models. Many researchers of geomorphology had studied in the field of morphometrical modeling of geomorphological features. Some of them had studied longitudinal and profile sections of mountainous valleys, until estimates glacial and fluvial valleys and the dominant conditions of their evolutionary phases. Several different morphometrical models have been employed in various field of geomorphology included deserts, mountains, plains and costal environments. Some of them had a tectonic or geologic approaches others have a morphogenic views. But in general, almost all of them are using mathematical, geometrical and physical equations and relations for investigating land surface phenomena.
Methodology In recent study, Digital Surface Models(DSMs), published by the Japanese Space Agency in May and October 2015, in 30m spatial resolution were used. This data is extracted from ALOS satellite images. This data is based on global 3D topographic DSM data (5m grid version) which is the most accurate elevation data in the global scale (T. Tadono et.al,2014). For extracting rivers, valleys, rural and urban centers, topographic maps published by Iran National Cartographic Center (NCC) were used. Drainage basin of each valley were delimited from Digital Elevation Model (DEM), Topographic maps and Hillshade model with using Arc Hydrology model in the Arc GIS package. Then, the longest drainage path from the outlet to the highest tip of each valley’s basin was drawn in the form of vector-based geometry. Each of vector layer divided into the vertices with a high density. Each vertex has an xyz coordinate which is stored in the form of txt and ASCII file formats. Data stored in the txt and ASCII files imported into python environment and was prepared to programming with. Morphometrical modeling, measurements and progressive algorithms were automated using python, in order to morphometry of longitudinal profiles purposes. Morphometrical results are classified into three main classes: including low-level (or basic), mid-level (or prerequisite) and high-level (or advanced) morphometrical indices.
Results and discussion Morphometrical indices shows that longitudinal profile concavity ratio is clearly different at north to northeast and south to southwest aspects in this mountainous unit. Numerical value of this index is maximum in northeast aspects and the rate is minimum at southwest part. Profile concavity and convexity index (C.C.I) has a similar trend and shows a clear difference between northeast and southwest slopes. Elevation Relief Ratio (E.R.R) has a completely different trend and reaches to the maximum and minimum values at southwest and northeast slopes respectively. The ratio between 2D and 3D longitudinal length shows a higher value in the northeast slopes or generally northern slopes.
Conclusion In this paper, longitudinal profile of Sahand’s valleys were modeled using 4 morphometrical indices (Including: 2D to 3D length ratio, profile concavity, Concavity and Convexity Index, and Elevation Relief Ratio). Results gotten from Profile Concavity Ratio show higher values of longidudinal profiles located on the noertheast valleys of sahand mountain, which suggest more morphological profile evolution. Concavity Index shows similar trends. Both Elevation Relieaf Ratio and 2L-3L.R have a higher value in the southwest slopes. with taking into account these 4 advanced morphometrical models, recognizable differences in evolution of logtidunial profiles of north to northeast slopes in Sahand mountain were detected. With regard to the fact that quaternary glaciation played a major role in the main mountainous unit of Iran, glacial and subglacial process had played a recognizable change on mountainous area especially the height above 3000m and higher latitude bands. Because of high latitude (near 37 Degree) and elevation (more than 3600m), Sahand mountain was affected by glacial and subglacial erosion. In the higher latitude bands, because of more winter inclination angle, southern slopes recive sunlights in a wider angle and so there is a difference between northen and southern slopes from the view point of radiation energy absorbtion. Eastern slopes have a lower radiation energy campared with western one and thus leaded to the less energy balance. Furthermorem, north and northeast slopes of the Sahand mountain are in the vicinity of Caspien sea water body, so it had received more precipitation during glacial phase in relation to Siberian cold wind. Despite of being young and having igneous lithology, Sahand mountain shows morphological evidence of glacial and subglacial evolution of longitudinal profiles due to the favorable climatic condition such as enough winter snow. These morphometric indicators are perfectly adjusted to the slope aspects and morphological changes are synchronized with glacial and subglacial process. Finally all these morphometric indices programed and designed in python Tkinter GUI programming enviornment and a GIS toolkit named Longi-Profile Analyzer V.1 prepared fundamentally for longitudinal profile analizing.

Solar radiation is the source of earth system that has many effects on all earths system. Energy forces of all earth systems and ecosystems provide with solar energy. Solar energy calculate with different function and formula and in the most of them calculate for horizontal plane that this is a major problems in solar radiation calculation. In this paper use earth roughness effects on solar radiation absorption. For earth roughness using digital elevation model (DEM) to simulate mountains surface. Keywords: Total Radiation, Direct Radiation, Diffuse Radiation, Duration of direct Radiation, Anthropogenic Activity, Morphoradiation, Morph genic Evolution. Introduction Solar radiation is the main source of earth planet energy and is the main factor of climate component control. Solar radiation control earth surface temperature and then determine temporal and spatial variation and patterns of moisture and pressure. With regards to solar radiation role in all morphological systems solar radiation importance in geomorphology can better understand. Solar calculation for eqlid mountain range have been done. And related maps illustrated. 1- Directed solar radiation Calculation Directed solar radiation is the radiated energy that reaches to the earth surfaces in form of straight and direct rays. When the sun is above horizon line in the sky directed solar radiation occur and in the other time there isn’t any directed radiation. The sky divided to some sun sectors with half hour interval and the sun position in the sky calculated for each part and according to this sun height and azimuth directed solar radiation on the 3 dimensional surface calculated. 2- Diffuse solar radiation Calculation In the energy analysis not only need the directed solar energy but also need to diffuse solar energy. As physical definition if there isn’t any diffuse radiation in the environment the temperature difference between light and shadow surfaces will increase. Diffuse solar radiation calculated based on Uniform Overcast Sky (UOS) model. 3- Duration Direct Radiation calculation Duration of direct radiation calculated for the case study in one year. Latitude of the area that shows day length indirectly and earth morphology are the factors in this analysis. 4- Total Radiation Summation of directed radiation and diffuse radiation in all sun sectors is total Radiation. Results 1- Radiation effects on the natural systems and ecosystems 1-1- effects on vegetation cover More radiation intensity in the south and south west skirt of the eqlids mountain lead to temperature variation and then flow over earth systems. Increase in the rate of temperature lead to high evapotranspiration and low relative humidity that these factors can cause directly on the vegetation growth. In the area study high energy skirts has low plants density and low energy skirts has more density of plants. 1-2- effects on pedogenic systems Soil creation and developing has strong correlation with wet and thermal condition. In result effects solar radiation on the soil development are specified. In fact solar radiation can effect on thermal variation and variation of temperature effects on moisture and evaporation Changes. These changes determine direction of soil evaluation and creation. 1-3- Effects on hydrological systems Radiation balance in the Eqlid Mountains lead to thermal changes and then evaporation, infiltration and volume of runoff. Reliability coefficient of hydrological streams has difference in opposite’s skirts. 1-4- Effects on pre-glaciers and glaciers systems North and north east direction of this mountains mass gain less solar radiation and then has less temperature. More evidence of glacial cirque in this direction will accept this theory. Glaciers activity has more evidence in the west and north direction of this mountains skirts. 1-5- effects on the underground water Less temperature, more humidity, less evapotranspiration and more pre-glacial and glacial activity in the north and east north direction of area study help to discharge underground water more than opposite’s skirts direction. 1-6- Effects on micro and macro organisms More vegetation cover, fertile soils, surface and subsurface water resource all can has effect on micro and macro organisms. 1-7- effects on morphologic features All parameters and factors mentioned above can lead to geomorphological morphogenesis. In the north and north east skirts of this mountains there are some great alluvial fan whereas in the opposite’s skirts there isn’t such evidences. 2- Radiation effects on the anthropogenic activity All factors that listed above together can have strong effects on the settlements and human activates. There are more cities and village with density population in the north and east-north skirts of Eqlid mountains range as south and south-west of this mountain. Spatial arrangement and farming and agricultural fields and gardens configuration have the same trend as mountains skirt direction.

In the present world with regard to development of tourism earn many countries to think about finding new ways to getting huge capital. One of this ways is tourism capital attraction. This Type of capital attraction can useful to help suitable development and Occupation. According to this problem we try to determine suitable area for creation geo tourism space. To receiving this goal we used Analytic Hierarchy Process (AHP). AHP Method with dividing one problem to smaller parts allowing more accurate and Completed Analysis on research topics and helps us to receiving final goal in our research. For running this process we use from Geographic Information System (GIS). In GIS Environment about 20 Layer created and edited and then processing in AHP Model. Thus series of Paired comparisons doing on this data and using this result to finding suitable area for geo tourism space creation. is this research we try to using national factor because national landscape and geomorphic potential is more important.

In order to supply of irrigatin water for recent developed pestachue cultivation area in Rafsanjan basin, overpumage of underground water caused discharge of underground water resulting lowering the. water table.. Falling of water table could have destruction effects on the hydrological pedological and biological aspects of region. In order to avoid the hazardness of lowering the water table recharging of aquifers may be an appropriate solution. For this purpose TOPSIS model was used to evaluate the most appropriate region in recharging of Rafsanjan basin aquifer. The most effective parametere in this regards was elevation. Based on elevation the reffered basin was divided to six separate region. In each region 13 parametere was used in TOPSIS model and final model analysis showed that the region section A4 which its elevation ranged from 1610 to 1745 meter was the most appropriate site for recharging.