جنرالیزاسیون عوارض ارتفاعی در تولید نقشه‌های کوچک مقیاس مبتنی بر نقشه‌های پایه با استفاده از الگوریتم‌های موجود

نوع مقاله: مقاله علمی پژوهشی

نویسنده

دانشیار دانشگاه صنعتی مالک اشتر

چکیده

نقشه، تصویر کوچک‌شده و قراردادی تمام کرة زمین یا بخشی از آن است که به روش هندسی، روی سطحی مستوی به نمایش درمی‌آید. با توجه به محدودیت فضای نقشه، انتخاب و طراحی عناصر نمایش اطلاعات زمین، نیازمند فرایندی انتخابی، متناسب با اهداف تهیه است تا به کاهش سیستماتیک اطلاعات جغرافیایی پردازد. نقشه­، عوارض زمینی را در مقیاسی کوچک‌تر از شکل حقیقی­اش به نمایش می‌گذارد. هرچه عدد مقیاس بزرگ‌تر باشد، جزئیات کمتری از عوارض قابل‌نمایش است. با تغییر عدد مقیاس باید ارتباط منطقی میان عوارض و ابعاد نقشه حفظ شود؛ بنابراین، عوارض باید به‌گونه‌ای حذف شوند که این رابطۀ منطقی از بین نرود. همچنین یک نقشة کامل در مقیاس جدید با توجه به نیازمندی‌های کاربران و اصول و قواعد کارتوگرافی حاصل شود. جنرالیزاسیون به‌عنوان یک فرایند کوچک‌سازی و تولید نقشه در مقیاس کوچک‌تر، همیشه مورد توجه بوده است. با توجه به مشکلات پیش­روی روند تولید نقشه‌های کوچک‌مقیاس و نیاز صرف زمان و هزینة زیاد برای گویاسازی و گسترة عملیات میدانی، امروزه این روش به‌عنوان یک راهکار اجرایی ضرورت یافته است. به‌طورکلی، جنرالیزاسیون در دو بخش عمده برای عوارض مسطحاتی و ارتفاعی انجام می‌شود. در این مقاله، به بررسی جنرالیزاسیون عوارض ارتفاعی به‌صورت اتوماتیک، شامل نقاط ارتفاعی و منحنی میزان‌ها پرداخته می­شود. جنرالیزة منحنی میزان‌ها، به دو روش استفادة مستقیم از نقشة مبنا یا تولید DEM انجام می­شود. سپس با توجه به عبور عوارض هیدرولوژیکی مانند آبریزها، منحنی‌ها تصحیح می‌شوند. در جنرالیزاسیون، نقاط ارتفاعی نیز نقاط براساس اهمیت و ارتفاع، انتخاب یا حذف می‌شوند. درنهایت، عوارض ارتفاعی نقشه‌هایی با مقیاس 100.000/1، 250.000/1 و 500.000/1- که به روش اتوماتیک جنرالیزه شده‌اند- نمایش و تجزیه و تحلیل می‌شوند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Generalization altimetry features on the production of small-scale map based on base map using the existing algorithm

نویسنده [English]

  • Mahdi Modiri
چکیده [English]

Extended Abstract

Introduction
A map is a drawing ground features on one side of the paper. The cartographic maps are representations of the Earth upon a flat surface in the smaller scale than it’s true. Large scale maps cover relatively small regions in great detail and small scale maps cover large regions such as nations, continents and the whole globe. Logical connection between the features and scale map must be maintained by changing the scale and it is important to recognize that even the most accurate maps sacrifice a certain amount of accuracy in scale to deliver a greater visual usefulness to its user. Cartographic generalization, or map generalization, is the method whereby information is selected and represented on a map in a way that adapts to the scale of the display medium of the map, not necessarily preserving all intricate geographical or other cartographic details. Cartographer is given license to adjust the content within their maps to create a suitable and useful map that conveys geospatial information, while striking the right balance between the map's purpose and actuality of the subject being mapped. Scaling hierarchy or far more small things than large ones is found to be a universal rule for cartographic generalization. Well generalized maps are those that emphasize the most important map elements while still representing the world in the most faithful and recognizable way. The level of detail and importance in what is remaining on the map must outweigh the insignificance of items that were generalized, as to preserve the distinguishing characteristics of what makes the map useful and important. Due to the problems facing small-scale map production process and the need to spend time and money for surveying, today’s generalization is used as executive approach. Selection, simplification, combination, smoothing and enhancement are some generalization methods that can be applied by cartographer. Automatic generalization methods have been considered recent years. Accordingly several Conceptual, theoretical and operations have been obtained. One of the biggest obstacles is the lack of standards on spatial data and the lack of a comprehensive approach to automate the process. Also there wasn’t full understanding of the generalized maps and cartographic rules which cartographers traditionally have used them for years and never found a good solution for computer automation. So far, there is no comprehensive answer for this problem until now and different organizations that produce maps are doing based on their needs and ability in this area. Generalization generally performed in two main parts for planimetric and altimetry features.
Methodology
This paper investigates altimetry features that include points and contours. In most generalization projects in the past, contours were processed as independent features and their relation to other side features were not considered. This causes confusion and mistake in generalized maps. In this study, we try to maintain topological relations between different features as roads, rivers, contours and so on.
Direct methods of base map and DEM (Digital Elevation Model) are used for contour production in generalization process. In direct method, contours are extracted from base map and then they smoothed according to the hydrological structures as rivers. The second method is mostly used in the contours that there isn’t on base maps and they should be extracted by interpolation. For example, 50 meter contours extraction from 1:50,000 map with 20 meter contours. After production of the contours both ways, their topology and accuracy is checked that including the following: 1) Control the contours at the junction points, 2) Softness of contours, 3) control elevation points by contours and 4) remove small contours.
The number of elevation points are transferred from base map to final maps several times higher than the number of points is required. Selection of appropriate points by computer process requires analysis each one of them by contours and other features and the observed density in different situations Map. Finally, the best point is selected and will be remain in generalized map. In this article a circle with a certain radius used to examine the elevation points and the best points are selected on this circle. The following points should be considered in the selection: Higher elevations are considered on military plans and it’s better to have more elevation points at mountainous than flat area. Elevation points on roads, near villages and strategic location are more important. Selected points should be as representative a certain height of the peaks, hills, pits and trenches.
Implementation and Results
At implementation stage, contours at final product and then summarizing the elevation points, again in terms of topological relationships is controlled and monitored by the Cartographer, then they are corrected automatically or conversational.
By applying the algorithm presented in this paper on the altimetry features on 1:50000 base map, contours and elevation points generalized and maps with various scales as 1:100,000, 1:250,000 and 1:500,000 are produced automatically. By applying this method automatically, maps by different scales are produced and time and money are saved.
Conclusion
Update Land Cover maps at the various small scale are regional foundation of planning, natural resource management, and land use planning schemes and defensive project and so on. For years, the absence of these information resources is a tangible and necessary. Altimetry features are one of the most important features in cartographic maps that is studied their generalization in this paper. With maps using automatic generalization, small-scale maps are produced with remarkable speed and the ability to review and update them as easily as possible. Geometric and graphic communication between maps, new production, Improve product quality, saving money and time in order to produce maps of inland and overseas with high accuracy and at various scales and update maps rapidly, are some advantage of automatic generalization plan.
Key words: Contours, Elevation points, Generalization, Hydrologic features

کلیدواژه‌ها [English]

  • Base Map
  • Contours
  • Elevation points
  • Generalization
  • Hydrologic features

تشیع، بهنام و محمد سعدی مسگری، 1389، طراحی و ایجاد یک وب سرویس خلاصه­سازی نقشه، پایان‌نامة کارشناسی ارشد، دانشگاه خواجه‌نصیرالدین طوسی، تهران.

ثنایی، مریم، 1389، بررسی چگونگی عملیات جنرالیزاسیون عوارض خطی با استفاده از الگوریتم‌هایDouglas Peucker- و Wang در محیط ArcGIS، دومین همایش سراسری دانشجویی جغرافیا، 1389.

همراه، مجید و سیدجعفر مقیمی، 1391، کارتوگرافی، ویرایش اول از چاپ نهم، مؤسسة تحقیق و توسعة خانة عمران، 1391.

Tashaiio, B. and Sadi Mesgari, M, ,2010, Designing and Creating a Web Summarization Map, MSc Thesis, University of Khajenasir Toussi, Tehran. (In Persian)

Sanaie, M., 2010, Examines How the Operations Generalization Linear Effects Using AlgorithmsDouglasPeucker- and Wang in ArcGIS, the second Congress of Geography Student. (In Persian)

Hamrah, M. and Moghimi, S. J., 2912, Cartography, 9th Edition, the Institute of Research and Development of Civil House, 2012. (In Persian)

Azimjon, S., Gupta, P. and Sukhmani, R., 2014, Comparative Study of Algorithms for Automated Generalization of Linear Objects, ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences,1, 159-163.

Bimonte, S., Gensel, J. and Bertolotto, M., 2008, Enriching spatial OLAP with map generalization: A conceptual multidimensional model, Paper presented at the Data Mining Workshops, 2008. ICDMW'08. IEEE International Conference on.

Bjørke, J.T., 2001, Map Generalization: An information Theoretic Approach to Feature Elimination, 18th international Cartographic Conference, Citeseer.

Dr. ing. Jan Terje Bjørke, 2004, Map Generalization of Road Networks, Visalization and the Common Operating Picture, PP. 1-8.

Foerster, T. and Stoter, J., 2006, Establishing an OGC Web Processing Service for Generalization Processes, 9th ICA Workshop on Map Generalization and Multiple Representations, 25th June 2006, Portant/Vancouver.http:// ica.ign.fr/

Gokgoz, T., 2005, Generalization of Contours Using Deviation Angles and Error Bands, The Cartographic Journal, Vol. 42, No. 2, PP. 145-156.

Harrie, L. E., 1999, The Constraint Method for Solving Spatial Conflicts in Cartographic Generalization, Cartography and Geographic Information Systems, Vol. 26, No. 1, PP. 55-69.

Mioc, D., Anton, F., Gold, C. M. and Moulin, B., 2013, Spatio-Temporal Map Generalizations with the Hierarchical Voronoi Data Structure, Paper presented at the Voronoi Diagrams in Science and Engineering (ISVD), 2013 10th International Symposium on.

Modiri, M., Mohebbi, M., Masoumi, M., Khanlu, H. and Eftekhari, A., 2014, Planimetric Features Generalization for the Production of Small-Scale Map by Using Base Maps and the Existing Algorithms, ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences,No. 1, PP. 197-201.

Ormsby, D. and Mackaness, W., 1999, The Development of Phenomenological Generalization within an Object-oriented Paradigm, Cartography and Geographic Information Science.

Palomar‐Vázquez, J. and Pardo‐Pascual, J., 2008, Automated Spot Heights Generalisation in Trail Maps, International Journal of Geographical Information Science,Vol.22, No. 1, PP. 91-110.

Qiao, Q. and Zhang, T., 2009, Automated Map Generalization in Distributed Environments, Paper presented at the Computational Sciences and Optimization, 2009. CSO 2009, International Joint Conference on.

Xiao, Z., Boganga, Y. and Zhang, H., 2014, Rule-base Generalization Method on Large-Scale Topographic Map, ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, No. 1, PP. 305-310.