Some aspects of the edge matching method of digital topographic maps in the scale of 1:50 000 for creation the main state topographic map

Author(s):  
N. Lazorenko-Hevel ◽  
D. Kin ◽  
Yu. Karpinskyi
Author(s):  
HIROMITSU YAMADA ◽  
KAZUHIKO YAMAMOTO ◽  
TAIICHI SAITO ◽  
KATSUMI HOSOKAWA

We have proposed the MAP (Multi-Angled Parallel) operation method which extracts geometric features from a topographic map using erosion-dilation operations on a directional feature field. We have also proposed the MAP matching method which recognizes fixed-shaped symbols in the topographic map by using parallel operations on the same directional feature field. We have shown that all kinds of feature extraction and recognition can be effectively performed within the framework of parallel operation. In this paper, we show that elevation values in a topographic map can be recognized by a combination of MAP operation with the MAP matching. Numerals and symbols are recognized by the MAP matching method, while small dots and lines are extracted by the MAP operation method. These results are used together to determine the value, position and attribute of elevations in topographic maps.


2020 ◽  
Vol 2 ◽  
pp. 1-2
Author(s):  
Neža Ema Komel ◽  
Klemen Kozmus Trajkovski ◽  
Dušan Petrovič

Abstract. Today, many software tools enable the production of contour lines from relief models, but the results of modelling complex karst relief are often inadequate. Reasons for this may be limited quality and resolution of relief models, limitations of algorithms for calculating contours, or limitations of algorithms for smoothing and displaying additional symbols that further describe relief, such as slope lines, steep slopes and smaller objects that cannot be effectively displayed with contours, etc.We will present research in the field of improving existing algorithms in rugged karst terrain. As a target result, the presentation of relief on the existing national topographic maps in Slovenia, which were made by manual photogrammetric survey of aerial photos stereo pairs, were used. Slovenian elevation model DMR1 (1 m density) is used as a source for the creation of contour lines in various commercial software packages, and by comparing the results with a relief presentation on a topographic map, we selected the most appropriate basic algorithm. This one is further upgraded mainly by enabling automatic selection of auxiliary contour lines in the area, presentation of individual smaller relief objects with appropriate point or linear symbols, addition of slope lines on contours and indications in the middle of depressions and displacement of contour lines in order to better depict the terrain morphology.The results were tested in four different areas in Slovenia. Figure 1 shows the contour lines for a testing area near village Opatje Selo near Slovenia-Italy border, which were made by the best commercial software. The results of the algorithm are shown in Figure 2. The comparison between the results of the algorithm and the national topographic maps in the chosen scale gave promising results. In future work, we are planning to extend the algorithm so that it will be able to provide modelling of different terrains in the region.


2014 ◽  
Vol 522-524 ◽  
pp. 1207-1210
Author(s):  
Qing Wu Meng ◽  
Lu Meng

Using three dimensional coordinate transformation model with 7 parameters the coordinate transformation parameters are solved. Comparing the coordinates of the kilometer grid point on topographic maps in Beijing54, Xian80 and Urban Independent Coordinate System with the observation coordinates of same point inCGCS2000, Through watching their coordinate changes the moving changes regularity on topographic maps are discovered between Beijing54 and CGCS2000, between Xian 80 and CGCS2000, Urban Independent Coordinate System and CGCS2000


eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Peng Liu ◽  
Anastasia Chrysidou ◽  
Juliane Doehler ◽  
Martin Hebart ◽  
Thomas Wolbers ◽  
...  

Topographic maps are a fundamental feature of cortex architecture in the mammalian brain. One common theory is that the de-differentiation of topographic maps links to impairments in everyday behavior due to less precise functional map readouts. Here, we tested this theory by characterizing de-differentiated topographic maps in primary somatosensory cortex (SI) of younger and older adults by means of ultra-high resolution functional magnetic resonance imaging together with perceptual finger individuation and hand motor performance. Older adults' SI maps showed similar amplitude and size to younger adults' maps, but presented with less representational similarity between distant fingers. Larger population receptive field sizes in older adults' maps did not correlate with behavior, whereas reduced cortical distances between D2 and D3 related to worse finger individuation but better motor performance. Our data uncover the drawbacks of a simple de-differentiation model of topographic map function, and motivate the introduction of feature-based models of cortical reorganization.


2018 ◽  
Vol 50 (2) ◽  
pp. 73-86
Author(s):  
Wiesław Ostrowski ◽  
Izabela Karsznia ◽  
Tomasz Panecki

Abstract Built-up area is a particularly important element of the content of topographic maps. Its presentation changes significantly when map scales are reduced, due to both conceptual and graphic generalization. What is more, historically, changes in the depiction of built-up area were consequences of changes in the intended use of topographic maps, development of technology and changes in the cultural landscape, of which the built-up area is an important component.1 The authors describe the method of presentation of built-up areas on six Polish topographic maps or series of maps. The above-mentioned maps include the following: – Topograficzna Karta Królestwa Polskiego (Topographic Map of the Polish Kingdom) at the scale of 1:126,000 developed in 1822–1843; – topographic maps of the Polish Military Geographical Institute (MGI) at the scales of 1:25,000 and 1:100,000, published in 1930s; – a series of military maps (or military-civilian maps) at the scales of 1:10,000, 1:25,000, 1:50,000 and 1:100,000, developed in 1956–1989, in accordance with the instruction for developing Soviet maps; – a series of civilian maps at the scales of 1:10,000, 1:25,000, 1:50,000 and 1:100,000 developed after 1995. The basis for a quantitative comparison of the content of the maps was the number of categories of objects (identifications) which constitute part of built-up area and are presented on individual maps as symbols, as well as the number of characteristics represented by these symbols. These characteristics are divided into two basic types: functional characteristics and physiognomic characteristics. The analysis shows that military maps issued after the Second World War differ from the civilian maps, as they contain a much larger share of physiognomic characteristics, which is caused mainly from the fact that the vast majority of military maps distinguish between wooden and brick buildings. This difference was to large extent already noticeable among the oldest of the analysed maps – the Quartermaster’s Map and nineteenth-century Russian maps, which were partly modelled on the Quartermaster’s Map, and later also Soviet maps. Due to political reasons, the model of these Soviet maps was later adopted for the development of post-war Polish military maps. Out of all maps drawn up by military services, the inter-war MGI map serves special attention, as it was modelled on German maps. The main difference between military and civilian maps is foremost the fact that civilian maps include more functional characteristics of buildings and take into consideration new physiognomic characteristics related to residential development (compact, dense, multifamily dwellings, single family dwellings). The analysed maps include not only the characteristics of buildings and built-up area, but also information on the features of the town – population size, number of village houses and the administrative function.


2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Hao Wu ◽  
Hongguo Jia

<p><strong>Abstract.</strong> Topographic maps (TM) contain plenty of geographic information, such as topographic fluctuations, hydrological networks, vegetation, administrative regions, residential areas, transportation routes and facilities and other man-made features. Based on geographic information, the map knowledge extracted from topographic maps has been widely used in many research fields, such as landscape ecology, land and resources management and urbanization.</p><p>Traditional topographic maps are generally in paper-format. It is difficult to use them for the spatial or multi-temporal analysis. Thus many research work focus on the extraction of geographic information based on scanned topographic maps (STM).Most of the existing studies developed many methods and algorithms to extract the geographical information from scanned topographic maps. However, these proposed methods usually only can extract a certain kind of feature, and parameters used in these methods are needed to set manually. However, for map knowledge, e.g. spatial distribution and spatial relationship among different map features, it is difficult to effectively combine different methods to extract map knowledge. Therefore, this paper proposes a method of extracting geographic knowledge based on deep-learning, which can be object-oriented and efficiently extract geographic knowledge. This method contains three steps: 1) establishing samples for different map features; 2) using the Convolutional Neural Networks (CNN), which is suited to the image recognition (Karpathy A et al. 2014), to classify the scanned topographic map; 3) estimating the proportion of different map features on maps and describing the spatial distribution based on a grid.</p><p>The method proposed in this study has been evaluated by some scale topographic maps. The results indicate that the extraction precise of this method can reach more than 70% for water and mountain areas and can also describe the spatial distribution for the features with larger map areas.</p>


2001 ◽  
Vol 23 ◽  
Author(s):  
N. Gunmg ◽  
Y. Iwao

This paper describes an innovative way of distinguishing landslide-prone regions by simple and direct measurement and statistical interpretation of a topographic map. For this purpose, the topographic maps are enlarged and the contour interval and cross-slope distances are measured. A frequency distribution histogram based on chi-square method is constructed from the measurements. Generally, two fundamental patterns emerge from the histogram: the landslide-prone area shows several peaks whereas the remaining area shows just a single peak. The technique was used to study the landslide-prone areas of the western Kyushu District of Japan. Six sub-regions were categorised depending upon the scale functions and probability parameters. The landslide-prone and safe areas were accurately discriminated under 0. 1 to 1% confidence level. The analysis independently discovered most of the hazardous areas that were later verified in the field.


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