KEYWORDS: Visualization, Data visualization, Image visualization, Information visualization, Eye, Research management, Statistical analysis, Graphic design, Chemical elements, Motion analysis
With the development of information and communication technologies, new technologies are leading to an exponential increase in the volume and types of data available. At this time of the information society, data is one of the most important arguments for policy making, crisis management, research and education, and many other fields. An essential task for experts is to share high-quality data providing the right information at the right time. Designing of data presentation can largely influence the user perception and the cognitive aspects of data interpretation. Significant amounts of data can be visualised in some way. One image can thus replace a considerable number of numeric tables and texts. The paper focuses on the accurate visualisation of data from the point of view of used colour schemes. Bad choose of colours can easily confuse the user and lead to the data misinterpretation. On the contrary, correctly created visualisations can make information transfer much simpler and more efficient.
The paper aims to apply the methods of image processing which are widely used in Earth remote sensing for processing and visualization of images in nano-resolution because most of these images are currently analyzed only by an expert researcher without proper statistical background. Nano-resolution level may range from a resolution in picometres to the resolution of a light microscope that may be up to about 200 nanometers. Images in nano-resolution play an essential role in physics, medicine, and chemistry. Three case studies demonstrate different image visualization and image analysis approaches for different scales at the nano-resolution level. The results of case studies prove the suitability and applicability of Earth remote sensing methods for image visualization and processing for the nanoresolution level. It even opens new dimensions for spatial analysis at such an extreme spatial detail.
The paper presents the algorithm for detection and clustering of feature in aerial photographs based on artificial neural networks. The presented approach is not focused on the detection of specific topographic features, but on the combination of general features analysis and their use for clustering and backward projection of clusters to aerial image. The basis of the algorithm is a calculation of the total error of the network and a change of weights of the network to minimize the error. A classic bipolar sigmoid was used for the activation function of the neurons and the basic method of backpropagation was used for learning. To verify that a set of features is able to represent the image content from the user's perspective, the web application was compiled (ASP.NET on the Microsoft .NET platform). The main achievements include the knowledge that man-made objects in aerial images can be successfully identified by detection of shapes and anomalies. It was also found that the appropriate combination of comprehensive features that describe the colors and selected shapes of individual areas can be useful for image analysis.
The paper deals with the approach of compiling of animations from a pair of oblique stereoimages. The authors investigated as simple and cheap way as possible to develop such approach which will be available for wide scope of ordinary users with common equipment. They concentrated on three procedures of oblique stereoimage handling to compile sets of images, animations and analogue documents. After capturing construction site by a pair of web cameras the data were corrected, photogrammetrically adjusted (due to radial distortion) and exported. Firstly, a set of anaglyphic images were compiled, then they were trimmed and timeline was inserted. The final anaglyph animations are compiled in various versions. In addition, an anaglyphic book containing 150 images was created in a special way that the user can easily browse through its content. The main outputs are several unique anaglyph products, but more beneficial outputs are developed procedures of anaglyph visualization that can be applied with minor modifications to photographing of any objects.
The Jeseníky Mountains tourism in Czech Republic is unique for its floristic richness, which is caused mainly by the
altitude division and polymorphism of the landscape; climate and oil structure are other important factors. This study
assesses the impacts of tourism on the land cover in the Jeseniky mountain region by comparing multi-temporal Landsat
imagery (1991, 2001 and 2013) to describe the rate and extent of land-cover change throughout the Jeseniky mountain
region. This was achieved through spectral classification of different land cover and by assessing the change in forest;
settlements; pasture and agriculture in relation to increasing distances (5, 10 and 15 km) from three tourism site. The
results indicate that the area was deforested (11.13%) from 1991 to 2001 than experienced forest regrowth (6.71%) from
2001 to 2013. In first decay pasture and agriculture areas was increase and then in next decay it was decrease. The
influence of tourism facilities on land cover is also variable. Around each of the tourism site sampled there was a general
trend of forest removal decreasing as the distance from each village increased, which indicates tourism does have a
negative impact on forests. However, there was an opposite trend from 2001 to 2013 that indicate conservation area. The
interplay among global (tourism, climate), regional (national policies, large-river management), and local (construction
and agriculture, energy and water sources to support the tourism industry) factors drives a distinctive but complex pattern
of land-use and land-cover disturbance.
One of the most objective methods of map use evaluation (in terms of reading, analysis and interpretation. is an analysis of eye movements of map reader, known as eye-tracking method. GazePlots and HeatMaps as the most commonly used visualization methods of eye-tracking data cannot effectively express the change of time. The authors introduce a Space-Time-Cube for spatio-temporal visualization. It displays the map at the base of the cube (axes X and Y) while Z axis is used to represent time. Spatial and temporal components of a map are shown together, and relationship between space and time can be revealed. During the authors’ research, the user interaction over the map legend of agriculture of the Czech Republic school maps was tested. Space-Time-Cube displayed both components (spatial and temporal) together and allowed easy visual analysis of four respondents’ (map readers’) work with a map. Using Space- Time-Cube for visual analysis provides satisfactory results, although this form of visualization is not widespread and for someone it may seem complex and confusing.
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