Seamless Visualization Research Articles

Machine learning-driven wind energy mapping enhanced by natural neighbor interpolation

In the present work, a prediction on the wind energy potential in Semarang City (Central Java Province, Indonesia) has been performed by leveraging a novel combination of machine learning and natural neighbor interpolation (NNI) methodology. This integrated approach uniquely combines the predictive power of machine learning to estimate wind speeds based on historical and spatial data, with the spatial mapping capabilities of NNI, which provides a more accurate and seamless visualization of wind speed distribution. This combination addresses challenges of data sparsity and variability, offering a more reliable and localized mapping approach than traditional methods. Additionally, air density is considered to calculate energy density, enabling a comprehensive evaluation of wind energy potential. The results show an average monthly wind speed of 5.23 m/s, ranging from 3.38 m/s to 7.39 m/s. Wind speeds between 7 m/s and 10 m/s are predicted to occur for up to 10 months annually, with an estimated energy density of 102.7 W/m². These findings underscore the feasibility of small-scale wind power generation in the study area and provide actionable insights for advancing renewable energy policies and implementations at the local level.

IoT based weather monitoring system for temperature, humidity, rainfall and seismic detection in real time

This paper presents the design and implementation of an IoT-based weather monitoring system enhanced with seismic detection capabilities, employing Node MCU microcontroller and the Blynk mobile application platform. The system incorporates various sensors including a rain sensor, Light light-dependent resistor (LDR), a DHT11 sensor for temperature and humidity measurement, and an accelerometer (MPU6050) for earthquake detection. The hardware components are interconnected with the Node MCU microcontroller, facilitating real-time data acquisition from the sensors. Programming of the Node MCU is conducted using the Arduino IDE, enabling data transmission to the Blynk app via Wi-Fi connectivity. The Blynk app serves as the user interface, allowing seamless visualization and monitoring of weather parameters and seismic activity on smartphones. Key functionalities of the system include periodic data collection from sensors, transmission of sensor data to the Blynk server, and updating of graphical representations in the Blynk app interface. The accelerometer sensor is utilized to detect changes in acceleration, indicative of seismic disturbances. Threshold values are defined to trigger alerts within the Blynk app in the event of potential seismic activity. The implementation undergoes rigorous testing to ensure accuracy, reliability, and responsiveness under diverse environmental conditions. Considerations such as network stability, power efficiency, and data security are addressed to enhance system performance and longevity. The system demonstrates promising capabilities for real-time weather monitoring and seismic event detection, offering valuable insights for disaster preparedness and environmental analysis. IoT-based weather monitoring system integrated with seismic detection provides an effective solution for comprehensive environmental monitoring, leveraging the power of IoT technology and mobile applications for enhanced data accessibility and analysis. Further advancements and optimizations can be explored to extend the functionality and scalability of the system for broader applications in environmental science and disaster management.

Whole-Body and Whole-Organ 3D Imaging of Hypoxia Using an Activatable Covalent Fluorescent Probe Compatible with Tissue Clearing.

Elucidation of biological phenomena requires imaging of microenvironments in vivo. Although the seamless visualization of in vivo hypoxia from the level of whole-body to single-cell has great potential to discover unknown phenomena in biological and medical fields, no methodology for achieving it has been established thus far. Here, we report the whole-body and whole-organ imaging of hypoxia, an important microenvironment, at single-cell resolution using activatable covalent fluorescent probes compatible with tissue clearing. We initially focused on overcoming the incompatibility of fluorescent dyes and refractive index matching solutions (RIMSs), which has greatly hindered the development of fluorescent molecular probes in the field of tissue clearing. The fluorescent dyes compatible with RIMS were then incorporated into the development of activatable covalent fluorescent probes for hypoxia. We combined the probes with tissue clearing, achieving comprehensive single-cell-resolution imaging of hypoxia in a whole mouse body and whole organs.

Interactive Scientific Visualization of Fluid Flow Simulation Data Using AR Technology-Open-Source Library OpenVisFlow

Computational fluid dynamics (CFD) are being used more and more in the industry to understand and optimize processes such as fluid flows. At the same time, tools such as augmented reality (AR) are becoming increasingly important with the realization of Industry 5.0 to make data and processes more tangible. Placing the two together paves the way for a new method of active learning and also for an interesting and engaging way of presenting industry processes. It also enables students to reinforce their understanding of the fundamental concepts of fluid dynamics in an interactive way. However, this is not really being utilized yet. For this reason, in this paper, we aim to combine these two powerful tools. Furthermore, we present the framework of a modular open-source library for scientific visualization of fluid flow “OpenVisFlow” which simplifies the creation of such applications and enables seamless visualization without other software by allowing users to integrate the visualization step into the simulation code. Using this framework and the open-source extension AR-Core, we show how a new markerless visualization tool can be implemented.

A Data Integration and Simplification Framework for Improving Site Planning and Building Design

Site planning and building design results are generally managed in Geographic Information System (GIS) and Building Information Modeling/Model (BIM) separately. The incompatibility of data has brought potential challenges for the assessment and delivery of the results. A data integration and simplification framework for improving site planning and building design is proposed in this paper. A BIM-GIS integrated model with a multi-scale data structure is developed to link the results of site planning and building design together. Geometric optimization algorithms are then designed to generate simplified building models with different levels of details (LODs) based on the information required at each scale. This paper provides a feasible way to integrate planning and design data from different sources to enhance the evaluation and delivery of the results. The proposed approach is validated by a village construction project in east China, and results show that the method is capable to integrate site planning and building design results from different platforms and support seamless visualization of multi-scale geometric data. It is also found that a seamless database facilitates understanding of planning and design results and improves communication efficiency. Currently, the main limitation of this paper is the limited access to 3D real-world data, and data collection techniques like point cloud are expected to solve the problem.

EXPLORATORY STUDY OF 3D POINT CLOUD TRIANGULATION FOR SMART CITY MODELLING AND VISUALIZATION

Abstract. The current trends of 3D scanning technologies allow us to acquire accurate 3D data of large-scale environment efficiently. The 3D data of large-scale environments is essential when generating 3D model is for the visualization of smart cities. For the seamless visualization of 3D model, large data size will be used during the 3D data acquisition. However, the processing time for large data size is time consuming and requires suitable hardware specification. In this study, different hardware capability in processing large data of 3D point cloud for mesh generation is investigated. Light Detection and Ranging (LiDAR) Airborne and Mobile Mapping System (MMS) are used as data input and processed using Bentley ContextCapture software. The study is conducted in Malaysia, specifically in Wilayah Persekutuan Kuala Lumpur and Selangor with the size of 49 km2. Several analyses have been performed to analyse the software and hardware specification based on the 3D mesh model generated. From the finding, we have suggested the most suitable hardware specification for 3D mesh model generation.

2000 Years of ‘globes vs. maps’ – lessons (to be) learned

ABSTRACTThis paper sheds light on the question of whether globes or maps are best suited to providing an adequate understanding of global phenomena. Drawing upon evidence from the history of cartography, we show how the ancient, medieval and early sixteenth-century mapmakers had already recognized the importance of globes and world maps. An analysis of Ptolemy, Strabo and the negotiations around the Treaty of Tordesillas will demonstrate how our basic assumptions regarding the relationships of globes and world maps have been present for a long time. These assumptions are discussed in the light of current user studies on world maps, for example on distance and area estimations and the issue of peripheral continuity. As we can see from this review of empirical research, designing an appropriate world map is not only an issue of map projection; the edge of a world map also affects the knowledge users may generate. In terms of the importance of ‘globes vs. world maps’, these findings indicate that globes are prominent because of their undistorted, but also seamless visualization of global phenomena.

Visualization in Meteorology-A Survey of Techniques and Tools for Data Analysis Tasks.

This article surveys the history and current state of the art of visualization in meteorology, focusing on visualization techniques and tools used for meteorological data analysis. We examine characteristics of meteorological data and analysis tasks, describe the development of computer graphics methods for visualization in meteorology from the 1960s to today, and visit the state of the art of visualization techniques and tools in operational weather forecasting and atmospheric research. We approach the topic from both the visualization and the meteorological side, showing visualization techniques commonly used in meteorological practice, and surveying recent studies in visualization research aimed at meteorological applications. Our overview covers visualization techniques from the fields of display design, 3D visualization, flow dynamics, feature-based visualization, comparative visualization and data fusion, uncertainty and ensemble visualization, interactive visual analysis, efficient rendering, and scalability and reproducibility. We discuss demands and challenges for visualization research targeting meteorological data analysis, highlighting aspects in demonstration of benefit, interactive visual analysis, seamless visualization, ensemble visualization, 3D visualization, and technical issues.

Another Perspective on the Peters Projection Controversy — Empirical Research on World Maps and Globes

Today, we can choose between approximately 250 map projections. However, cartographic practice is dominated by just a few of them, and constant discussion is held on the most suitable way of mapping the world. In this paper, we will approach this discussion via the Peters projection controversy. A review of this controversy will allow us to highlight several shortcomings inherent to the current discourse on world maps and globes by mainstream cartography, among them a lack of empirical research. Drawing upon evidence from cartographic history, I will show that main aspects for a comprehensive analysis were already considered by ancient mapmakers. I will also summarize different viewpoints empirical research can take on globes and maps. As we shall see from this discussion, designing a world map is not only an issue of projection. Also map edges and seamless visualization on a globe shape the user’s spatial mind.

Quad Tree-Based Surface Construction of Digital Globe for Real Time Application

ABSTRACTThe huge availability of high-resolution geographical data using the space/air borne platforms has made it possible to create and visualize the three-dimensional (3D) model of any part on the Earth. The seamless visualization of the adjacent data in a mosaic manner not only requires the specialized techniques for data representation but also require sophisticated techniques of rendering to meet the requirements of certain applications like flight simulator, missile path animation. The high speed rendering of the 3D frames is the key requirement in such applications where each frame rendering time is bounded. This paper presents a novel technique for efficient representation of the geographical data covering the complete globe and a new methodology of rendering of 3D frames that guarantees each frame construction within the desired time bound.

Multi-Scale Seamless Visualization of the Global Terrain Based on DQG

Real-time and seamless visualization of the Earth terrain based on Global Discrete Grids is a subject of considerable current attention. In this paper a multi-scales visualization model of the global terrain based on DQG (Degenerate Quadtree Grid) is approached. Our approach starts with a partition method, called Degenerate Quadtree Grid (DQG) and an encoding scheme of the corresponding grids is introduced briefly. Next, a multiple level of detail model related to viewpoint is presented. In this model, a criterion of terrain model simplification based on viewpoint and roughness of the degenerate quadtree node is developed. Then, making full use of the characteristics of quadtree structure, the cracks within quadtree blocks are induced by simplification. Thus, the cracks splicing are all seamless. In the end, the experiment and analysis are made with the global terrain data, GTOPO30. The results illustrate that: (1) the global terrain based on the DQG is seamless, hierarchical, and regular over the whole Earth; (2) the quantity of global DEM data can be reduced significantly; (3) the visual effect of the global multi-scale terrain is seamless by the model simplification ensuring the accuracy and efficiency of the terrain display.

Using KML and Virtual Globes to Access and Visualize Heterogeneous Datasets and Explore Their Relationships Along the A-Train Tracks

Keyhole Markup Language (KML), the de facto standard for representing, visualizing and transmitting geospatial data on Virtual Globes, lately approved by the Open Geospatial Consortium (OGC), Inc., has been widely used by the Earth Science communities. Most of the popular virtual globe systems, such as Google Earth and Microsoft Virtual Earth support KML format. This new online approach is changing the way in which scientists and the general public interact with three-dimensional geospatial data in a virtual environment. The so-called A-Train, a series of seven U.S. and international Sun-synchronous satellites, flying in tight formation just seconds to minutes apart, across the local afternoon equator, has been producing abundant measurements of vertical profiles of atmospheric parameters. This paper first discusses the key technical points for access to and visualization of three-dimensional Earth science data by using KML and Virtual Globes. Then, the Virtual Globes are taken as a virtual three-dimensional platform to synergize horizontal data and vertical profiles along the A-Train tracks to explore the scientific relationships among multiple physical phenomena. Two kinds of scientific scenarios are investigated: a) The relationships among cloud, aerosol and atmospheric temperature, and b) the relationships among cloud, wind and precipitation. The seamless visualization and synergy of multiple versatile datasets facilitate scientists to easily explore and find critical relationships between some phenomena that would not be easily found otherwise.

Complex Logarithmic Views for Small Details in Large Contexts

Commonly known detail in context techniques for the two-dimensional Euclidean space enlarge details and shrink their context using mapping functions that introduce geometrical compression. This makes it difficult or even impossible to recognize shapes for large differences in magnification factors. In this paper we propose to use the complex logarithm and the complex root functions to show very small details even in very large contexts. These mappings are conformal, which means they only locally rotate and scale, thus keeping shapes intact and recognizable. They allow showing details that are orders of magnitude smaller than their surroundings in combination with their context in one seamless visualization. We address the utilization of this universal technique for the interaction with complex two-dimensional data considering the exploration of large graphs and other examples.