Bubble-Wall Plot: A New Tool for Data Visualization

This research aimed to design a new tool for data visualization with performed features - named Bubble-Wall Plot and assumed that it could be an effective tool for developing data visualization systems. This research reviewed seven data visualization approaches for identifying the outliers, including Line Charts, Parallel Coordinates Plot, Scatter Plots, TreeMap, Glyphs, Pixel-based techniques, and Redial visualizations. The challenges for current data visualization approaches were also summarized. Two principles were addressed to design the new tool- keep it simple strategy with the smallest strategy. As a result, the newly designed Bubble-Wall Plot has successfully been adopted to develop a warning system for identifying the outliers in a Case Study company, which was deployed for user acceptance testing in May 2021. The main contribution is that this newly designed tool with the simplest style was well-designed and proven to effectively develop a warning visualization system

New Generation Platforms for Exploration of Crowdsourced Geo-Data

This chapter addresses two recent topics in the field of geo-information, the former more technological and the latter more scientific. On one side, there is an emerging trend of visualizing data and their changes in space and time through multidimensional geospatial clients and/or virtual globes. In the most advanced cases, these are not simply plain viewers but also allow analysis of the data by acting as “multidimensional intelligent geo-viewers”. On the other side, citizen science is providing a great momentum to the possibility of lay people taking part in scientific development. It is a new, citizen-centred paradigm which, in most cases, takes advantage of the individual and collective augmented capability of sensing the surrounding world through the sensors that we wear. The “citizen sensors” will consciously contribute to this development, either through volunteered geographic information or by being themselves an unconscious part of the data analytics, which makes use of geo-crowdsourced data to extract information in order to create a higher level understanding of natural and manmade phenomena. This chapter seeks to outline the Web technological solutions for visualizing and analyzing such data, through a summary of the current state of the art and the original applications developed by the authors

An Analysis of Proximal Volcanic Ash Emissions

Volcanic ash is a product of explosive volcanic eruptions and refers to those particles < 2 mm in size that are ejected from a volcano. Once erupted into the atmosphere, ash can be transported vast distances. Satellite remote sensing has provided us with the tools to map and monitor these plumes. These methods are restricted in viewing only that portion that is optically transparent, due to the requirement to observe the interaction of ground upwelling radiation with the plume. For this study, methods have been developed to map not only the opaque portion of the plume, but in higher spatial resolution than has been attempted previously. This has been done by using the unique emissivity spectra that are produced by materials in the thermal infrared portion of the electromagnetic spectrum. By using an end-member linear unmixing model with a spectral emissivity library of different volcanic ash types, opaque plume bearing pixels of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data have been processed. These end-member results have shown the applicability of this technique, with sampled volcanoes mapped with very low root mean square (RMS) errors. Volcanoes with unknown composition were also mapped with the library with varying degrees of success. Further expansion of the laboratory spectral library will allow more accurate assessment of these volcanoes. The collection of per pixel emissivity spectra of opaque plumes was also attempted using an experimental multispectral FLIR thermal camera apparatus, in order to collect data on the rising volcanic ash column. These data showed that the camera can produce emissivity spectra, however further calibration and correction is required in order to make a volcanological assessment of the eruptive products. Finally, a method of better tracking disconnected ash plumes is assessed. In cases where a plume is detected disconnected from or distally from the source volcano, the application of geostatistical methods to backward trajectory model data can yield the source location. This could then be used to helped point the ASTER sensor off-axis towards erupting targets, thus providing a greater quantity of data to be analyzed

Earth Observation Open Science and Innovation

geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc