Stavros Kolios

Achieving downscaling of Meteosat thermal infrared imagery using artificial neural networks

This study presents the successful application of artificial neural networks (ANNs) for downscaling Meteosat Second Generation thermal infrared satellite imagery. The scope is to examine, propose, and develop an integrated methodology to improve the spatial resolution of Meteosat satellite images. The proposed approach may contribute to the development of a general methodology for monitoring and downscaling Earth’s surface characteristics and cloud systems, where there is a clear need for contiguous, accurate, and high-spatial resolution data sets (e.g. improvement of climate model input data sets, early warning systems about extreme weather phenomena, monitoring of parameters such as solar radiation fluxes, land-surface temperature, etc.). Moderate Resolution Imaging Spectroradiometer (MODIS) images are used to validate the downscaled Meteosat images. In terms of the ANNs, a multilayer perceptron (MLP) is used and the results are shown to compare favourably against a linear regression approach.

Examining nominal and ordinal classifiers for forecasting wind speed

Wind speed forecasting is essential for environmental related reasons and many applications i.e. estimating the short-term energy production from wind farm operations. This work investigates and compares different approaches for the problem of wind forecasting in a simplified manner introducing and considering the prediction of the range within which the mean wind value will fall in the next time step. The proposed forecasting approach treats the forecasting task as a classification problem, which is suitable for this specific application. It takes advantage of the fact that, it is a natural/hidden ordering problem of the predefined classes, thus in this work ordinal classification - also known as ordinal regression- approaches are tested and compared with conventional nominal classifiers. The preliminary results indicate that considering the natural ordering of the classes yields the best performance for the specific test site involved in this study.

Coastal Marine Environment Monitoring Using Satellite Data Derived from MODIS Instrument

The quality of marine environment has a vital importance for the sustainable future of the Earth. On the other hand, the human activities, the sea commerce and transportation, affect significantly the marine environment especially in coastal areas, port areas, and the sea corridors. These induced activities impose contiguous and accurate methods for marine environment monitoring. Nowadays, modern satellite instruments gather data and the relative products derived from them can be used as an alternative, robust, and accurate way to monitor many basic marine parameters such as chlorophyll, sea surface temperature (SST), euphotic depth, dissolved organic matter and examine their long-term (climatic) tendencies. This study comprises an effort to assess the accuracy of satellite products, comparing them with relative ground-based measurements and it also focuses on provision of satellite-based mean variations on monthly basis regarding two important marine parameters (Chlorophyll-a and SST). In this study, available measurements of two different ports are used, i.e., the port of Bar in Montenegro and the port of Burgas in Bulgaria, which are partners of Transnational ENhancement of ECOPORT8 network (TEN ECOPORT) project.

Integrated Large-Scale Environmental Information Systems: A Short Survey

The installation and operation of instrument/sensor networks has great importance in monitoring the physical environment from local to global scale. Nowadays, such networks comprise vital parts of integrated information systems that are called Environmental Information Systems (EIS). Such systems provide real time monitoring, forecasts and interesting conclusions extracted from the collected data sets that are stored in huge databases. These systems are used as the main source of data for model parameterization and as verification tools for accuracy assessment techniques. This paper comprises a short survey aiming to highlight the significant role of existing Environmental Information Systems (ELIS) consisted of instrument/sensor networks that are used for large-scale monitoring of environmental issues regarding atmospheric and marine environment. The operating principles of these systems, their usefulness, restrictions and their perspectives in the environmental sciences, are studied and described.

Mathematical Methods of Geomagnetic Field Modeling

The geomagnetic field, as the Earth’s magnetic field is called, extends from Earth’s interior to outer space. The magnetosphere is the region defined by the areal extent and the shape of the magnetic field of a celestial body, like the planet Earth. The Earth’s magnetosphere extends several tens of thousands of kilometers into space beyond the ionosphere. The magnetosphere protects the Earth from the charged particles emitted by the Sun (the so−called solar wind) and the cosmic rays that would, otherwise, strip away the upper atmosphere, including the ozone layer that protects the Earth from harmful ultraviolet radiation.

Geographic Information Systems

The concept of geographic information systems (GIS) was introduced to cover all the essential needs of the scientific community to provide spatial information, analyze data, and create digital thematic maps through a computer. A fundamental for GIS is the overlaying of different kinds of information and data. Professor Ian L. McHarg (1920–2001) was one of the first scientists who described the GIS concept and the usefulness of map overlaying. In 1954, he took a position as Professor of Landscape Architecture and Regional Planning at the University of Pennsylvania and during the mid-1960s he came to be recognized worldwide for introducing ecological concerns into land planning (McHarg 1992). He introduced the concept of overlaying (Fig. 1.1) and highlighted the four basic principles (measuring, mapping, monitoring, and modeling) that founded GIS.

The GEOMAGNET WebGIS Application

Modeling and visualization of the Earth’s magnetic field is a challenging and complicated issue whose effective description and solution will contribute to better understanding of the principles and effects of geomagnetic field parameter distribution on the Earth’s surface, in its subsoil, and in circumterrestrial space. All measured and collected data concerning the geomagnetic field are distributed in various sources and storages, so their integration into a single information means is of major importance. Nowadays, modern information technologies and capabilities provide a wide variety of tools for mathematical modeling and visualization using computer graphics that could play a key role also in the parameterization of the geomagnetic field and the modeling of its variations.

WebGIS Applications for Weather, Marine, and Atmospheric Environments

During the last decade, there has been an increasing tendency for development of GIS applications regarding the environment. These applications not only focus on spatial analysis, decision making and future planning using the wide range of GIS capabilities, but they also provide to end users and the public integrated Web-based applications visualizing the final results of scientific efforts via maps and graphs (e.g., Fustes et al. 2014; Kulkarni et al. 2014). These computer-based applications are essential for modern visual representation of environmental issues through the monitoring of spatial and temporal changes, even in remote areas, helping planners and stakeholders to design and envision, on medium- to long-term scales, an environmentally sustainable future.

A WebGIS Application for Cloud Storm Monitoring

Extreme weather phenomena (i.e. heavy precipitation, hail and lightings) frequently cause damages in properties and agricultural production and usually originate from the cloud storms. Automated systems able to provide timely and accurate monitoring and predictions would contribute to prevent the effects of physical disasters and reduce economic losses. Nowadays, meteorological satellites have a significant role in weather monitoring and forecasting, providing accurate and high resolution data. Such data can be analyzed using Geographical Information Systems (GIS) and modern web technologies to develop integrated automated web based monitoring systems. This study describes a WebGIS application focused on monitoring and forecasting cloud tops of storm evolution. The application has developed using modern tools, to exploit their features through an innovative web based monitoring system. There are used open source framework to ensure mobility, stability and portability of the application.

Ambient Systems for the Environmental Monitoring: Characteristic Examples at Different Spatial Scales

This article is a short review highlighting the important role of ambient systems for the environmental monitoring. The article focuses on modern intelligent and fully automated systems that are able to use different kinds of data coming from scientific instrumentation and sensors as informational background in order to identify, analyze, monitor and forecast a vast series of parameters and phenomena that concern the atmosphere, the weather, land and seas. Here some characteristic examples of such systems are presented along with their basic operating principles, their usefulness and their perspectives in the environmental monitoring. Ambient systems have nowadays become essential solutions for the environmental monitoring and they are going to lead to the development of fully automated systems worldwide contributing in the efforts to preserve the Earth’s environment.