Публікація: Intelligent Data Processing in Global Monitoring for Environment and Security
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Дата
2011
Назва журналу
ISSN журналу
Назва тома
Видавництво
ITHEA
Анотація
The chapter is devoted one of possible approaches to automation in the field of the risk management, based on data processing of remote space monitoring of the spatially-distributed natural and technogenic objects for timely detection maintenance, diagnostics and the development predicate of the dangerous phenomena and emergencies. For acquisition of a digital image set for Earth's surface it is offered to use shooting from space satellites and unmanned aerial vehicles. We propose to eliminate a disadvantage inherent in standard unmanned aerial vehicles management schemes which are associated with a limited range of management through the use of digital imaging systems included in the control loop. The visualization system synthesizes a three-dimensional image of cockpit-exterior space on the basis of the unmanned aerial vehicles position and terrain. The set of mathematical methods and stage-by-stage procedures of computer processing of the space images are offered, allowing to make a preliminary filtration, to estimate them information compatibility, to carry out qualitative recognition, fixing and tracing of artificial objects. The considered integrated automation means complex provides necessary reliability and quality of achieved results, and also differs high speed that allows to use it and for the analysis of situations in real time.
Опис
Studies carried out separately by Russian and U.S. experts clearly indicate that we are soon expected to undergo global climate changes. An ever increasing number of natural disasters and technological accidents clearly confirm this. Therefore tasks for improving the quality of forecasting, reconnaissance and monitoring the situation with the emergencies are relevant.
Using digital area images allows you to automate the process of monitoring and improving the quality of forecasting and detection of abnormal situations. Digital images obtained by satellites are not always informative because of time and weather factors. The use of UAV allows you to minimize the influence of these factors and improve the information content of images. The fact that UAVs can be used in areas hazardous to human is particularly valuable. It enables you to perform aerial surveillance of highways, pipelines, power lines, to fly in emergency situations, man-made and natural disasters, floods, large-scale fires at industrial enterprises, military depots; aerial photography, environmental and radiation monitoring with the possibility of mapping the extent of radiation (or other) contamination.The proposed methods of image processing enables to estimate the information content of the images obtained and to carry out restoration of the height of objects represented on the photo, with the aim of their further recognition and registration of movement within the monitoring zone. The proposed method uses the representation of the brightness function curvature at different levels of scale to increase the original data resistance to noise and sampling. The approach proposed for calculating the curvature of the curve is distinguished by improved performance and availability of monitoring the accuracy of curvature estimation at the points of the contour. Together with the method of adaptive sampling for fast curvature scale space representation it allows to solve the task of restoring the height of objects in limited time mode with high accuracy.
As area of effective practical use of the offered synergy of technologies, mathematical methods and algorithms of digital images processing the main gas pipelines of a high pressure which are objects with a high risk level of emergencies occurrence are considered.
Ключові слова
risks emergency management, remote space monitoring data
Бібліографічний опис
Intelligent Data Processing in Global Monitoring for Environment and Security : монография / Bilous N., Bondarenko M., Borisenko V. and ect. –ITHEA, Kiev-Sofia, 2011, First Edition. - 409p.