Paper Info
Title
Information Technologies For Environmental Monitoring Of Plankton Algae Distribution Based On Satellite Image Data
Abstract
The paper discusses the features and specifics of using the methods of remote sensing of the Earth when monitoring the ecological and technical state of water management process systems. A technology for monitoring surface waters according to remote sensing of the Earth is proposed. A method of satellite monitoring of algal bloom intensity (monitoring of planktonic algae clusters) has been proposed and substantiated. An approach to flood risk assessment using satellite observations is proposed. The technique of quantitative assessment of water quality according to the space monitoring of surface waters is substantiated. As a result of the research, it was found that when assessing the complex effects of pollutants on the ecological state of aquatic ecosystems using aerospace technologies, it is advisable to take into account changes in biological indicators (indicators of biomass and species composition of phytoplankton and higher aquatic plants). A method has been developed for predicting the long-term risks of emergency situations of a hydrological and hydrometeorological nature based on physical and mathematical modeling and the use of satellite observations and spatially distributed data. According to the results of further studies based on the results obtained in this work, it is planned to create flood risks distribution maps, quantitative predictions of surface water quality deterioration, as well as an assessment of the risks of air and soil pollution.
Year
DOI
Venue
2019
10.1007/978-3-030-26474-1_31
LECTURE NOTES IN COMPUTATIONAL INTELLIGENCE AND DECISION MAKING
Keywords
DocType
Volume
Aerospace technologies, Water system, Remote sensing of the Earth, Ecological state of ecosystems, Environmental risks, Surface water, Satellite monitoring, Algal blooms
Conference
1020
ISSN
Citations 
PageRank 
2194-5357
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Oleg Mashkov100.68
Victoria Kosenko200.34
Nataliia Savina312.72
Yuriy Rozov400.68
Svitlana Radetska500.34
Mariia Voronenko612.04