Operational use of open satellite data for marine water quality monitoring

2017 ◽  
Author(s):  
Theodoros Vakkas ◽  
Panagiotis Symeonidis
Keyword(s):  
Water Quality ◽  
Satellite Data ◽  
Water Quality Monitoring ◽  
Marine Water ◽  
Quality Monitoring

Internet of Maritime Things Platform for Remote Marine Water Quality Monitoring

2021 ◽  
pp. 1-1
Author(s):  
Yujae Song ◽  
Huicheol Shin ◽  
Sungmin Koo ◽  
Seungjae Baek ◽  
Jungmin Seo ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Quality Monitoring ◽  
Marine Water ◽  
Quality Monitoring

Marine water quality monitoring: A review

2013 ◽  
Vol 77 (1-2) ◽  
pp. 23-36 ◽  
Author(s):  
Michael Karydis ◽  
Dimitra Kitsiou
Keyword(s):  
Water Quality ◽  
Water Quality Monitoring ◽  
Marine Water ◽  
Quality Monitoring

Machine learning approaches to coastal water quality monitoring using GOCI satellite data

2014 ◽  
Vol 51 (2) ◽  
pp. 158-174 ◽  
Author(s):  
Yong Hoon Kim ◽  
Jungho Im ◽  
Ho Kyung Ha ◽  
Jong-Kuk Choi ◽  
Sunghyun Ha
Keyword(s):  
Machine Learning ◽  
Water Quality ◽  
Coastal Water ◽  
Satellite Data ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Learning Approaches ◽  
Coastal Water Quality

A centrifugal microfluidic-based approach for multi-toxin detection for real-time marine water-quality monitoring

2017 ◽  
Author(s):  
Ivan Maguire ◽  
Jenny Fitzgerald ◽  
Daniel McPartlin ◽  
Brendan Heery ◽  
Caroline Murphy ◽  
...  
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Water Quality Monitoring ◽  
Marine Water ◽  
Quality Monitoring ◽  
Toxin Detection

scholarly journals Research and Application of Rule Updating Mining Algorithm for Marine Water Quality Monitoring Data

2018 ◽  
Vol 25 (s3) ◽  
pp. 136-140
Author(s):  
Qiuhong Sun ◽  
Junhai Zhang ◽  
Xinhang Xu
Keyword(s):  
Water Quality ◽  
Random Search ◽  
Water Quality Monitoring ◽  
Original Data ◽  
Marine Water ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Massive Data ◽  
Photoelectric Sensor ◽  
Continuous Accumulation

Abstract This paper studies the characteristics of marine water quality monitoring data monitored by photoelectric sensor network, mines the potential information from the massive data. on account of the continuous accumulation of monitoring data, this paper focuses on the study of database with numerical attribute and proposes a rule updating algorithm for solving the rule maintenance issues caused by changes in the database. according to the rule, the algorithm forms a new database from part of the original data and the new data, and searches the new database by random search, thus can avoid creating a large number of redundant rules and can quickly mine effective rules at the same time. experimental results show that this method not only can avoid mining in the whole original massive data, but also can improve work efficiency, and can quickly and effectively find new data and find useful rules in the data with high practicability.

scholarly journals CITIZEN SCIENCE FOR EARTH OBSERVATION: APPLICATIONS IN ENVIRONMENTAL MONITORING AND DISASTER RESPONSE

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1221-1226 ◽  
Author(s):  
V. Kotovirta ◽  
T. Toivanen ◽  
R. Tergujeff ◽  
T. Häme ◽  
M. Molinier
Keyword(s):  
Water Quality ◽  
Citizen Science ◽  
Satellite Imagery ◽  
Satellite Data ◽  
Forest Biomass ◽  
Water Quality Monitoring ◽  
Earth Observation ◽  
Quality Monitoring ◽  
Landsat 8

Citizen science is a promising way to increase temporal and spatial coverages of in-situ data, and to aid in data processing and analysis. In this paper, we present how citizen science can be used together with Earth observation, and demonstrate its value through three pilot projects focusing on forest biomass analysis, data management in emergencies and water quality monitoring. We also provide recommendations and ideas for follow-up activities. <br><br> In the forest biomass analysis pilot, in the state of Durango (Mexico), local volunteers make in-situ forest inventory measurements with mobile devices. The collected data is combined with Landsat-8 imagery to derive forest biomass map of the area. The study area includes over 390 permanent sampling plots that will provide reference data for concept validation and verification. <br><br> The emergency data management pilot focuses in the Philippines, in the areas affected by the typhoons Haiyan in November 2013 and Hagupit in December 2014. Data collected by emergency workers and citizens are combined with satellite data (Landsat-8, VHR if available) to intensify the disaster recovery activities and the coordination efforts. Simple processes for citizens, nongovernmental organisations and volunteers are developed to find and utilize up to date and freely available satellite imagery for coordination purposes and for building new not-for-profit services in disaster situations. <br><br> In the water quality monitoring pilot, citizens around the Baltic Sea area contribute to the algae situation awareness by collecting algae observations using a mobile application. In-situ observations are compared with surface algal bloom products based on the satellite imagery, e.g. Aqua MODIS images with 500 meter resolution. As an outcome, the usability of the citizen observations together with satellite data in the algae monitoring will be evaluated.

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