Literature DB >> 25956441

Integrated environmental mapping and monitoring, a methodological approach to optimise knowledge gathering and sampling strategy.

Ingunn Nilssen1, Øyvind Ødegård2, Asgeir J Sørensen3, Geir Johnsen4, Mark A Moline5, Jørgen Berge6.   

Abstract

New technology has led to new opportunities for a holistic environmental monitoring approach adjusted to purpose and object of interest. The proposed integrated environmental mapping and monitoring (IEMM) concept, presented in this paper, describes the different steps in such a system from mission of survey to selection of parameters, sensors, sensor platforms, data collection, data storage, analysis and to data interpretation for reliable decision making. The system is generic; it can be used by authorities, industry and academia and is useful for planning- and operational phases. In the planning process the systematic approach is also ideal to identify areas with gap of knowledge. The critical stages of the concept is discussed and exemplified by two case studies, one environmental mapping and one monitoring case. As an operational system, the IEMM concept can contribute to an optimised integrated environmental mapping and monitoring for knowledge generation as basis for decision making.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Keywords:  Adaptive sampling; Decision making; Integrated environmental mapping and monitoring; Multidisciplinary approach; Sensor platform

Mesh:

Year:  2015        PMID: 25956441     DOI: 10.1016/j.marpolbul.2015.04.045

Source DB:  PubMed          Journal:  Mar Pollut Bull        ISSN: 0025-326X            Impact factor:   5.553


  4 in total

1.  Use of an Autonomous Surface Vehicle reveals small-scale diel vertical migrations of zooplankton and susceptibility to light pollution under low solar irradiance.

Authors:  Martin Ludvigsen; Jørgen Berge; Maxime Geoffroy; Jonathan H Cohen; Pedro R De La Torre; Stein M Nornes; Hanumant Singh; Asgeir J Sørensen; Malin Daase; Geir Johnsen
Journal:  Sci Adv       Date:  2018-01-10       Impact factor: 14.136

2.  Automated multivariate analysis of multi-sensor data submitted online: Real-time environmental monitoring.

Authors:  Ingvar Eide; Frank Westad
Journal:  PLoS One       Date:  2018-01-12       Impact factor: 3.240

3.  Automatic real-time uncertainty estimation for online measurements: a case study on water turbidity.

Authors:  Joonas Kahiluoto; Jukka Hirvonen; Teemu Näykki
Journal:  Environ Monit Assess       Date:  2019-04-02       Impact factor: 2.513

4.  Computational Visual Stress Level Analysis of Calcareous Algae Exposed to Sedimentation.

Authors:  Jonas Osterloff; Ingunn Nilssen; Ingvar Eide; Marcia Abreu de Oliveira Figueiredo; Frederico Tapajós de Souza Tâmega; Tim W Nattkemper
Journal:  PLoS One       Date:  2016-06-10       Impact factor: 3.240

  4 in total

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