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

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.

[1]  Andrew S. Brierley,et al.  Diel vertical migration of Arctic zooplankton during the polar night , 2008, Biology Letters.

[2]  Mark A. Moline,et al.  Ice Detection For Under Ice AUV Navigation , 2011 .

[3]  Jörg Ontrup,et al.  Use of machine-learning algorithms for the automated detection of cold-water coral habitats: a pilot study , 2009 .

[4]  M. Moline,et al.  Improved monitoring of HABs using autonomous underwater vehicles (AUV) , 2006 .

[5]  Gregory Dudek,et al.  Unsupervised Learning of Terrain Appearance for Automated Coral Reef Exploration , 2009, 2009 Canadian Conference on Computer and Robot Vision.

[6]  P. Wiebe,et al.  Patterns and Processes in the Time-Space Scales of Plankton Distributions , 1978 .

[7]  Jacob Carstensen,et al.  Marine management--towards an integrated implementation of the European Marine Strategy Framework and the Water Framework Directives. , 2010, Marine pollution bulletin.

[8]  Daniel O.B. Jones.  Offshore Environmental monitoring for the Oil and Gas Industry , 2012 .

[9]  Dana R. Yoerger,et al.  A novel trigger-based method for hydrothermal vents prospecting using an autonomous underwater robot , 2010, Auton. Robots.

[10]  G. Johnsen,et al.  In vivo absorption characteristics in 10 classes of bloom-forming phytoplankton: taxonomic characteristics and responses to photoadaptation by means of discriminant and HPLC analysis , 1994 .

[11]  J. Berge,et al.  Arctic complexity: a case study on diel vertical migration of zooplankton , 2014, Journal of plankton research.

[12]  N A Cruz,et al.  Adaptive sampling of thermoclines with Autonomous Underwater Vehicles , 2010, OCEANS 2010 MTS/IEEE SEATTLE.

[13]  Paul R. Carlile,et al.  Transferring, Translating, and Transforming: An Integrative Framework for Managing Knowledge Across Boundaries , 2004, Organ. Sci..

[14]  L. Freitag,et al.  Under-ice operations with a REMUS-100 AUV in the Arctic , 2010, 2010 IEEE/OES Autonomous Underwater Vehicles.

[15]  K. McLeod,et al.  Confronting the challenges of implementing marine ecosystem‐based management , 2007 .

[16]  Craig M. Lee,et al.  Gliders as a Component of Future Observing Systems , 2010 .

[17]  Harald Wesenberg,et al.  Integrated Environmental Monitoring in Daily Operations , 2012 .

[18]  Robert J. Nicholls,et al.  How Do Polar Marine Ecosystems Respond to Rapid Climate Change , 2010 .

[19]  Walter Munk.  Chapter 1 Oceanography before, and after, the advent of satellites , 2000 .

[20]  J. McDonnell,et al.  Educational needs in the changing field of operational oceanography: training the people that will sustain Munk's 1+1 = 3 scenario , 2005, Proceedings of OCEANS 2005 MTS/IEEE.

[21]  Einar Landre,et al.  Decision Support and Monitoring Using Autonomous Systems , 2010 .

[22]  T. Schoening,et al.  Investigation of hidden parameters influencing the automated object detection in images from the deep seafloor of the HAUSGARTEN observatory , 2012, 2012 Oceans.

[23]  S. Johnsen,et al.  Monitoring of Impact of Drilling Discharges to a Calcareous Algae Habitat in the Peregrino Oil Field in Brazil , 2014 .

[24]  J. G. Bellingham,et al.  Using an Autonomous Underwater Vehicle to Track a Coastal Upwelling Front , 2012, IEEE Journal of Oceanic Engineering.

[25]  Asgeir J. Sørensen,et al.  Sea floor geometry approximation and altitude control of ROVs , 2014 .

[26]  Michael Elliott,et al.  Integrated marine science and management: wading through the morass. , 2014, Marine pollution bulletin.

[27]  A. C. Trembanis,et al.  Automated optimal processing of phase differencing side-scan sonar data using the Most-Probable Angle Algorithm , 2012, 2012 Oceans.

[28]  M. Moline,et al.  Remote Environmental Monitoring Units: An Autonomous Vehicle for Characterizing Coastal Environments* , 2005 .

[29]  M. Greenacre,et al.  Quantifying the light sensitivity of Calanus spp. during the polar night: potential for orchestrated migrations conducted by ambient light from the sun, moon, or aurora borealis? , 2013, Polar Biology.

[30]  Ángel Borja,et al.  Assessing the environmental quality status in estuarine and coastal systems: Comparing methodologies and indices , 2008 .

[31]  James G. Bellingham,et al.  Have robot, will travel , 2014 .

[32]  Mark A. Moline,et al.  Phytoplankton Pigments: Optical monitoring of phytoplankton bloom pigment signatures , 2011 .

[33]  Asgeir J. Sørensen,et al.  Development of dynamic positioning and tracking system for the ROV Minerva , 2012 .

[34]  Karl Johan Åström,et al.  Computer-Controlled Systems: Theory and Design , 1984 .

[35]  Ingunn Nilssen,et al.  Holistic environmental management of discharges from the oil and gas industry - Combining quantitative risk assessment and environmental monitoring , 2008 .

[36]  J. Gutt,et al.  Semi-Automated Image Analysis for the Assessment of Megafaunal Densities at the Arctic Deep-Sea Observatory HAUSGARTEN , 2012, PloS one.

[37]  Gwyn Griffiths,et al.  The Role of adaptive mission planning and control in persistent autonomous underwater vehicles presence , 2012, 2012 IEEE/OES Autonomous Underwater Vehicles (AUV).

[38]  J. Berge,et al.  Life history of Onisimus caricus (Amphipoda: Lysianassoidea) in a high Arctic fjord , 2009 .

[39]  H. Hop,et al.  Aspects of Reproduction and Larval Biology of Arctic Cod ( Boreogadus saida ) , 1995 .

[40]  J. Berge,et al.  Bioluminescence in the high Arctic during the polar night , 2011, Marine Biology.

[41]  Geir Huse,et al.  Marine ecosystem acoustics (MEA): quantifying processes in the sea at the spatio-temporal scales on which they occur , 2014 .

[42]  R. Coutinho,et al.  The effect of sediment mimicking drill cuttings on deep water rhodoliths in a flow-through system: Experimental work and modeling. , 2015, Marine pollution bulletin.

[43]  Autun Purser,et al.  Monitoring strategies for drill cutting discharge in the vicinity of cold-water coral ecosystems. , 2012, Marine pollution bulletin.