|TITLE||Practical Baseline of Oceanography|
|LEVEL||05 - Postgraduate Modular Diploma or Degree Course|
|DESCRIPTION||Students will be introduced to various software packages that are typically used for oceanographic and scientific data processing and analysis. These include Matlab and ArcGIS which are commercial packages, and freeware packages such as OceanDataView (ODV), SAGA Panoply, R and Google Earth/Maps. This study-unit will deal with the basic usage of these software packages in dedicated practical sessions, and their further usage will be done in other SUs. In the particular case of spatial data, SAGA will be introduced as a tool to put in practice the concepts of marine GIS and spatial planning that are presented and further elaborated through more elaborated applications in SU3.
Students will be introduced to the concepts underlying the ecosystem-based management of the coastal and marine domains defining the seaward extent of the coast and its biological and socio-economic importance and, the concept of integrated and adaptive management (ICZM). They will also be provided with an overview of the regional (Mediterranean), European and International efforts at (i) assessing and monitoring marine ecosystem health, and (ii) sustaining fisheries resources. The intention is to stress the link between science and management, and on how policy undertakings and decision making can be supported by science.
A focus will be placed on the observational technologies and methodologies available for (i) the operational monitoring of the ecosystem health of the ocean and coastal seas following recommended measurements of biochemical parameters for water quality and addressing international directives and protocols, and (ii) fish stock assessments. The study-unit will highlight the specific ways in which sampling and monitoring methodologies are tailored in different sectors of marine resource mapping, management and harvesting/exploitation control.
The aim of this study-unit is to provide students with the necessary practical skills that will allow them to visualize, process and analyse scientific data using professional software packages. Students will be introduced to different types and formats of met-ocean data and will be trained in hands-on sessions to use such data to identify, understand, and quantify marine ecosystem processes and forcings, identify their temporal and spatial evolutions, and extract knowledge for assessments and management. The students will be also engaged in learning how to draw conclusions and prove theories on the basis of scientific data. These practical skills constitute a basic element of the course and will prove useful for the other study-units and are essential to the final project.
1. Knowledge & Understanding:
By the end of the study-unit the student will be able to:
- Identify different types and formats of available scientific data;
- Demonstrate an understanding of the basics of data processing and extraction of knowledge from data;
- Demonstrate an understanding of the basics of coastal resource management: mainly ICZM utilising an ecosystem-based approach;
- Use timely delivery of routine, reliable, quality-assured marine data assists in meeting expected standards of environmental monitoring, assessments and management in support of sustainable development;
- Comprehend how relevant data may be acquired to fit the needs of users such as in fisheries resource assessment and management, water quality monitoring and the general state of health of the sea;
- Evaluate importance of data to prove theoretical concepts and/or draw scientific conclusions.
By the end of the study-unit the student will be able to:
- Apply the scientific method in the design of studies and assessments, in establishing feasible sampling and surveying protocols, in the sound interpretation of data, and in deriving meaningful conclusions;
- Integrate several data sources (models, in-situ instruments and remote sensing); different types of data (time series, gridded data, etc.); data formats (ascii vs binary formats);
- Convert between different data types;
- Practice data processing and analysis through the use of various software packages such as MATLAB, R, ODV, ArcGIS, SAGA, Panoply, Google Earth and Google Maps;
- Recall and use available scientific resources – using climatologies, catalogues and databases;
- Adopt data processing methodologies to prove scientific theories and/or draw conclusions on the basis of a dataset;
- Process and analyse scientific data using software typically used in oceanographic (and other types of scientific) research;
- Comprehend the data needs of environmental managers to perform coastal zone management using an ecosystem-based approach.
Main Text/s and any supplementary readings
Main Recommended Books:
• Amos Gilat (2008). MATLAB: An Introduction with Applications. 3Rd edition. WileyRichard T. Watson (2005). Data Management: Databases & Organizations. 5Th edition. Wiley.
• McLeod, K. & Leslie, H. (2009). Ecosystem-Based Management for the Oceans. Island Press: 368pp. ISBN: 978-1597261555
• J. Burczynski (Author), M. Ben-Yami (Author), S. Maureri (Author): 1985. Finding Fish With Echo-Sounders (Fao Training Series 7/F2829) [Paperback]: (FAO – Rome): 97pp.
Additional reference books and online resources:
• Luis Torgo (2010). Data Mining with R: Learning with Case Studies. Chapman and Hall.
• Robert Nisbet, John Elder IV, Gary Miner (2009). Handbook of Statistical Analysis and Data Mining Applications. Elsevier.
• Wendy L. Martinez, Angel R. Martinez (2007). Computational Statistics Handbook with MATLAB. Chapman and Hal
• James B. Campbell PhD, Randolph H. Wynne (2011). Introduction to Remote Sensing. 5Th edition. Guildford press.
• Levner, E., Linkov, I., Proth, J.M. (2005) Strategic management of marine ecosystems. Proceedings of the NATO Advanced Study Institute on Strategic Management of Marine Ecosystems, Nice, France, 1-11 October, 2003. Springer Verlag Gmbh. ISBN: 978-9048102051
• John G. Field (Editor), Gotthilf Hempel, Colin P. Summerhayes (Editors). 2002. Oceans 2020: Science, Trends, and the Challenge of Sustainability. Island Press, Washington D.C.: 365pp.
|ADDITIONAL NOTES||Pre-Requisite qualifications: Preferably a first degree which includes any two in combination of the following subjects: mathematics, physics (including computational physics), IT, and statistics as well as to applicants with an engineering degree. Students with a degree in just one of these subjects, in conjunction with biology, chemistry and geography will also be considered if the maximum course uptake numbers are not reached. Mature students and professionals with experience and already engaged on related jobs will be eligible for admission.|
|STUDY-UNIT TYPE||Lecture and Tutorial|
|METHOD OF ASSESSMENT||
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the study-unit description above applies to the academic year 2018/9, if study-unit is available during this academic year, and may be subject to change in subsequent years.