Marine Spatial Planning Using High-Resolution Synthetic Aperture Radar Measurements

In this paper, we highlight the importance of high-resolution wind data on the application of multicriteria evaluation technique to colocate offshore wind farms and open-water mussel cultivations. An index of colocation sustainability (SI), based on an environmental information, is constructed using remote sensing data and taking into account both physical constraints (i.e., water depth and wind speed) and environmental data (i.e., chlorophyll-a, sea surface temperature anomaly, and particulate organic carbon). To verify the proposed methodology, five showcases are presented, where SI is evaluated considering potential installation sites in Kattegat, Denmark, using both low-resolution (LR) wind reanalysis maps related to the Modern Era Retrospective-Analysis for Research and Application data set and fine-resolution wind maps obtained by processing synthetic aperture radar (SAR) data. Experimental results show that the availability of a reliable fine-resolution wind information is of great importance in coastal areas where the presence of the land and the isles limits the use of LR wind data.

[1]  Francisco J. Ocampo-Torres,et al.  Seasonal and interannual variability of satellite-derived chlorophyll pigment, surface height, and temperature off Baja California , 2004 .

[2]  Bertrand Chapron,et al.  Observation of Wind Direction Change on the Sea Surface Temperature Front Using High-Resolution Full Polarimetric SAR Data , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[3]  G. Benassai,et al.  Coastal risk assessment of a micro-tidal littoral plain in response to sea level rise , 2015 .

[4]  Maurizio Migliaccio,et al.  Sea wave modeling with X-band COSMO-SkyMed © SAR-derived wind field forcing and applications in coastal vulnerability assessment , 2013 .

[5]  J. Pempkowiak,et al.  DOC and POC in the southern Baltic Sea. Part II – Evaluation of factors affecting organic matter concentrations using multivariate statistical methods , 2015 .

[6]  S. Ray,et al.  Relationship between possible available food and the composition, condition, and reproductive state of oysters from Galveston Bay, Texas. , 1985 .

[7]  W. Timothy Liu,et al.  Evaluation of high-resolution ocean surface vector winds measured by QuikSCAT scatterometer in coastal regions , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Guido Benassai,et al.  A Sustainability Index of potential co-location of offshore wind farms and open water aquaculture , 2014 .

[9]  G. Becker Sea surface temperature changes in the North Sea and their causes , 1996 .

[10]  Maurizio Migliaccio,et al.  Sea wave numerical simulations with COSMO-SkyMed© SAR data , 2013 .

[11]  V. Piscopo,et al.  Ultimate and accidental limit state design for mooring systems of floating offshore wind turbines , 2014 .

[12]  Bianca Federici,et al.  A spatial multi-criteria evaluation for site selection of offshore marine fish farm in the Ligurian Sea, Italy , 2015 .

[13]  Maurizio Migliaccio,et al.  The use of COSMO-SkyMed© SAR data for coastal management , 2015 .

[14]  A. Palialexis,et al.  Critical regions: A GIS-based model of marine productivity hotspots , 2004, Aquatic Sciences.

[15]  Laurence A. Anderson,et al.  On the hydrogen and oxygen content of marine phytoplankton , 1995 .

[16]  K. Wirtz,et al.  Mythos offene See: Nutzungskonflikte im Meeresraum , 2002 .

[17]  Kerry Black,et al.  An integrated GIS approach for sustainable aquaculture management area site selection , 2008 .

[18]  Theocharis Tsoutsos,et al.  Strategies to improve sustainability and offset the initial high capital expenditure of wave energy converters (WECs) , 2017 .

[19]  J. E. Winter A review on the knowledge of suspension-feeding in lamellibranchiate bivalves, with special reference to artificial aquaculture systems , 1978 .

[20]  V. Piscopo,et al.  Optimization of Mooring Systems for Floating Offshore Wind Turbines , 2015 .

[21]  Maurizio Migliaccio,et al.  Sea Wave Numerical Simulations and Verification in Tyrrhenian Coastal Area with X-Band Cosmo-Skymed SAR Data , 2012 .

[22]  V. Piscopo,et al.  Mooring Control of Semi-submersible Structures for Wind Turbines☆ , 2014 .

[23]  Guido Benassai,et al.  A sustainability index for offshore wind farms and open water aquaculture , 2011, CP 2011.

[24]  Adam H. Monahan,et al.  The Probability Distribution of Sea Surface Wind Speeds , 2006 .

[25]  T. Michler-Cieluch,et al.  Perceived concerns and possible management strategies for governing 'wind farm-mariculture integration' , 2008 .

[26]  Maurizio Migliaccio,et al.  Wave Simulations Through Sar Cosmo-Skymed Wind Retrieval And Verification With Buoy Data , 2012 .

[27]  W. Ouellette,et al.  Remote sensing for Marine Spatial Planning and Integrated Coastal Areas Management: Achievements, challenges, opportunities and future prospects , 2016 .

[28]  William Perrie,et al.  Wind retrieval with cross-polarized SAR returns , 2011, 2011 IEEE International Geoscience and Remote Sensing Symposium.

[29]  Xiaofeng Li,et al.  SAR-derived wind fields at the coastal region in the East/Japan Sea and relation to coastal upwelling , 2014 .

[30]  J. Aguilar-Manjarrez Development and evaluation of GIS-based models for planning and management of coastal aquaculture : a case study in Sinaloa, Mexico , 1996 .

[31]  J. Carstensen,et al.  Frequency, composition, and causes of summer phytoplankton blooms in a shallow coastal ecosystem, the Kattegat , 2004 .