Special attention has been paid to sustainable macroalgae cultivation in Europe. The question on where suitable cultivation areas lie, without conflicting with current marine socio-economic activities and respecting the environment, remains a great challenge. Considering 13 criteria critical to seaweed farming such as depth, shipping traffic, and distance to ports, this paper aimed to identify suitable and sustainable offshore areas on the West Coast of Sweden for the cultivation of the Sugar Kelp, Saccharina latissima. An integrated approach with the tools geographic information systems (GIS) and multi-criteria analysis (MCA) was used to aggregate the criteria by means of Boolean and weighted linear combination (WLC) techniques. The Boolean method singled out 544?km2 as suitable, whereas the WLC method indicated 475?km2 as highly suitable. Both techniques complement each other in finding optimal sites. Furthermore, the integrated models excelled in providing an overview for effective spatial decision-making that fosters sustainable development of macroalgae cultivations within marine and coastal systems.
Highlights
To the authors’ knowledge no study on seaweed aquaculture site selection has been conducted using such a range of criteria with the purpose of including sustainability aspects within a comparative GIS-MCDA.
The large areas identified on the West Coast of Sweden as suitable highlight the potential of this new industry and the complexity of associated marine spatial planning.
Boolean and weighted linear combination methods were applied and compared, providing valuable insights in the selection of methods for spatial decision-making support. These insights should support a more sustainable development of macroalgae cultivation in the region, as well as a more resilient marine spatial planning process for blue growth strategies.
Most of the information necessary for driving a vehicle is regarded as visual information. In spite of its importance, visibility conditions at the time of a crash are often not documented at a high level of detail. Past studies have not examined the quantified values of visibility and its association with crashes. The current study merged data collected from the National Oceanic and Atmospheric Administration (NOAA) with 2010–2012 Florida crash data. From the thousands of logged weather events compiled by the NOAA, the researchers isolated periods of normal visibility and comparable periods of reduced visibility in a matched-pairs study. The NOAA data provided real visibility score based on the spatiotemporal data of the crashes. Additionally, the crash data, obtained from Roadway Information Database (RID), contains several geometric and traffic variables that allow for effects of factors and visibility. The study aims to associate crash occurrence under different levels of visibility with factors included in the crash database by developing ordinal logistic regression. The intent is to observe how different visibility conditions contribute to a crash occurrence. The findings indicate that the likelihood of a crash increase during periods of low visibility, despite the tendency for less traffic and for lower speeds to prevail during these times. The findings of this study will add valuable knowledge to the realm of the impact of visibility in the way of using and designing appropriate countermeasures. 相似文献