Wind resource mapping using landscape roughness and spatial interpolation methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders.

Allocentric spatial performance higher in early-blind and sighted adults than in retinopathy-of-prematurity adults

The question as to whether people totally blind since infancy process allocentric or ‘external’ spatial information like the sighted has caused considerable debate within the literature. Due to the extreme rarity of the population, researchers have often included individuals with Retinopathy of Prematurity (RoP – over oxygenation at birth) within the sample. However, RoP is inextricably confounded with prematurity per se. Prematurity, without visual disability, has been associated with spatial processing difficulties. In this experiment, blindfolded sighted and two groups of functionally totally blind participants heard text descriptions from a survey (allocentric) or route (egocentric) perspective. One blind group lost their sight due to retinopathy of prematurity (RoP – over oxygenation at birth) and a second group before 24 months of age. The accuracy of participants’ mental representations derived from the text descriptions were assessed via questions and maps. The RoP participants had lower scores than the sighted and early blind, who performed similarly. In other words, it was not visual impairment alone that resulted in impaired allocentric spatial performance in this task, but visual impairment together with RoP. This finding may help explain the contradictions within the existing literature on the role of vision in allocentric spatial processing.

Wind Resource Mapping Using Landscape Roughness and Spatial Interpolation Methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders (Belgium).