Estimering av blågrønn faktor i eksisterende bymiljø ved bruk av hyperspektrale data og laserdata

The amount of precipitation in Norway has increased by about 20 percent since the 1900s. Large amounts of precipitation in a short period of time creates some of the biggest problems like stormwater and urban flooding. Increased urbanization leads to an increased need to build denser in urban areas. Densification in urban areas lead to more stormwater, loss of vegetation and biodiversity. As a measure for the increasing amount of precipitation and the densely populated area, > (BGF-Oslo) was made by plan and the building agency. The BGF guide is intended for the planning phase of before the building phase. The guide is used to calculate different BGF-value for different types of planned blue and green measures. Value for the various blue and green measures is emphasized based on which measures provide better handling of stormwater, biodiversity and good urban life. Although the BGF guide is intended as a guide in the planning phase, there is also a need to look at BGF in connection with the existing urban environment. This thesis will look at the possibilities of estimating BGF in the existing urban environment in a semi-automatic method, with BGF-Oslo. The project area chosen was Fredrikstad, Cicignon. To determine the various BGF subfactors, both hyperspectral data and laser data sets are used. The hyperspectral data sets consist of radians values. The datasets were used to distinguish different materials, in this thesis was; gravel, asphalt and vegetation. The laser data was used to look at spatial variations in the terrain. The laser data is used in this thesis to find; terrain depressions and watersheds from dense surfaces. Hyperspectral data and laser data are also used in combination to find bushes and grass. Because radians data sets are used in the thesis without shadow correction leads to challenges in the classification of; gravel, asphalt and vegetation. To automate the method, it is important to look at algorithms for shadow correction. Although shadows turned out to be a challenge, the results of this thesis show great potential for automating the method of determining BGF in existing urban environments. In the thesis BGF-Oslo is used which is intended to calculate BGF-values. This turned out not to be a challenge as both Fredrikstad and Oslo carry the typical urban environments. Although the thesis is based on BGF-Oslo which is used in the planning phase of building, it turned out tha