Print Email Facebook Twitter Rapid assessment tool to quantify the spatial influence of surfaces on heat stress Title Rapid assessment tool to quantify the spatial influence of surfaces on heat stress: Estimating the Physical Equivalent Temperature in urban regions using dependence modelling Author Koot, Paul (TU Delft Civil Engineering and Geosciences; TU Delft Hydraulic Engineering; Nelen & Schuurmans) Contributor Morales Napoles, O. (mentor) Torres Alves, G.A. (graduation committee) Alvarez Antolinez, J.A. (graduation committee) Aparicio Medrano, E (graduation committee) Lokhorst, I. (graduation committee) Degree granting institution Delft University of Technology Programme Civil Engineering | Hydraulic Engineering Date 2021-07-02 Abstract Climate change causes cities to deal with increased temperatures and more frequent weather extremes. Heat waves will occur more often, becoming a more prevalent issue in especially urban areas. The quantification of heat stress is a first step to define mitigation measures. For that purpose, a standardised method to assess the spatial influence of surfaces on the Physiological Equivalent Temperature (PET) was developed. This study aims to reshape this model into a statistical dependence model which is more flexible regarding missing data. To this end, we used a Non-Parametric Bayesian Network (NBPN). We created a model driven by both data and expert knowledge, that is capable of dealing with input data layers with a grid resolution up to 20 m. Results show that training the model with only 20 sample points did not affect the performance considerably, compared to using 2,000 data points. Inclusion of a layer with sky view factor mainly improves the estimation of observations in the tails of the distribution. The model predicts the PET with a Mean Absolute Error (MAE) of 1 to 2 ºC, dealing adequately with missing data layers. With this limited amount of necessary input, the NPBN in our study helps in standardising the assessment of heat stress outside the borders of the Netherlands. Also, our model offers a framework to make a first assessment regarding the effect of NBSs on heat stress. Subject Dependence modellingnon-parametric Bayesian NetworksStatistical AnalysisHeat stressPhysiological Equivalent Temperature (PET)NPBN To reference this document use: http://resolver.tudelft.nl/uuid:6f0c047d-eecd-41b0-9f8b-c55f712b5777 Part of collection Student theses Document type master thesis Rights © 2021 Paul Koot Files PDF Thesis_Civil_Engineering_ ... 210727.pdf 4.05 MB Close viewer /islandora/object/uuid:6f0c047d-eecd-41b0-9f8b-c55f712b5777/datastream/OBJ/view