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To understand how daylight gives shape and life to architectural spaces, whether existing or imagined, requires quantifying its dynamism and energy. Maintaining these details presents a challenge to simulation and analysis methods that flatten data into discrete images or virtual sensor points from a point and time. To address this challenge, this thesis presents a new method for sampling and evaluating simulated daylight. It is intended as a bridge between image-based and sensor-based methods; one that can produce image-level high accuracy directional distribution data with much shorter simulation times that are closer to sensor-based methods.Instead of producing a fixed grid of points, pixels, and sun directions, an iteratively guided sampling approach structured by the discrete wavelet transformation captures the distribution of light incident on a viewpoint with a variable density. By storing the direction vector and effective solid-angle of each sampled ray, the data can be directly evaluated for any luminance-based quantity and view direction. Coupled with daylight coefficients, where the contributions from regions of the sky-dome are recorded rather than associating a value to every possible sky distribution, these methods reduce simulation time at three stages by reducing the number of samples. With fewer samples, it takes less time to render, less time to combine with sky values, and less time to evaluate potential glare sources.Through a series of simulated reference validations, this thesis shows that the proposed method can reproduce the value predicted by a high quality reference simulation in a small fraction of the time. The method achieves higher accuracy results compared to those of existing simulation methods that rely on simplifications. The method is robust across a wide range of daylight conditions and can be tuned to the desired scope of the output. The method can be applied to render a single image in high detail or used to calculate glare metrics in order to evaluate a whole building zone.This method enables a more complete characterization of daylight and visual comfort across an occupied zone; one that is less biased by proxy measurements, representative point selection, or assumptions about glare-causing pathways. Using these methods, we can more reliably understand how daylight will respond to proposed interventions, which should be useful for guiding design, regulatory standards, and improving performance.