A sensor view model to investigate the influence of tree crowns on effective urban thermal anisotropy

A sensor view model is modified to include trees using a gap probability approach to estimate foliage view factors and an energy budget model for leaf surface temperatures (SUMVEG). The model is found to compare well with airborne thermal infrared (TIR) surface temperature measurements. SUMVEG is used to investigate the influence of trees on thermal anisotropy for narrow field-of-view TIR remote sensors over treed residential urban surfaces. Tests on regularly-spaced arrays of cubes on March 28 and June 21 at latitudes of 47.6°N and 25.8°N show that trees both decrease and increase anisotropy as a function of tree crown and building plan fractions. In compact geometries, anisotropy tends to decrease with tree crown plan fraction, with the opposite in open geometries, though trees taller than building height cause anisotropy to increase for all building plan fractions. These results help better understand and potentially correct urban thermal anisotropy

A Method for Hemispherical Ground Based Remote Sensing of Urban Surface Temperatures

This thesis presents a method for deriving time-continuous urban surface temperature and heat island assessments from hemispherical ground-based measurements of upwelling thermal radiation. The method, developed to overcome geometric and temporal biases inherent in traditional thermal remote sensing of urban surface climates, uses a sensor view model in conjunction with a radiative transfer code to derive atmospherically corrected, hemispherical radiometric urban surface temperatures. These are used to derive two long-term climatologies of surface urban heat island (sUHI) magnitudes for Basel, Switzerland and Vancouver, Canada. sUHI development shows significant variation based on time-of-day, season, and ambient and synoptic conditions. Results also show large differences in remote sensed sUHI from hemispherical, nadir and complete representations of the urban surface, with a nadir view overestimating seasonal sUHImax from a complete view by nearly a factor of two. In contrast, a hemispherical view provides significantly more representative, time-continuous urban surface temperature and sUHI analysis

Urban storage heat flux variability explored using satellite, meteorological and geodata

The storage heat flux (ΔQS) is the net flow of heat stored within a volume that may include the air, trees, buildings and ground. Given the difficulty of measurement of this important and large flux in urban areas, we explore the use of Earth Observation (EO) data. EO surface temperatures are used with ground-based meteorological forcing, urban morphology, land cover and land use information to estimate spatial variations of ΔQS in urban areas using the Element Surface Temperature Method (ESTM). First, we evaluate ESTM for four “simpler” surfaces. These have good agreement with observed values. ESTM coupled to SUEWS (an urban land surface model) is applied to three European cities (Basel, Heraklion, London), allowing EO data to enhance the exploration of the spatial variability in ΔQS. The impervious surfaces (paved and buildings) contribute most to ΔQS. Building wall area seems to explain variation of ΔQS most consistently. As the paved fraction increases up to 0.4, there is a clear increase in ΔQS. With a larger paved fraction, the fraction of buildings and wall area is lower which reduces the high values of ΔQS

Urban ground-based thermography

Urban climates are driven by micro-meteorological processes associated with the complex urban form, materials, and land cover patterns. Given its close link to the surface energy balance, surface temperature observations are key to the improvement and evaluation of models. This work contributes to the application of ground-based thermography in urban settings as an observational method to further our understanding of urban climate processes. In this thesis, ground-based thermography observations are collected and interpreted in a unique way so that they are relatable to scales used by urban climate models and earth observation (EO) satellites. At two measurement sites (simplified outdoor scale model and complex central urban setting), variations in surface temperature are quantitatively linked to micro-scale features such as shadow patterns and material characteristics at unprecedented levels of detail. Previous studies with low level of detail have inferred these properties. The detected upwelling longwave radiation is corrected to surface temperature (Ts) using a novel, high-resolution three-dimensional (3D) radiative transfer (RT) approach. From multi-day observational evaluation, the atmospheric correction has 0.39 K mean absolute error. Ground-based observations are combined with a comprehensive 3D radiative transfer model, enabling detailed simulation of EO land surface temperature (TsEO). For a mainly clear-sky summer day, TsEO at night underestimates the unbiased “complete” surface temperature (Tc) by 0.5 – 1 K, is similar to Tc during morning and evening, and for other times varies significantly with view angle (up to 5.1 K). Generally, view angle variation is smaller than prior studies as they typically use simpler geometry and temperature descriptions, and lack vegetation. Here, the observational basis and high-resolution modelling in a real central urban setting serves as a benchmark for future improvements of simplified model parameterisations

A novel method to obtain three-dimensional urban surface temperature from ground-based thermography

Urban geometry and materials combine to create complex spatial, temporal and directional patterns of longwave infrared (LWIR) radiation. Effective anisotropy (or directional variability) of thermal radiance causes remote sensing (RS) derived urban surface temperatures to vary with RS view angles. Here a new and novel method to resolve effective thermal anisotropy processes from LWIR camera observations is demonstrated at the Comprehensive Outdoor Scale MOdel (COSMO) test site. Pixel-level differences of brightness temperatures reach 18.4 K within one hour of a 24-h study period. To understand this variability, the orientation and shadowing of surfaces is explored using the Discrete Anisotropic Radiative Transfer (DART) model and Blender three-dimensional (3D) rendering software. Observed pixels and the entire canopy surface are classified in terms of surface orientation and illumination. To assess the variability of exitant longwave radiation (M_LW) from the 3D COSMO surface (M_LW^3D), the observations are prescribed based on class. The parameterisation is tested by simulating thermal images using a camera view model to determine camera perspectives of M_LW^3D fluxes. The mean brightness temperature differences per image (simulated and observed) are within 0.65 K throughout a 24-h period. Pixel-level comparisons are possible with the high spatial resolution of M_LW^3D and DART camera view simulations. At this spatial scale (< 0.10 m), shadow hysteresis, surface sky view factor and building edge effects are not completely resolved by M_LW^3D. By simulating apparent brightness temperatures from multiple view directions, effective thermal anisotropy of M_LW^3D is shown to be up to 6.18 K. The developed methods can be extended to resolve some of the identified sources of sub-facet variability in realistic urban settings. The extension of DART to the interpretation of ground-based RS is shown to be promising

AN INVESTIGATION OF REMOTELY SENSED URBAN HEAT ISLAND CLIMATOLOGY

Satellite remotely sensed temperatures are widely used for urban heat island (UHI) studies. However, the abilities of satellite surface and atmospheric data to assess the climatology of UHI face many unknowns and challenges. This research addresses the problems and potential for satellite remotely sensed UHI climatology by examining three different issues. The first issue is related to the temporal aggregation of land surface temperature (LST) and the potential biases that are induced on the surface UHI (SUHI) intensity. Composite LST data usually are preferred to avoid the missing values due to clouds for long-term UHI monitoring. The impact of temporal aggregation shows that SUHI intensities are more notably enhanced in the daytime than nighttime with an increasing trend for larger composite periods. The cause of the biases is highly related to the amount and distribution of clouds. The second issue is related to model validation and the appropriate use of LST for comparison to modeled radiometric temperatures in the urban environment. Sensor view angle, cloud distribution, and cloud contaminated pixels can confound comparisons between satellite LST and modeled surface radiometric temperature. Three practical sampling methods to minimize the confounding factors are proposed and evaluated for validating different aspects of model performance. The third issue investigated is to assess to what extent remotely sensed atmospheric profiles collected over the urban environment can be used to examine the UHI. The remotely sensed air and dew-point temperatures are compared with the ground observations, showing an ability to capture the temporal and spatial dynamics of atmospheric UHI at a fine scale. Finally, a new metric for quantifying the urban heat island is proposed. The urban heat island curve (UHIC), is developed to represent UHI intensity by integrating the urban surface heterogeneity in a curve. UHIC illustrates the relationship between the air temperature and the urban fractions, and emphasizes the temperature gradients, consequently decreasing the impact of the data biases. This research illustrates the potential for satellite data to monitor and increase our understanding of UHI climatology

Airborne Observations of Thermal Anisotropy from Urban Residential Neighbourhoods in Salt Lake City, Utah

Urban surface temperatures are important variables in urban climatological processes. This thesis examines the directional variability of remotely sensed urban surface temperatures (thermal anisotropy or Λ) for three vegetated residential neighbourhoods in Salt Lake City, Utah, USA. Airborne thermal remote sensing using a thermal imager sampled the directional brightness temperature (DBT) at three times within a day for each site. Results indicate that temporal variability over a 20 – 30-minute flight was not negligible. Average DBT were then extracted from atmospherically corrected images and plotted on polar plots. For low density residential neighbourhoods Λ is increased with increasing tree-canopy coverage (λtree) due to the increased temperature contrast. The ΛMax for the sites with large λtree were ~8°C compared to ~6°C for the site with sparse λtree. These results indicate Λ for low density residential neighbourhoods is significant and must be considered when discussing land surface temperatures for similar sites

The Effect of Sub-Facet Scale Geometry on Vertical Facet Temperatures in Urban Street Canyons

Surface temperature plays a key role in many micro-scale urban processes. Walls comprise a significant percentage of the urban surface, yet are under-represented by many methods of thermal remote sensing and not considered in detail by micro-scale surface temperature mod- els. This thesis presents a novel method of mobile thermal observation performed in urban street canyons in London, ON that uses a thermal imager as well as a visual spectrum camera to provide dense spatial and temporal resolution of micro-scale wall temperature distributions. Images are manually classified by a series of nominal variables and the resulting data set discusses the influence of micro-scale wall geometry on shading patterns and temperature distributions. Results show that micro-scale geometry both cools and heats walls, that small amounts of geo- metric complexity significantly affect temperature distributions, and that micro-scale structure may warm facets at night. Implications for temperature and wind applications are discussed

Atmospheric and emissivity corrections for ground-based thermography using 3D radiative transfer modelling

Methods to retrieve urban surface temperature (Ts) from remote sensing observations with sub-building scale resolution are developed using the Discrete Anisotropic Radiative Transfer (DART, Gastellu-Etchegorry, Grau and Lauret, 2012) model. Corrections account for the emission and absorption of radiation by air between the surface and instrument (atmospheric correction), and for the reflected longwave infrared (LWIR) radiation from non-black-body surfaces (“emissivity” correction) within a single modelling framework. The atmospheric correction a) can use horizontally and vertically variable distributions of atmosphere properties at high resolution (< 5 m); b) is applied here with vertically extrapolated weather observations and MODTRAN atmosphere profiles; and c) is a solution to ray tracing and cross section (e.g. absorption) conflicts (e.g. cross section needs the path length but it is typically unavailable during ray tracing). The emissivity correction resolves the reflection of LWIR radiation as a series of scattering events at high spatial (< 1 m) and angular (ΔΩ ≈ 0.02 sr) resolution using a heterogeneous distribution of radiation leaving the urban surfaces. The method is applied to a novel network of seven ground-based cameras measuring LWIR radiation across a dense urban area (extent: 420 m x 420 m) where a detailed 3-dimensional representation of the surface and vegetation geometry is used. Our unique observation set allows the method to be tested over a range of realistic conditions as there are variations in: path lengths, view angles, brightness temperatures, atmospheric conditions and observed surface geometry. For pixels with 250 (± 10) m path length the median (5th and 95th percentile) atmospheric correction magnitude is up to 4.5 (3.1 and 8.1) K at 10:10 on a mainly clear-sky day. The detailed surface geometry resolves camera pixel path lengths accurately, even with complex features such as sloped roofs. The atmospheric correction method evaluation, with simultaneous “near” (~15 m) and “far” (~155 m) observations, has a mean absolute error of 0.39 K. Using broadband approximations, the emissivity correction has clear diurnal variability, particularly when a cool and shaded surface (e.g. north facing) is irradiated by warmer (up to 17.0 K) surfaces (e.g. south facing). Varying the material emissivity with bulk values common for dark building materials (ε = 0.89 → 0.97) alters the corrected roof (south facing) surface temperatures by ~3 (1.5) K, and the corrected cooler north facing surfaces by less than 0.1 K. Corrected observations, assuming a homogeneous radiation distribution from surfaces (analogous to a sky view factor correction), differ from a heterogeneous distribution by up to 0.25 K. Our proposed correction provides more accurate Ts observations with improved uncertainty estimates. Potential applications include ground-truthing airborne or space-borne surface temperatures and evaluation of urban energy balance models