3-D Reconstruction of an Urban Landscape to Assess the Influence of Vegetation in the Radiative Budget

Abstract

Increased urbanization and climate change have resulted in the intensification of the urban heat island (UHI) effect, particularly in tropical cities. One of the main causes of UHI is the man-made urban surfaces influencing the radiation budget by absorbing, reflecting, and emitting radiation at various wavelengths. The radiative budget of a city is directly influenced by the urban geometry, surface materials, direct solar radiation and incident angle, and atmospheric diffuse radiation. Vegetation cover, in contrast, can decrease UHI by intercepting radiation and through the process of photosynthesis. Better understanding the effect of urban vegetation on the radiative budget can thus contribute towards the mitigation of the UHI effect and ultimately the development of climate resilient urban spaces. To analyze the contribution of vegetation to the radiative budget of a city, a detailed simulation of the complex interaction between the built environment and the vegetation is required. This study proposes an approach for analyzing the 3-D structure of both vegetation and built environment to quantify the contribution of vegetation to the radiative budget of an urban landscape. In a first step, a detailed 3-D model of Singapore including buildings and vegetation was reconstructed using a combination of free and commercial Earth Observation data. Then, the 3-D Discrete Anisotropic Radiative Transfer (DART) model was repurposed to estimate the radiation absorbed by the urban surfaces accounting for the presence of vegetation cover with changing Leaf Area Density (LAD) conditions. The presence of trees in the scene accounted for a significant reduction of the absorbed radiation by buildings and ground. For example, in the case of a residential low-building neighborhood, although having low tree cover, the reduction of the absorbed radiation by buildings and ground was up to 15.5% for a LAD =1. The field validation shows good agreement (R2 = 0.9633, RMSE = 10.8830 and Bias = −1.3826) between the DART-simulated shortwave exitance and upwelling shortwave measurements obtained from a net radiometer mounted on a local flux tower in the urban area of Singapore, over the studied period. Our approach can be used for neighborhood-scale analysis, at any desired location of a city, to allow test scenarios with varying surface materials and vegetation properties.

Introduction of Clouds in Dart Model

“…The inversion procedure proposed in this work can be potentially used for a wide range of experiment applications if only broadband BOA irradiance is available. Indeed, direct and diffuse BOA irradiance in narrow bands are commonly required for many urban and vegetation studies (Dissegna et al 2019). This is typically the case for studying the sun induced chlorophyll fluorescence (Gastellu-Etchegorry et al 2017).…”

Nature-Based Solutions for Urban Sustainability: An Ecosystem Services Assessment of Plans for Singapore’s First “Forest Town”

“…Singapore include maps of ecosystem cover (Gaw et al, 2019), topography (Dissegna et al, 2019), vegetation height (Dissegna et al, 2019), leaf area index (LAI) (Richards and Wang, 2020), building locations and heights (Dissegna et al, 2019), the locations of publicly accessible nature spaces (Richards et al, 2020a), and the road network (OpenStreetMap, 2020).…”

“…gov.sg archive (Singstat, 2016). Building data were taken from a dataset originally sourced from OpenStreetMap (OpenStreetMap, 2020), but with additional digitization to include all buildings in Singapore in approximately 2017 (Dissegna et al, 2019). This dataset also included the height of all buildings, by cross-referencing with a high resolution digital surface model (Dissegna et al, 2019).…”

“…Building data were taken from a dataset originally sourced from OpenStreetMap (OpenStreetMap, 2020), but with additional digitization to include all buildings in Singapore in approximately 2017 (Dissegna et al, 2019). This dataset also included the height of all buildings, by cross-referencing with a high resolution digital surface model (Dissegna et al, 2019). To identify the likely residential buildings in Singapore, we first cross-referenced the buildings dataset to include only those buildings that were located within "residential," "residential with commercial at first storey," and "residential/institution" land use classes as defined on the 2008 Singapore Master Plan.…”

Comment on “High‐Resolution, Multilayer Modeling of Singapore's Urban Climate Incorporating Local Climate Zones” by Mughal et al. (2019)

“…Vegetation covers 56% of the total land area (Yee et al, 2011). The evapotranspiration's cooling effect and shade provided by trees have been widely investigated in Singapore, even by some coauthors of Mughal et al (2019), who have concluded that trees cannot be ignored to assess the local climate (Dissegna et al, 2019; Liu et al, 2017). However, in this study, Mughal et al did not consider the presence of trees.…”