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Wednesday, July 5 • 1:30pm - 1:48pm
**shadow**: R Package for Geometric Shade Calculations in an Urban Environment

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Keywords: shadow, sun position, geometry, solar radiation, building facades
Webpage: https://CRAN.R-project.org/package=shadow
Spatial analysis of the urban environment frequently requires estimating whether a given point is shaded or not, given a representation of spatial obstacles (e.g. buildings) and a time-stamp with its associated solar position. For example, we may be interested in -
  • Calculating the amount of time a given roof or facade is shaded, to determine the utility of installing Photo-Voltaic cells for electricity production.
  • Calculating shade footprint on vegetated areas, to determine the expected microclimatic influence of a new tall building.
These types of calculations are usually applied in either vector-based 3D (e.g. ESRI’s ArcScene) or raster-based 2.5D (i.e. Digital Elevation Model, DEM) settings. However, the former solutions are mostly restricted to proprietary software associated with specific 3D geometric model formats. The latter DEM-based solutions are more common, in both open-source (e.g. GRASS GIS) as well as proprietary (e.g. ArcGIS) software. The insol R package provides such capabilities in R. Though conceptually and technically simpler to work with, DEM-based approaches are less suitable for an urban environment, as opposed to natural terrain, for two reasons -
  • A continuous elevation surface at sufficiently high resolution for the urban context (e.g. LIDAR) may not be available and is expensive to produce.
  • DEMs cannot adequately represent individual vertical urban elements (e.g. building facades), thus limiting the interpretability of results.
The shadow package aims at addressing these limitations. Functions in this package operate on a vector layer of building outlines along with their heights (class SpatialPolygonsDataFrame from package sp), rather than a DEM. Such data are widely available, either from local municipalities or from global datasets such as OpenStreetMap. Currently functions to calculate shadow height, Sky View Factor (SVF) and shade footprint on ground are implemented. Since the inputs are vector-based, the resulting shadow estimates are easily associated with specific urban elements such as buildings, roofs or facades.
We present a case study where package shadow was used to calculate shading on roofs and facades in a large neighborhood (Rishon-Le-Zion city, Israel), on an hourly temporal resolution and a 1-m spatial resolution. The results were combined with Typical Meteorological Year (TMY) direct solar radiation data to derive total annual insolation for each 1-m grid cell. Subsequently the locations where installation of photovoltaic (PV) cells is worthwhile, given a predefined threshold production, were mapped.
The approach is currently applicable to a flat terrain and does not treat obstacles (e.g. trees) other than the buildings. Our case study demonstrates that subject to these limitations package shadow can be used to calculate shade and insolation estimates in an urban environment using widely available polygonal building data. Future development of the package will be aimed at combining vector-associated shadow calculations with raster data representing non-flat terrain.


Wednesday July 5, 2017 1:30pm - 1:48pm
3.01 Wild Gallery