Instruments measuring the outdoor radiant environment are limited spatially. They aggregate observations to singular points, eliminating variations from surrounding surface temperatures. Computational methods can characterize the heterogeneous outdoor radiant environment, but spatial validation with accurate tools remains difficult. We use two novel sensing platforms (MaRTy and SMaRT) and an innovative computational validation method to explore Mean Radiant Temperature (MRT) spatial variation outdoors. MaRTy is a mobile instrument that evaluates MRT with directional weighting for hemispherical radiation flux density observations. The SMaRT sensor uses a non-contacting infrared surface temperature sensor and LIDAR to map surrounding surface temperatures. We conducted a case study combining the methodology of both instruments to improve spatial mapping of MRT for five locations on Temple University's main campus in Philadelphia, PA in July. For comparison, we collected thermal images to build a data-driven simulation model for MRT. Results demonstrate the improved resolution of combining both sensors to resolve variations in outdoor longwave radiation fluxes. The instruments show variations in surface temperatures up to 10 °C for SMaRT from longwave radiation and MRT variations of 40 °C for MaRTy, which included shortwave influences. These demonstrations of significant spatial variations were measured across an area typically evaluated at one position.
All Science Journal Classification (ASJC) codes
- Geography, Planning and Development
- Environmental Science (miscellaneous)
- Urban Studies
- Atmospheric Science