Geospatial Technologies to Improve Urban Energy Efficiency

Abstract

Abstract:The HEAT (Home Energy Assessment Technologies) pilot project is a FREE Geoweb mapping service, designed to empower the urban energy efficiency movement by allowing residents to visualize the amount and location of waste heat leaving their homes and communities as easily as clicking on their house in Google Maps. HEAT incorporates Geospatial solutions for residential waste heat monitoring using Geographic Object-Based Image Analysis (GEOBIA) and Canadian built Thermal Airborne Broadband Imager technology (TABI-320) to provide users with timely, in-depth, easy to use, location-specific waste-heat information; as well as opportunities to save their money and reduce their green-house-gas emissions. We first report on the HEAT Phase I pilot project which evaluates 368 residences in the Brentwood community of Calgary, Alberta, Canada, and describe the development and implementation of interactive waste heat maps, energy use models, a Hot Spot tool able to view the 6+ hottest locations on each home and a new HEAT Score for inter-city waste heat comparisons. We then describe current challenges, lessons learned and new solutions as we begin Phase II and scale from 368 to 300,000+ OPEN ACCESSRemote Sens. 2011, 3 1381 homes with the newly developed TABI-1800. Specifically, we introduce a new object-based mosaicing strategy, an adaptation of Emissivity Modulation to correct for emissivity differences, a new Thermal Urban Road Normalization (TURN) technique to correct for scene-wide microclimatic variation. We also describe a new Carbon Score and opportunities to update city cadastral errors with automatically defined thermal house objects.

Collective Sensing: Integrating Geospatial Technologies to Understand Urban Systems—An Overview

“…Similarly, we will soon face mass market applications based on sensing applications for non-expert users. As components of Al Gore's Digital Earth become not only available but also used daily by hundreds of millions of people worldwide, we envision rapid advancements in sensor and application development, see example [102].…”

“…Biophysical attributes from remotely sensed optical data also provide great potential to parameterize urban construction materials and the composition and structure of urban canopies, and for linking with pixel-based LST measurements to better understand and model the surface energy budget and the UHI phenomenon. Hay et al [101,102] report on the HEAT (Home Energy Assessment Technologies) project, which uses high-resolution Thermal Airborne Broadband Imager data (TABI 320: 1.0 m spatial resolution, 0.1 °C temperature resolution) and geospatial analysis for individual home (community and city) wasteheat monitoring. They also provide related energy models, and greenhouse gas estimates delivered in a free-to-use Geoweb service, as easily as clicking on your house in Google Maps (see Figure 5).…”

Integration of Aerial Thermal Imagery, LiDAR Data and Ground Surveys for Surface Temperature Mapping in Urban Environments

“…In particular, remotely-sensed imagery in the thermal infrared is able to provide a synoptic and time-synchronized view of the investigated landscape, allowing the generation of coherent maps of surface temperature [4,5]. Airborne sensors are also able to acquire data at high geometrical resolution over very large areas, so they can be applied for the evaluation of the energetic performance of buildings at an urban scale [6][7][8].…”

Supporting Urban Energy Efficiency with Volunteered Roof Information and the Google Maps API

“…[T kin = T rad /ε 1/4 ] (2) By default, the HEAT project assumes that asphalt composes 100% of the roof material in the study area, which is assigned an emissivity value of 0.91 [8]. However, based on more recent real-estate information, this number is actually closer to ~80% of the roofs in Calgary.…”

“…In practice, emissivity values range from 0.00 (e.g., shiny mirror) to 1.00 (e.g., blackbody), where the material absorbs all of the incoming incident TIR radiation [15]. For the HEAT project, the emissivity of roof materials is required to convert relative radiant temperature (T rad ) as seen by the airborne TIR sensor into absolute kinetic temperature (T kin ), which represents the true temperature of a roof object [8,15]. This information is then used to accurately generate HEAT Scores [13], Hot Spots, and estimated Savings information.…”