Supporting Urban Energy Efficiency with Volunteered Roof Information and the Google Maps API
| Autor: | Rustam Kamberov, Bilal Abdulkarim, Geoffrey J. Hay |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Volunteered geographic information
Computer science Science media_common.quotation_subject computer.software_genre Public domain urban energy efficiency Geoweb thermal imaging Quality (business) Roof Remote sensing media_common geo-information HEAT Score GEOBIA Database VGI waste heat Workflow Google Maps API emissivity General Earth and Planetary Sciences computer Efficient energy use |
| Zdroj: | Remote Sensing Volume 6 Issue 10 Pages 9691-9711 Remote Sensing, Vol 6, Iss 10, Pp 9691-9711 (2014) |
| ISSN: | 2072-4292 |
| DOI: | 10.3390/rs6109691 |
| Popis: | The Heat Energy Assessment Technologies (HEAT) project uses high-resolution airborne thermal imagery, Geographic Object-Based Image Analysis (GEOBIA), and a Geoweb environment to allow the residents of Calgary, Alberta, Canada to visualize the amount and location of waste heat leaving their houses, communities, and the city. To ensure the accuracy of these measures, the correct emissivity of roof materials needs to be known. However, roof material information is not readily available in the Canadian public domain. To overcome this challenge, a unique Volunteered Geographic Information (VGI) application was developed using Google Street View that engages citizens to classify the roof materials of single dwelling residences in a simple and intuitive manner. Since data credibility, quality, and accuracy are major concerns when using VGI, a private Multiple Listing Services (MLS) dataset was used for cross-verification. From May–November 2013, 1244 volunteers from 85 cities and 14 countries classified 1815 roofs in the study area. Results show (I) a 72% match between the VGI and MLS data and (II) in the majority of cases, roofs with greater than, or equal to five contributions have the same material defined in both datasets. Additionally, this research meets new challenges to the GEOBIA community to incorporate existing GIS vector data within an object-based workflow and engages the public to provide volunteered information for urban objects from which new geo-intelligence is created in support of urban energy efficiency. |
| Databáze: | OpenAIRE |
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