The Remote Sensing of Urban Energy Efficiency

城市能源效率遥感

• 批准号: RGPIN-2019-07185
• 负责人: Hay, Geoffrey
• 金额: $ 2.26万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=684107
• 关键词: Remote; Sensing; Urban; Energy; Efficiency

THE REMOTE SENSING OF URBAN ENERGY EFFICIENCY******The world wastes more energy than it uses every year. It is estimated that the existing building stock consumes approximately 40% of the world's energy, of which 50% is wasted, while contributing to one third of planetary greenhouse gases (GHGs). Although energy-efficiency programs exist world-wide, most only measure energy consumption - not waste energy. This is because waste-energy is invisible to the human eye, and it's very difficult to measure, monitor, or manage something that we can't see. Yet, waste-energy is responsible for an estimated 50% of urban energy demand, but is missing from urban energy efficiency equations.******In order to solve this challenge, the long-term goal of my research program is to evaluate whether high-resolution airborne thermal infrared (TIR) imagery acquired by the Canadian made TABI-1800 (Thermal Airborne Broadband Imager) can be used to quantify, map and monitor urban energy efficiency over time, at the resolution of individual houses, and the scale of a large Canadian city with over 1 million residents. ******We propose that this challenge can be met by achieving 3 short term goals: (i) To understand the effects that environmental and sensor related noise have on the raw thermal image and to develop and test methods to normalize their effects. (ii) To evaluate a combination of Geographic Object-Based Image Analysis and machine learning methods over very large and detailed thermal scenes, to better isolate the emitted TIR building signal from the background scene, resulting in improved heat-loss maps and measures specific to the building, rather than a mix of landscape features. (iii) To evolve the state-of-the-art in urban thermal infrared remote sensing by combining these improved heat-loss measures with building consumption data and machine learning to develop the first measures of urban energy efficiency directly from airborne TIR data for entire urban centres.******By making energy efficiency visible for entire cities at the resolution of a single house, we envision the potential for residents and communities to save money, increase home comfort, reduce GHGs, support the development of a green economy (to fix inefficient homes), verify building construction quality and reduce the waste of expensive energy resources. This will also create new opportunities to promote Canadian leadership in urban energy efficiency and export Canadian TIR science and technology solutions world-wide.*****

城市能源效率的遥感 ** 世界每年浪费的能源比使用的还要多。据估计，现有的建筑物消耗了大约40%的世界能源，其中50%被浪费，同时贡献了三分之一的全球温室气体（GHG）。虽然世界各地都有节能项目，但大多数项目只衡量能源消耗，而不衡量浪费能源。这是因为废能是肉眼看不见的，我们很难测量、监控或管理我们看不到的东西。然而，废物能源估计占城市能源需求的50%，但却没有出现在城市能源效率方程中。为了解决这一挑战，我的研究计划的长期目标是评估加拿大制造的TABI-1800（热机载宽带成像仪）获得的高分辨率机载热红外（TIR）图像是否可用于量化，绘制和监测城市能源效率随时间的变化，在单个房屋的分辨率下，以及拥有超过100万居民的加拿大大城市的规模。** 我们建议通过实现3个短期目标来应对这一挑战：（i）了解环境和传感器相关噪声对原始热图像的影响，并开发和测试方法来规范其影响。(ii)在非常大和详细的热场景中评估基于地理对象的图像分析和机器学习方法的组合，以更好地将发出的TIR建筑信号与背景场景隔离开来，从而改进建筑物的热损失地图和测量，而不是混合景观特征。(iii)通过将这些改进的热损失措施与建筑物消耗数据和机器学习相结合，发展城市热红外遥感的最新技术，以直接从整个城市中心的机载TIR数据开发城市能源效率的第一个措施。通过让整个城市的能源效率在一栋房屋的分辨率上可见，我们设想居民和社区可以节省资金，提高家居舒适度，减少温室气体排放，支持绿色经济的发展（以修复低效房屋），验证建筑施工质量并减少昂贵能源资源的浪费。这也将为促进加拿大在城市能源效率方面的领导地位和向全球出口加拿大TIR科学和技术解决方案创造新的机会。