Evaluating effects of land pattern with regional characteristic curves: Land cover indicators and estimating building energy use from thermal image data.

Abstract

Sustainability is a word that represents a wide spectrum of complex and interrelated topics, but it is fundamentally a concept that describes a balanced relationship with the physical environment. There is a need for timely feedback on that relationship in order for individuals and societies to make informed decisions. Investigating the relationship between the physical form of our cities and regions and the impacts that these regions have on their supporting ecological environment requires both a method for categorizing form and a method for quantifying impact. The latter was addressed through the development of the regional characteristic curve method. This method collects, summarizes, analyzes, and displays spatial data in a graphical form that is intuitive, informative, and has advantages over existing tabular methods. Regional characteristic curves are calculated using concentric rings as the basis for evaluating impact metrics from any kind of areal data. The method was investigated in an examination of spatial change over time in the Ann Arbor region and in a comparison between Ann Arbor and Detroit. Curves for several types of metrics were used, based on land-cover and demographic data. The lack of a suitable energy use data set was highlighted, as well as great impact that energy use causes. One aspect of energy use, energy use in buildings, was singled out for further investigation. The possible link between building energy use and thermal image data collected by satellite was explored. Satellite thermal image data has been shown to be primarily related to variation in land-cover, but remaining variability in satellite data may be related to energy use in buildings. This link was investigated in both summer and winter case studies, revealing no significant relationship in summer and a weak relationship in winter. The winter relationship was also in a counterintuitive direction, in that higher building energy use was associated with cooler thermal image data. The poor spatial resolution and timing of the satellite data collection were not advantageous, so the presence of even a weak and counterintuitive result encouraged further exploration of this topic.