Remote Sensing Cool Roofs

Ban weiss ga woods j levinson r submitted using remote sensing to quantify albedo of roofs in seven california cities part 1.

Remote sensing cool roofs.

Active 8 years 1 month ago. Albedo quantification using remote sensing techniques. Using training samples collected during field surveys thematic classification was able to detect the majority of asbestos surfaces. Remote sensing and gis have been widely used in urban environmental analysis.

Garage doors or roll up doors on residential and commercial structures are vulnerable components that are often damaged in windstorms. An urban area containing various urban roofing materials and characteristics was selected. Cool roof in the metropolitan area of mendoza argentina article pdf available in iop conference series earth and environmental science 503. Opensource remote sensing tools for classifying roofs.

Ban weiss ga woods j millstein d levinson r submitted. 2012 found that use of cool roofs in chicago for reducing urban heat islands has increased city wide albedo and decreased roof surface temperatures as detected by the landsat satellite. Remote sensing of the urban heat island effect across biomes in the continental usa marc imhoff nasa earth resource technology et al we find that ecological context significantly influences the amplitude of summer daytime uhi urban rural temperature difference the largest 8 c average observed for cities built in biomes dominated by temperate broadleaf and mixed forest. Ask question asked 8 years 4 months ago.

A remote sensing study mackey et al. Blue green red and near infrared. Evaluating chicago s urban heat island policy with remote sensing chris mackey yale university ron smith yale university and xuhui lee yale university since the great chicago heat wave of 1995 the city government has enacted a large number of policies under the pretense that it is combating its urban heat island. With envi image processing and classification tools you can get roofs from images with some spectral value and then you can convert it some vector data for your app.

Considering the total amount of asbestos areas validation showed a correct detection of about 80. Thus this study aimed to develop the roofing layer in order to assess the potential area for rooftop rainwater harvesting adoption by integrating remote sensing and gis approach. To derive the albedo of roofs in each city we first locate roof pixels within gis building outlines. Various mesoscale climate modeling studies have simulated the climate effects of hypothetical increases in urban albedo.

This paper describes the use of airborne hyperspectral remote sensing for mapping asbestos roofs in an orographic complex area in northern italy the aosta valley. This study utilized high spatial resolution oblique remote sensing data to assess the condition of garage doors and roof. Using remote sensing to quantify albedo of roofs in seven california cities part 2. Viewed 7k times 30.