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Yujia Zhang

Researcher at Arizona State University

Publications -  11
Citations -  577

Yujia Zhang is an academic researcher from Arizona State University. The author has contributed to research in topics: Land cover & Urban heat island. The author has an hindex of 7, co-authored 8 publications receiving 362 citations. Previous affiliations of Yujia Zhang include Clark University.

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Optimizing green space locations to reduce daytime and nighttime urban heat island effects in Phoenix, Arizona

TL;DR: In this paper, the authors developed a framework to identify the best locations and configuration of new green space with respect to cooling benefits in order to mitigate the effect of urban heat island effects.
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Use of intensity analysis to link patterns with processes of land change from 1986 to 2007 in a coastal watershed of southeast China

TL;DR: In this paper, the authors applied intensity analysis to quantify the annual intensity of the changes at three levels: time interval, category, and transition, and found that overall land transformation is accelerating across the three time intervals.
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Object-based land-cover classification for metropolitan Phoenix, Arizona, using aerial photography

TL;DR: This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program that employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data.
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Solar reflective pavements-A policy panacea to heat mitigation?

TL;DR: In this article, the authors present the first biometeorological observations of solar reflective coating to investigate its thermal performance from a pedestrian perspective and demonstrate the benefits and disadvantages of reflective pavement with respect to various thermal performance metrics.
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Evaluating the effect of 3D urban form on neighborhood land surface temperature using Google Street View and geographically weighted regression

TL;DR: In this paper, the authors compared and integrated spherical land cover fractions derived from Google Street View (GSV) with the conventional planar land-cover fractions in estimating daytime and nighttime LST variations in the Phoenix metropolitan area, AZ.