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Chuanrong Zhang

Researcher at University of Connecticut

Publications -  151
Citations -  4097

Chuanrong Zhang is an academic researcher from University of Connecticut. The author has contributed to research in topics: Geospatial analysis & Categorical variable. The author has an hindex of 29, co-authored 151 publications receiving 3002 citations. Previous affiliations of Chuanrong Zhang include University of Wisconsin–Milwaukee & Kent State University.

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Assessing street-level urban greenery using Google Street View and a modified green view index

TL;DR: The authors explored Google Street View (GSV) as a street-level, urban greenery assessment tool and found that GSV to be well suited for assessing street level greenery.
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Gaps-fill of SLC-off Landsat ETM+ satellite image using a geostatistical approach

TL;DR: The case study shows that the ordinary kriging techniques may provide a powerful tool for interpolating the missing pixels in the SLC‐off ETM+ imagery, and demonstrates that the standardized ordinary cokriging provides little improvement in interpolation of the data gap.
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The roles of geography markup language (GML), scalable vector graphics (SVG), and Web feature service (WFS) specifications in the development of Internet geographic information systems (GIS)

TL;DR: The case studies show that the combination of GML, SVG, and WFS has an immense potential to achieve interoperability while not requiring considerable changes to existing legacy data.
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Predictive mapping of soil total nitrogen at a regional scale: A comparison between geographically weighted regression and cokriging

TL;DR: In this article, the authors compare GWR and OCK in predicting soil total nitrogen (TN) using multiple environmental variables, including elevation, land use types, and soil types.
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Who lives in greener neighborhoods? The distribution of street greenery and its association with residents' socioeconomic conditions in Hartford, Connecticut, USA

TL;DR: In this paper, the authors used Google Street View (GSV) images captured at different horizontal and vertical view angles to quantitatively represent how much greenery a pedestrian can see from ground level.