Remotely-sensed imagery vs. eye-level photography: Evaluating associations among measurements of tree cover density

Bin Jiang, Brian M Deal, Hao Zhi Pan, Linda Larsen, Chung Heng Hsieh, Chun Yen Chang, William C Sullivan

Research output: Contribution to journalArticle

Abstract

The easy availability and widespread use of remotely-sensed imagery, especially Google Earth satellite imagery, makes it simple for urban forestry professionals to assess a site and measure tree cover density without visiting the site. Remotely-sensed tree cover density has become the dominant criterion for urban forestry regulations in many countries, but it is unclear how much such measures match the eye-level tree cover density that people experience; or the information gained through site visits, eye-level photography, or from consulting with citizens. To address this uncertainty, we assessed associations among two remotely-sensed and three eye-level tree cover density measures for 140 community street sites across the Midwestern United States with low, medium, or high tree cover coverage by using linear regression analysis. We found significant associations among the two remotely-sensed measures and the three eye-level measures across the three levels of tree cover. The associations between any pair of remotely-sensed and eye-level measures, however, diminish dramatically as canopy cover increased. At high levels of canopy cover, all associations between the remotely-sensed measures and the eye-level measures became statistically insignificant. These findings suggest that measures from remotely-sensed imagery fail to represent the amount of tree cover people perceive at eye-level when canopy cover is medium or high at the site scale. Therefore, the current urban forestry planning regulations, which rely heavily on remotely-sensed tree cover density measurements, need to be revised. We suggest strategic spots where eye-level measures of tree cover density should be emphasized.

Original languageEnglish (US)
Pages (from-to)270-281
Number of pages12
JournalLandscape and Urban Planning
Volume157
DOIs
StatePublished - Jan 1 2017

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photography
imagery
urban forestry
canopy
satellite imagery
regression analysis

Keywords

  • Association
  • Eye-level photography
  • Remotely-sensed imagery
  • Tree cover density
  • Urban forestry

ASJC Scopus subject areas

  • Ecology
  • Nature and Landscape Conservation
  • Management, Monitoring, Policy and Law

Cite this

Remotely-sensed imagery vs. eye-level photography : Evaluating associations among measurements of tree cover density. / Jiang, Bin; Deal, Brian M; Pan, Hao Zhi; Larsen, Linda; Hsieh, Chung Heng; Chang, Chun Yen; Sullivan, William C.

In: Landscape and Urban Planning, Vol. 157, 01.01.2017, p. 270-281.

Research output: Contribution to journalArticle

Jiang, Bin ; Deal, Brian M ; Pan, Hao Zhi ; Larsen, Linda ; Hsieh, Chung Heng ; Chang, Chun Yen ; Sullivan, William C. / Remotely-sensed imagery vs. eye-level photography : Evaluating associations among measurements of tree cover density. In: Landscape and Urban Planning. 2017 ; Vol. 157. pp. 270-281.
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