The Laboratory for Remote Sensing and Environmental Change (LRSEC)
The Laboratory for Remote Sensing and Environmental Change (LRSEC)
An Interdisciplinary Research Group Using Remote Sensing and Geospatial Science to Understand Landscape Change
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Latest News in LRSEC

  • Welcome Austin Barbee to join LRSEC October 3, 2024
  • Welcome Justin Erlick to join the lab September 16, 2024
  • Welcome Rachel to join the lab March 21, 2024

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Dr. Gang Chen
Address: McEniry 446, 9201 University City Blvd, Charlotte, NC 28223, USA (35°18'26"N 80°43'48"W)
Email: Gang.Chen 'at' charlotte.edu

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  • Department of Earth, Environmental and Geographical Sciences
  • College of Humanities & Earth and Social Sciences
  • University of North Carolina at Charlotte

Urban forest research paper accepted by Ecological Indicators

March 02, 2020 by Gang Chen
Categories: Updates

Chen, G., Singh, K.K., Lopez, J., Zhou, Y. (in press). Tree canopy cover and carbon density are different proxy indicators for assessing the relationship between forest structure and urban socio-ecological conditions. Ecological Indicators.

Abstract
Forest canopy cover and carbon density are two pivotal biophysical parameters for assessing urban forest structure and its ecosystem services. While canopy cover (horizontal structure) has been extensively studied for understanding the relationship between socio-ecological dynamics and urban forests, carbon density (vertical structure) received little attention in the urban setting. The goal of this study was twofold: (i) exploring the differences between canopy cover and carbon density, and their relationships with socio-ecological factors across an urbanizing landscape, and (ii) assessing the effect of neighborhood category (i.e., low, medium and high development intensity) on the relationships at the neighborhood level. We used Mecklenburg County located in the Charlotte Metropolitan area of North Carolina, United States as a case study area, where rapid urban sprawl has fragmented the pine-oak-hickory dominated forests into a range of low to high housing density neighborhoods. We observed two major findings. First, canopy cover and carbon density demonstrated a generally weak correlation across various types of residential neighborhoods, although such relationship became relatively stronger in areas featuring a higher level of development intensity. Second, ecological factors (e.g., landscape spatial patterns) were found to dominate the statistical models explaining the variance in both canopy cover and carbon density compared to urban socioeconomic factors (e.g., income and age). However, the models and the explanatory factors were different for the two forest parameters, and they varied across neighborhoods of diverse development intensities. Based upon these findings, we argue that canopy cover and carbon density are different proxy indicators of forest functioning in the urban setting, and should be independently treated in urban forest management. The best management practices should be developed at the inner-city, neighborhood level, rather than the typical city level, owing to the significant, variable influence of socio-ecological conditions across neighborhood types.

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