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Developing General Equations for Urban Tree Biomass Estimation with High-Resolution Satellite Imagery

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  • Jindong Wu

    (Department of Geography and the Environment, California State University Fullerton, Fullerton, CA 92831, USA)

Abstract

Urban trees provide various important ecological services, the quantification of which is vital to sustainable urban development and requires accurate estimation of tree biomass. A limited number of allometric biomass equations, however, have been developed for urban species due to the prohibitive cost. Remote sensing has provided cost-effective means for estimating urban forest biomass, although the propagation of error in the estimation process is not well understood. This study aimed to offer a baseline assessment of the feasibility of estimating urban tree biomass with remote sensing-based general equations applicable to broad taxonomic groups by conducting a large urban tree inventory on a university campus. The biomasses of 191 trees of seven species from the inventory, separated into two categories (i.e., evergreen and deciduous), were calculated exclusively with urban-based species-specific allometric equations. WorldView-2 satellite imagery data were acquired to retrieve normalized difference vegetation index (NDVI) values at the location, crown, and stand levels. The results indicated that biomass correlated with NDVI in varying forms and degrees. The general equations at the crown level yielded the most accurate biomass estimates, while the location-level estimates were the least accurate. Crown-level spectral responses provided adequate information for delivering spatially explicit biomass estimation.

Suggested Citation

  • Jindong Wu, 2019. "Developing General Equations for Urban Tree Biomass Estimation with High-Resolution Satellite Imagery," Sustainability, MDPI, vol. 11(16), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:16:p:4347-:d:256844
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    Cited by:

    1. Márton Takács & Ákos Malatinszky, 2021. "Half of the Ancient Trees in Hungary Stand in Human-Altered Environments," Sustainability, MDPI, vol. 13(22), pages 1-18, November.

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