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Article

Quantifying the Spatial Heterogeneity and Driving Factors of Aboveground Forest Biomass in the Urban Area of Xi’an, China

1
College of Landscape Architecture and Art, Northwest A&F University, Xianyang 712100, China
2
College of Forestry, Northwest A&F University, Xianyang 712100, China
3
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(12), 744; https://doi.org/10.3390/ijgi9120744
Received: 14 October 2020 / Revised: 6 December 2020 / Accepted: 10 December 2020 / Published: 12 December 2020
(This article belongs to the Special Issue Geo-Information Technology and Its Applications)
Investigating the spatial distribution of urban forest biomass and its potential influencing factors would provide useful insights for configuring urban greenspace. Although China is experiencing an unprecedented scale of urbanization, the spatial pattern of the urban forest biomass distribution as a critical component in the urban landscape has not been fully examined. Using the geographic detector method, this research examines the impacts of four geographical factors (GFs)—dominant tree species, forest categories, land types, and age groups—on the aboveground biomass distribution of urban forests in 1480 plots in Xi’an, China. The results indicate that (1) the aboveground biomass and four GFs show obvious heterogeneity regarding their spatial distribution in Xi’an; (2) the dominant tree species and age group which impacts the patterns of aboveground biomass are the primary GFs, with the independent q value (a statistic metric used to quantify the impacts of GFs in this study) reaching 0.595 and 0.202, respectively, while the forest category and land type were weakly linked to the spatial variation of aboveground biomass, with a q value of 0.087 and 0.076, respectively; and (3) the interactions among these four GFs also tend to contribute to the distribution pattern of aboveground biomass. The interactions between GFs achieved a larger impact than the sum of impacts that were independently obtained from the factors. Our results showed that the method of using a geographical detector is a useful tool in the urban area, and can reveal the driver pattern of aboveground biomass and provide a reference for city planning and management. View Full-Text
Keywords: urban forest; forest biomass; biomass distribution; geographic detector urban forest; forest biomass; biomass distribution; geographic detector
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MDPI and ACS Style

Zhao, X.; Liu, J.; Hao, H.; Yang, Y. Quantifying the Spatial Heterogeneity and Driving Factors of Aboveground Forest Biomass in the Urban Area of Xi’an, China. ISPRS Int. J. Geo-Inf. 2020, 9, 744. https://doi.org/10.3390/ijgi9120744

AMA Style

Zhao X, Liu J, Hao H, Yang Y. Quantifying the Spatial Heterogeneity and Driving Factors of Aboveground Forest Biomass in the Urban Area of Xi’an, China. ISPRS International Journal of Geo-Information. 2020; 9(12):744. https://doi.org/10.3390/ijgi9120744

Chicago/Turabian Style

Zhao, Xuan, Jianjun Liu, Hongke Hao, and Yanzheng Yang. 2020. "Quantifying the Spatial Heterogeneity and Driving Factors of Aboveground Forest Biomass in the Urban Area of Xi’an, China" ISPRS International Journal of Geo-Information 9, no. 12: 744. https://doi.org/10.3390/ijgi9120744

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