Landsat Imagery-Based Above Ground Biomass Estimation and Change Investigation Related to Human Activities

Chaofan Wu, Huanhuan Shen, Ke Wang, Aihua Shen, Jinsong Deng and Muye Gan
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Chaofan Wu: College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Huanhuan Shen: College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Ke Wang: College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Aihua Shen: Zhejiang Forestry Academy, Hangzhou 310023, China
Jinsong Deng: College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Muye Gan: College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China

Sustainability, 2016, vol. 8, issue 2, 1-13

Abstract: Forest biomass is a significant indicator for substance accumulation and forest succession, and a spatiotemporal biomass map would provide valuable information for forest management and scientific planning. In this study, Landsat imagery and field data cooperated with a random forest regression approach were used to estimate spatiotemporal Above Ground Biomass (AGB) in Fuyang County, Zhejiang Province of East China. As a result, the AGB retrieval showed an increasing trend for the past decade, from 74.24 ton/ha in 2004 to 99.63 ton/ha in 2013. Topography and forest management were investigated to find their relationships with the spatial distribution change of biomass. In general, the simulated AGB increases with higher elevation, especially in the range of 80–200 m, wherein AGB acquires the highest increase rate. Moreover, the forest policy of ecological forest has a positive effect on the AGB increase, particularly within the national level ecological forest. The result in this study demonstrates that human activities have a great impact on biomass distribution and change tendency. Furthermore, Landsat image-based biomass estimates would provide illuminating information for forest policy-making and sustainable development.

Keywords: Landsat imagery; Above Ground Biomass; Fuyang County; topography; ecological forest; human activities (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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