Combining allometry and landsat-derived disturbance history to estimate tree biomass in subtropical planted forests

REMOTE SENSING OF ENVIRONMENT

卷:235

Article

Fang, Lei¹  Yang, Jian²  Zhang, Wenqiu¹  Zhang, Weidong^1,3  Yan, Qiaoling^1,4 

[1] Chinese Acad Sci, Inst Appl Ecol, CAS Key Lab Forest Ecol & Management, Shenyang 110016, Liaoning, Peoples R China

[2] Univ Kentucky, Dept Forestry & Nat Resources, TP Cooper Bldg, Lexington, KY 40546 USA

[3] Chinese Acad Sci, Huitong Expt Stn Forest Ecol, Huitong 418307, Peoples R China

[4] Chinese Acad Sci, Qingyuan Forest CERN, Shenyang 110016, Liaoning, Peoples R China

关键词: Allometric equation;    Disturbance history;    Forest age;    Tree biomass;    Landsat time series;    Chinese fir plantation;   

DOI  :  10.1016/j.rse.2019.111423

来源: Elsevier

【 摘 要 】

Planted forests are a key component of sustainable forest management, as their fast-growing biomass can provide many important ecosystem goods and services essential to human well-being. Accurate estimation of forest biomass is important for global carbon accounting and afforestation policy making, yet saturated reflectance signals over vegetation and a shortage of cloud-free images during the growing season largely limit the utility of optical remote sensing for biomass estimation of planted forests in subtropical and tropical regions. Stand age is a crucial factor in determining forest growth and stand development but hasn't been widely used in remote sensing-based biomass estimation approaches. The main objective of this study was to investigate the applicability of an allometric analysis approach combined with Landsat-derived forest age structure to estimate stand biomass of fast-growing forest plantations in a subtropical landscape of China. We used the Vegetation Change Tracker (VCT) approach and Landsat time series data from 1986 to 2016 to detect annual stand-replacing disturbance and estimate forest stand age. Allometric equations and relative growth rate functions were combined to establish the linkage between tree biomass and forest stand age. We also modeled the spatial distribution of tree biomass using a conventional remote sensing (CRS) method that only utilizes spectral and textural variables and an extended CRS method that incorporates stand age (CRS_EX). We then compared the CRS and CRS_EX methods with the allometric analysis method to highlight the importance of stand age and post-disturbance forest regrowth for biomass estimation. The Landsat-derived disturbance history was significantly correlated with stand age (R-2 = 0.82, RMSE = 3.7 year, p < 0.01). The CRS_EX and allometric analysis methods substantially improved tree biomass estimates (R-CRS_EX(2) = 0.77, RMSECRS_Ex = 37.7 t/ha; R-Allometric(2) = 0.70, RMSEAllometric = 43.5 t/ha) compared to the CRS method (R-CRS( )2= 0.53, RMSE (CRS) = 54.38 t/ha). Tree biomass estimated from the allometric analysis method aligned better with the allometric growth curves, while CRS_EX and CRS methods both exhibited notable overestimation for young and mid-aged forests. This study suggests that allometric models have the potential to be applied in subtropical forest plantations through the use of the existing forest stand development knowledge and increasingly open access remote sensing data.

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