Estimation of Forest Biomass Patterns across Northeast China Based on Allometric Scale Relationship

Xiliang Ni,Hong Hu,Sungho Choi,Chunxiang Cao,Taejin Park,Yuke Zhou,Xuejun Wang,Xiao Fu,Lin Ding,Yuli Shi

doi:10.3390/f8080288

Abstract

This study develops a modeling framework for utilizing the large footprint LiDAR waveform data from the Geoscience Laser Altimeter System (GLAS) onboard NASA’s Ice, Cloud, and Land Elevation Satellite (ICESat), Moderate Resolution Imaging Spectro-Radiometer (MODIS) imagery, meteorological data, and forest measurements for monitoring stocks of total biomass (including aboveground biomass and root biomass). The forest tree height models were separately used according to the artificial neural network (ANN) and the allometric scaling and resource limitation (ASRL) tree height models which can both combine the climate data and satellite data to predict forest tree heights. Based on the allometric approach, the forest aboveground biomass model was developed from the field measured aboveground biomass data and the tree heights derived from two tree height models. Then, the root biomass should scale with the aboveground biomass. To investigate whether this approach is efficient for estimating forest total biomass, we used Northeast China as the object of study. Our results generally proved that the method proposed in this study could be meaningful for forest total biomass estimation (R2 = 0.699, RMSE = 55.86).

Highlights

As the principal part of terrestrial ecosystems, forest ecosystems hold approximately 80% of the terrestrial aboveground and below-ground biomass, and play very important roles in the global carbon cycle and climate change [1,2,3]
Due to the great difficulties difficulties in root measuring biomass forbiomass forest total biomass estimation, it ismethod the primary method in measuring biomassroot for forest total estimation, it is the primary for estimating for estimating root biomass by building the allomeric relationship with aboveground biomass root biomass by building the allomeric relationship with aboveground biomass [54]
Based on the collected field measured forest plots data, we developed the allometric models for predicting the aboveground biomass and root biomass

Summary

Introduction

As the principal part of terrestrial ecosystems, forest ecosystems hold approximately 80% of the terrestrial aboveground and below-ground biomass, and play very important roles in the global carbon cycle and climate change [1,2,3]. Many studies have shown that the lack of accurate forest biomass maps has generated a large uncertainty in forest carbon stocks of temperate and boreal forest regions [7,8,9]. The accurate estimation of forest biomass is necessary for improving the estimation of carbon pools, and very important for forest management and understanding the response to climate change [10,11,12,13]. There are some problems related to obtaining reliable forest biomass estimation results in large scale studies, because of the lack of field data, inconsistency of data collection methods, and less consideration of root biomass [19].

Methods

Discussion

Conclusion