Title
Forest Biomass Mapping of Northeastern China Using GLAS and MODIS Data
Abstract
In this study, several major issues associated with forest biomass mapping have been investigated using an integrated dataset, and a preliminary forest biomass map of northeastern China is presented. Three biomass regression models, stepwise regression (SR), partial least-squares regression (PLSR), and support vector regression (SVR), were developed based on field biomass data, Geoscience Laser Altimeter System (GLAS) data, and Moderate Resolution Imaging Spectroradiometer (MODIS) data. The biomass estimates using the SVR model were the most reasonable. The accuracy of the biomass predictions was improved through a combination of bootstrapping and the SVR method. The rich temporal information in MODIS data and the multiple-angle information in Multi-angle Imaging Spectro Radiometer (MISR) data were also explored for forest biomass mapping. Results indicated that a MODIS time series data alone, without MISR data, was capable of mapping forest biomass. A forest biomass map was generated using the optimal biomass regression model and the MODIS time series data. Finally, an uncertainty analysis of the biomass map was carried out and a comparison with published results using other methods was made.
Year
DOI
Venue
2014
10.1109/JSTARS.2013.2256883
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
Keywords
Field
DocType
partial least-squares regression,geoscience laser altimeter system (glas) data,geoscience laser altimeter system,stepwise regression,support vector regression,regression analysis,svr model,misr data,biomass prediction,modis time series data,random forests,temporal information,field biomass data,multiangle imaging spectroradiometer,northeastern china,least squares approximations,plsr,glas data,biomass regression model,multiple-angle information,biomass estimate,uncertainty analysis,vegetation mapping,moderate resolution imaging spectroradiometer,time series,forest biomass mapping,vegetation,support vector machines,bootstrapping
Biomass,Time series,Moderate-resolution imaging spectroradiometer,Altimeter,Vegetation,Stepwise regression,Regression analysis,Remote sensing,Mathematics,Radiometer
Journal
Volume
Issue
ISSN
7
1
1939-1404
Citations 
PageRank 
References 
10
0.91
3
Authors
3
Name
Order
Citations
PageRank
Yuzhen Zhang1100.91
Shunlin Liang2611116.22
Guoqing Sun316249.24