National Forest Aboveground Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China

Hong Chi,Wenjian Ni,Jinliang Huang,Zhifeng Guo,Guoqing Sun,Anmin Fu

doi:10.3390/rs70505534

Abstract

Forest aboveground biomass (AGB) was mapped throughout China using 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 and forest inventory data. The entire land of China was divided into seven zones according to the geographic characteristics of the forests. The forest AGB prediction models were separately developed for different forest types in each of the seven forest zones at GLAS footprint level from GLAS waveform parameters and biomass derived from height and diameter at breast height (DBH) field observation. Some waveform parameters used in the prediction models were able to reduce the effects of slope on biomass estimation. The models of GLAS-based biomass estimates were developed by using GLAS footprints with slopes less than 20° and slopes ≥ 20°, respectively. Then, all GLAS footprint biomass and MODIS data were used to establish Random Forest regression models for extrapolating footprint AGB to a nationwide scale. The total amount of estimated AGB in Chinese forests around 2006 was about 12,622 Mt vs. 12,617 Mt derived from the seventh national forest resource inventory data. Nearly half of all provinces showed a relative error (%) of less than 20%, and 80% of total provinces had relative errors less than 50%.

Highlights

As the major component of terrestrial ecosystems, forests hold 70%–80% of terrestrial aboveground and belowground biomass and play an essential role in the global carbon cycle and climate change [1].Forests are vulnerable to fire, logging, pests, and land conversion, which release carbon to the atmosphere [2]
Because of the lack of field survey data and low forest coverage in the Neimeng-Xinjiang arid zone, the models of aboveground biomass (AGB) estimation from Geoscience Laser Altimeter System (GLAS) data in this zone were referred to the models in the Qinghai-Xizang plateau alpine zone, which is dominated by spruce and fir trees, similar to the forest types in the Neimeng-Xinjiang arid zone
Fifteen provinces had relative errors less than 20%, and the relative errors of ten provinces were between 20% and 50%, indicating overall high consistency between estimated AGB and statistical results at the province scale (Table 7)

Summary

Introduction

As the major component of terrestrial ecosystems, forests hold 70%–80% of terrestrial aboveground and belowground biomass and play an essential role in the global carbon cycle and climate change [1].Forests are vulnerable to fire, logging, pests, and land conversion, which release carbon to the atmosphere [2]. Regional to global information on the human impact on carbon stocks and ecological balance requires accurate determination of forest biomass and monitoring of its changes, especially in areas of fragmented forest cover and in developing countries [6,7,8]. These scientific objectives require accurate mapping of forest biomass at the national level for the assessment of forest carbon stocks and their dynamics

Methods

Results

Discussion

Conclusion