Training Area Concept in a Two-Phase Biomass Inventory Using Airborne Laser Scanning and RapidEye Satellite Data

Parvez Rana,Laura Mononen,Qing Xu,Lauri Korhonen,Timo Kumpula,Timo Tokola,Petteri Vihervaara

doi:10.3390/rs6010285

Parvez Rana, Laura Mononen + Show 5 more

Open Access

https://doi.org/10.3390/rs6010285

Copy DOI

Abstract

This study evaluated the accuracy of boreal forest above-ground biomass (AGB) and volume estimates obtained using airborne laser scanning (ALS) and RapidEye data in a two-phase sampling method. Linear regression-based estimation was employed using an independent validation dataset and the performance was evaluated by assessing the bias and the root mean square error (RMSE). In the phase I, ALS data from 50 field plots were used to predict AGB and volume for the 200 surrogate plots. In the phase II, the ALS-simulated surrogate plots were used as a ground-truth to estimate AGB and volume from the RapidEye data for the study area. The resulting RapidEye models were validated against a separate set of 28 plots. The RapidEye models showed a promising accuracy with a relative RMSE of 19%–20% for both volume and AGB. The evaluated concept of biomass inventory would be useful to support future forest monitoring and decision making for sustainable use of forest resources.

Highlights

Forests play an important role in global carbon cycling, since the world’s forests sequestrate and conserve more carbon than all other terrestrial ecosystems, and account for 90% of the annual carbon flux between the atmosphere and the Earth’s land surface [1]
We examined here the above-ground biomass (AGB) and volume estimation employing airborne laser scanning (ALS) and RapidEye data in a two-phase sampling method
The present study has confirmed that the accuracy of AGB and volume comparable to the forest inventory by compartments in Finland

Summary

Introduction

Forests play an important role in global carbon cycling, since the world’s forests sequestrate and conserve more carbon than all other terrestrial ecosystems, and account for 90% of the annual carbon flux between the atmosphere and the Earth’s land surface [1]. Accurate estimation of forest biomass is required for countries ratifying the Kyoto Protocol to the United Nations Framework. Assessment of biomass within all compartments of forest ecosystems can be achieved by choosing the appropriate scientific techniques. The combination of remote sensing with ground surveys potentially offers way to guarantee accurate monitoring, reporting and verification of terrestrial forest biomass [3,4,5]. Southworth and Gibbes [6] reviewed the past, present and future directions of remote sensing applications in the forestry sector. They concluded that the fusion of different remote sensing techniques is promising for the monitoring and assessing of forest ecosystems

Objectives

Methods

Results

Discussion

Conclusion